From 4d9483bd1119294bd7fd784c999e769fa77ade90 Mon Sep 17 00:00:00 2001
From: FGeo <fg.sarafanov@ipfran.ru>
Date: Sat, 13 Apr 2024 01:35:38 +0300
Subject: [PATCH] Initial commit for Part 1/2 scipts

Create readme file with scripts description

Fix comments / fix readme

Start Part2

Scripts for IP simulations

Upload data

Note about prepare

Print variables

Fix small discrepancy

Completed data preprocessing script commenting

Small fix titles

Small fix figure numbers and clear import

Add comments

Use new Vostok data. Add amplitudes on figures. Update diu.-seas.var. figure

Use new source of T2 data

Fix 25 hour in T2
---
 0_prepare_data.ipynb                          |    471 +
 1_Earlier_measurements_images.ipynb           |    326 +
 2_Vostok_measurements_images.ipynb            |   1085 +
 3_WRF_T2_images.ipynb                         |    192 +
 4_IP_simulations_temporal_images.ipynb        |    567 +
 5_IP_simulations_spatial_images.ipynb         |   1475 +
 data/INMCM/INMCM_HOURLY_TOTAL_IP_1000.npy     |    Bin 0 -> 700928 bytes
 data/INMCM/INMCM_HOURLY_TOTAL_IP_1200.npy     |    Bin 0 -> 700928 bytes
 data/INMCM/INMCM_HOURLY_TOTAL_IP_800.npy      |    Bin 0 -> 700928 bytes
 data/INMCM/INMCM_IP_1000_LATxMON.npy          |    Bin 0 -> 11648 bytes
 data/INMCM/INMCM_IP_1200_LATxMON.npy          |    Bin 0 -> 11648 bytes
 data/INMCM/INMCM_IP_800_LATxMON.npy           |    Bin 0 -> 11648 bytes
 data/INMCM/INMCM_NUMDAYS_MON.npy              |    Bin 0 -> 224 bytes
 ...8_2004_hourly_80percent_all-checkpoint.tsv |  40528 +++++
 .../vostok_daily_temp-checkpoint.csv          |   6004 +
 ...thout_calibration_and_empty-checkpoint.tsv | 109365 +++++++++++++
 data/Vostok/.npy                              |    Bin 0 -> 320 bytes
 .../vostok_1998_2004_hourly_80percent_all.tsv |  40528 +++++
 data/Vostok/vostok_2006_2020_results.npz      |    Bin 0 -> 1610 bytes
 data/Vostok/vostok_daily_pressure_mm_hg.csv   |   6004 +
 data/Vostok/vostok_daily_temp.csv             |   6004 +
 data/Vostok/vostok_daily_wind.csv             |   6004 +
 data/Vostok/vostok_diurnal_2006_2020.npy      |    Bin 0 -> 320 bytes
 ...rom_10_s_without_calibration_and_empty.tsv | 118789 +++++++++++++++
 ...om_5_min_without_calibration_and_empty.tsv |  70352 +++++++++
 data/WRF/WRF_HOURLY_TOTAL_IP_1000.npy         |    Bin 0 -> 958592 bytes
 data/WRF/WRF_HOURLY_TOTAL_IP_1200.npy         |    Bin 0 -> 958592 bytes
 data/WRF/WRF_HOURLY_TOTAL_IP_500_T2_25.npy    |    Bin 0 -> 958592 bytes
 data/WRF/WRF_HOURLY_TOTAL_IP_800.npy          |    Bin 0 -> 958592 bytes
 data/WRF/WRF_IP_1000_LATxMON.npy              |    Bin 0 -> 17408 bytes
 data/WRF/WRF_IP_1200_LATxMON.npy              |    Bin 0 -> 17408 bytes
 data/WRF/WRF_IP_500_T2_25_LATxMON.npy         |    Bin 0 -> 17408 bytes
 data/WRF/WRF_IP_800_LATxMON.npy               |    Bin 0 -> 17408 bytes
 data/WRF/WRF_NUMDAYS_MON.npy                  |    Bin 0 -> 224 bytes
 data/WRF/WRF_T2_LATxMON.npy                   |    Bin 0 -> 17408 bytes
 readme.md                                     |    102 +
 36 files changed, 407796 insertions(+)
 create mode 100644 0_prepare_data.ipynb
 create mode 100644 1_Earlier_measurements_images.ipynb
 create mode 100644 2_Vostok_measurements_images.ipynb
 create mode 100644 3_WRF_T2_images.ipynb
 create mode 100644 4_IP_simulations_temporal_images.ipynb
 create mode 100644 5_IP_simulations_spatial_images.ipynb
 create mode 100644 data/INMCM/INMCM_HOURLY_TOTAL_IP_1000.npy
 create mode 100644 data/INMCM/INMCM_HOURLY_TOTAL_IP_1200.npy
 create mode 100644 data/INMCM/INMCM_HOURLY_TOTAL_IP_800.npy
 create mode 100644 data/INMCM/INMCM_IP_1000_LATxMON.npy
 create mode 100644 data/INMCM/INMCM_IP_1200_LATxMON.npy
 create mode 100644 data/INMCM/INMCM_IP_800_LATxMON.npy
 create mode 100644 data/INMCM/INMCM_NUMDAYS_MON.npy
 create mode 100644 data/Vostok/.ipynb_checkpoints/vostok_1998_2004_hourly_80percent_all-checkpoint.tsv
 create mode 100644 data/Vostok/.ipynb_checkpoints/vostok_daily_temp-checkpoint.csv
 create mode 100644 data/Vostok/.ipynb_checkpoints/vostok_hourly_from_10_s_without_calibration_and_empty-checkpoint.tsv
 create mode 100644 data/Vostok/.npy
 create mode 100644 data/Vostok/vostok_1998_2004_hourly_80percent_all.tsv
 create mode 100644 data/Vostok/vostok_2006_2020_results.npz
 create mode 100644 data/Vostok/vostok_daily_pressure_mm_hg.csv
 create mode 100644 data/Vostok/vostok_daily_temp.csv
 create mode 100644 data/Vostok/vostok_daily_wind.csv
 create mode 100644 data/Vostok/vostok_diurnal_2006_2020.npy
 create mode 100644 data/Vostok/vostok_hourly_from_10_s_without_calibration_and_empty.tsv
 create mode 100644 data/Vostok/vostok_hourly_from_5_min_without_calibration_and_empty.tsv
 create mode 100644 data/WRF/WRF_HOURLY_TOTAL_IP_1000.npy
 create mode 100644 data/WRF/WRF_HOURLY_TOTAL_IP_1200.npy
 create mode 100644 data/WRF/WRF_HOURLY_TOTAL_IP_500_T2_25.npy
 create mode 100644 data/WRF/WRF_HOURLY_TOTAL_IP_800.npy
 create mode 100644 data/WRF/WRF_IP_1000_LATxMON.npy
 create mode 100644 data/WRF/WRF_IP_1200_LATxMON.npy
 create mode 100644 data/WRF/WRF_IP_500_T2_25_LATxMON.npy
 create mode 100644 data/WRF/WRF_IP_800_LATxMON.npy
 create mode 100644 data/WRF/WRF_NUMDAYS_MON.npy
 create mode 100644 data/WRF/WRF_T2_LATxMON.npy
 create mode 100644 readme.md

