Figure10.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "40b99b32",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/weitao/anaconda3/lib/python3.10/site-packages/geopandas/_compat.py:106: UserWarning: The Shapely GEOS version (3.8.0-CAPI-1.13.1) is incompatible with the GEOS version PyGEOS was compiled with (3.10.4-CAPI-1.16.2). Conversions between both will be slow.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "from netCDF4 import Dataset as NetCDFFile \n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "# from mpl_toolkits.basemap import Basemap\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "%matplotlib inline\n",
    "from cartopy.mpl.geoaxes import GeoAxes\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "from cartopy.feature import ShapelyFeature\n",
    "import cartopy.io.shapereader as shpreader\n",
    "from mpl_toolkits.axes_grid1 import AxesGrid, ImageGrid\n",
    "import pandas as pd \n",
    "import geopandas as gpd\n",
    "import seaborn as sns\n",
    "# import pygeos\n",
    "# Import modules\n",
    "import xarray as xr\n",
    "import matplotlib.ticker as mticker\n",
    "from matplotlib.gridspec import GridSpec\n",
    "import math\n",
    "import datetime\n",
    "from datetime import timedelta\n",
    "\n",
    "import math\n",
    "# importing the libraries \n",
    "from sklearn.preprocessing import LabelBinarizer \n",
    "import matplotlib as mpl\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1b8d35ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Fire/GFED/GFED4.1s_2021_beta.hdf5', 'Fire/GFED/GFED4.1s_2022_beta.hdf5']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GFEDlis = []\n",
    "for path in Path('Fire/GFED/').rglob('*.hdf5'):\n",
    "    GFEDlis.append(str(path))\n",
    "# for path in Path('./ZonalTableSEA1015/').rglob('*2022*.csv'):\n",
    "#     lisSEA.append(str(path))\n",
    "GFEDlis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fa8d0bc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "GEMSlis0245 = ['Fire/GEMS/GEMS_2022m2021_01_0245.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_02_0245.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_03_0245.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_04_0245.nc']\n",
    "GEMSlis0445 = ['Fire/GEMS/GEMS_2022m2021_01_0445.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_02_0445.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_03_0445.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_04_0445.nc']\n",
    "GEMSlis0645 = ['Fire/GEMS/GEMS_2022m2021_01_0645.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_02_0645.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_03_0645.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_04_0645.nc']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7db2367a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>C</th>\n",
       "      <th>DM</th>\n",
       "      <th>UTC_0-3h</th>\n",
       "      <th>UTC_12-15h</th>\n",
       "      <th>UTC_15-18h</th>\n",
       "      <th>UTC_18-21h</th>\n",
       "      <th>UTC_21-24h</th>\n",
       "      <th>UTC_3-6h</th>\n",
       "      <th>UTC_6-9h</th>\n",
       "      <th>UTC_9-12h</th>\n",
       "      <th>DM_AGRI</th>\n",
       "      <th>DM_BORF</th>\n",
       "      <th>DM_DEFO</th>\n",
       "      <th>DM_PEAT</th>\n",
       "      <th>DM_SAVA</th>\n",
       "      <th>DM_TEMF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>346680</th>\n",
       "      <td>29.875</td>\n",
       "      <td>90.125</td>\n",
       "      <td>2021</td>\n",
       "      <td>01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.031380</td>\n",
       "      <td>0.096860</td>\n",
       "      <td>0.054151</td>\n",
       "      <td>0.033291</td>\n",
       "      <td>0.031302</td>\n",
       "      <td>0.168124</td>\n",
       "      <td>0.356744</td>\n",
       "      <td>0.228148</td>\n",
       "      <td>0.030389</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.969611</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346681</th>\n",
       "      <td>29.875</td>\n",
       "      <td>90.375</td>\n",
       "      <td>2021</td>\n",
       "      <td>01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.031380</td>\n",
       "      <td>0.096860</td>\n",
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       "      <td>0.033291</td>\n",
       "      <td>0.031302</td>\n",
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       "      <td>0.356744</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.969611</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346682</th>\n",
