{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0f09a974-37fe-440e-8daf-4aa0f2caae69",
   "metadata": {},
   "source": [
    "# Analysis of temperature seasonal variation across a latitude bands"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a464e3d4-2cd3-470e-8f29-7f8f6793eb6e",
   "metadata": {},
   "source": [
    "### Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a80a0a4-ef03-411d-b441-21434947e6ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing the necessary libraries for data visualization and numerical operations\n",
    "# matplotlib.pyplot is used for plotting graphs, and numpy is used for handling numerical data efficiently\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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": 3,
   "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": 4,
   "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": 5,
   "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": 6,
   "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
}