diff --git a/0_prepare_data.ipynb b/0_prepare_data.ipynb
new file mode 100644
index 0000000..533f9ad
--- /dev/null
+++ b/0_prepare_data.ipynb
@@ -0,0 +1,471 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "98e6e23d-5ca7-4706-b1d9-dd57b54888ef",
+   "metadata": {},
+   "source": [
+    "# Data preprocessing for further calculations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5324ceb9-24e7-454b-87b9-ba9a717078ae",
+   "metadata": {},
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7b2a7f44-b0cb-4471-a0c6-e56da23caf86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import datetime as dt\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6b2b903f-fa30-4e35-97e1-74bc0ee6b944",
+   "metadata": {},
+   "source": [
+    "### Helper variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "36b9f49e-32e6-4544-a9d3-f6a8ba49d867",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# also available at https://eee.ipfran.ru/files/seasonal-variation-2024/\n",
+    "# attention: the files are very large (~ 350 GB totally)\n",
+    "src_path = \"../shared_files/eee_public_files/seasonal-variation-2024/\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "78a4350c-59fb-479a-b7cd-e2bf9b996d36",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# used numbers of simulated days for analysis\n",
+    "wrf_N_days = 4992\n",
+    "inmcm_N_days = 3650"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "53cb9cc3-0e56-4da4-920b-2f071a0846fb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dates corresponding to the indices (0 axis) of the data arrays\n",
+    "# note: for WRF dates correspond to real dates\n",
+    "\n",
+    "wrf_dt_indicies = np.array(\n",
+    "    [dt.date(1980, 1, 1) + dt.timedelta(i * 3) for i in range(wrf_N_days)]\n",
+    ")\n",
+    "inmcm_dt_indicies = np.array(\n",
+    "    [dt.date(2022, 1, 1) + dt.timedelta(i % 365) for i in range(inmcm_N_days)]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e16ee8e-f3b0-4251-9691-19d7dfd4aff7",
+   "metadata": {},
+   "source": [
+    "### Preprocessing WRF T2m data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "87860fa8-0a9c-4304-9c3c-94561c3e966c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# air temperature at the height of 2 m with the shape\n",
+    "# (number of days, number of hours, number of latitudes, number of longitudes)\n",
+    "# contains temperature values depending on (d, h, lat, lon)\n",
+    "#   d (axis 0) is the number of a day starting with 0 and ending with 5113\n",
+    "#              every third day is taken\n",
+    "#              d = 0 corresponds to 1 Jan 1980, \n",
+    "#              d = 5113 corresponds to 30 Dec 2021\n",
+    "#              d = 4991 corresponds to 29 Dec 2020\n",
+    "#              (we will restrict our attention to 1980–2020)\n",
+    "#   h (axis 1) is the hour of the day (an integer in [0, 25])\n",
+    "#              the values corresponding to h = 0 and h = 24 are the same\n",
+    "# lat (axis 2) describes the latitude (an integer in [0, 179]) \n",
+    "# lon (axis 3) describes the longitude (an integer in [0, 359])\n",
+    "\n",
+    "wrf_T2_data = np.load(f\"{src_path}/WRF-T2-MAP.npy\")[:wrf_N_days, :24]\n",
+    "wrf_T2_data_DAYxLAT = wrf_T2_data.mean(axis=(1, 3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "1124d9f9-95d9-4c02-8176-82b9c0331d34",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4992, 180)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wrf_T2_data_DAYxLAT.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "ec569ffd-93c2-4490-8ba1-69af4fab8f23",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# air temperature averaged over latitudes and months\n",
+    "wrf_mon_T2 = np.zeros((180, 12))\n",
+    "\n",
+    "for month_idx in range(12):\n",
+    "    # filter indicies by month number\n",
+    "    monthly_indicies = [\n",
+    "        i for i, date in enumerate(wrf_dt_indicies) if date.month == month_idx + 1\n",
+    "    ]\n",
+    "\n",
+    "    # putting values at specific month into averaged array\n",
+    "    wrf_mon_T2[:, month_idx] = wrf_T2_data_DAYxLAT[monthly_indicies].mean(axis=0)-273.15\n",
+    "\n",
+    "np.save(f\"./data/WRF/WRF_T2_LATxMON.npy\",wrf_mon_T2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "b480c05f-4b06-4d33-9527-dbe2655ed251",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "27.894258059212177"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wrf_mon_T2.max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46d4f093-a420-42c7-b885-a8409d9d8ee4",
+   "metadata": {},
+   "source": [
+    "### Preprocessing INMCM and WRF IP: classic parametrization"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "94a603c3-982d-4c78-be1c-bb6c74b86b5b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dictionaries where processed data is saved\n",
+    "# the dictionary keys represent the threshold value of CAPE\n",
+    "\n",
+    "# for storing arrays with averaged by hours and summarized by longitude,\n",
+    "# i.e. with dimensions (4992, 180) for WRF and (3650, 120) for INMCM\n",
+    "wrf_daily_latitudal_ip = {}\n",
+    "inmcm_daily_latitudal_ip = {}\n",
+    "\n",
+    "# for storing arrays summarized by longitude and latitude,\n",
+    "# i.e. with dimensions (4992, 24) for WRF and (3650, 24) for INMCM\n",
+    "wrf_hourly_total_ip = {}\n",
+    "inmcm_hourly_total_ip = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8e43c4f-59af-483c-8979-535c696abb4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# iterating over the CAPE threshold (J/kg) values used in modeling \n",
+    "# for each threshold, there are corresponding model datasets\n",
+    "for cape_thres in [800, 1000, 1200]:\n",
+    "\n",
+    "    # grid cell contributions to the IP (not normalised) with the shape\n",
+    "    # (number of days, number of hours, number of latitudes, number of longitudes)\n",
+    "    wrf_raw_ip_data = np.load(f\"{src_path}/WRF-IP-MAP-{cape_thres}.npy\")[:wrf_N_days]\n",
+    "    # modelled using WRF model with CAPE threshold = `cape_thres` J/kg\n",
+    "    # contains values of contributions to the IP depending on (d, h, lat, lon)\n",
+    "    #   d (axis 0) is the number of a day starting with 0 and ending with 5113\n",
+    "    #              every third day is taken\n",
+    "    #              d = 0 corresponds to 1 Jan 1980, \n",
+    "    #              d = 5113 corresponds to 30 Dec 2021\n",
+    "    #              d = 4991 corresponds to 29 Dec 2020\n",
+    "    #              (we will restrict our attention to 1980–2020)\n",
+    "    #   h (axis 1) is the hour of the day (an integer in [0, 24])\n",
+    "    #              the values corresponding to h = 0 and h = 24 are the same\n",
+    "    # lat (axis 2) describes the latitude (an integer in [0, 179]) \n",
+    "    # lon (axis 3) describes the longitude (an integer in [0, 359])\n",
+    "\n",
+    "    # discarding the last hour, which duplicates the first one\n",
+    "    wrf_raw_ip_data = wrf_raw_ip_data[:, :24, :, :]\n",
+    "    \n",
+    "    # normalisation of contributions to the IP to the global mean of 240 kV\n",
+    "    wrf_raw_ip_data /= (1/240e3) * wrf_raw_ip_data.sum(axis=(-2,-1)).mean()\n",
+    "\n",
+    "    # filling dictionaries with averaged arrays\n",
+    "    wrf_daily_latitudal_ip[cape_thres] = wrf_raw_ip_data.mean(axis=1).sum(axis=-1)\n",
+    "    wrf_hourly_total_ip[cape_thres] = wrf_raw_ip_data.sum(axis=(-2, -1))\n",
+    "\n",
+    "    np.save(f\"./data/WRF/WRF_HOURLY_TOTAL_IP_{cape_thres}.npy\",\n",
+    "            wrf_hourly_total_ip[cape_thres])\n",
+    "\n",
+    "    # grid cell contributions to the IP (not normalised) reshaped to\n",
+    "    # (number of days, number of hours, number of latitudes, number of longitudes)\n",
+    "    inmcm_raw_ip_data = np.load(f\"{src_path}/INMCM-IP-MAP-{cape_thres}.npy\")\\\n",
+    "                          .reshape((inmcm_N_days, 24, 120, 180))\n",
+    "    # modelled using INMCM model with CAPE threshold = `cape_thres` J/kg\n",
+    "    # contains values of contributions to the IP depending on (d, h, lat, lon)\n",
+    "    #   d (axis 0) is the number of a day (not correspond to real days,\n",
+    "    #              10 consecutive 365-day years have been simulated)\n",
+    "    #   h (axis 1) is the hour of the day (an integer in [0, 23])\n",
+    "    # lat (axis 2) describes the latitude (an integer in [0, 179]) \n",
+    "    # lon (axis 3) describes the longitude (an integer in [0, 359])\n",
+    "\n",
+    "    # normalisation of contributions to the IP to the global mean of 240 kV\n",
+    "    inmcm_raw_ip_data /= (1/240e3) * inmcm_raw_ip_data.sum(axis=(-2,-1)).mean()\n",
+    "\n",
+    "    # filling dictionaries with averaged arrays\n",
+    "    inmcm_daily_latitudal_ip[cape_thres] = inmcm_raw_ip_data.mean(axis=1).sum(axis=-1)\n",
+    "    inmcm_hourly_total_ip[cape_thres] = inmcm_raw_ip_data.sum(axis=(-2, -1))\n",
+    "\n",
+    "    np.save(f\"./data/INMCM/INMCM_HOURLY_TOTAL_IP_{cape_thres}.npy\",\n",
+    "            inmcm_hourly_total_ip[cape_thres])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb28cbc7-eb0a-49be-8cc1-734bba1d06f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# iterating over the CAPE threshold (J/kg) values used in modeling \n",
+    "# for each threshold, there are corresponding model datasets\n",
+    "for cape_thres in [800, 1000, 1200]:\n",
+    "\n",
+    "    # initialization of an arrays to store time-averaged data over months\n",
+    "    wrf_data_LATxMON = np.zeros((180, 12))\n",
+    "    inmcm_data_LATxMON = np.zeros((120, 12))\n",
+    "\n",
+    "    # iteration over month number (starting with 0)\n",
+    "    for month_idx in range(12):\n",
+    "\n",
+    "        # filtering day indices belonging to a specific month\n",
+    "        wrf_monthly_indicies = [i for i, date in enumerate(wrf_dt_indicies) \n",
+    "                                if date.month == month_idx + 1]\n",
+    "        inm_monthly_indicies = [i for i, date in enumerate(inmcm_dt_indicies) \n",
+    "                                if date.month == month_idx + 1]\n",
+    "\n",
+    "        # filling with modeling values with a CAPE threshold \n",
+    "        # averaged over months of the year\n",
+    "        wrf_data_MONxLAT[:, month_idx] = \\\n",
+    "            wrf_daily_latitudal_ip[cape_thres][monthly_indicies].mean(axis=0)\n",
+    "        inmcm_data_LATxMON[:, month_idx] = \\\n",
+    "            inmcm_daily_latitudal_ip[cape_thres][monthly_indicies].mean(axis=0)\n",
+    "\n",
+    "    np.save(f\"./data/WRF/WRF_IP_{cape_thres}_LATxMON.npy\",\n",
+    "            wrf_data_MONxLAT)\n",
+    "    np.save(f\"./data/INMCM/INMCM_IP_{cape_thres}_LATxMON.npy\",\n",
+    "            inmcm_data_LATxMON)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91bc6d7a-393c-4078-9a6d-1955393d55f5",
+   "metadata": {},
+   "source": [
+    "### Preprocessing WRF IP: new parametrization"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2b6f987e-ba3c-4371-af7b-c9857a7d33d9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# grid cell contributions to the IP (not normalised) reshaped to\n",
+    "# (number of days, number of hours, number of latitudes, number of longitudes)\n",
+    "wrf_raw_ip_data = np.load(f\"{src_path}/WRF-IP-MAP-500-T2-25.npy\")[:wrf_N_days]\n",
+    "# modelled using WRF model using new parametrization based on\n",
+    "# CAPE and T2 with corresponding thresholds 500 J/kg and 25°C.\n",
+    "# contains values of contributions to the IP depending on (d, h, lat, lon)\n",
+    "#   d (axis 0) is the number of a day starting with 0 and ending with 5113\n",
+    "#              every third day is taken\n",
+    "#              d = 0 corresponds to 1 Jan 1980, \n",
+    "#              d = 5113 corresponds to 30 Dec 2021\n",
+    "#              d = 4991 corresponds to 29 Dec 2020\n",
+    "#              (we will restrict our attention to 1980–2020)\n",
+    "#   h (axis 1) is the hour of the day (an integer in [0, 24])\n",
+    "#              the values corresponding to h = 0 and h = 24 are the same\n",
+    "# lat (axis 2) describes the latitude (an integer in [0, 179]) \n",
+    "# lon (axis 3) describes the longitude (an integer in [0, 359])\n",
+    "\n",
+    "# discarding the last hour, which duplicates the first one\n",
+    "wrf_raw_ip_data = wrf_raw_ip_data[:, :24, :, :]\n",
+    "\n",
+    "# normalisation of contributions to the IP to the global mean of 240 kV\n",
+    "wrf_raw_ip_data /= (1/240e3) * wrf_raw_ip_data.sum(axis=(-2,-1)).mean()\n",
+    "\n",
+    "# filling dictionaries with averaged arrays\n",
+    "wrf_daily_latitudal_ip = wrf_raw_ip_data.mean(axis=1).sum(axis=-1)\n",
+    "wrf_hourly_total_ip = wrf_raw_ip_data.sum(axis=(-2, -1))\n",
+    "\n",
+    "np.save(\n",
+    "    f\"./data/WRF/WRF_HOURLY_TOTAL_IP_500_T2_25.npy\",\n",
+    "    wrf_hourly_total_ip,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5797fffa-a795-4241-a574-6c95f0195a5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# iterating over the CAPE threshold (J/kg) values used in modeling \n",
+    "# for each threshold, there are corresponding model datasets\n",
+    "for cape_thres in [800, 1000, 1200]:\n",
+    "\n",
+    "    # initialization of an arrays to store time-averaged data over months\n",
+    "    wrf_data_LATxMON = np.zeros((180, 12))\n",
+    "    inmcm_data_LATxMON = np.zeros((120, 12))\n",
+    "\n",
+    "    # iteration over month number (starting with 0)\n",
+    "    for month_idx in range(12):\n",
+    "\n",
+    "        # filtering day indices belonging to a specific month\n",
+    "        wrf_monthly_indicies = [i for i, date in enumerate(wrf_dt_indicies) \n",
+    "                                if date.month == month_idx + 1]\n",
+    "        inm_monthly_indicies = [i for i, date in enumerate(inmcm_dt_indicies) \n",
+    "                                if date.month == month_idx + 1]\n",
+    "\n",
+    "        # filling with modeling values with a CAPE threshold \n",
+    "        # averaged over months of the year\n",
+    "        wrf_data_MONxLAT[:, month_idx] = \\\n",
+    "            wrf_daily_latitudal_ip[cape_thres][monthly_indicies].mean(axis=0)\n",
+    "        inmcm_data_LATxMON[:, month_idx] = \\\n",
+    "            inmcm_daily_latitudal_ip[cape_thres][monthly_indicies].mean(axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17036c19-95f8-40df-a6c9-f8a23cf426f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# initialization of a array to store time-averaged data over months\n",
+    "wrf_data_LATxMON = np.zeros((180, 12))\n",
+    "\n",
+    "# iteration over month number (starting with 0)\n",
+    "for month_idx in range(12):\n",
+    "    # filtering day indices belonging to a specific month\n",
+    "    monthly_indicies = [i for i, date in enumerate(wrf_dt_indicies)\n",
+    "                        if date.month == month_idx + 1]\n",
+    "\n",
+    "    # filling with modeling values averaged over months of the year\n",
+    "    wrf_data_LATxMON[:, month_idx] = \\\n",
+    "        wrf_daily_latitudal_ip[monthly_indicies].mean(axis=0)\n",
+    "\n",
+    "np.save(f\"./data/WRF/WRF_IP_500_T2_25_LATxMON.npy\", wrf_data_LATxMON)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e24297fc-cf81-4ea7-9a80-cdcaf277474a",
+   "metadata": {},
+   "source": [
+    "### Saving number of days (used for monthly mean) for each month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "894ad630-17a5-4744-907e-a07768ff7848",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# saving the number of days for each month\n",
+    "# necessary for correct averaging due to \n",
+    "# different numbers of days in different months\n",
+    "\n",
+    "wrf_days = np.array([len([i for i, date in enumerate(wrf_dt_indicies) \n",
+    "                          if date.month == m + 1]) \n",
+    "                     for m in range(12)])\n",
+    "\n",
+    "inm_days = np.array([len([i for i, date in enumerate(inmcm_dt_indicies) \n",
+    "                          if date.month == m + 1]) \n",
+    "                     for m in range(12)])\n",
+    "\n",
+    "np.save(f\"./data/WRF/WRF_NUMDAYS_MON.npy\", wrf_days)\n",
+    "np.save(f\"./data/INMCM/INMCM_NUMDAYS_MON.npy\", inm_days)\n",
+    "\n",
+    "# for average over months use\n",
+    "# `(wrf_data_LATxMON[:, :].sum(axis=0)*days).sum()/days.sum()`\n",
+    "# unstead\n",
+    "# `wrf_data_LATxMON[:, :].sum(axis=0).mean()`\n",
+    "# because\n",
+    "# `((a1+a2+a3)/3 + (b1+b2)/2)/2 != (a1+a2+a3+b1+b2)/5`"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/1_Earlier_measurements_images.ipynb b/1_Earlier_measurements_images.ipynb
new file mode 100644
index 0000000..cae0022
--- /dev/null
+++ b/1_Earlier_measurements_images.ipynb
@@ -0,0 +1,326 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "63c4ff9b-a25e-400d-8800-70c3b643c091",
+   "metadata": {},
+   "source": [
+    "# Processing digitized data from external sources to construct Figure 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "156aeb14-9418-45a5-90a4-0c9bf7352f6f",
+   "metadata": {},
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "c4d7641a-fe60-4177-95d8-9f10e7622f87",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a9d89f2a-2da0-4279-9355-05926c39084d",
+   "metadata": {},
+   "source": [
+    "### Helper functions and variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "89b9f394-8d80-4db6-bd44-0b9778b03f9d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define an array of abbreviated month names to use as labels on the x-axis of plots\n",
+    "month_name = ['J', 'F', 'M', 'A', 'M', 'J', 'J', 'A', 'S', 'O', 'N', 'D']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4fac1ed4-536f-4e57-9ea5-820eeb0449e2",
+   "metadata": {},
+   "source": [
+    "### Digitized measurement results from external sources"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "47ac4d85-be01-4961-b983-6d3b5eecaaf6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# air—Earth current values measured at Kew in Jun 1930 — May 1931\n",
+    "# units are A·m^(−2)\n",
+    "# source: Scrase (1933), Table 2\n",
+    "\n",
+    "kew_data = (\n",
+    "    np.array([40, 66, 86, 76, 90, 114, 113, 138, 94, 93, 65, 55])\n",
+    "    * 10**4 * 10**(-18)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "1fe2e924-d64d-4db7-9d79-8f42c3cd06a9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# air—Earth current values measured at Mauna Loa in 1977–1983\n",
+    "# units are A·m^(−2)\n",
+    "# source: Adlerman & Williams (1996), Fig. 6 (data by Cobb)\n",
+    "\n",
+    "mauna_loa_data = (\n",
+    "    np.array([30.8, 31.7, 31.3, 28.0, 33.7, 36.4,\n",
+    "              35.7, 34.1, 33.2, 33.9, 34.0, 32.2])\n",
+    "    * 10**(-13)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "1873f063-f3ad-45ef-b460-310377aba194",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# air—Earth current values measured at Athens in 1965–1980\n",
+    "# units are A·m^(−2)\n",
+    "# source: Retalis (1991), Fig. 6\n",
+    "\n",
+    "athens_data = (\n",
+    "    np.array([23.3, 19.7, 18.4, 21.6, 19.2, 24.1,\n",
+    "              24.1, 26.0, 23.2, 20.5, 21.0, 19.0])\n",
+    "    * 10**(-13)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6583858f-a9ad-4185-833d-a2571a88c78d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# potential gradient values measured during Carnegie and Maud expeditions\n",
+    "# (1915–1929)\n",
+    "# units are V·m^(−1)\n",
+    "# source: Adlerman & Williams (1996), Fig. 7b\n",
+    "\n",
+    "carnegie_maud_data = (\n",
+    "    np.array([121, 131, 128, 121, 131, 161,\n",
+    "              180, 111, 127, 121, 117, 126])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8c2fb7aa-510d-4169-9894-9b6d56958ee4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ionospheric potential values measured at different sites over 1955–2004\n",
+    "# units are V\n",
+    "# source: Markson (2007), Fig. 7 (various data)\n",
+    "\n",
+    "ip_data = (\n",
+    "    np.array([212, 236, 239, 238, 245, 234,\n",
+    "              240, 263, 260, 255, 229, 262])\n",
+    "    * 10**3\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "b2c21350-cad0-42ee-a56b-a97a7a712961",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# potential gradient values measured at Vostok station in (1998–2001)\n",
+    "# units are V·m^(−1)\n",
+    "# source: Burns et al. (2012), Table 2\n",
+    "\n",
+    "vostok_old_data = (\n",
+    "    np.array([195, 201, 205, 192, 188, 195,\n",
+    "              209, 198, 209, 195, 193, 192])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5772bcf6-3ee6-49fe-9310-71cdbd09273a",
+   "metadata": {},
+   "source": [
+    "### Figure 1.1\n",
+    "Seasonal variation based on earlier measurement results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "ecc36887-ab8c-4dae-b3cb-da81c7da33d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "\n",
+    "# create a list of axes objects to hold subplots.\n",
+    "ax = [None for _ in range(6)]\n",
+    "\n",
+    "# configure each subplot in the figure\n",
+    "# subplots are arranged in a 4×4 grid\n",
+    "for n in range(6):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "\n",
+    "# lower, upper limits, y-axis ticks interval, y-scaling coefficient for each subplot\n",
+    "low = [100, 160, 0e-13, 15e-13, 25e-13, 200e3]\n",
+    "high = [200, 240, 20e-13, 30e-13, 40e-13, 280e3]\n",
+    "step = [20, 20, 5e-13, 5e-13, 5e-13, 20e3]\n",
+    "coeff = [1, 1, 1e-12, 1e-12, 1e-12, 1e3]\n",
+    "\n",
+    "caption = ['Carnegie and Maud, 1915–1929',\n",
+    "           'Vostok station, 1998–2001 (adjusted)',\n",
+    "           'Kew, 1930–1931',\n",
+    "           'Athens, 1965–1980',\n",
+    "           'Mauna Loa, 1977–1983',\n",
