{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0f09a974-37fe-440e-8daf-4aa0f2caae69",
   "metadata": {},
   "source": [
    "# Seasonal variation of air temperatures averaged over different latitudes\n",
    "The source code of Figures 1.4 and 2.3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a464e3d4-2cd3-470e-8f29-7f8f6793eb6e",
   "metadata": {},
   "source": [
    "### Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a80a0a4-ef03-411d-b441-21434947e6ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "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 temperatures at 2 m (T2m) for each 1° wide latitude strip;\n",
    "# T2m values are calculated with the WRF model, the shape is (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)\n",
    "    - 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": "markdown",
   "id": "149a1d22-3f64-438f-b425-15afbd3692bf",
   "metadata": {},
   "source": [
    "### Figure 1.4/2.3\n",
    "Seasonal variation of air temperatures averaged over different latitudes"
   ]
  },
  {
   "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((np.arange(low[n], high[n] + step[n] / 2,\n",
    "                                     step[n]) / coeff[n]).astype(int),\n",
    "                          fontsize=\"large\")\n",
    "    ax[n].set_ylabel(\"Mean surface\\nair temperature, °C\",\n",
    "                     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",
    "    # averaging temperature values taking into account\n",
    "    # variable areas of 1° wide latitude strips\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(-0.25, 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=1.0)\n",
    "\n",
    "fig.savefig(\"figures/t2.eps\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e9b11449-5115-492e-8529-c9bfb01a65f9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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