+    "           'Ion. potent. measurements, 1955–2004']\n",
+    "\n",
+    "ins_caption = ['(after $\\it{Adlerman~&~Williams}$, 1996)',\n",
+    "               '(after $\\it{Burns~et~al.}$, 2012)',\n",
+    "               '(after $\\it{Scrase}$, 1933)',\n",
+    "               '(after $\\it{Retalis}$, 1991)',\n",
+    "               '(after $\\it{Adlerman~&~Williams}$, 1996)',\n",
+    "               '(after $\\it{Markson}$, 2007)']\n",
+    "\n",
+    "data = np.array([carnegie_maud_data,\n",
+    "                 vostok_old_data,\n",
+    "                 kew_data,\n",
+    "                 athens_data,\n",
+    "                 mauna_loa_data,\n",
+    "                 ip_data])\n",
+    "\n",
+    "# assign colors for each dataset\n",
+    "col = ['orangered', 'orangered', 'teal', 'teal', 'teal', 'royalblue']\n",
+    "\n",
+    "for n in range(6):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    ax[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    if n in [2, 3, 4]:\n",
+    "        ax[n].set_yticklabels([f'{x:.1f}' for x in\n",
+    "                               np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                         step[n]) / coeff[n]\n",
+    "                               ],\n",
+    "                              fontsize='large')\n",
+    "        ax[n].set_ylabel('Monthly mean fair-weather\\n'\n",
+    "                         'air—Earth current, pA/m²',\n",
+    "                         fontsize='large')\n",
+    "    else:\n",
+    "        ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                         step[n]) / coeff[n]).astype(int),\n",
+    "                              fontsize='large')\n",
+    "        if n in [0, 1]:\n",
+    "            ax[n].set_ylabel('Monthly mean fair-weather\\n'\n",
+    "                             'potential gradient, V/m',\n",
+    "                             fontsize='large')\n",
+    "        else:\n",
+    "            ax[n].set_ylabel('Monthly mean\\nionospheric potential, kV',\n",
+    "                             fontsize='large')\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize='large')\n",
+    "    ax[n].text(0.5,\n",
+    "               1 - 0.01\n",
+    "               * (ax[n].get_position().x1 - ax[n].get_position().x0)\n",
+    "               / (ax[n].get_position().y1 - ax[n].get_position().y0)\n",
+    "               * fig.get_size_inches()[0] / fig.get_size_inches()[1],\n",
+    "               ins_caption[n],\n",
+    "               fontsize='large', ha='center', va='top',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "    ax[n].annotate('', xy=(12, np.min(data[n])), xycoords='data',\n",
+    "                   xytext=(12, np.max(data[n])), textcoords='data',\n",
+    "                   annotation_clip=False,\n",
+    "                   arrowprops=dict(\n",
+    "                       arrowstyle='<|-|>,head_length=0.8,head_width=0.3',\n",
+    "                       patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                       connectionstyle='arc3,rad=0.', fc='black',\n",
+    "                       linewidth=0.5\n",
+    "                   ))\n",
+    "    ampl = (np.max(data[n]) - np.min(data[n])) / np.mean(data[n])\n",
+    "    ax[n].text(12.2, (np.min(data[n]) + np.max(data[n])) / 2,\n",
+    "               f'{ampl * 100:.0f}%',\n",
+    "               fontsize='large', ha='left', va='center', rotation=270)\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2], ax[4]])\n",
+    "fig.align_ylabels([ax[1], ax[3], ax[5]])\n",
+    "\n",
+    "for n in range(6):\n",
+    "    ax[n].bar(np.arange(12), data[n], 0.8, color=col[n])\n",
+    "\n",
+    "for n in range(6):\n",
+    "    ax[n].text(-0.3, 1.05, chr(ord('a') + n), fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.6)\n",
+    "\n",
+    "fig.savefig('figures_two_parts/earlier_measurements.eps', bbox_inches='tight')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/2_Vostok_measurements_images.ipynb b/2_Vostok_measurements_images.ipynb
new file mode 100644
index 0000000..bf8627d
--- /dev/null
+++ b/2_Vostok_measurements_images.ipynb
@@ -0,0 +1,1085 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "113058f9-8324-4368-99ed-b088987c683a",
+   "metadata": {},
+   "source": [
+    "# Comprehensive analysis of Vostok station data\n",
+    "Seasonal-diurnal diagram, hour crossections, adjustment using meteoparameters"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5870ae4e-8a7d-4d76-a7e0-a542ee0fbd25",
+   "metadata": {},
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "c4d7641a-fe60-4177-95d8-9f10e7622f87",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.transforms as tf\n",
+    "from matplotlib import cm, colors, colormaps\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import scipy.stats as st\n",
+    "\n",
+    "import datetime as dt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eb2d634e-ccc5-4fd2-a9e8-05d314f12c1b",
+   "metadata": {},
+   "source": [
+    "### Loading source PG datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "80dbd8bc-6286-4b35-8de7-900551e1026e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# potential gradient values measured at Vostok station in (1998–2001)\n",
+    "# units are V·m^(−1)\n",
+    "# source: Burns et al. (2012), Table 2\n",
+    "\n",
+    "vostok_old_data = (\n",
+    "    np.array([195, 201, 205, 192, 188, 195,\n",
+    "              209, 198, 209, 195, 193, 192])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "c63b60de-82fa-4dcd-af67-a3d4738a0431",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load hourly data derived from 10-second intervals \n",
+    "# \"Field\" column contains PG values [V/m] without scale and calibration\n",
+    "df_10s = pd.read_csv('./data/Vostok/vostok_hourly_from_10_s_without_calibration_and_empty.tsv', \n",
+    "                     sep='\\t', parse_dates=['Datetime']).set_index('Datetime')\n",
+    "\n",
+    "# Add a new column 'Mark' to label this dataframe's data as originating from 10-second averages\n",
+    "df_10s[\"Mark\"] = '10s'  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "d2d83b75-97ce-42ba-8a99-8597f84d7946",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load hourly data derived from 5-minute intervals \n",
+    "# \"Field\" column contains PG values [V/m] without scale and calibration\n",
+    "df_5min = pd.read_csv('./data/Vostok/vostok_hourly_from_5_min_without_calibration_and_empty.tsv', \n",
+    "                      sep='\\t', parse_dates=['Datetime']).set_index('Datetime')\n",
+    "\n",
+    "# Add a new column 'Mark' to label this dataframe's data as originating from 5-minute averages\n",
+    "df_5min[\"Mark\"] = '5min'  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "26da1848-ad4f-4e58-8a75-d02428fb12c7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load earlier dataset (1998-2004) \n",
+    "earlier_df_src = pd.read_csv('./data/Vostok/vostok_1998_2004_hourly_80percent_all.tsv', \n",
+    "                             sep='\\t', parse_dates=['Datetime']).set_index('Datetime')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "d126b8b1-0b66-4817-a556-8f33860608ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Note that all the aforementioned files are averaged with 80% data availability, which \n",
+    "# means that the hourly value was calculated only when at least 80% of the readings were \n",
+    "# available (at least 288 10-second averages or at least 9 5-minute averages)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "7de3455e-ba80-420d-8fec-8f82ee28804a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Combine the two dataframes: fill in gaps in the 10-second data with the 5-minute data.\n",
+    "df_src = df_10s.combine_first(df_5min)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cf820033-d3f9-4432-a425-db7bcf047a4d",
+   "metadata": {},
+   "source": [
+    "### Helper functions and variables for PG"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "42979690-97b5-4e86-8777-db48896539ac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def std_error(avg_val, avg_sqr, counter):\n",
+    "    \"\"\"\n",
+    "    Estimate the standard error from the average value\n",
+    "    and the average value of the square.\n",
+    "    \n",
+    "    :param avg_val: the average value\n",
+    "    :param avg_sqr: the average square value\n",
+    "    :param counter: the size of the sample\n",
+    "    \n",
+    "    :return: the standard error\n",
+    "    \"\"\"\n",
+    "\n",
+    "    return np.sqrt((avg_sqr - avg_val**2) / (counter - 1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "b13f968c-f9db-4b05-86ae-0e997383f9c1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def pass_fair_weather(df, scale_factor=None):\n",
+    "    \"\"\"\n",
+    "    Filter and adjust potential gradient (PG) data to represent fair weather conditions.\n",
+    "\n",
+    "    :param df: The input dataframe containing 'Field' values for hourly averaged potential gradient (PG) data\n",
+    "               and 'Count' values indicating the number of valid measurements per day.\n",
+    "    :param scale_factor: A factor used to normalize the 'Field' values to mitigate external influences\n",
+    "                         such as nearby metal structures (default is None, implying no scaling).\n",
+    "\n",
+    "    :return: A dataframe with hourly data filtered to likely represent fair weather conditions only.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # normalize 'Field' values by the scale_factor if provided.\n",
+    "    if scale_factor:\n",
+    "        df[\"Field\"] = df[\"Field\"] / scale_factor\n",
+    "    \n",
+    "    # exclude records with non-positive PG values\n",
+    "    df = df[df[\"Field\"] > 0]\n",
+    "    \n",
+    "    # exclude records with PG values > 300 V/m\n",
+    "    df = df[df[\"Field\"] <= 300]\n",
+    "    \n",
+    "    # retain only days with complete hourly data (24 counts)\n",
+    "    df[\"Count\"] = df[\"Field\"].resample('D').transform('count')\n",
+    "    df = df[df[\"Count\"] == 24]\n",
+    "    \n",
+    "    # compute diurnal PG stats\n",
+    "    df['Emax'] = df['Field'].resample('D').transform('max')\n",
+    "    df['Emin'] = df['Field'].resample('D').transform('min')\n",
+    "    df['Emean'] = df['Field'].resample('D').transform('mean')\n",
+    "    \n",
+    "    # exclude days with peak-to-peak amplitude over 150% of the daily mean\n",
+    "    df['Var'] = ((df[\"Emax\"]-df[\"Emin\"]))/df[\"Emean\"]\n",
+    "    df = df[df['Var'] <= 1.5]\n",
+    "    \n",
+    "    # # debug output for '5min' marked data counts per year\n",
+    "    # (averaged from 5-min data) included in individual years \n",
+    "    # z = df[df.Mark == '5min']\n",
+    "    # print(z.groupby(z.index.year).count()[\"Mark\"])\n",
+    "    \n",
+    "    # remove temporary columns used for calculations\n",
+    "    df = df[[\"Field\"]]\n",
+    "\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "350d271c-0337-4e2b-89df-f90a42671d5c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def calculate_seasonal_var_params(cond_df, key=\"Field\"):\n",
+    "    \"\"\"\n",
+    "    Calculate parameters necessary for assessing the seasonal \n",
+    "    variability of fair weather potential gradients (FW PG).\n",
+    "\n",
+    "    :param cond_df: DataFrame containing conditioned data with a datetime \n",
+    "                    index and at least one numerical column.\n",
+    "    :param key: Column label in 'cond_df' which contains the potential \n",
+    "                gradient data (default is 'Field').\n",
+    "\n",
+    "    :return: A list containing arrays of:\n",
+    "             monthly mean PG values, \n",
+    "             counts of fair weather days, and \n",
+    "             adjusted monthly mean square PG values.\n",
+    "    \"\"\"\n",
+    "    # compute the monthly mean of fair weather PG\n",
+    "    mon_pg = cond_df[key].groupby(cond_df.index.month).mean().to_numpy().flatten()\n",
+    "\n",
+    "    # count the number of fair weather days for each month\n",
+    "    mon_counter = cond_df.groupby(cond_df.index.month).count().to_numpy().flatten()\n",
+    "\n",
+    "    # sum((daily mean FW PG)**2)/(count FW days) over months\n",
+    "    mon_pg_sqr = cond_df[key].pow(2).groupby(cond_df.index.month).sum().to_numpy().flatten() / mon_counter\n",
+    "\n",
+    "    return [mon_pg, mon_counter, mon_pg_sqr]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "89b9f394-8d80-4db6-bd44-0b9778b03f9d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "month_name = [\"J\", \"F\", \"M\", \"A\", \"M\", \"J\", \"J\", \"A\", \"S\", \"O\", \"N\", \"D\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f1c0ca4-15bb-448e-b85b-1f6b3a8a555f",
+   "metadata": {},
+   "source": [
+    "### Applying fair weather criteria "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "d1f85dec-45b7-47b2-b421-d528776fff39",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# apply the fair weather filter to the newdataset with a scale factor of 3 to normalize field values.\n",
+    "df = pass_fair_weather(df_src, scale_factor=3)\n",
+    "\n",
+    "# apply the fair weather filter to earlier dataset data with a scale factor of 1 for normalization.\n",
+    "earlier_df = pass_fair_weather(earlier_df_src, scale_factor=1)\n",
+    "\n",
+    "# Optional: Adjust the scale factor to 1.35 for earlier data to equalize the mean values of FW histograms across datasets.\n",
+    "# earlier_df = pass_fair_weather(earlier_df, scale_factor=1.35)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "fbce521b-c249-4441-b962-9a7991fb521f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # debug figure for check the mean values of FW histograms\n",
+    "# fig, ax = plt.subplots(1,1)\n",
+    "# df.hist(ax=ax,bins=600, color='red')\n",
+    "# earlier_df.hist(ax=ax,bins=600, color='blue')\n",
+    "# plt.xlim(-200,500)\n",
+    "# plt.xlabel('V/m')\n",
+    "# plt.ylabel('Counts')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4aebf84b-3335-450e-8379-bee1f0f01c05",
+   "metadata": {},
+   "source": [
+    "### Resampling daily fair-weather datasets "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "c339ed78-e4ba-43a9-89b8-85e8a0c57236",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# resample the filtered data to calculate the daily mean of FW PG\n",
+    "# then drop any days with missing data to ensure completeness of the dataset\n",
+    "\n",
+    "daily_df = df.resample('D').mean().dropna()\n",
+    "daily_edf = earlier_df.resample('D').mean().dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "a0aa9a7f-c65a-46f7-bb85-fcd1c133e4be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# saving intermediate data for plotting in other scripts\n",
+    "\n",
+    "np.save('./data/Vostok/vostok_diurnal_2006_2020.npy', \n",
+    "        df.groupby(df.index.hour)\n",
+    "            .mean().dropna().to_numpy().flatten())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e5a58975-053a-4162-bccb-f0dbef39b0ed",
+   "metadata": {},
+   "source": [
+    "### Figure 1.2: Seasonal variation (new data) for different years"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "6d6b5a71-6dd3-4471-b081-f3606c7b6956",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate seasonal variation parameters for specific years: \n",
+    "# average FW PG, count of FW days, the sum of squares of FW PG hourly values\n",
+    "\n",
+    "data, data_counter, data_sqr = np.array(\n",
+    "    [\n",
+    "        calculate_seasonal_var_params(daily_df),\n",
+    "        calculate_seasonal_var_params(daily_df[daily_df.index.year <= 2012]),\n",
+    "        calculate_seasonal_var_params(daily_df[daily_df.index.year > 2012])\n",
+    "    ]\n",
+    ").swapaxes(0,1)\n",
+    "\n",
+    "data_counter = data_counter.astype(int)\n",
+    "\n",
+    "# saving intermediate data for plotting in other scripts\n",
+    "np.savez('./data/Vostok/vostok_2006_2020_results', mean=data, counter=data_counter, sqr=data_sqr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "4e29c652-918d-47e2-ac67-1d0c2a898eea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "ax = [None for _ in range(3)]\n",
+    "ax[0] = fig.add_subplot(4, 4, (2, 3))\n",
+    "for n in range(2, 4):\n",
+    "    ax[n-1] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "\n",
+    "low = [100] + [80] * 2\n",
+    "high = [180] * 3\n",
+    "step = [20] * 3\n",
+    "coeff = [1] * 3\n",
+    "caption = ['Vostok station, 2006–2020',\n",
+    "           'Vostok station, 2006–2012',\n",
+    "           'Vostok station, 2013–2020']\n",
+    "col = ['orangered'] * 3\n",
+    "\n",
+    "for n in range(3):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    ax[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]).astype(int),\n",
+    "                          fontsize='large')\n",
+    "    ax[n].set_ylabel('Monthly mean fair-weather\\npotential gradient, V/m',\n",
+    "                     fontsize='large')\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize='large')\n",
+    "\n",
+    "    ax[n].annotate('', xy=(12, np.min(data[n])), xycoords='data',\n",
+    "                   xytext=(12, np.max(data[n])), textcoords='data',\n",
+    "                   annotation_clip=False,\n",
+    "                   arrowprops=dict(\n",
+    "                       arrowstyle='<|-|>,head_length=0.8,head_width=0.3',\n",
+    "                       patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                       connectionstyle='arc3,rad=0.', fc='black',\n",
+    "                       linewidth=0.5\n",
+    "                   ))\n",
+    "\n",
+    "    ampl = (np.max(data[n]) - np.min(data[n])) / \\\n",
+    "        np.sum(data[n] * data_counter[n]) * np.sum(data_counter[n])\n",
+    "    ax[n].text(12.2, (np.min(data[n]) + np.max(data[n])) / 2,\n",
+    "               f'{ampl * 100:.0f}%',\n",
+    "               fontsize='large', ha='left', va='center', rotation=270)\n",
+    "\n",
+    "for n in range(3):\n",
+    "    ax[n].bar(np.arange(12), data[n],\n",
+    "              yerr=std_error(data[n],\n",
+    "                             data_sqr[n],\n",
+    "                             data_counter[n]),\n",
+    "              width=0.8, color=col[n])\n",
+    "\n",
+    "for n in range(3):\n",
+    "    ax[n].text(-0.3, 1.05, chr(ord('a') + n),\n",
+    "               fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.6)\n",
+    "\n",
+    "for n in range(3):\n",
+    "    for m in range(12):\n",
+    "        ax[n].annotate(f'{data_counter[n, m]}',\n",
+    "                       xy=(m-0.15, ax[n].get_ylim()[0] + 3),\n",
+    "                       rotation=270, ha='center', va='bottom',\n",
+    "                       fontsize='large', color='0.')\n",
+    "\n",
+    "fig.savefig('figures_two_parts/pg_total_partial.eps', bbox_inches='tight')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b65fb2a-8f3d-4d23-a8a2-c4c7f031c910",
+   "metadata": {},
+   "source": [
+    "### Figure 1.3: Diurnal-Seasonal Diagram"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "19eddef4-207d-4fcd-af6b-fc3fcd02e7cd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create a seasonal-diurnal array by grouping the data by hour of the day and month, \n",
+    "# then calculating the mean FW PG for each combination.\n",
+    "\n",
+    "sd_df = df.groupby([df.index.hour, df.index.month]).mean()\n",
+    "sd_df.index.set_names(['hour', 'month'], inplace=True)\n",
+    "\n",
+    "vostok_pg_data_to_plot = sd_df.values.reshape(24,12).T\n",
+    "vostok_mean_pg_data = vostok_pg_data_to_plot.mean(axis=1).reshape(12,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "5b03d7c6-e23e-45a9-8188-024d21851176",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate seasonal var params (avg FW PG, count FW days, \n",
+    "# sum of squares of FW PG) for specific years\n",
+    "data, data_counter, data_sqr = np.array(\n",
+    "    [\n",
+    "        calculate_seasonal_var_params(daily_df),\n",
+    "        calculate_seasonal_var_params(df[df.index.hour == 3]),\n",
+    "        calculate_seasonal_var_params(df[df.index.hour == 9]),\n",
+    "        calculate_seasonal_var_params(df[df.index.hour == 15]),\n",
+    "        calculate_seasonal_var_params(df[df.index.hour == 21]),\n",
+    "    ]\n",
+    ").swapaxes(0,1)\n",
+    "\n",
+    "data_counter = data_counter.astype(int)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "762c01a9-2ee5-428c-b331-ef44d1801127",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1100 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig_width = 10\n",
+    "fig_height = 11\n",
+    "\n",
+    "height = 12\n",
+    "heightC = 1\n",
+    "heightB = 12\n",
+    "hsep1 = 3.5\n",
+    "hsep2 = 5\n",
+    "hsep3 = 3.5\n",
+    "hsp = 3\n",
+    "tot_height = height + heightC + 2 * heightB + hsep1 + hsep2 + hsep3 + 2 * hsp\n",
+    "\n",
+    "width = 12\n",
+    "widthM = heightC/tot_height * fig_height/fig_width\n",
+    "widthB = 12\n",
+    "wsep1 = 1\n",
+    "wsep2 = 3.5\n",
+    "wsp = 4\n",
+    "wshift = 1.5\n",
+    "tot_width = (width + widthB + wsep1 + wsep2 + 2 * wsp) / (1 - widthM)\n",
+    "widthM *= tot_width\n",
+    "\n",
+    "fig = plt.figure(figsize=(fig_width, fig_height), constrained_layout=False)\n",
+    "\n",
+    "ax = fig.add_axes(\n",
+    "    (\n",
+    "        (wsp - wshift) / tot_width,\n",
+    "        (hsp + 2 * heightB + hsep2 + hsep3 + heightC + hsep1) / tot_height,\n",
+    "        width / tot_width,\n",
+    "        height / tot_height\n",
+    "    )\n",
+    ")\n",
+    "axM = fig.add_axes(\n",
+    "    (\n",
+    "        (wsp - wshift + width + wsep1) / tot_width,\n",
+    "        (hsp + 2 * heightB + hsep2 + hsep3 + heightC + hsep1) / tot_height,\n",
+    "        widthM / tot_width,\n",
+    "        height / tot_height\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "axB = [None for _ in range(5)]\n",
+    "\n",
+    "axB[0] = fig.add_axes(\n",
+    "    (\n",
+    "        (wsp + width + wsep1 + widthM + wsep2) / tot_width,\n",
+    "        (hsp + heightB + hsep2 + hsep3 + heightC + hsep1 + height) / tot_height,\n",
+    "        widthB / tot_width,\n",
+    "        heightB / tot_height\n",
+    "    )\n",
+    ")\n",
+    "for n in range(2):\n",
+    "    axB[3 - 2*n] = fig.add_axes(\n",
+    "        (\n",
+    "            wsp / tot_width,\n",
+    "            (hsp + n * (heightB + hsep3)) / tot_height,\n",
+    "            widthB / tot_width,\n",
+    "            heightB / tot_height\n",
+    "        )\n",
+    "    )\n",
+    "    axB[4 - 2*n] = fig.add_axes(\n",
+    "        (\n",
+    "            (wsp + width + wsep1 + widthM + wsep2) / tot_width,\n",
+    "            (hsp + n * (heightB + hsep3)) / tot_height,\n",
+    "            widthB / tot_width,\n",
+    "            heightB / tot_height\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "caption = 'Pot. gradient, Vostok station, 2006–2020'\n",
+    "\n",
+    "for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "    ax.spines[axis].set_linewidth(0.5)\n",
+    "ax.tick_params(length=6, width=0.5)\n",
+    "ax.tick_params(length=0, width=0.5, which='minor')\n",
+    "ax.grid(False)\n",
+    "\n",
+    "ax.set_xlim((0, 24))\n",
+    "ax.set_xticks(np.arange(0, 25, 2))\n",
+    "ax.set_xticklabels(np.arange(0, 25, 2), fontsize='large')\n",
+    "ax.set_xlabel('UTC, hours', fontsize='large')\n",
+    "\n",
+    "ax.set_ylim((0, 12))\n",
+    "ax.set_yticks(np.arange(0, 12.5, 1))\n",
+    "ax.set_yticks(np.arange(0.5, 12, 1), minor=True)\n",
+    "ax.set_yticklabels([])\n",
+    "ax.set_yticklabels(month_name, fontsize='large', ha='center',\n",
+    "                   minor=True)\n",
+    "tr = []\n",
+    "for label in ax.yaxis.get_majorticklabels():\n",
+    "    tr.append(label.get_transform())\n",
+    "for label in ax.yaxis.get_minorticklabels():\n",
+    "    label.set_transform(\n",
+    "        tr[0] + tf.ScaledTranslation(\n",
+    "            -0.05, 0, fig.dpi_scale_trans\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "    axM.spines[axis].set_linewidth(0.5)\n",
+    "axM.tick_params(length=0, width=0.5)\n",
+    "axM.tick_params(length=6, width=0.5, which='minor')\n",
+    "axM.grid(False)\n",
+    "\n",
+    "axM.set_xlim((0, 1))\n",
+    "axM.set_xticks([])\n",
+    "axM.set_xticks([0.5], minor=True)\n",
+    "axM.set_xticklabels([])\n",
+    "axM.set_xticklabels(['mean'], fontsize='large', minor=True)\n",
+    "\n",
+    "axM.set_ylim((0, 12))\n",
+    "axM.set_yticks([])\n",
+    "axM.set_yticklabels([])\n",
+    "\n",
+    "lbl = ax.set_title(caption, fontsize='large')\n",
+    "pos = (width + wsep1 + widthM) / 2 / width\n",
+    "lbl.set_position((pos, 1.))\n",
+    "\n",
+    "# the bounds of the colour bars (in V/m)\n",
+    "pg_bound = np.arange(100, 191, 10)\n",
+    "\n",
+    "# the colours\n",
+    "colour_hour = np.array([[71, 71, 255], [1, 14, 236],\n",
+    "                        [4, 79, 149], [6, 143, 63], [49, 192, 13],\n",
+    "                        [142, 220, 7], [234, 249, 1], [255, 184, 0],\n",
+    "                        [255, 92, 0], [255, 0, 0]]) / 255\n",
+    "\n",
+    "pg_cmap = colors.ListedColormap(colour_hour[1:])\n",
+    "pg_norm = colors.BoundaryNorm(pg_bound, pg_cmap.N)\n",
+    "\n",
+    "pg_cax = fig.add_axes(\n",
+    "    (\n",
+    "        (wsp - wshift) / tot_width,\n",
+    "        (hsp + 2 * heightB + hsep2 + hsep3) / tot_height,\n",
+    "        (width + wsep1 + widthM)  / tot_width,\n",
+    "        heightC / tot_height\n",
+    "    )\n",
+    ")\n",
+    "pg_cbar = fig.colorbar(cm.ScalarMappable(norm=pg_norm,\n",
+    "                                         cmap=pg_cmap),\n",
+    "                       cax=pg_cax, orientation='horizontal')\n",
+    "pg_cbar.outline.set_linewidth(0.5)\n",
+    "pg_cbar.ax.tick_params(length=6, width=0.5)\n",
+    "pg_cbar.set_ticks(pg_bound)\n",
+    "pg_cbar.ax.set_xticklabels(list(map(str,\n",
+    "                                    pg_bound.astype(int))),\n",
+    "                           fontsize='large')\n",
+    "pg_cbar.set_label('Potential gradient, V/m',\n",
+    "                  fontsize='large')\n",
+    "\n",
+    "ax.imshow(vostok_pg_data_to_plot,\n",
+    "          cmap=pg_cmap, norm=pg_norm,\n",
+    "          extent=[0, 24, 12, 0], aspect='auto', interpolation='none',\n",
+    "          rasterized=True)\n",
+    "\n",
+    "axM.imshow(vostok_mean_pg_data,\n",
+    "           cmap=pg_cmap, norm=pg_norm,\n",
+    "           extent=[0, 1, 12, 0], aspect='auto', interpolation='none',\n",
+    "           rasterized=True)\n",
+    "\n",
+    "low = [100] + [80] * 2 + [100] * 2\n",
+    "high = [180] * 3 + [200] * 2\n",
+    "step = [20] * 5\n",
+    "coeff = [1] * 5\n",
+    "captionB = ['Vostok station, 2006–2020, diurnal mean',\n",
+    "            'Vostok station, 2006–2020, 3–4 UTC',\n",
+    "            'Vostok station, 2006–2020, 9–10 UTC',\n",
+    "            'Vostok station, 2006–2020, 15–16 UTC',\n",
+    "            'Vostok station, 2006–2020, 21–22 UTC']\n",
+    "\n",
+    "col = ['orangered'] * 5\n",
+    "\n",
+    "for n in range(5):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        axB[n].spines[axis].set_linewidth(0.5)\n",
+    "    axB[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    axB[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    axB[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    axB[n].set_xlim((-0.5, 11.5))\n",
+    "    axB[n].set_xticks(np.arange(12))\n",
+    "    axB[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    axB[n].set_ylim((low[n], high[n]))\n",
+    "    axB[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    axB[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                      step[n]) / coeff[n]).astype(int),\n",
+    "                           fontsize='large')\n",
+    "    axB[n].set_ylabel('Monthly mean fair-weather\\npotential gradient, V/m',\n",
+    "                      fontsize='large')\n",
+    "\n",
+    "    axB[n].set_title(captionB[n], fontsize='large')\n",
+    "\n",
+    "    axB[n].annotate('', xy=(12, np.min(data[n])), xycoords='data',\n",
+    "                    xytext=(12, np.max(data[n])), textcoords='data',\n",
+    "                    annotation_clip=False,\n",
+    "                    arrowprops=dict(\n",
+    "                        arrowstyle='<|-|>,head_length=0.8,head_width=0.3',\n",
+    "                        patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                        connectionstyle='arc3,rad=0.', fc='black',\n",
+    "                        linewidth=0.5\n",
+    "                    ))\n",
+    "\n",
+    "    ampl = (np.max(data[n]) - np.min(data[n])) / \\\n",
+    "        np.sum(data[n] * data_counter[n]) * np.sum(data_counter[n])\n",
+    "    axB[n].text(12.2, (np.min(data[n]) + np.max(data[n])) / 2,\n",
+    "                f'{ampl * 100:.0f}%',\n",
+    "                fontsize='large', ha='left', va='center', rotation=270)\n",
+    "\n",
+    "for n in range(5):\n",
+    "    axB[n].bar(np.arange(12), data[n],\n",
+    "               yerr=std_error(data[n],\n",
+    "                              data_sqr[n],\n",
+    "                              data_counter[n]),\n",
+    "               width=0.8, color=col[n])\n",
+    "\n",
+    "ax.text(-(0.3 * widthB - wshift)/width, 1 + 0.05 * heightB/height, 'a',\n",
+    "        fontsize='x-large',\n",
+    "        fontweight='semibold', ha='left', va='bottom',\n",
+    "        transform=ax.transAxes)\n",
+    "for n in range(5):\n",
+    "    axB[n].text(-0.3, 1.05, chr(ord('b') + n),\n",
+    "                fontsize='x-large',\n",
+    "                fontweight='semibold', ha='left', va='bottom',\n",
+    "                transform=axB[n].transAxes)\n",
+    "\n",
+    "fig.savefig('figures_two_parts/pg_diurnal_seasonal.eps', bbox_inches='tight')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7b9bf03b-5a1b-4ccf-aaf7-c47337cd05a1",
+   "metadata": {},
+   "source": [
+    "### Data adjustment using meteoparameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "d16e0930-f81f-4288-a7a9-2f3942194f81",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# load and filter meteorological data from CSV files into separate dataframes, \n",
+    "# then join them with the daily FW PG dataframe to create a combined dataframe\n",
+    "# without missing values\n",
+    "\n",
+    "temp_df = pd.read_csv('./data/Vostok/vostok_daily_temp.csv', parse_dates=['UTC']).set_index('UTC')\n",
+    "temp_df = temp_df[temp_df[\"COUNT\"] == 4][['T']]\n",
+    "\n",
+    "wind_df = pd.read_csv('./data/Vostok/vostok_daily_wind.csv', parse_dates=['UTC']).set_index('UTC')\n",
+    "wind_df = wind_df[wind_df[\"COUNT\"] == 4][['Ff']]\n",
+    "\n",
+    "pressure_df = pd.read_csv('./data/Vostok/vostok_daily_pressure_mm_hg.csv', parse_dates=['UTC']).set_index('UTC')\n",
+    "pressure_df = pressure_df[pressure_df[\"COUNT\"] == 4][['Po']]\n",
+    "\n",
+    "meteo_df = temp_df.join([wind_df, pressure_df, daily_df]).dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "c45bdf6b-d725-4d87-b033-d90fa4f3f9a9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate anomalies for potential gradient (pg_anom), temperature\n",
+    "# (temp_anom), wind speed (wind_anom), and pressure (pres_anom)\n",
+    "# based on a moving average window of +/-10 days.\n",
+    "\n",
+    "pg_anom = np.zeros((len(meteo_df.index)))\n",
+    "temp_anom = np.zeros((len(meteo_df.index)))\n",
+    "wind_anom = np.zeros((len(meteo_df.index)))\n",
+    "pres_anom = np.zeros((len(meteo_df.index)))\n",
+    "\n",
+    "halfwidth = 10\n",
+    "for i in range(len(meteo_df.index)):\n",
+    "    sum_pg = 0\n",
+    "    sum_temp = 0\n",
+    "    sum_pres = 0\n",
+    "    sum_wind = 0\n",
+    "    counter = 0\n",
+    "    for j in range(max(i - halfwidth, 0),\n",
+    "                   min(i + halfwidth + 1, len(meteo_df.index))):\n",
+    "        if abs((meteo_df.index[j]-meteo_df.index[i]).days) <= halfwidth:\n",
+    "            sum_pg += meteo_df[\"Field\"].iloc[j]\n",
+    "            sum_temp += meteo_df[\"T\"].iloc[j]\n",
+    "            sum_pres += meteo_df[\"Po\"].iloc[j]\n",
+    "            sum_wind += meteo_df[\"Ff\"].iloc[j]\n",
+    "            counter += 1\n",
+    "    pg_anom[i] =  meteo_df[\"Field\"].iloc[i] - (sum_pg / counter)\n",
+    "    temp_anom[i] =  meteo_df[\"T\"].iloc[i] - (sum_temp / counter)\n",
+    "    wind_anom[i] =  meteo_df[\"Ff\"].iloc[i] - (sum_wind / counter)\n",
+    "    pres_anom[i] =  meteo_df[\"Po\"].iloc[i] - (sum_pres / counter)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "326311ea-74ce-4de1-ac7a-e30e173fc8d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Temp: a=-0.38283510510880514\tb=-0.003032362343859364\n",
+      "Temp: Correlation coefficient: −0.08\n",
+      "Temp: Significance level: 0.01.\n",
+      "Temp: Number of points: 2252.\n",
+      "Temp: Critical value (((P − 2)r^2/(1 − r^2))^(1/2)): 2.578016182019777.\n",
+      "Temp: Threshold correlation coefficient: 0.0542692606142489.\n",
+      "\n",
+      "\n",
+      "Wind: a=2.9091927832965867\tb=-0.005838450636248837\n",
+      "Wind: Correlation coefficient: 0.13\n",
+      "Wind: Significance level: 0.01.\n",
+      "Wind: Number of points: 2252.\n",
+      "Wind: Critical value (((P − 2)r^2/(1 − r^2))^(1/2)): 2.578016182019777.\n",
+      "Wind: Threshold correlation coefficient: 0.0542692606142489.\n",
+      "\n",
+      "\n",
+      "Pres: a=0.029923256849570173\tb=-0.008695565945834233\n",
+      "Pres: Correlation coefficient: 0.01\n",
+      "Pres: Significance level: 0.01.\n",
+      "Pres: Number of points: 2252.\n",
+      "Pres: Critical value (((P − 2)r^2/(1 − r^2))^(1/2)): 2.578016182019777.\n",
+      "Pres: Threshold correlation coefficient: 0.0542692606142489.\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculate linear regression coefficients for temperature, wind speed \n",
+    "# and pressure anomalies against potential gradient anomalies.\n",
+    "\n",
+    "temp_coeffs = np.polyfit(temp_anom, pg_anom, deg=1)\n",
+    "wind_coeffs = np.polyfit(wind_anom, pg_anom, deg=1)\n",
+    "pres_coeffs = np.polyfit(pres_anom, pg_anom, deg=1)\n",
+    "\n",
+    "\n",
+    "for title, anom, coeffs in zip(\n",
+    "    [\"Temp\", \"Wind\", \"Pres\"],\n",
+    "    [temp_anom, wind_anom, pres_anom],\n",
+    "    [temp_coeffs, wind_coeffs, pres_coeffs],\n",
+    "):\n",
+    "    P = len(meteo_df.index)  # the number of points\n",
+    "    a = 0.01  # significance level\n",
+    "\n",
+    "    q = st.t.ppf(1 - a / 2, P - 2) # critical value\n",
+    "    r = q / np.sqrt(q**2 + P - 2) # threshold correlation coefficient\n",
+    "\n",
+    "    corr = np.corrcoef(anom, pg_anom)[0, 1]\n",
+    "    print(f\"{title}: a={coeffs[0]}\\tb={coeffs[1]}\")\n",
+    "    print(\n",
+    "        f\"{title}: Correlation coefficient: −{-corr:.2f}\"\n",
+    "        if corr < 0\n",
+    "        else f\"{title}: Correlation coefficient: {corr:.2f}\"\n",
+    "    )\n",
+    "    print(f\"{title}: Significance level: {a}.\")\n",
+    "    print(f\"{title}: Number of points: {P}.\")\n",
+    "    print(f\"{title}: Critical value (((P − 2)r^2/(1 − r^2))^(1/2)): {q}.\")\n",
+    "    print(f\"{title}: Threshold correlation coefficient: {r}.\")\n",
+    "    print(\"\\n\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "dafd0f56-b6fa-4883-9640-01fdcb4a3870",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# update the \"CorrectedField\" column (copy of \"Field\" column) in the `meteo_df`\n",
+    "# by subtracting the linear regression adjustments \n",
+    "# based on temperature and wind anomalies.\n",
+    "\n",
+    "meteo_df[\"CorrectedField\"] = meteo_df[\"Field\"]\n",
+    "meteo_df[\"CorrectedField\"] -= temp_coeffs[0] * (meteo_df[\"T\"] - meteo_df[\"T\"].mean())\n",
+    "meteo_df[\"CorrectedField\"] -= wind_coeffs[0] * (meteo_df[\"Ff\"] - meteo_df[\"Ff\"].mean())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0590fff-4817-440f-9550-d4438b742769",
+   "metadata": {},
+   "source": [
+    "### Figure 1.5: source vs adjustment PG for new and earlier Vostok datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "9a209c25-af4a-4c67-80cc-2ce657f9cb3d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate seasonal variation parameters for specific years: \n",
+    "# average FW PG, count of FW days, and the sum of squares of FW PG hourly values\n",
+    "\n",
+    "data, data_counter, data_sqr = np.array(\n",
+    "    [\n",
+    "        calculate_seasonal_var_params(daily_edf[daily_edf.index.year <= 2001]),\n",
+    "        [vostok_old_data, np.zeros(12).astype(int), np.zeros(12)],\n",
+    "        calculate_seasonal_var_params(daily_df),\n",
+    "        calculate_seasonal_var_params(meteo_df[[\"CorrectedField\"]], key=\"CorrectedField\")\n",
+    "    ]\n",
+    ").swapaxes(0,1)\n",
+    "\n",
+    "data_counter = data_counter.astype(int)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "84050d4a-259f-4513-8d91-0ffc9840f542",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "ax = [None for _ in range(4)]\n",
+    "\n",
+    "for n in range(4):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "\n",
+    "low = [140] * 2 + [100] * 2\n",
+    "high = [220] * 2 + [180] * 2\n",
+    "step = [20] * 4\n",
+    "coeff = [1] * 4\n",
+    "\n",
+    "caption = ['Vostok station, 1998–2001',\n",
+    "           'Vostok station, 1998–2001 (adjusted)',\n",
+    "           'Vostok station, 2006–2020',\n",
+    "           'Vostok station, 2006–2020 (adjusted)']\n",
+    "col = ['orangered'] * 4\n",
+    "\n",
+    "for n in range(4):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    ax[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]).astype(int),\n",
+    "                          fontsize='large')\n",
+    "    ax[n].set_ylabel('Monthly mean fair-weather\\npotential gradient, V/m',\n",
+    "                     fontsize='large')\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize='large')\n",
+    "    if np.sum(data_counter[n]) == 0:\n",
+    "        ax[n].text(0.5,\n",
+    "                   1 - 0.01\n",
+    "                   * (ax[n].get_position().x1 - ax[n].get_position().x0)\n",
+    "                   / (ax[n].get_position().y1 - ax[n].get_position().y0)\n",
+    "                   * fig.get_size_inches()[0] / fig.get_size_inches()[1],\n",
+    "                   '(after $\\it{Burns~et~al.}$, 2012)',\n",
+    "                   fontsize='large', ha='center', va='top',\n",
+    "                   transform=ax[n].transAxes)\n",
+    "\n",
+    "    ax[n].annotate('', xy=(12, np.min(data[n])), xycoords='data',\n",
+    "                   xytext=(12, np.max(data[n])), textcoords='data',\n",
+    "                   annotation_clip=False,\n",
+    "                   arrowprops=dict(\n",
+    "                       arrowstyle='<|-|>,head_length=0.8,head_width=0.3',\n",
+    "                       patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                       connectionstyle='arc3,rad=0.', fc='black',\n",
+    "                       linewidth=0.5\n",
+    "                   ))\n",
+    "    if np.sum(data_counter[n]) == 0:\n",
+    "        ampl = (np.max(data[n]) - np.min(data[n])) / np.mean(data[n])\n",
+    "    else:\n",
+    "        ampl = (np.max(data[n]) - np.min(data[n])) / \\\n",
+    "            np.sum(data[n] * data_counter[n]) * np.sum(data_counter[n])\n",
+    "    ax[n].text(12.2, (np.min(data[n]) + np.max(data[n])) / 2,\n",
+    "               f'{ampl * 100:.0f}%',\n",
+    "               fontsize='large', ha='left', va='center', rotation=270)\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2]])\n",
+    "fig.align_ylabels([ax[1], ax[3]])\n",
+    "\n",
+    "for n in range(4):\n",
+    "    if np.sum(data_counter[n]) == 0:\n",
+    "        ax[n].bar(np.arange(12), data[n],\n",
+    "          width=0.8, color=col[n])\n",
+    "    else:\n",
+    "        ax[n].bar(np.arange(12), data[n],\n",
+    "                  yerr=std_error(data[n],\n",
+    "                                 data_sqr[n],\n",
+    "                                 data_counter[n]),\n",
+    "                  width=0.8, color=col[n])\n",
+    "\n",
+    "for n in range(4):\n",
+    "    ax[n].text(-0.3, 1.05, chr(ord('a') + n), fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.6)\n",
+    "\n",
+    "for n in range(4):\n",
+    "    if np.sum(data_counter[n]) > 0:\n",
+    "        for m in range(12):\n",
+    "            ax[n].annotate(f'{data_counter[n, m]}',\n",
+    "                           xy=(m-0.15, ax[n].get_ylim()[0] + 3),\n",
+    "                           rotation=270, ha='center', va='bottom',\n",
+    "                           fontsize='large', color='0.')\n",
+    "\n",
+    "fig.savefig('figures_two_parts/pg_corrected.eps', bbox_inches='tight')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83a15933-44ff-4abc-baf6-7a99a069f8ca",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/3_WRF_T2_images.ipynb b/3_WRF_T2_images.ipynb
new file mode 100644
index 0000000..9822146
--- /dev/null
+++ b/3_WRF_T2_images.ipynb
@@ -0,0 +1,192 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0f09a974-37fe-440e-8daf-4aa0f2caae69",
+   "metadata": {},
+   "source": [
+    "# Analysis of temperature seasonal variation across a latitude bands\n",
+    "Figure 1.4 and 2.3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a464e3d4-2cd3-470e-8f29-7f8f6793eb6e",
+   "metadata": {},
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "9a80a0a4-ef03-411d-b441-21434947e6ac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "56ca6e5b-3400-4ba7-a050-9e241da9dea8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# montly averaged 2-meter level temperature (T2m) for each 1° latitude band across a full 360° longitude\n",
+    "# T2m are calculated with the Weather Research and Forecasting model (WRF) version 4.3.\n",
+    "# shape = (180, 12)\n",
+    "wrf_mon_T2 = np.load(\"./data/WRF/WRF_T2_LATxMON.npy\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4161a87b-68b7-4fc2-aeff-3a05404a4bab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# area factors for different latitudes\n",
+    "area_factor = (\n",
+    "    np.cos(np.arange(180) * np.pi / 180) - np.cos(np.arange(1, 181) * np.pi / 180)\n",
+    ") / 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "3ce18021-7bed-43a9-ba6d-6a4436700fff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "month_name = [\"J\", \"F\", \"M\", \"A\", \"M\", \"J\", \"J\", \"A\", \"S\", \"O\", \"N\", \"D\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "33118b18-72fc-464a-a710-a7606a031e15",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# boundary latitudes for the plot\n",
+    "lat = [20, 30, 40, 50]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "4ed444ff-2b06-416a-ac08-bf56eda7ae12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "ax = [None for _ in range(4)]\n",
+    "for n in range(4):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2 * n + 1, 2 * n + 2))\n",
+    "\n",
+    "low = [23, 22, 20, 18]\n",
+    "high = [27, 26, 24, 22]\n",
+    "step = [1] * 4\n",
+    "coeff = [1] * 4\n",
+    "caption = [f\"WRF, 1980–2020, {lt}° S–{lt}° N\" for lt in lat]\n",
+    "# thin spaces (' ') are used between ‘°’ signs and letters\n",
+    "col = [\"firebrick\"] * 4\n",
+    "\n",
+    "for n in range(4):\n",
+    "    for axis in [\"top\", \"bottom\", \"left\", \"right\"]:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis=\"y\")\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis=\"x\")\n",
+    "    ax[n].grid(color=\"0.\", linewidth=0.5, axis=\"y\")\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize=\"large\", va=\"top\")\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels(\n",
+    "        (np.arange(low[n], high[n] + step[n] / 2, step[n]) / coeff[n]).astype(int),\n",
+    "        fontsize=\"large\",\n",
+    "    )\n",
+    "    ax[n].set_ylabel(\"Mean surface\\nair temperature, °C\", fontsize=\"large\")\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize=\"large\")\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2]])\n",
+    "fig.align_ylabels([ax[1], ax[3]])\n",
+    "\n",
+    "for n in range(4):\n",
+    "    # normalization of temperature values on the \n",
+    "    # area of degree cells before summation:\n",
+    "    # T_avg =(T_1*S_1+T_2*S_2+...+T_2*S_N)/(S_1 + S_2 + ... +S_N)\n",
+    "    T_values = np.sum(\n",
+    "        wrf_mon_T2[90 - lat[n] : 90 + lat[n]]\n",
+    "        * area_factor[90 - lat[n] : 90 + lat[n], np.newaxis],\n",
+    "        axis=0,\n",
+    "    ) / np.sum(area_factor[90 - lat[n] : 90 + lat[n]])\n",
+    "    \n",
+    "    ax[n].bar(np.arange(12), T_values, width=0.8, color=col[n])\n",
+    "\n",
+    "for n in range(4):\n",
+    "    ax[n].text(\n",
+    "        -0.25, 1.05,\n",
+    "        chr(ord(\"a\") + n),\n",
+    "        fontsize=\"x-large\",\n",
+    "        fontweight=\"semibold\",\n",
+    "        ha=\"left\", va=\"bottom\",\n",
+    "        transform=ax[n].transAxes,\n",
+    "    )\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.0)\n",
+    "\n",
+    "fig.savefig(\n",
+    "    \"figures_two_parts/t2.eps\", bbox_inches=\"tight\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e9b11449-5115-492e-8529-c9bfb01a65f9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/4_IP_simulations_temporal_images.ipynb b/4_IP_simulations_temporal_images.ipynb
new file mode 100644
index 0000000..7dd816d
--- /dev/null
+++ b/4_IP_simulations_temporal_images.ipynb
@@ -0,0 +1,567 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3c579838-fc52-4949-999a-0f7b0aa70449",
+   "metadata": {},
+   "source": [
+    "# Analysis of simulated IP grouped by model parameters and years"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2a991079-f69f-4b4e-85e9-dd0eb6817d17",
+   "metadata": {},
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "e6e8b28e-203f-4c4b-907f-fe6183e5d331",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import datetime as dt\n",
+    "\n",
+    "import numpy as np\n",
+    "import scipy.stats as st\n",
+    "\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "83163834-de47-4f28-8add-768c7b76e1d3",
+   "metadata": {},
+   "source": [
+    "### Helper functions, variables and classes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "61405aa1-0b4d-4a8a-85a5-3097d37c644e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "month_name = [\"J\", \"F\", \"M\", \"A\", \"M\", \"J\", \"J\", \"A\", \"S\", \"O\", \"N\", \"D\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "42ca4c03-8fbf-451c-bd17-607e42450130",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def std_error(avg_val, avg_sqr, counter):\n",
+    "    \"\"\"\n",
+    "    Estimate the standard error from the average value\n",
+    "    and the average value of the square.\n",
+    "    \n",
+    "    :param avg_val: the average value\n",
+    "    :param avg_sqr: the average square value\n",
+    "    :param counter: the size of the sample\n",
+    "    \n",
+    "    :return: the standard error\n",
+    "    \"\"\"\n",
+    "\n",
+    "    return np.sqrt((avg_sqr - avg_val**2) / (counter - 1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d00db06e-dd79-4422-b62b-f10ca8a81f9a",
+   "metadata": {},
+   "source": [
+    "### Loading precalculated arrays"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2dd01e73-6586-4e1b-b519-4f3e84ae8940",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# numbers of simulated days for analysis\n",
+    "wrf_N_days = 4992\n",
+    "inm_N_days = 3650"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "9252215e-9586-444e-bb63-b65dcb945dd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dates corresponding to the indices (0 axis) of the data arrays\n",
+    "# note: for WRF dates correspond to real dates\n",
+    "\n",
+    "wrf_dt_indicies = np.array(\n",
+    "    [dt.date(1980, 1, 1) + dt.timedelta(i * 3) for i in range(wrf_N_days)]\n",
+    ")\n",
+    "\n",
+    "inm_dt_indicies = np.array(\n",
+    "    [dt.date(2022, 1, 1) + dt.timedelta(i % 365) for i in range(inm_N_days)]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "69602993-2005-4fed-b425-69575f9fd2cf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dictionaries where processed data is saved. The dictionary keys represent the\n",
+    "# threshold value of CAPE - integer numbers from the list 500, 800, 1000, 1200,\n",
+    "# where the key 500 relates only to temperature-based modeling and is present \n",
+    "# only in dictionaries wrf_<...>, while keys 800, 1000, 1200 correspond to \n",
+    "# classical modeling using the WRF or INMCM model.\n",
+    "\n",
+    "# dict contains arrays with dimensions (4992, 24)\n",
+    "# where axis 0 contains the day index (see `wrf_dt_indicies`)\n",
+    "wrf_hourly_total_ip = {\n",
+    "    key: np.load(f\"./data/WRF/WRF_HOURLY_TOTAL_IP_{parameters}.npy\")[:wrf_N_days]\n",
+    "    for key, parameters in zip([500, 800, 1000, 1200],\n",
+    "                              [\"500_T2_25\", \"800\", \"1000\", \"1200\"])\n",
+    "}\n",
+    "\n",
+    "# dict contains arrays with dimensions (3650, 24)\n",
+    "# where axis 0 contains the day index (see `inm_dt_indicies`)\n",
+    "# note:  years in `inm_dt_indicies` is not real\n",
+    "inm_hourly_total_ip = {\n",
+    "    key: np.load(f\"./data/INMCM/INMCM_HOURLY_TOTAL_IP_{parameters}.npy\")[:inm_N_days]\n",
+    "    for key, parameters in zip([800, 1000, 1200],\n",
+    "                              [\"800\", \"1000\", \"1200\"])\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ae294872-6a91-44d9-8f26-17ab169a9c30",
+   "metadata": {},
+   "source": [
+    "### Figure 2.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "b57ba36b-077d-4fd0-8d7b-f0755d3c9b45",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate seasonal variation parameters for different parametrizations\n",
+    "\n",
+    "# 7 sets for different axes of the figure\n",
+    "# each set with 12 values for each month\n",
+    "\n",
+    "# monthly mean values of IP \n",
+    "data = np.zeros((7, 12))\n",
+    "\n",
+    "# count of days per month\n",
+    "data_counter = np.zeros((7, 12), dtype=int)\n",
+    "\n",
+    "# the sum of squares of IP daily values\n",
+    "data_sqr = np.zeros((7, 12))\n",
+    "\n",
+    "for j, cape_thres in enumerate([800, 1000, 1200]):\n",
+    "    for m in range(12):\n",
+    "\n",
+    "        # the indices `ax_idx` from 0 to 6 correspond to the axes:\n",
+    "        # 0 - WRF, 1980-2020, CAPE=800,\n",
+    "        # 1 - INMCM, 10 years, CAPE=800,\n",
+    "        # 2 - WRF, 1980-2020, CAPE=1000,\n",
+    "        # 3 - INMCM, 10 years, CAPE=1000,\n",
+    "        # 4 - WRF, 1980-2020, CAPE=1200,\n",
+    "        # 5 - INMCM, 10 years, CAPE=1200,\n",
+    "        # 6 - Vostok station, 2006-2020\n",
+    "\n",
+    "        # calculate axes index for WRF axes (0, 2, 4)\n",
+    "        ax_idx = j * 2\n",
+    "\n",
+    "        # filtering day indices belonging to a specific month\n",
+    "        wrf_inds = [i for i, date in enumerate(wrf_dt_indicies) \n",
+    "                    if date.month == m + 1]\n",
+    "\n",
+    "        # slice IP for specific CAPE and day indices\n",
+    "        ip = wrf_hourly_total_ip[cape_thres][wrf_inds]\n",
+    "\n",
+    "        # calculate seasonal variation parameters\n",
+    "        data[ax_idx, m] = ip.mean()\n",
+    "        data_counter[ax_idx, m] = len(ip)\n",
+    "        data_sqr[ax_idx, m] = np.sum(ip.mean(axis=-1) ** 2) / len(ip)\n",
+    "\n",
+    "        # calculate axes index for INMCM axes (1, 3, 5)\n",
+    "        ax_idx = j * 2 + 1\n",
+    "\n",
+    "        # filtering day indices belonging to a specific month\n",
+    "        inmcm_inds =[i for i, date in enumerate(inm_dt_indicies) \n",
+    "                     if date.month == m + 1]\n",
+    "        \n",
+    "        # slice IP for specific CAPE and day indices\n",
+    "        ip = inm_hourly_total_ip[cape_thres][inmcm_inds]\n",
+    "\n",
+    "        # calculate seasonal variation parameters\n",
+    "        data[ax_idx, m] = ip.mean()\n",
+    "        data_counter[ax_idx, m] = len(ip)\n",
+    "        data_sqr[ax_idx, m] = np.sum(ip.mean(axis=-1) ** 2) / len(ip)\n",
+    "\n",
+    "# the last set is loaded from the processed data of Vostok station in script 2\n",
+    "# the data is loaded as a dictionary with keys `mean`, `counter`, `sqr`\n",
+    "# index 0: 2006-2020, index 1: 2006-2012, index 2: 2013-2020\n",
+    "vostok_results = np.load(\"./data/Vostok/vostok_2006_2020_results.npz\")\n",
+    "\n",
+    "data[-1] = vostok_results[\"mean\"][0]\n",
+    "data_counter[-1] = vostok_results[\"counter\"][0]\n",
+    "data_sqr[-1] = vostok_results[\"sqr\"][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a2da339e-fd7a-4a90-a79b-b7f81e563d94",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 7 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "ax = [None for _ in range(7)]\n",
+    "for n in range(6):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "ax[6] = fig.add_subplot(4, 4, (14, 15))\n",
+    "\n",
+    "low = [200e3] * 6 + [100]\n",
+    "high = [280e3] * 6 + [180]\n",
+    "step = [20e3] * 6 + [20]\n",
+    "coeff = [1e3] * 6 + [1]\n",
+    "caption = [\"WRF, 1980–2020, $\\\\varepsilon_0 = 0.8$ kJ/kg\",\n",
+    "           \"INMCM, 10 years, $\\\\varepsilon_0 = 0.8$ kJ/kg\",\n",
+    "           \"WRF, 1980–2020, $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"INMCM, 10 years, $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"WRF, 1980–2020, $\\\\varepsilon_0 = 1.2$ kJ/kg\",\n",
+    "           \"INMCM, 10 years, $\\\\varepsilon_0 = 1.2$ kJ/kg\",\n",
+    "           \"Vostok station, 2006–2020\"]\n",
+    "\n",
+    "col = [\"royalblue\"] * 6 + [\"orangered\"]\n",
+    "\n",
+    "for n in range(7):\n",
+    "    for axis in [\"top\", \"bottom\", \"left\", \"right\"]:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis=\"y\")\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis=\"x\")\n",
+    "    ax[n].grid(color=\"0.\", linewidth=0.5, axis=\"y\")\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize=\"large\", va=\"top\")\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]).astype(int),\n",
+    "                          fontsize=\"large\")\n",
+    "    if n < 6:\n",
+    "        ax[n].set_ylabel(\"Monthly mean\\nionospheric potential, kV\",\n",
+    "                         fontsize=\"large\")\n",
+    "    else:\n",
+    "        ax[n].set_ylabel(\"Monthly mean fair-weather\\npotential gradient, V/m\",\n",
+    "                         fontsize=\"large\")\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize=\"large\")\n",
+    "\n",
+    "    ax[n].annotate(\"\", xy=(12, np.min(data[n])), xycoords=\"data\",\n",
+    "                   xytext=(12, np.max(data[n])), textcoords=\"data\",\n",
+    "                   annotation_clip=False,\n",
+    "                   arrowprops=dict(\n",
+    "                       arrowstyle=\"<|-|>,head_length=0.8,head_width=0.3\",\n",
+    "                       patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                       connectionstyle=\"arc3,rad=0.\", fc=\"black\",\n",
+    "                       linewidth=0.5\n",
+    "                   ))\n",
+    "    # ampl = (np.max(data[n]) - np.min(data[n])) / np.mean(data[n])\n",
+    "    ampl = (np.max(data[n]) - np.min(data[n])) / \\\n",
+    "        np.sum(data[n] * data_counter[n]) * np.sum(data_counter[n])\n",
+    "    ax[n].text(12.2, (np.min(data[n]) + np.max(data[n])) / 2,\n",
+    "               f\"{ampl * 100:.0f}%\",\n",
+    "               fontsize=\"large\", ha=\"left\", va=\"center\", rotation=270)\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2], ax[4]])\n",
+    "fig.align_ylabels([ax[1], ax[3], ax[5]])\n",
+    "\n",
+    "for n in range(7):\n",
+    "    ax[n].bar(np.arange(12), data[n],\n",
+    "              yerr=std_error(data[n],\n",
+    "                             data_sqr[n],\n",
+    "                             data_counter[n]),\n",
+    "              width=0.8, color=col[n])\n",
+    "\n",
+    "for n in range(6):\n",
+    "    ax[n].text(-0.3, 1.05, chr(ord(\"a\") + 3 * (n % 2) + n // 2),\n",
+    "               fontsize=\"x-large\",\n",
+    "               fontweight=\"semibold\", ha=\"left\", va=\"bottom\",\n",
+    "               transform=ax[n].transAxes)\n",
+    "ax[6].text(-0.3, 1.05, chr(ord(\"a\") + 6), fontsize=\"x-large\",\n",
+    "           fontweight=\"semibold\", ha=\"left\", va=\"bottom\",\n",
+    "           transform=ax[6].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.6)\n",
+    "\n",
+    "for m in range(12):\n",
+    "    ax[6].annotate(f\"{data_counter[6, m]}\",\n",
+    "                   xy=(m-0.15, ax[6].get_ylim()[0] + 3),\n",
+    "                   rotation=270, ha=\"center\", va=\"bottom\",\n",
+    "                   fontsize=\"large\", color=\"0.\")\n",
+    "\n",
+    "fig.savefig(\"./figures_two_parts/ip_pg_total.eps\", bbox_inches=\"tight\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d2b0559-ca51-4dd7-98e8-af08fb402886",
+   "metadata": {},
+   "source": [
+    "### Figure 2.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "5c2a949e-1c6c-409f-9a62-6012fe5900a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate seasonal variation parameters for different temporal parts\n",
+    "\n",
+    "# 8 sets for different axes of the figure\n",
+    "# each set with 12 values for each month\n",
+    "\n",
+    "# monthly mean values of IP \n",
+    "data = np.zeros((7, 12))\n",
+    "\n",
+    "# count of days per month\n",
+    "data_counter = np.zeros((7, 12), dtype=int)\n",
+    "\n",
+    "# the sum of squares of IP daily values\n",
+    "data_sqr = np.zeros((7, 12))\n",
+    "\n",
+    "data = np.zeros((8, 12))\n",
+    "data_counter = np.zeros((8, 12), dtype=int)\n",
+    "data_sqr = np.zeros((8, 12))\n",
+    "\n",
+    "# to construct this figure we divide the datasets into equal ranges of years\n",
+    "# the dictionary keys below denote the axis number on the figure\n",
+    "wrf_ranges = {\n",
+    "    0: range(1981, 1990 + 1),\n",
+    "    1: range(1991, 2000 + 1),\n",
+    "    2: range(2001, 2010 + 1),\n",
+    "    3: range(2011, 2020 + 1),\n",
+    "}\n",
+    "\n",
+    "inm_ranges = {\n",
+    "    4: range(0, 5),\n",
+    "    5: range(5, 10)\n",
+    "}\n",
+    "\n",
+    "for m in range(12):\n",
+    "    for ax_idx in range(6):\n",
+    "        if ax_idx in [0, 1, 2, 3]:\n",
+    "\n",
+    "            # filtering day indices belonging to a specific month\n",
+    "            wrf_inds = [i for i, date in enumerate(wrf_dt_indicies)\n",
+    "                        if date.month == m + 1\n",
+    "                        and date.year in wrf_ranges[ax_idx]\n",
+    "                       ]\n",
+    "\n",
+    "            # slice IP for CAPE = 1000 and aforementioned day indices\n",
+    "            ip = wrf_hourly_total_ip[1000][wrf_inds]\n",
+    "\n",
+    "            # calculate seasonal variation parameters\n",
+    "            data[ax_idx, m] = ip.mean()\n",
+    "            data_counter[ax_idx, m] = len(ip)\n",
+    "            data_sqr[ax_idx, m] = np.sum(ip.mean(axis=-1) ** 2) / len(ip)\n",
+    "\n",
+    "        if ax_idx in [4, 5]:\n",
+    "            inmcm_inds = [i for i, date in enumerate(inm_dt_indicies) \n",
+    "                          if date.month == m + 1\n",
+    "                          and i//365 in inm_ranges[ax_idx]\n",
+    "                         ]\n",
+    "\n",
+    "            # slice IP for CAPE = 1000 and aforementioned day indices\n",
+    "            ip  = inm_hourly_total_ip[1000][inmcm_inds]\n",
+    "\n",
+    "             # calculate seasonal variation parameters\n",
+    "            data[ax_idx, m] = ip.mean()\n",
+    "            data_counter[ax_idx, m] = len(ip)\n",
+    "            data_sqr[ax_idx, m] = np.sum(ip.mean(axis=-1) ** 2) / len(ip)\n",
+    "\n",
+    "# the last sets is loaded from the processed data of Vostok station in script 2\n",
+    "# the data is loaded as a dictionary with keys `mean`, `counter`, `sqr`\n",
+    "# index 0: 2006-2020, index 1: 2006-2012, index 2: 2013-2020\n",
+    "vostok_results = np.load(\"./data/Vostok/vostok_2006_2020_results.npz\")\n",
+    "\n",
+    "# part 2006-2012\n",
+    "data[6] = vostok_results[\"mean\"][1]\n",
+    "data_counter[6] = vostok_results[\"counter\"][1]\n",
+    "data_sqr[6] = vostok_results[\"sqr\"][1]\n",
+    "\n",
+    "# part 2013-2020\n",
+    "data[7] = vostok_results[\"mean\"][2]\n",
+    "data_counter[7] = vostok_results[\"counter\"][2]\n",
+    "data_sqr[7] = vostok_results[\"sqr\"][2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "97cc13ff-e014-4626-90ec-1c65a60bdcac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "ax = [None for _ in range(8)]\n",
+    "\n",
+    "for n in range(8):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "\n",
+    "low = [200e3] * 6 + [80] * 2\n",
+    "high = [280e3] * 6 + [180] * 2\n",
+    "step = [20e3] * 6 + [20] * 2\n",
+    "coeff = [1e3] * 6 + [1] * 2\n",
+    "\n",
+    "caption = [\"WRF, 1981–1990, $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"WRF, 1991–2000, $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"WRF, 2001–2010, $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"WRF, 2011–2020, $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"INMCM, 5 years (1–5), $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"INMCM, 5 years (6–10), $\\\\varepsilon_0 = 1$ kJ/kg\",\n",
+    "           \"Vostok station, 2006–2012\",\n",
+    "           \"Vostok station, 2013–2020\"]\n",
+    "\n",
+    "col = [\"royalblue\"] * 6 + [\"orangered\"] * 2\n",
+    "\n",
+    "for n in range(8):\n",
+    "    for axis in [\"top\", \"bottom\", \"left\", \"right\"]:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis=\"y\")\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis=\"x\")\n",
+    "    ax[n].grid(color=\"0.\", linewidth=0.5, axis=\"y\")\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize=\"large\", va=\"top\")\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]).astype(int),\n",
+    "                          fontsize=\"large\")\n",
+    "    if n <= 5:\n",
+    "        ax[n].set_ylabel(\"Monthly mean\\nionospheric potential, kV\",\n",
+    "                         fontsize=\"large\")\n",
+    "    else:\n",
+    "        ax[n].set_ylabel(\"Monthly mean fair-weather\\npotential gradient, V/m\",\n",
+    "                         fontsize=\"large\")\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize=\"large\")\n",
+    "\n",
+    "    ax[n].annotate(\"\", xy=(12, np.min(data[n])), xycoords=\"data\",\n",
+    "                   xytext=(12, np.max(data[n])), textcoords=\"data\",\n",
+    "                   annotation_clip=False,\n",
+    "                   arrowprops=dict(\n",
+    "                       arrowstyle=\"<|-|>,head_length=0.8,head_width=0.3\",\n",
+    "                       patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                       connectionstyle=\"arc3,rad=0.\", fc=\"black\",\n",
+    "                       linewidth=0.5\n",
+    "                   ))\n",
+    "    # ampl = (np.max(data[n]) - np.min(data[n])) / np.mean(data[n])\n",
+    "    ampl = (np.max(data[n]) - np.min(data[n])) / \\\n",
+    "        np.sum(data[n] * data_counter[n]) * np.sum(data_counter[n])\n",
+    "    ax[n].text(12.2, (np.min(data[n]) + np.max(data[n])) / 2,\n",
+    "               f\"{ampl * 100:.0f}%\",\n",
+    "               fontsize=\"large\", ha=\"left\", va=\"center\", rotation=270)\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2], ax[4], ax[6]])\n",
+    "fig.align_ylabels([ax[1], ax[3], ax[5], ax[7]])\n",
+    "\n",
+    "for n in range(8):\n",
+    "    ax[n].bar(np.arange(12), data[n],\n",
+    "              yerr=std_error(data[n],\n",
+    "                             data_sqr[n],\n",
+    "                             data_counter[n]),\n",
+    "              width=0.8, color=col[n])\n",
+    "\n",
+    "for n in range(8):\n",
+    "    ax[n].text(-0.3, 1.05, chr(ord(\"a\") + n), fontsize=\"x-large\",\n",
+    "               fontweight=\"semibold\", ha=\"left\", va=\"bottom\",\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.6)\n",
+    "\n",
+    "for n in range(6, 8):\n",
+    "    for m in range(12):\n",
+    "        ax[n].annotate(f\"{data_counter[n, m]}\",\n",
+    "                       xy=(m-0.15, ax[n].get_ylim()[0] + 3),\n",
+    "                       rotation=270, ha=\"center\", va=\"bottom\",\n",
+    "                       fontsize=\"large\", color=\"0.\")\n",
+    "\n",
+    "fig.savefig(\"./figures_two_parts/ip_pg_partial.eps\", bbox_inches=\"tight\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7af55182-03fb-4e9f-979b-0df94edbd451",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/5_IP_simulations_spatial_images.ipynb b/5_IP_simulations_spatial_images.ipynb
new file mode 100644
index 0000000..2edfb6f
--- /dev/null
+++ b/5_IP_simulations_spatial_images.ipynb
@@ -0,0 +1,1475 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3b98d562-23d5-405b-bfe1-5073e8fcbd76",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Analysis of simulated IP and temperature grouped by latitude"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "51ec2f41-a148-4a64-84f0-03e822f585f9",
+   "metadata": {},
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e6e8b28e-203f-4c4b-907f-fe6183e5d331",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import datetime as dt\n",
+    "\n",
+    "import numpy as np\n",
+    "import scipy.stats as st\n",
+    "\n",
+    "import cartopy.crs as ccrs\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib import cm, colormaps, colors, transforms"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "83163834-de47-4f28-8add-768c7b76e1d3",
+   "metadata": {},
+   "source": [
+    "### Helper functions, variables and classes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "61405aa1-0b4d-4a8a-85a5-3097d37c644e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "month_name = [\"J\", \"F\", \"M\", \"A\", \"M\", \"J\", \n",
+    "              \"J\", \"A\", \"S\", \"O\", \"N\", \"D\"]\n",
+    "month_name_3 = [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\",\n",
+    "                \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b929a567-c60d-47e4-a5e3-3ca83b29d07a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# area factors for different latitudes\n",
+    "area_factor = (\n",
+    "    np.cos(np.arange(180) * np.pi / 180) - \n",
+    "    np.cos(np.arange(1, 181) * np.pi / 180)\n",
+    ") / 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "42ca4c03-8fbf-451c-bd17-607e42450130",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def std_error(avg_val, avg_sqr, counter):\n",
+    "    \"\"\"\n",
+    "    Estimate the standard error from the average value\n",
+    "    and the average value of the square.\n",
+    "    \n",
+    "    :param avg_val: the average value\n",
+    "    :param avg_sqr: the average square value\n",
+    "    :param counter: the size of the sample\n",
+    "    \n",
+    "    :return: the standard error\n",
+    "    \"\"\"\n",
+    "\n",
+    "    return np.sqrt((avg_sqr - avg_val**2) / (counter - 1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4250ebc7-1c87-4ff0-bc58-faaf6732008f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class LatitudeBand():\n",
+    "    \"\"\"\n",
+    "    Represents a latitude band object with specific \n",
+    "    latitude range and model information\n",
+    "\n",
+    "    Attributes:\n",
+    "        slice (slice): slice for the latitude range\n",
+    "        indices (tuple): indices within the latitude range\n",
+    "        model (str): model associated with the latitude band\n",
+    "        color (str): color associated with the latitude band.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    def __init__(self, expression, model=None):\n",
+    "        \"\"\"\n",
+    "        Initializes a LatitudeBand object with the given latitude \n",
+    "        expression and model.\n",
+    "\n",
+    "        Args:\n",
+    "            expression (str): latitude range expr. like '0-8S', '8N-8S'\n",
+    "            model (str, optional): 'WRF' or 'INMCM', defaults to None\n",
+    "        \"\"\"\n",
+    "\n",
+    "        # split the expression into two parts \n",
+    "        # and replace \"0\" with \"0S\" if necessary\n",
+    "        s1, s2 = [s if s != \"0\" else \"0S\" for s in expression.split(\"-\")]\n",
+    "        assert all(s[-1] in \"NS\" and s[:-1].isdigit() for s in [s1, s2])\n",
+    "\n",
+    "        # calculate values for the latitude bands \n",
+    "        # taking into account direction\n",
+    "        N1 = int(s1[:-1]) * (-1 if s1[-1] == \"S\" else 1)\n",
+    "        N2 = int(s2[:-1]) * (-1 if s2[-1] == \"S\" else 1)\n",
+    "        \n",
+    "        # format latitude values for display using thin spaces\n",
+    "        p1 = f\"0°\" if N1 == 0 else f\"{abs(N1):d}° {'S' if N1 < 0 else 'N'}\"\n",
+    "        p2 = f\"0°\" if N2 == 0 else f\"{abs(N2):d}° {'S' if N2 < 0 else 'N'}\"\n",
+    "\n",
+    "        # set color for each latitude band\n",
+    "        Z = (N1 + N2) / 2\n",
+    "        cmap = colormaps.get_cmap('tab20')\n",
+    "        if 0 < Z < 9:\n",
+    "            self.color = cmap(7 / 40)\n",
+    "        elif -9 < Z < 0:\n",
+    "            self.color = cmap(5 / 40)\n",
+    "        elif -18 < Z < -9:\n",
+    "            self.color = cmap(39 / 40)\n",
+    "        elif -90 < Z < -18:\n",
+    "            self.color = cmap(37 / 40)\n",
+    "        elif 9 < Z < 18:\n",
+    "            self.color = cmap(35 / 40)\n",
+    "        elif 18 < Z < 90:\n",
+    "            self.color = cmap(33 / 40)\n",
+    "\n",
+    "        # ensure the model is valid and set degrees \n",
+    "        # and central index based on the model\n",
+    "        assert model in [\"WRF\", \"INMCM\"]\n",
+    "        degrees = 1 if model == \"WRF\" else 1.5\n",
+    "        central_idx = 90 if model == \"WRF\" else 60\n",
+    "\n",
+    "        # check that latitude values are divisible \n",
+    "        # by the appropriate degrees\n",
+    "        assert all(N % degrees == 0 for N in [N1, N2])\n",
+    "\n",
+    "        # convert latitude values to indices and sort them\n",
+    "        N1, N2 = sorted([int(N // degrees + central_idx) for N in [N1, N2]])\n",
+    "\n",
+    "        # create a slice for the latitude range \n",
+    "        # and generate indices within that range\n",
+    "        self.slice = slice(N1, N2, 1)\n",
+    "        self.indicies = tuple(np.arange(*self.slice.indices(1000000)).tolist())\n",
+    "\n",
+    "        # store latitude bands model and prettify title\n",
+    "        self.model = model\n",
+    "        self.title = f\"{p1}–{p2}\" # like 9° S–18° S\n",
+    "        self.label = self.title.replace(\" \", \"\")\n",
+    "\n",
+    "    def __repr__(self):\n",
+    "        return self.label"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d00db06e-dd79-4422-b62b-f10ca8a81f9a",
+   "metadata": {},
+   "source": [
+    "### Loading precalculated arrays"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2dd01e73-6586-4e1b-b519-4f3e84ae8940",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# numbers of simulated days for analysis\n",
+    "wrf_N_days = 4992\n",
+    "inm_N_days = 3650"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "9252215e-9586-444e-bb63-b65dcb945dd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dates corresponding to the indices (0 axis) of the data arrays\n",
+    "# note: for WRF dates correspond to real dates\n",
+    "\n",
+    "wrf_dt_indicies = np.array(\n",
+    "    [dt.date(1980, 1, 1) + dt.timedelta(i * 3) for i in range(wrf_N_days)]\n",
+    ")\n",
+    "\n",
+    "inm_dt_indicies = np.array(\n",
+    "    [dt.date(2022, 1, 1) + dt.timedelta(i % 365) for i in range(inm_N_days)]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "69602993-2005-4fed-b425-69575f9fd2cf",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# dictionaries where processed data is saved. The dictionary keys represent the\n",
+    "# threshold value of CAPE - integer numbers from the list 500, 800, 1000, 1200,\n",
+    "# where the key 500 relates only to temperature-based modeling and is present \n",
+    "# only in dictionaries wrf_<...>, while keys 800, 1000, 1200 correspond to \n",
+    "# classical modeling using the WRF or INMCM model.\n",
+    "\n",
+    "# averaged air temperature at the height of 2 meter with the shape (180, 12)\n",
+    "wrf_LATxMON_t2 = np.load(\"./data/WRF/WRF_T2_LATxMON.npy\")\n",
+    "\n",
+    "# summed WRF IP along longitudes and averaged over months with shape (180, 12)\n",
+    "wrf_LATxMON_ip = {\n",
+    "    key: np.load(f\"./data/WRF/WRF_IP_{parameters}_LATxMON.npy\")\n",
+    "    for key, parameters in zip([500, 800, 1000, 1200],\n",
+    "                              [\"500_T2_25\", \"800\", \"1000\", \"1200\"])\n",
+    "}\n",
+    "\n",
+    "# the same for INMCM\n",
+    "inm_LATxMON_ip = {\n",
+    "    key: np.load(f\"./data/INMCM/INMCM_IP_{parameters}_LATxMON.npy\")\n",
+    "    for key, parameters in zip([800, 1000, 1200],\n",
+    "                              [\"800\", \"1000\", \"1200\"])\n",
+    "}\n",
+    "\n",
+    "# dict contains arrays with dimensions (4992, 24)\n",
+    "# where axis 0 contains the day index (see `wrf_dt_indicies`)\n",
+    "wrf_hourly_total_ip = {\n",
+    "    key: np.load(f\"./data/WRF/WRF_HOURLY_TOTAL_IP_{parameters}.npy\")[:wrf_N_days]\n",
+    "    for key, parameters in zip([500, 800, 1000, 1200],\n",
+    "                              [\"500_T2_25\", \"800\", \"1000\", \"1200\"])\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "123b905f-c3c3-4592-b29d-92aeef3faf3a",
+   "metadata": {},
+   "source": [
+    "### Auxiliary calculations of values to mention in the text"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "728962ea-6e40-4827-bbf3-0da19b8e5c5b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for averaging over months we use\n",
+    "# `(wrf_data_LATxMON[:, :].sum(axis=0)*days).sum()/days.sum()`\n",
+    "# unstead\n",
+    "# `wrf_data_LATxMON[:, :].sum(axis=0).mean()`\n",
+    "# because\n",
+    "# ((a1+a2+a3)/3 + (b1+b2)/2)/2 != (a1+a2+a3+b1+b2)/5\n",
+    "\n",
+    "wrf_numdays = np.load(\"./data/WRF/WRF_NUMDAYS_MON.npy\")\n",
+    "inm_numdays = np.load(\"./data/INMCM/INMCM_NUMDAYS_MON.npy\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "90002efb-7421-46cc-8e64-96c6d465c617",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model | CAPE | T2,°C |     Band   |  % \n",
+      "-----------------------------------------\n",
+      "WRF   |  500 | 25    |    9°S–9°N | 57.53%\n",
+      "INMCM |  800 | -     |    9°S–9°N | 51.72%\n",
+      "WRF   |  800 | -     |    9°S–9°N | 60.19%\n",
+      "INMCM | 1000 | -     |    9°S–9°N | 52.99%\n",
+      "WRF   | 1000 | -     |    9°S–9°N | 62.30%\n",
+      "INMCM | 1200 | -     |    9°S–9°N | 53.66%\n",
+      "WRF   | 1200 | -     |    9°S–9°N | 63.40%\n",
+      "-----------------------------------------\n",
+      "INMCM | 1000 | -     |  18°S–18°N | 86.08%\n",
+      "WRF   | 1000 | -     |  18°S–18°N | 92.08%\n",
+      "-----------------------------------------\n",
+      "INMCM | 1000 | -     |  30°S–30°N | 96.51%\n",
+      "WRF   | 1000 | -     |  30°S–30°N | 98.83%\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculate the average contribution of the regions to \n",
+    "# the ionospheric potential (as % of total IP)\n",
+    "# for specific latitudinal bands and parameterizations\n",
+    "\n",
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"9S-9N\", \"18S-18N\", \"30S-30N\"]\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "inmcm_bands = [LatitudeBand(t, model=\"INMCM\") for t in band_names]\n",
+    "\n",
+    "print(\"Model | CAPE | T2,°C |     Band   |  % \")\n",
+    "\n",
+    "# iterate over the latitude bands selected above\n",
+    "for i, (wrf_band, inm_band) in enumerate(zip(wrf_bands, inmcm_bands)):\n",
+    "    print(\"-\"*41)\n",
+    "\n",
+    "    # we will analyze all parameterizations only in the 9N-9S band; in the \n",
+    "    # other bands, we will consider only the parameterization with CAPE = 1000\n",
+    "    capes = [1000]\n",
+    "    if i == 0:\n",
+    "        capes = [500, 800, 1000, 1200]\n",
+    "\n",
+    "    # iterate over different parameterizations\n",
+    "    for cape in capes:\n",
+    "        # calculation of the seasonal variation of contribution to IP \n",
+    "        # from i-nth band -> array (12,)\n",
+    "        wrf_ip_MON = wrf_LATxMON_ip[cape][wrf_band.slice].sum(axis=0)\n",
+    "\n",
+    "        # calculation of the contribution of the n-th band \n",
+    "        # to the total IP in percentage -> single value\n",
+    "        wrf_share = (wrf_ip_MON*wrf_numdays).sum() / wrf_numdays.sum() / 240e3 * 100\n",
+    "        # note: The averaging by months takes into account the number of \n",
+    "        # days taken from the original series for each month, as direct \n",
+    "        # averaging may lead to a slight error\n",
+    "\n",
+    "        # the same for INMCM\n",
+    "        if cape != 500:\n",
+    "            inm_ip_MIN = inm_LATxMON_ip[cape][inm_band.slice].sum(axis=0)\n",
+    "            inm_share = (inm_ip_MIN*inm_numdays).sum() / inm_numdays.sum() / 240e3 * 100\n",
+    "            print(f\"INMCM | {cape:4d} | -     |{inm_band.label:>11} | {inm_share:>4.2f}%\")\n",
+    "\n",
+    "        p = \"25   \" if cape == 500 else \"-    \"\n",
+    "        print(f\"WRF   | {cape:4d} | {p} |{wrf_band.label:>11} | {wrf_share:>4.2f}%\")          "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7cc0c763-f1ec-4ff4-b4fe-2730be6daec9",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model | CAPE | T2,°C |     Band   | Min | Max | Peak-to-peak, %\n",
+      "---------------------------------------------------------------\n",
+      "WRF   |  500 | 25    |   90°S–9°S | Aug | Feb | 208.77%\n",
+      "INMCM |  800 | -     |   90°S–9°S | Sep | Feb | 165.65%\n",
+      "WRF   |  800 | -     |   90°S–9°S | Sep | Feb | 165.65%\n",
+      "INMCM | 1000 | -     |   90°S–9°S | Aug | Feb | 190.49%\n",
+      "WRF   | 1000 | -     |   90°S–9°S | Aug | Feb | 190.49%\n",
+      "INMCM | 1200 | -     |   90°S–9°S | Aug | Feb | 212.74%\n",
+      "WRF   | 1200 | -     |   90°S–9°S | Aug | Feb | 212.74%\n",
+      "---------------------------------------------------------------\n",
+      "WRF   |  500 | 25    |    9°S–9°N | Aug | Apr |  57.68%\n",
+      "INMCM |  800 | -     |    9°S–9°N | Jul | May |  29.09%\n",
+      "WRF   |  800 | -     |    9°S–9°N | Jul | May |  29.09%\n",
+      "INMCM | 1000 | -     |    9°S–9°N | Jul | May |  32.93%\n",
+      "WRF   | 1000 | -     |    9°S–9°N | Jul | May |  32.93%\n",
+      "INMCM | 1200 | -     |    9°S–9°N | Jul | May |  38.38%\n",
+      "WRF   | 1200 | -     |    9°S–9°N | Jul | May |  38.38%\n",
+      "---------------------------------------------------------------\n",
+      "WRF   |  500 | 25    |   9°N–90°N | Feb | Aug | 226.01%\n",
+      "INMCM |  800 | -     |   9°N–90°N | Feb | Aug | 181.46%\n",
+      "WRF   |  800 | -     |   9°N–90°N | Feb | Aug | 181.46%\n",
+      "INMCM | 1000 | -     |   9°N–90°N | Feb | Jul | 190.60%\n",
+      "WRF   | 1000 | -     |   9°N–90°N | Feb | Jul | 190.60%\n",
+      "INMCM | 1200 | -     |   9°N–90°N | Feb | Jul | 201.56%\n",
+      "WRF   | 1200 | -     |   9°N–90°N | Feb | Jul | 201.56%\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculation of: \n",
+    "#  (i) the positions of the extrema of the seasonal  \n",
+    "#      variation of the contribution to IP from \n",
+    "#      individual latitudinal bands,\n",
+    "# (ii) the amplitudes of the peak-to-peak amplitudes \n",
+    "#      of the seasonal variation <-//->,\n",
+    "# for different parameterizations\n",
+    "\n",
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"90S-9S\", \"9S-9N\", \"9N-90N\"]\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "inmcm_bands = [LatitudeBand(t, model=\"INMCM\") for t in band_names]\n",
+    "\n",
+    "print(\"Model | CAPE | T2,°C |     Band   | Min | Max | Peak-to-peak, %\")\n",
+    "\n",
+    "# iterate over the latitude bands selected above\n",
+    "for i, (wrf_band, inm_band) in enumerate(zip(wrf_bands, inmcm_bands)):\n",
+    "    print(\"-\"*63)\n",
+    "    for cape in [500, 800, 1000, 1200]:\n",
+    "        \n",
+    "        # calculation of the seasonal variation of contribution to IP \n",
+    "        # from i-nth band -> array (12,)\n",
+    "        seas_var = wrf_LATxMON_ip[cape][wrf_band.slice].sum(axis=0)\n",
+    "\n",
+    "        # calculation of the positions of the extrema\n",
+    "        month_min = month_name_3[np.argmin(seas_var)]\n",
+    "        month_max = month_name_3[np.argmax(seas_var)]\n",
+    "\n",
+    "        # calculation of the peak-to-peak amplitude of the seasonal variation\n",
+    "        pk_pk_ampl = (seas_var.max() - seas_var.min())/seas_var.mean() * 100\n",
+    "\n",
+    "        # the same for INMCM\n",
+    "        if cape != 500:\n",
+    "            seas_var = inm_LATxMON_ip[cape][inm_band.slice].sum(axis=0)    \n",
+    "            month_min = month_name_3[np.argmin(seas_var)]\n",
+    "            month_max = month_name_3[np.argmax(seas_var)]\n",
+    "            pk_pk_ampl = (seas_var.max() - seas_var.min())/seas_var.mean() * 100\n",
+    "\n",
+    "            print(f\"INMCM | {cape:4} | -     |{inm_band.label:>11} | {month_min} | {month_max} | {pk_pk_ampl:>6.2f}%\")\n",
+    "\n",
+    "        p = \"25   \" if cape == 500 else \"-    \"\n",
+    "        print(f\"WRF   | {cape:4} | {p:<5} |{inm_band.label:>11} | {month_min} | {month_max} | {pk_pk_ampl:>6.2f}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "12e57219-ea3e-447b-b858-5240e2f8004b",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CAPE = 1000 J/kg\n",
+      "\n",
+      "Model | Band      | Max IP contrib.\n",
+      "-------------------------------\n",
+      "WRF   | 18°N–90°N |  39632.12 V\n",
+      "INMCM | 18°N–90°N |  55489.63 V\n",
+      "-------------------------------\n",
+      "WRF   |  9°N–18°N |  87966.76 V\n",
+      "INMCM |  9°N–18°N |  81507.39 V\n",
+      "-------------------------------\n",
+      "WRF   |    0°–9°N | 119554.24 V\n",
+      "INMCM |    0°–9°N |  80137.23 V\n",
+      "-------------------------------\n",
+      "WRF   |    0°–9°S | 101478.67 V\n",
+      "INMCM |    0°–9°S |  89818.48 V\n",
+      "-------------------------------\n",
+      "WRF   |  9°S–18°S |  69905.52 V\n",
+      "INMCM |  9°S–18°S |  77321.06 V\n",
+      "-------------------------------\n",
+      "WRF   | 18°S–90°S |  17133.10 V\n",
+      "INMCM | 18°S–90°S |  24639.04 V\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculation of the maximum values of the contribution\n",
+    "# to IP from latitudinal bands, calculation is needed for \n",
+    "# manual refinement of the figure boundaries.\n",
+    "\n",
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"18N-90N\", \"9N-18N\", \"0-9N\", \"0-9S\", \"9S-18S\", \"18S-90S\"]\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "inmcm_bands = [LatitudeBand(t, model=\"INMCM\") for t in band_names]\n",
+    "\n",
+    "print(\"CAPE = 1000 J/kg\\n\")\n",
+    "print(\"Model | Band      | Max IP contrib.\")\n",
+    "\n",
+    "# iterate over the latitude bands selected above\n",
+    "for i, (wrf_band, inm_band) in enumerate(zip(wrf_bands, inmcm_bands)):\n",
+    "    print(\"-\"*31)\n",
+    "\n",
+    "    # calculation of the maximum (over months axis) values, V\n",
+    "    wrf_max = wrf_LATxMON_ip[1000][wrf_band.slice].sum(axis=0).max()\n",
+    "    inm_max = inm_LATxMON_ip[1000][inm_band.slice].sum(axis=0).max()\n",
+    "    print(f\"WRF   | {wrf_band.label:>9} | {wrf_max:>9.2f} V\")\n",
+    "    print(f\"INMCM | {inm_band.label:>9} | {inm_max:>9.2f} V\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "df0d50ea-4001-4007-9a4d-bc37b8a1be9f",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model | Band      | Min T2  | Max T2\n",
+      "-------------------------------------\n",
+      "WRF   | 18°N–30°N | 18.10°C | 26.98°C\n",
+      "WRF   |  9°N–18°N | 24.65°C | 27.64°C\n",
+      "WRF   |    0°–9°N | 26.21°C | 27.24°C\n",
+      "WRF   |    0°–9°S | 25.20°C | 27.02°C\n",
+      "WRF   |  9°S–18°S | 23.15°C | 26.29°C\n",
+      "WRF   | 18°S–30°S | 18.62°C | 24.83°C\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculation of the maximum and minimum values of the temperature at the\n",
+    "# 2-meter level in each latitude band. The temperature is averaged over \n",
+    "# spatial cells within each band. Calculation is needed for manual \n",
+    "# refinement of the figure boundaries.\n",
+    "\n",
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"18N-30N\", \"9N-18N\", \"0-9N\", \"0-9S\", \"9S-18S\", \"18S-30S\"]\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "\n",
+    "print(\"Model | Band      | Min T2  | Max T2\")\n",
+    "print(\"-\" * 37)\n",
+    "\n",
+    "# iterate over the latitude bands selected above\n",
+    "for wrf_band in wrf_bands:\n",
+    "\n",
+    "    # averaging is performed with consideration of the area factor\n",
+    "    tmp_t2 = (\n",
+    "        wrf_LATxMON_t2[wrf_band.slice] * area_factor[wrf_band.slice, np.newaxis]\n",
+    "    ).sum(axis=0) / area_factor[wrf_band.slice, np.newaxis].sum()\n",
+    "\n",
+    "    print(f\"WRF   | {wrf_band.label:>9} | {tmp_t2.min():>3.2f}°C | {tmp_t2.max():>3.2f}°C\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "497b3797-3076-43c3-a66e-e827bc00df66",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "### Figure 2.4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "34e25ddd-4815-4c70-bc3b-982cad6b65b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"0-9N\", \"0-9S\", \"9S-18S\", \"18S-90S\", \"9N-18N\", \"18N-90N\"]\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "inmcm_bands = [LatitudeBand(t, model=\"INMCM\") for t in band_names]\n",
+    "\n",
+    "bar_data = np.zeros((6, len(band_names), 12))\n",
+    "# (axes, strips, months)\n",
+    "\n",
+    "for j, cape in enumerate([800, 1000, 1200]):\n",
+    "    ax_idx = j * 2\n",
+    "    for i, band in enumerate(wrf_bands):\n",
+    "        bar_data[ax_idx, i] = wrf_LATxMON_ip[cape][band.slice].sum(axis=0)\n",
+    "\n",
+    "    ax_idx = j * 2 + 1\n",
+    "    for i, band in enumerate(inmcm_bands):\n",
+    "        bar_data[ax_idx, i] = inm_LATxMON_ip[cape][band.slice].sum(axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "fc39428e-ea03-494e-97d7-c38ecd8cb044",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1400 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 14), constrained_layout=False)\n",
+    "ax = [None for _ in range(6)]\n",
+    "for n in range(6):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "\n",
+    "low = [0e3] * 6\n",
+    "high = [300e3] * 6\n",
+    "step = [50e3] * 6\n",
+    "coeff = [1e3] * 6\n",
+    "caption = ['WRF, 1980–2020, $\\\\varepsilon_0 = 0.8$ kJ/kg',\n",
+    "           'INMCM, 10 years, $\\\\varepsilon_0 = 0.8$ kJ/kg',\n",
+    "           'WRF, 1980–2020, $\\\\varepsilon_0 = 1$ kJ/kg',\n",
+    "           'INMCM, 10 years, $\\\\varepsilon_0 = 1$ kJ/kg',\n",
+    "           'WRF, 1980–2020, $\\\\varepsilon_0 = 1.2$ kJ/kg',\n",
+    "           'INMCM, 10 years, $\\\\varepsilon_0 = 1.2$ kJ/kg']\n",
+    "lab = ['18° S–90° S',\n",
+    "       '9° S–18° S',\n",
+    "       '0°–9° S',\n",
+    "       '0°–9° N',\n",
+    "       '9° N–18° N',\n",
+    "       '18° N–90° N']\n",
+    "# thin spaces (' ') are used between ‘°’ signs and letters\n",
+    "\n",
+    "for n in range(6):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    ax[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]).astype(int),\n",
+    "                          fontsize='large')\n",
+    "    ax[n].set_ylabel('Monthly mean\\nionospheric potential, kV',\n",
+    "                     fontsize='large')\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize='large')\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2], ax[4]])\n",
+    "fig.align_ylabels([ax[1], ax[3], ax[5]])\n",
+    "\n",
+    "\n",
+    "for n in range(6):\n",
+    "    bottom_data = np.zeros(12)\n",
+    "    for k in range(len(band_names)):\n",
+    "        data = bar_data[n, k]\n",
+    "        ax[n].bar(\n",
+    "            np.arange(12),\n",
+    "            data,\n",
+    "            0.8,\n",
+    "            color=wrf_bands[k].color,\n",
+    "            bottom=bottom_data,\n",
+    "            label=wrf_bands[k].title,\n",
+    "        )\n",
+    "        bottom_data += data\n",
+    "        \n",
+    "\n",
+    "for n in range(6):\n",
+    "    ax[n].text(-0.28, 1.05, chr(ord('a') + 3 * (n % 2) + n // 2),\n",
+    "               fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.3, wspace=1.)\n",
+    "\n",
+    "leg_width_rel = (ax[5].get_position().x1 - ax[4].get_position().x0) \\\n",
+    "    / (ax[4].get_position().x1 - ax[4].get_position().x0)\n",
+    "\n",
+    "leg = ax[4].legend(bbox_to_anchor=(0., -1./3, leg_width_rel, 1./6), ncols=6,\n",
+    "                   loc='lower center', borderaxespad=0.,\n",
+    "                   mode='expand', fontsize='large',\n",
+    "                   framealpha=1, edgecolor='0.',\n",
+    "                   handlelength=1., handletextpad=0.5)\n",
+    "leg.get_frame().set_linewidth(0.5)\n",
+    "\n",
+    "fig.savefig('figures_two_parts/ip_decomposed.eps', bbox_inches='tight')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ed8b0d4-c9d0-4a9a-ab87-263350eeed15",
+   "metadata": {},
+   "source": [
+    "### Figure 2.2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "57a55242-5fc1-4339-a386-297c20320f3e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"18N-90N\", \"9N-18N\", \"0-9N\", \"0-9S\", \"9S-18S\", \"18S-90S\"]\n",
+    "\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "inm_bands = [LatitudeBand(t, model=\"INMCM\") for t in band_names]\n",
+    "wrf_t2_bands = [LatitudeBand(t, model=\"WRF\") for t in [\"18N-30N\"]+band_names[1:-1]+[\"18S-30S\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "92d565d9-fd1f-4bff-91e7-1a5185de08a7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wrf_slice = LatitudeBand(\"30S-30N\", model=\"WRF\").slice\n",
+    "inm_slice = LatitudeBand(\"30S-30N\", model=\"INMCM\").slice\n",
+    "\n",
+    "WRF_IP_LxM = wrf_LATxMON_ip[1000][wrf_slice] / 360\n",
+    "INM_IP_LxM = inm_LATxMON_ip[1000][inm_slice] / 180\n",
+    "T2_LxM = wrf_LATxMON_t2[wrf_slice]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "421b6814-7f62-4325-8f40-08d9dffc720b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "strip_map = np.full((180, 360, 4), 1.)\n",
+    "\n",
+    "for band in wrf_t2_bands:\n",
+    "    for i in band.indicies:\n",
+    "        for j in range(360):\n",
+    "            strip_map[i, j] = band.color"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "04ac548c-47d9-4643-b26c-58b3359bd9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wrf_ip_sum_over_bands = np.zeros((6, 12))\n",
+    "inm_ip_sum_over_bands = np.zeros((6, 12))\n",
+    "wrf_t2_avg_over_bands = np.zeros((6, 12))\n",
+    "\n",
+    "for j in range(6):\n",
+    "    wrf_ip_sum_over_bands[j] = wrf_LATxMON_ip[1000][wrf_bands[j].slice].sum(axis=0)\n",
+    "    inm_ip_sum_over_bands[j] = inm_LATxMON_ip[1000][inm_bands[j].slice].sum(axis=0)\n",
+    "\n",
+    "    wrf_t2_avg_over_bands[j] = np.sum(\n",
+    "        wrf_LATxMON_t2[wrf_t2_bands[j].slice]\n",
+    "        * area_factor[wrf_t2_bands[j].slice, np.newaxis],\n",
+    "        axis=0,\n",
+    "    ) / np.sum(area_factor[wrf_t2_bands[j].slice, np.newaxis])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "8fc9d1a5-e75b-4dd7-971d-67d900c89207",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1200 with 25 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig_width = 10\n",
+    "fig_height = 12\n",
+    "\n",
+    "width = 3.\n",
+    "wsp = 1.\n",
+    "tot_width = 3 * width + 4 * wsp\n",
+    "widthM = 0.6 * tot_width\n",
+    "\n",
+    "height = np.array([2., 2., 3., 3., 2., 1.])\n",
+    "hsp = 0.8\n",
+    "hsep1 = 2.\n",
+    "hsep2 = 3.5\n",
+    "assert len(height) == 6\n",
+    "heightD = 4.\n",
+    "heightM = widthM/tot_width * 60/360 * fig_width/fig_height\n",
+    "tot_height = (sum(height) + heightD + 8 * hsp + hsep1 + hsep2) / (1 - heightM)\n",
+    "heightM *= tot_height\n",
+    "\n",
+    "sizeT = np.array([6., 3., 2., 2., 3., 4.])\n",
+    "hspT = hsp\n",
+    "assert len(sizeT) == 6\n",
+    "heightT = sizeT * (sum(height) + 5 * hsp - 5 * hspT) / sum(sizeT)\n",
+    "minT = np.array([16., 24., 24., 24., 22., 18.])\n",
+    "\n",
+    "fig = plt.figure(figsize=(fig_width, fig_height), constrained_layout=False)\n",
+    "\n",
+    "ax = [None for _ in range(12)]\n",
+    "axT = [None for _ in range(6)]\n",
+    "\n",
+    "for n in range(6):\n",
+    "    ax[2*n] = fig.add_axes(\n",
+    "        (\n",
+    "            (width + 2 * wsp) / tot_width,\n",
+    "            (sum(height[n+1:]) + heightM + (6 - n) * hsp + hsep1) / tot_height,\n",
+    "            width / tot_width,\n",
+    "            height[n] / tot_height\n",
+    "        )\n",
+    "    )\n",
+    "    ax[2*n + 1] = fig.add_axes(\n",
+    "        (\n",
+    "            (2 * width + 3 * wsp) / tot_width,\n",
+    "            (sum(height[n+1:]) + heightM + (6 - n) * hsp + hsep1) / tot_height,\n",
+    "            width / tot_width,\n",
+    "            height[n] / tot_height\n",
+    "        )\n",
+    "    )\n",
+    "    axT[n] = fig.add_axes(\n",
+    "        (\n",
+    "            wsp / tot_width,\n",
+    "            (sum(heightT[n+1:]) + (5 - n) * hspT\n",
+    "             + heightM + hsp + hsep1) / tot_height,\n",
+    "            width / tot_width,\n",
+    "            heightT[n] / tot_height\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "axD = [None for _ in range(3)]\n",
+    "\n",
+    "for n in range(3):\n",
+    "    axD[n] = fig.add_axes(\n",
+    "        (\n",
+    "            (n * width + (n + 1) * wsp) / tot_width,\n",
+    "            (sum(height) + heightM + 7 * hsp + hsep1 + hsep2) / tot_height,\n",
+    "            width / tot_width,\n",
+    "            heightD / tot_height\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "axM = fig.add_axes(\n",
+    "    (\n",
+    "        (1 - widthM / tot_width) / 2,\n",
+    "        hsp / tot_height,\n",
+    "        widthM / tot_width,\n",
+    "        heightM / tot_height\n",
+    "    ),\n",
+    "    projection=ccrs.PlateCarree(central_longitude=0)\n",
+    ")\n",
+    "axM.coastlines('110m', linewidth=0.5)\n",
+    "\n",
+    "caption = ['WRF, 1980–2020, $\\\\varepsilon_0 = 1$ kJ/kg',\n",
+    "           'INMCM, 10 years, $\\\\varepsilon_0 = 1$ kJ/kg']\n",
+    "\n",
+    "captionT = 'WRF, 1980–2020'\n",
+    "\n",
+    "captionD = ['WRF, 1980–2020',\n",
+    "            'WRF, 1980–2020, $\\\\varepsilon_0 = 1$ kJ/kg',\n",
+    "            'INMCM, 10 years, $\\\\varepsilon_0 = 1$ kJ/kg']\n",
+    "\n",
+    "for n in range(12):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    ax[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    low = 0\n",
+    "    high = 50e3 * height[n // 2]\n",
+    "    step = 50e3\n",
+    "    coeff = 1e3\n",
+    "    ax[n].set_ylim((low, high))\n",
+    "    ax[n].set_yticks(np.arange(low, high + step / 2, step))\n",
+    "    ax[n].set_yticklabels((np.arange(low, high + step / 1,\n",
+    "                                     step) / coeff).astype(int),\n",
+    "                          fontsize='large')\n",
+    "\n",
+    "    if n < 2:\n",
+    "        ax[n].set_title(caption[n], fontsize='large')\n",
+    "\n",
+    "\n",
+    "for n in range(2):\n",
+    "    lbl = ax[n].set_ylabel('Monthly mean contributions '\n",
+    "                           'to the ionospheric potential, kV',\n",
+    "                           fontsize='large', labelpad=0.)\n",
+    "    lbl.set_position((0., 1 - (sum(height) + 5 * hsp) / 2 / height[0]))\n",
+    "\n",
+    "for n in range(6):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        axT[n].spines[axis].set_linewidth(0.5)\n",
+    "    axT[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    axT[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    axT[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    axT[n].set_xlim((-0.5, 11.5))\n",
+    "    axT[n].set_xticks(np.arange(12))\n",
+    "    axT[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    low = minT[n]\n",
+    "    step = 2\n",
+    "    high = minT[n] + step * sizeT[n]\n",
+    "    coeff = 1\n",
+    "    axT[n].set_ylim((low, high))\n",
+    "    axT[n].set_yticks(np.arange(low, high + step / 2, step))\n",
+    "    axT[n].set_yticklabels((np.arange(low, high + step / 2,\n",
+    "                                      step) / coeff).astype(int),\n",
+    "                           fontsize='large')\n",
+    "\n",
+    "    if n == 0:\n",
+    "        axT[n].set_title(captionT, fontsize='large')\n",
+    "\n",
+    "\n",
+    "lbl = axT[0].set_ylabel('Monthly mean surface air temperature, °C',\n",
+    "                        fontsize='large')\n",
+    "lbl.set_position((0., 1 - (sum(heightT) + 5 * hspT) / 2 / heightT[0]))\n",
+    "\n",
+    "for n in range(3):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        axD[n].spines[axis].set_linewidth(0.5)\n",
+    "    axD[n].tick_params(length=6, width=0.5)\n",
+    "    axD[n].tick_params(length=0, width=0.5, which='minor')\n",
+    "    axD[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    axD[n].set_xlim((0, 12))\n",
+    "    axD[n].set_xticks(np.arange(0, 12.5, 1))\n",
+    "    axD[n].set_xticks(np.arange(0.5, 12, 1), minor=True)\n",
+    "    axD[n].set_xticklabels([])\n",
+    "    axD[n].set_xticklabels(month_name, fontsize='large', va='top',\n",
+    "                           minor=True)\n",
+    "\n",
+    "    axD[n].set_ylim((-30, 30))\n",
+    "    axD[n].set_yticks(np.arange(-30, 31, 10))\n",
+    "    axD[n].set_yticklabels(['0' if v == 0 else f'{-v}S' if v < 0 else f'{v}N'\n",
+    "                            for v in range(-30, 31, 10)],\n",
+    "                           fontsize='large')\n",
+    "\n",
+    "    axD[n].set_title(captionD[n], fontsize='large')\n",
+    "\n",
+    "cax = [None for _ in range(3)]\n",
+    "for n in range(3):\n",
+    "    cax[n] = fig.add_axes(\n",
+    "        [axD[n].get_position().x0,\n",
+    "         axD[n].get_position().y0 - 0.035,\n",
+    "         axD[n].get_position().x1 - axD[n].get_position().x0,\n",
+    "         0.01])\n",
+    "\n",
+    "min_val = [10, 0, 0]\n",
+    "max_val = [30, 50, 120]\n",
+    "step_val = [5, 10, 20]\n",
+    "cbar_cmap = ['inferno', 'plasma_r', 'plasma_r']\n",
+    "cbar_norm = [None] * 3\n",
+    "\n",
+    "for n in range(3):\n",
+    "    cbar_norm[n] = colors.Normalize(vmin=min_val[n], vmax=max_val[n])\n",
+    "    cbar = fig.colorbar(cm.ScalarMappable(norm=cbar_norm[n],\n",
+    "                                          cmap=cbar_cmap[n]),\n",
+    "                        cax=cax[n], orientation='horizontal')\n",
+    "    cbar.outline.set_linewidth(0.5)\n",
+    "    cbar.ax.tick_params(length=6, width=0.5)\n",
+    "    cbar.set_ticks(np.arange(min_val[n], max_val[n] + 1, step_val[n]))\n",
+    "    cbar.ax.set_xticklabels(['0' if v == 0 else f'−{-v}' if v < 0 else f'{v}'\n",
+    "                             for v in range(min_val[n], max_val[n] + 1,\n",
+    "                                            step_val[n])],\n",
+    "                            fontsize='large')\n",
+    "    if n == 0:\n",
+    "        cbar.set_label('Mean surface air temperature, °C',\n",
+    "                       fontsize='large')\n",
+    "    else:\n",
+    "        cbar.set_label('Mean grid cell contributions\\n'\n",
+    "                       'to the ionospheric potential, V',\n",
+    "                       fontsize='large')\n",
+    "\n",
+    "for axis in ['geo']:\n",
+    "    axM.spines[axis].set_linewidth(0.5)\n",
+    "axM.tick_params(top=True, right=True, which='both')\n",
+    "axM.tick_params(length=6, width=0.5)\n",
+    "axM.tick_params(length=3, width=0.5, which='minor')\n",
+    "axM.grid(False)\n",
+    "\n",
+    "axM.set_xticks(np.arange(-180, 181, 30))\n",
+    "axM.set_xticks(np.arange(-180, 181, 10), minor=True)\n",
+    "axM.set_xticklabels(['180°', '', '120° W', '', '60° W', '', '0°',\n",
+    "                     '', '60° E', '', '120° E', '', '180°'],\n",
+    "                    fontsize='large', va='top')\n",
+    "# thin spaces (' ') are used between ‘°’ signs and letters\n",
+    "\n",
+    "axM.set_yticks(np.arange(-90, 91, 30))\n",
+    "axM.set_yticks(np.arange(-90, 91, 10), minor=True)\n",
+    "axM.set_yticklabels(['', '', '30° S', '0°', '30° N', '', ''],\n",
+    "                    fontsize='large')\n",
+    "# thin spaces (' ') are used between ‘°’ signs and letters\n",
+    "\n",
+    "axM.set_title('Partition of the Earth’s surface into regions',\n",
+    "              fontsize='large', pad=10)\n",
+    "\n",
+    "for j in range(6):\n",
+    "    ax[2*j].bar(range(12), wrf_ip_sum_over_bands[j],\n",
+    "                0.8, color=wrf_bands[j].color)\n",
+    "\n",
+    "    ax[2*j+1].bar(range(12), inm_ip_sum_over_bands[j],\n",
+    "                0.8, color=inm_bands[j].color)\n",
+    "\n",
+    "    axT[j].bar(range(12), wrf_t2_avg_over_bands[j],\n",
+    "                0.8, color=wrf_t2_bands[j].color)\n",
+    "\n",
+    "    offset = lambda p: transforms.ScaledTranslation(0, p/72, fig.dpi_scale_trans)\n",
+    "    for AX in [ax[2*j], ax[2*j+1]]:\n",
+    "        AX.text(0.01 if j<2 else 0.99, 1,\n",
+    "               wrf_bands[j].title,\n",
+    "               fontsize='large', \n",
+    "               ha='left' if j<2 else 'right', \n",
+    "               va='top',\n",
+    "               transform=AX.transAxes + offset(-2))\n",
+    "\n",
+    "    axT[j].text(0.01 if j<2 else 0.99, 1,\n",
+    "               wrf_t2_bands[j].title,\n",
+    "               fontsize='large', \n",
+    "               ha='left' if j<2 else 'right', \n",
+    "               va='top',\n",
+    "               transform=axT[j].transAxes + offset(-2))\n",
+    "\n",
+    "\n",
+    "axD[0].imshow(T2_LxM,\n",
+    "              cmap=cbar_cmap[0], norm=cbar_norm[0],\n",
+    "              extent=[0, 12, 30, -30], aspect='auto', interpolation='none',\n",
+    "              rasterized=True)\n",
+    "axD[1].imshow(WRF_IP_LxM,\n",
+    "              cmap=cbar_cmap[1], norm=cbar_norm[1],\n",
+    "              extent=[0, 12, 30, -30], aspect='auto', interpolation='none',\n",
+    "              rasterized=True)\n",
+    "axD[2].imshow(INM_IP_LxM,\n",
+    "              cmap=cbar_cmap[2], norm=cbar_norm[2],\n",
+    "              extent=[0, 12, 30, -30], aspect='auto', interpolation='none',\n",
+    "              rasterized=True)\n",
+    "\n",
+    "axM.imshow(np.flip(strip_map[60:-60], axis=0), extent=[-180, 180, -30, 30])\n",
+    "\n",
+    "for n in range(3):\n",
+    "    axD[n].text(-0.28 * width/width, 1 + 0.1 * heightD/heightD,\n",
+    "                chr(ord('a') + 2 * n), fontsize='x-large',\n",
+    "                fontweight='semibold', ha='left', va='bottom',\n",
+    "                transform=axD[n].transAxes)\n",
+    "\n",
+    "axT[0].text(-0.28 * width/width, 1 + 0.1 * heightD/heightT[0],\n",
+    "            'b', fontsize='x-large',\n",
+    "            fontweight='semibold', ha='left', va='bottom',\n",
+    "            transform=axT[0].transAxes)\n",
+    "\n",
+    "for n in range(2):\n",
+    "    ax[n].text(-0.28 * width/width, 1 + 0.1 * heightD/height[0],\n",
+    "               chr(ord('d') + 2 * n), fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "axM.text(-0.28 * width/widthM, 1 + 0.1 * heightD/heightM,\n",
+    "         'g', fontsize='x-large',\n",
+    "         fontweight='semibold', ha='left', va='bottom',\n",
+    "         transform=axM.transAxes)\n",
+    "\n",
+    "fig.savefig('figures_two_parts/ip_separate.eps', bbox_inches='tight')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fb649ed7-f596-4156-b861-cb72461523ce",
+   "metadata": {},
+   "source": [
+    "### Figure 2.6"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "cd3ddeed-7054-46bc-9764-7324b89ad4fe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vostok_diurnal = np.load('./data/Vostok/vostok_diurnal_2006_2020.npy')\n",
+    "vostok_seasonal = np.load('./data/Vostok/vostok_2006_2020_results.npz')['mean'][0]\n",
+    "vostok_seasonal_counter = np.load('./data/Vostok/vostok_2006_2020_results.npz')['counter'][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "15f1693c-53bd-448b-9388-6cf4fd53acf6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wrf_diurnal = wrf_hourly_total_ip[1000].mean(axis=0) / 240e3\n",
+    "wrf_new_diurnal = wrf_hourly_total_ip[500].mean(axis=0) / 240e3\n",
+    "vostok_diurnal /= vostok_diurnal.mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "72c110be-1294-4df7-a7d7-e3197b38a5b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ring \n",
+    "vostok_diurnal = [*vostok_diurnal, vostok_diurnal[0]]\n",
+    "wrf_new_diurnal = [*wrf_new_diurnal, wrf_new_diurnal[0]]\n",
+    "wrf_diurnal = [*wrf_diurnal, wrf_diurnal[0]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "0dc8e9ad-9444-4880-85b0-405a4f26e6bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# select the latitudinal bands for analysis\n",
+    "band_names = [\"0-9N\", \"0-9S\", \"9S-18S\", \"18S-90S\", \"9N-18N\", \"18N-90N\"]\n",
+    "wrf_bands = [LatitudeBand(t, model=\"WRF\") for t in band_names]\n",
+    "inmcm_bands = [LatitudeBand(t, model=\"INMCM\") for t in band_names]\n",
+    "\n",
+    "bar_data = np.zeros((2, len(band_names), 12))\n",
+    "# (axes, bands, months)\n",
+    "\n",
+    "for i, band in enumerate(wrf_bands):\n",
+    "    bar_data[0, i] = wrf_LATxMON_ip[1000][band.slice].sum(axis=0)\n",
+    "    bar_data[1, i] = wrf_LATxMON_ip[500][band.slice].sum(axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "1cf42d06-6fa5-4065-b51a-4092c6d2c550",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# helper function for reuse code of indicate peak-to-peak amplitude \n",
+    "def external_arrows(ax=None, miny=0, maxy=1, arrow_pos=12, text_pos=12.2, ampl=2):\n",
+    "    ax.annotate(\n",
+    "        \"\",\n",
+    "        xy=(arrow_pos, miny),\n",
+    "        xycoords=\"data\",\n",
+    "        xytext=(arrow_pos, maxy),\n",
+    "        textcoords=\"data\",\n",
+    "        annotation_clip=False,\n",
+    "        arrowprops=dict(\n",
+    "            arrowstyle=\"-\",\n",
+    "            patchA=None,\n",
+    "            patchB=None,\n",
+    "            shrinkA=0.0,\n",
+    "            shrinkB=0.0,\n",
+    "            connectionstyle=\"arc3,rad=0.\",\n",
+    "            fc=\"black\",\n",
+    "            linewidth=0.5,\n",
+    "        ),\n",
+    "    )\n",
+    "    ax.annotate(\n",
+    "        \"\",\n",
+    "        xy=(arrow_pos, maxy + 30e3),\n",
+    "        xycoords=\"data\",\n",
+    "        xytext=(arrow_pos, maxy),\n",
+    "        textcoords=\"data\",\n",
+    "        annotation_clip=False,\n",
+    "        arrowprops=dict(\n",
+    "            arrowstyle=\"<|-,head_length=0.8,head_width=0.3\",\n",
+    "            patchA=None,\n",
+    "            patchB=None,\n",
+    "            shrinkA=0.0,\n",
+    "            shrinkB=0.0,\n",
+    "            connectionstyle=\"arc3,rad=0.\",\n",
+    "            fc=\"black\",\n",
+    "            linewidth=0.5,\n",
+    "        ),\n",
+    "    )\n",
+    "    ax.annotate(\n",
+    "        \"\",\n",
+    "        xy=(arrow_pos, miny - 30e3),\n",
+    "        xycoords=\"data\",\n",
+    "        xytext=(arrow_pos, miny),\n",
+    "        textcoords=\"data\",\n",
+    "        annotation_clip=False,\n",
+    "        arrowprops=dict(\n",
+    "            arrowstyle=\"<|-,head_length=0.8,head_width=0.3\",\n",
+    "            patchA=None,\n",
+    "            patchB=None,\n",
+    "            shrinkA=0.0,\n",
+    "            shrinkB=0.0,\n",
+    "            connectionstyle=\"arc3,rad=0.\",\n",
+    "            fc=\"black\",\n",
+    "            linewidth=0.5,\n",
+    "        ),\n",
+    "    )\n",
+    "\n",
+    "    ax.text(\n",
+    "        text_pos,\n",
+    "        (miny + maxy) / 2,\n",
+    "        f\"{ampl * 100:.0f}%\",\n",
+    "        fontsize=\"large\",\n",
+    "        ha=\"left\",\n",
+    "        va=\"center\",\n",
+    "        rotation=270,\n",
+    "    )\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "id": "9a85ba47-cb25-4a1f-a036-f1d09f63438b",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1500 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 15), constrained_layout=False)\n",
+    "ax = [None for _ in range(6)]\n",
+    "for n in range(6):\n",
+    "    ax[n] = fig.add_subplot(4, 4, (2*n + 1, 2*n + 2))\n",
+    "\n",
+    "low = [0.8, 0] + [0.8, 0e3] * 2\n",
+    "high = [1.2, 180] + [1.2, 300e3] * 2\n",
+    "step = [0.1, 30] + [0.1, 50e3] * 2\n",
+    "coeff = [1] * 2 + [1, 1e3] * 2\n",
+    "caption = ['Vostok station, 2006–2020',\n",
+    "           'Vostok station, 2006–2020',\n",
+    "           'WRF, 1980–2020, $\\\\varepsilon_0 = 1$ kJ/kg',\n",
+    "           'WRF, 1980–2020, $\\\\varepsilon_0 = 1$ kJ/kg',\n",
+    "           'WRF, 1980–2020, $\\\\varepsilon_0 = 0.5$ kJ/kg, $T_0 = 25$ °C',\n",
+    "           'WRF, 1980–2020, $\\\\varepsilon_0 = 0.5$ kJ/kg, $T_0 = 25$ °C']\n",
+    "lab = ['18° S–90° S',\n",
+    "       '9° S–18° S',\n",
+    "       '0°–9° S',\n",
+    "       '0°–9° N',\n",
+    "       '9° N–18° N',\n",
+    "       '18° N–90° N']\n",
+    "# thin spaces (' ') are used between ‘°’ signs and letters\n",
+    "\n",
+    "for n in range(0, 5, 2):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5)\n",
+    "    ax[n].grid(color='0.', linewidth=0.5)\n",
+    "\n",
+    "    ax[n].set_xlim((0, 24))\n",
+    "    ax[n].set_xticks(np.arange(0, 25, 2))\n",
+    "    ax[n].set_xticklabels(np.arange(0, 25, 2), fontsize='large')\n",
+    "    ax[n].set_xlabel('UTC, hours', fontsize='large')\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels([f'{x:.1f}' for x in\n",
+    "                           np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]],\n",
+    "                          fontsize='large')\n",
+    "    if n == 0:\n",
+    "        ax[n].set_ylabel('Fair-weather pot. gradient\\n'\n",
+    "                         'as a fraction of the mean',\n",
+    "                     fontsize='large')\n",
+    "    else:\n",
+    "        ax[n].set_ylabel('Ionospheric potential\\nas a fraction of the mean',\n",
+    "                         fontsize='large')\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize='large')\n",
+    "\n",
+    "for n in range(1, 6, 2):\n",
+    "    for axis in ['top', 'bottom', 'left', 'right']:\n",
+    "        ax[n].spines[axis].set_linewidth(0.5)\n",
+    "    ax[n].tick_params(length=6, width=0.5, axis='y')\n",
+    "    ax[n].tick_params(length=0, width=0.5, axis='x')\n",
+    "    ax[n].grid(color='0.', linewidth=0.5, axis='y')\n",
+    "\n",
+    "    ax[n].set_xlim((-0.5, 11.5))\n",
+    "    ax[n].set_xticks(np.arange(12))\n",
+    "    ax[n].set_xticklabels(month_name, fontsize='large', va='top')\n",
+    "\n",
+    "    ax[n].set_ylim((low[n], high[n]))\n",
+    "    ax[n].set_yticks(np.arange(low[n], high[n] + step[n] / 2, step[n]))\n",
+    "    ax[n].set_yticklabels((np.arange(low[n], high[n] + step[n] / 2,\n",
+    "                                     step[n]) / coeff[n]).astype(int),\n",
+    "                          fontsize='large')\n",
+    "    if n == 1:\n",
+    "        ax[n].set_ylabel('Monthly mean fair-weather\\npotential gradient, V/m',\n",
+    "                         fontsize='large')\n",
+    "    else:\n",
+    "        ax[n].set_ylabel('Monthly mean\\nionospheric potential, kV',\n",
+    "                         fontsize='large')\n",
+    "\n",
+    "    ax[n].set_title(caption[n], fontsize='large')\n",
+    "\n",
+    "\n",
+    "fig.align_ylabels([ax[0], ax[2], ax[4]])\n",
+    "fig.align_ylabels([ax[1], ax[3], ax[5]])\n",
+    "\n",
+    "# diurnal variations\n",
+    "ax[0].plot(np.arange(0, 25),\n",
+    "           vostok_diurnal,\n",
+    "           linewidth=1.5, color='purple', clip_on=False,\n",
+    "           zorder=4)\n",
+    "\n",
+    "ax[2].plot(np.arange(0, 25),\n",
+    "           wrf_diurnal,\n",
+    "           linewidth=1.5, color='purple', clip_on=False,\n",
+    "           zorder=4)\n",
+    "ax[4].plot(np.arange(0, 25),\n",
+    "           wrf_new_diurnal,\n",
+    "           linewidth=1.5, color='purple', clip_on=False,\n",
+    "           zorder=4)\n",
+    "\n",
+    "# arrows and amplitudes\n",
+    "for ax_number, data_diurnal in zip([0, 2, 4], [vostok_diurnal, wrf_diurnal, wrf_new_diurnal]):\n",
+    "    ax[ax_number].annotate('', xy=(25, np.min(data_diurnal)), xycoords='data',\n",
+    "                   xytext=(25, np.max(data_diurnal)), textcoords='data',\n",
+    "                   annotation_clip=False,\n",
+    "                   arrowprops=dict(\n",
+    "                       arrowstyle='<|-|>,head_length=0.8,head_width=0.3',\n",
+    "                       patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                       connectionstyle='arc3,rad=0.', fc='black',\n",
+    "                       linewidth=0.5\n",
+    "                   ))\n",
+    "    ampl = np.max(data_diurnal) - np.min(data_diurnal)\n",
+    "    ax[ax_number].text(25.2, (np.min(data_diurnal) +\n",
+    "                      np.max(data_diurnal)) / 2,\n",
+    "               f'{ampl * 100:.0f}%',\n",
+    "               fontsize='large', ha='left', va='center', rotation=270)\n",
+    "\n",
+    "# seasonal variation of PG\n",
+    "ax[1].bar(np.arange(12), vostok_seasonal, 0.8, color='orangered')\n",
+    "\n",
+    "# arrows and percent label for seasonal variation of PG\n",
+    "vostok_ampl = (vostok_seasonal.max() - vostok_seasonal.min())\n",
+    "vostok_ampl /= (vostok_seasonal*vostok_seasonal_counter).sum()/vostok_seasonal_counter.sum()\n",
+    "\n",
+    "ax[1].annotate('', xy=(12, np.min(vostok_seasonal)), xycoords='data',\n",
+    "               xytext=(12, np.max(vostok_seasonal)), textcoords='data',\n",
+    "               annotation_clip=False,\n",
+    "               arrowprops=dict(\n",
+    "                   arrowstyle='<|-|>,head_length=0.8,head_width=0.3',\n",
+    "                   patchA=None, patchB=None, shrinkA=0., shrinkB=0.,\n",
+    "                   connectionstyle='arc3,rad=0.', fc='black',\n",
+    "                   linewidth=0.5\n",
+    "               ))\n",
+    "ax[1].text(12.2, (np.min(vostok_seasonal) +\n",
+    "                  np.max(vostok_seasonal)) / 2,\n",
+    "           f'{vostok_ampl * 100:.0f}%',\n",
+    "           fontsize='large', ha='left', va='center', rotation=270)\n",
+    "\n",
+    "# seasonal variations of simulated IP (separated by latitude bands)\n",
+    "for n in range(2):\n",
+    "    bottom_data = np.zeros(12)\n",
+    "    for k in range(len(band_names)):\n",
+    "        data = bar_data[n, k]\n",
+    "        ax[2*n+3].bar(\n",
+    "            np.arange(12),\n",
+    "            data,\n",
+    "            0.8,\n",
+    "            color=wrf_bands[k].color,\n",
+    "            bottom=bottom_data,\n",
+    "            label=wrf_bands[k].title,\n",
+    "        )\n",
+    "        bottom_data += data\n",
+    "\n",
+    "\n",
+    "# arrows and percent label for seasonal variations of simulated IP\n",
+    "variation_1000 = wrf_LATxMON_ip[1000].sum(axis=0)\n",
+    "variation_500 = wrf_LATxMON_ip[500].sum(axis=0)\n",
+    "for ax_number, seasonal_variation in zip([3, 5], [variation_1000, variation_500]):\n",
+    "    seasonal_ampl = (seasonal_variation.max() - seasonal_variation.min())\n",
+    "    seasonal_ampl /= (seasonal_variation*wrf_numdays).sum()/wrf_numdays.sum()\n",
+    "    external_arrows(ax=ax[ax_number], \n",
+    "                    miny=seasonal_variation.min(), \n",
+    "                    maxy=seasonal_variation.max(), \n",
+    "                    ampl=seasonal_ampl)\n",
+    "        \n",
+    "\n",
+    "for n in range(0, 5, 2):\n",
+    "    ax[n].text(-0.27, 1.05, chr(ord('a') + n),\n",
+    "               fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "for n in range(1, 6, 2):\n",
+    "    ax[n].text(-0.28, 1.05, chr(ord('a') + n),\n",
+    "               fontsize='x-large',\n",
+    "               fontweight='semibold', ha='left', va='bottom',\n",
+    "               transform=ax[n].transAxes)\n",
+    "\n",
+    "fig.subplots_adjust(hspace=0.45, wspace=1.6)\n",
+    "\n",
+    "leg_width_rel = (ax[5].get_position().x1 - ax[4].get_position().x0) \\\n",
+    "    / (ax[5].get_position().x1 - ax[5].get_position().x0)\n",
+    "\n",
+    "leg = ax[5].legend(bbox_to_anchor=(1. - leg_width_rel, -1./2,\n",
+    "                                   leg_width_rel, 1./6), ncols=6,\n",
+    "                   loc='lower center', borderaxespad=0.,\n",
+    "                   mode='expand', fontsize='large',\n",
+    "                   framealpha=1, edgecolor='0.',\n",
+    "                   handlelength=1., handletextpad=0.5)\n",
+    "leg.get_frame().set_linewidth(0.5)\n",
+    "\n",
+    "fig.savefig('figures_two_parts/new_parameterisation.eps', bbox_inches='tight')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/data/INMCM/INMCM_HOURLY_TOTAL_IP_1000.npy b/data/INMCM/INMCM_HOURLY_TOTAL_IP_1000.npy
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diff --git a/data/INMCM/INMCM_HOURLY_TOTAL_IP_1200.npy b/data/INMCM/INMCM_HOURLY_TOTAL_IP_1200.npy
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diff --git a/data/INMCM/INMCM_IP_1000_LATxMON.npy b/data/INMCM/INMCM_IP_1000_LATxMON.npy
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diff --git a/data/INMCM/INMCM_IP_1200_LATxMON.npy b/data/INMCM/INMCM_IP_1200_LATxMON.npy
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diff --git a/data/INMCM/INMCM_IP_800_LATxMON.npy b/data/INMCM/INMCM_IP_800_LATxMON.npy
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diff --git a/data/Vostok/.ipynb_checkpoints/vostok_1998_2004_hourly_80percent_all-checkpoint.tsv b/data/Vostok/.ipynb_checkpoints/vostok_1998_2004_hourly_80percent_all-checkpoint.tsv
new file mode 100644
index 0000000..a6b827e
--- /dev/null
+++ b/data/Vostok/.ipynb_checkpoints/vostok_1998_2004_hourly_80percent_all-checkpoint.tsv
@@ -0,0 +1,40528 @@
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diff --git a/data/Vostok/.ipynb_checkpoints/vostok_daily_temp-checkpoint.csv b/data/Vostok/.ipynb_checkpoints/vostok_daily_temp-checkpoint.csv
new file mode 100644
index 0000000..c946f7a
--- /dev/null
+++ b/data/Vostok/.ipynb_checkpoints/vostok_daily_temp-checkpoint.csv
@@ -0,0 +1,6004 @@
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diff --git a/data/Vostok/.ipynb_checkpoints/vostok_hourly_from_10_s_without_calibration_and_empty-checkpoint.tsv b/data/Vostok/.ipynb_checkpoints/vostok_hourly_from_10_s_without_calibration_and_empty-checkpoint.tsv
new file mode 100644
index 0000000..7d29754
--- /dev/null
+++ b/data/Vostok/.ipynb_checkpoints/vostok_hourly_from_10_s_without_calibration_and_empty-checkpoint.tsv
@@ -0,0 +1,109365 @@
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diff --git a/data/Vostok/vostok_daily_pressure_mm_hg.csv b/data/Vostok/vostok_daily_pressure_mm_hg.csv
new file mode 100644
index 0000000..b8f647b
--- /dev/null
+++ b/data/Vostok/vostok_daily_pressure_mm_hg.csv
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diff --git a/data/Vostok/vostok_daily_temp.csv b/data/Vostok/vostok_daily_temp.csv
new file mode 100644
index 0000000..c946f7a
--- /dev/null
+++ b/data/Vostok/vostok_daily_temp.csv
@@ -0,0 +1,6004 @@
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diff --git a/data/Vostok/vostok_daily_wind.csv b/data/Vostok/vostok_daily_wind.csv
new file mode 100644
index 0000000..9ac7375
--- /dev/null
+++ b/data/Vostok/vostok_daily_wind.csv
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diff --git a/data/Vostok/vostok_hourly_from_10_s_without_calibration_and_empty.tsv b/data/Vostok/vostok_hourly_from_10_s_without_calibration_and_empty.tsv
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diff --git a/data/Vostok/vostok_hourly_from_5_min_without_calibration_and_empty.tsv b/data/Vostok/vostok_hourly_from_5_min_without_calibration_and_empty.tsv
new file mode 100644
index 0000000..c66b1b8
--- /dev/null
+++ b/data/Vostok/vostok_hourly_from_5_min_without_calibration_and_empty.tsv
@@ -0,0 +1,70352 @@
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diff --git a/data/WRF/WRF_HOURLY_TOTAL_IP_1000.npy b/data/WRF/WRF_HOURLY_TOTAL_IP_1000.npy
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diff --git a/data/WRF/WRF_HOURLY_TOTAL_IP_1200.npy b/data/WRF/WRF_HOURLY_TOTAL_IP_1200.npy
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diff --git a/data/WRF/WRF_HOURLY_TOTAL_IP_500_T2_25.npy b/data/WRF/WRF_HOURLY_TOTAL_IP_500_T2_25.npy
new file mode 100644
index 0000000000000000000000000000000000000000..5ab612d3822910ac47f0a28cecc45c0c01617504
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diff --git a/data/WRF/WRF_IP_500_T2_25_LATxMON.npy b/data/WRF/WRF_IP_500_T2_25_LATxMON.npy
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diff --git a/readme.md b/readme.md
new file mode 100644
index 0000000..b564c65
--- /dev/null
+++ b/readme.md
@@ -0,0 +1,102 @@
+# Short Description of the Scripts
+
+> **_Note:_** For analysis, we use simulation data of the ionospheric potential through climate models. Since these data are very large (around 350 Gb), we only upload preprocessed lower-dimensional data (around 20 Mb) to the repository. Data preparation is possible using the script `0_prepare_data.ipynb`, but this would require downloading large files from https://eee.ipfran.ru/files/seasonal-variation-2024/.
+
+* `1_Earlier_measurements_images.ipynb` plots seasonal variations from external sources
+* `2_Vostok_measurements_images.ipynb` plots seasonal variations and seasonal-dirunal diagram using new and early Vostok PG measurements
+* `3_WRF_T2_images.ipynb` plots seasonal variation of `T2m` temperature averaged across different latitude bands
+* `4_IP_simulations_temporal_images.ipynb` plots seasonal variation of simulated IP grouped by datasets and different year ranges
+* `5_IP_simulations_spatial_images.ipynb` plots seasonal variation of simulated IP grouped by latitude ranges
+
+> **_Note:_** The scripts should be executed sequentially one after another; at the very least, scripts 4 and 5 should be run after script 2. This is necessary because script 2 saves intermediate arrays of preprocessed data from the Vostok station, which are used in scripts 4 and 5.
+
+# Detailed Description of the Scripts
+
+## Script `1_Earlier_measurements_images.ipynb`
+
+This program contains digitized data from external sources, necessary for constructing Figure 1.1.
+
+At the beginning of the script, the necessary libraries are loaded and arrays with digitized data are declared; at the end, a graph is constructed. 
+
+Data analysis in this file is minimal - it calculates the amplitude of seasonal variation (as a percentage relative to the annual average value).
+
+## Script `2_Vostok_measurements_images.ipynb`
+
+This script is quite voluminous (for further understanding, see the comments in the code).
+
+Firstly, the introduction of digitized data is repeated in the code (in this case, only for the earlier data from the Vostok station, which are also used in the first script).
+
+### Preparing PG data
+
+Secondly, measurement data from the Vostok station (pre-averaged by the hour) are loaded into Pandas dataframes, both new (dataframes `df_10s` and `df_5min`) and earlier (dataframe `earlier_df_src`) datasets.
+
+New measurements at the Vostok station are combined from hourly data derived from 10-second files and hourly data derived from 5-minute files; it should be noted that the dataset primarily relies on the 10-second data, and the 5-minute data are only used when the 10-second data were unavailable (there were 24 such hours in 2013, 312 in 2015, 1752 in 2017, and 3600 in 2020). The composite series of new measurements is saved in the dataframe `df_src`.
+
+Next, we introduce helper functions. Notably, the `pass_fair_weather` function, when applied to a dataframe, retains only those days when (1) there were no gaps, (2) the potential gradient did not exceed 300 V/m and was non-negative, and (3) the peak-to-peak amplitude was no more than 150% of the average daily value of the potential gradient.
+
+The next helper functions to mention are `calculate_seasonal_var_params` and `std_error`. 
+
+They are structured such that the input to the first function is a dataframe with average daily values, and the function returns (1) an array of 12 average monthly values of PG, (2) an array of 12 counts of fair weather days per month, and (3) an array of 12 sums of squares of the average daily PG values of fair weather divided by the number of fair weather days, annotated by the following formula:
+
+sumₘ = Σ(daily mean PG for the `i`-th fair weather day)² / (count of fair weather days),
+
+where `m` denotes the month number `m = 1...12`, and `i` iterates over all fair weather days for which the month of the date equals `m`.
+
+The `std_error` function is designed to take the output from the `calculate_seasonal_var_param`s function and return 12 values of the standard error, one for each month.
+
+Both described functions are used to compute values necessary for plotting graphs (mean value ± standard error).
+
+For both new and early Vostok data, we apply the `pass_fair_weather` function, resulting in two datasets that contain only the hours of fair weather days (`df` and `earlier_df`)
+
+### Figure 1.2
+
+To construct Figure 1.2, using the prepared data and helper functions, we calculate the mean values, the count of fair weather days and standard errors for three sets of data:
+
+1. The complete series of new Vostok data.
+2. The same series up to and including the year 2012.
+3. The same series after the year 2012.
+
+> **_Note:_** The data from this figure is saved in the temporary file `vostok_2006_2020_results.npz` for use in the second article. This helps avoid code duplication or merging code to build different entities in a single cumbersome file.
+
+### Figure 1.3
+
+To construct Figure 1.3, we transform the Vostok data series into a matrix of 12 months x 24 hours. To do this, we group the original dataframe of fair weather hours by months and hours, and then find the mean value for all data points taken at a specific hour of a specific month (saved in dataframe `sd_df`).
+
+For clarity, we also present slices of this diurnal-seasonal diagram at 3, 9, 15, and 21 hours UTC.
+
+> **_Note:_**  Renaming the axes of the multi-index resulting from grouping (`sd_df.index.set_names(['hour', 'month'], inplace=True)`) is not necessary for the code and can be commented out; however, it may be convenient for further work with the diurnal-seasonal dataframe `sd_df`.
+
+### Figure 1.5
+#### Removal of field anomalies associated with meteorological parameters
+
+First, we load the meteorological datasets (`temp_df`, `wind_df`, `pressure_df`), averaged by days (`vostok_daily_temp`, `vostok_daily_wind`, `vostok_daily_pressure_mm_hg`). For further analysis, we use the `meteo_df` dataframe, which is created by merging the dataframe with daily average potential gradient values (`daily_df`).
+
+Next, we compile arrays of PG anomalies and anomalies for all meteorological parameters. The anomaly is calculated using a moving window of +-10 days.
+
+We then find the regression coefficients `temp_coeffs`, `wind_coeffs`, and `pres_coeffs` between the PG anomaly and the corresponding meteorological parameter anomalies, and calculate some statistical characteristics.
+
+Using the found regression coefficients, we remove the linear relationship with meteorological parameter anomalies. The corrected PG is saved in `meteo_df["CorrectedField"]`.
+
+Finally, we construct Figure 1.5 using the prepared data in the same manner as was done for Figures 1.2 and 1.3.
+
+
+## Script `3_WRF_T2_images.ipynb`
+
+This script calculates the seasonal variation of the 2m-level temperature (T2m) taken from climate modeling results (see article 1).
+
+In the script, temperature data averaged by longitude and by month are loaded (see data description below) from `WRF_T2_MONxLAT.npy`.
+
+Next, the temperature is averaged across latitude bands 20° S–20° N, 30° S–30° N, 40° S–40° N, and 50° S–50° N. The averaging takes into account the latitudinal area factor; degree cells at higher latitudes are summed with a diminishing coefficient. The results of the averaging (seasonal temperature variation in the specified latitude band) are displayed on a figure 1.4, 2.3 consisting of four panels.
+
+## Script `4_IP_simulations_temporal_images.ipynb`
+...
+
+## Script `5_IP_simulations_spatial_images.ipynb`
+...
+
+# Description of the data files
+
+* `WRF_T2_MONxLAT.npy` - a `numpy` array with the shape `(180, 12)`, containing montly averaged 2-meter level temperature (`T2m`) for each 1° latitude band across a full 360° longitude. `T2m` are calculated with the Weather Research and Forecasting model (WRF) version 4.3.
+* `vostok_hourly <...>.txt` - text files containing  two columns, one of which represents the date and time (column `Datetime`) and the other, hourly averaged potential gradient (PG) values on the basis of the latest measurements at the Russian Antarctic station Vostok (column `Field`, the units are V/m).
+* `vostok_1998_2004_hourly_80percent_all.tsv` - the same as the previous file, but these are early data collected by a different sensor during 1998-2004 
+* `vostok_daily <...>.txt` - text files containing three columns: one for the date (column `UTC`), the second for the daily averaged meteorological parameter based on measurements at the Russian Antarctic station Vostok, and the third column `Count` indicating the number of measurements per day (entries with fewer than 4 measurements must be filtered out before analysis).
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