       "      <td>29.875</td>\n",
       "      <td>90.625</td>\n",
       "      <td>2021</td>\n",
       "      <td>01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.031380</td>\n",
       "      <td>0.096860</td>\n",
       "      <td>0.054151</td>\n",
       "      <td>0.033291</td>\n",
       "      <td>0.031302</td>\n",
       "      <td>0.168124</td>\n",
       "      <td>0.356744</td>\n",
       "      <td>0.228148</td>\n",
       "      <td>0.030389</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.969611</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346683</th>\n",
       "      <td>29.875</td>\n",
       "      <td>90.875</td>\n",
       "      <td>2021</td>\n",
       "      <td>01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.031380</td>\n",
       "      <td>0.096860</td>\n",
       "      <td>0.054151</td>\n",
       "      <td>0.033291</td>\n",
       "      <td>0.031302</td>\n",
       "      <td>0.168124</td>\n",
       "      <td>0.356744</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346684</th>\n",
       "      <td>29.875</td>\n",
       "      <td>91.125</td>\n",
       "      <td>2021</td>\n",
       "      <td>01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.031380</td>\n",
       "      <td>0.096860</td>\n",
       "      <td>0.054151</td>\n",
       "      <td>0.033291</td>\n",
       "      <td>0.031302</td>\n",
       "      <td>0.168124</td>\n",
       "      <td>0.356744</td>\n",
       "      <td>0.228148</td>\n",
       "      <td>0.030389</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.969611</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>460515</th>\n",
       "      <td>10.125</td>\n",
       "      <td>108.875</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050068</td>\n",
       "      <td>0.062124</td>\n",
       "      <td>0.034230</td>\n",
       "      <td>0.013260</td>\n",
       "      <td>0.011477</td>\n",
       "      <td>0.258091</td>\n",
       "      <td>0.405644</td>\n",
       "      <td>0.165106</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>460516</th>\n",
       "      <td>10.125</td>\n",
       "      <td>109.125</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050068</td>\n",
       "      <td>0.062124</td>\n",
       "      <td>0.034230</td>\n",
       "      <td>0.013260</td>\n",
       "      <td>0.011477</td>\n",
       "      <td>0.258091</td>\n",
       "      <td>0.405644</td>\n",
       "      <td>0.165106</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>460517</th>\n",
       "      <td>10.125</td>\n",
       "      <td>109.375</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050068</td>\n",
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       "      <td>0.034230</td>\n",
       "      <td>0.013260</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>460518</th>\n",
       "      <td>10.125</td>\n",
       "      <td>109.625</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050068</td>\n",
       "      <td>0.062124</td>\n",
       "      <td>0.034230</td>\n",
       "      <td>0.013260</td>\n",
       "      <td>0.011477</td>\n",
       "      <td>0.258091</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>460519</th>\n",
       "      <td>10.125</td>\n",
       "      <td>109.875</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050068</td>\n",
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       "      <td>0.034230</td>\n",
       "      <td>0.013260</td>\n",
       "      <td>0.011477</td>\n",
       "      <td>0.258091</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>153600 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           lat      lon  year month    C   DM  UTC_0-3h  UTC_12-15h  \\\n",
       "346680  29.875   90.125  2021    01  0.0  0.0  0.031380    0.096860   \n",
       "346681  29.875   90.375  2021    01  0.0  0.0  0.031380    0.096860   \n",
       "346682  29.875   90.625  2021    01  0.0  0.0  0.031380    0.096860   \n",
       "346683  29.875   90.875  2021    01  0.0  0.0  0.031380    0.096860   \n",
       "346684  29.875   91.125  2021    01  0.0  0.0  0.031380    0.096860   \n",
       "...        ...      ...   ...   ...  ...  ...       ...         ...   \n",
       "460515  10.125  108.875  2022    12  0.0  0.0  0.050068    0.062124   \n",
       "460516  10.125  109.125  2022    12  0.0  0.0  0.050068    0.062124   \n",
       "460517  10.125  109.375  2022    12  0.0  0.0  0.050068    0.062124   \n",
       "460518  10.125  109.625  2022    12  0.0  0.0  0.050068    0.062124   \n",
       "460519  10.125  109.875  2022    12  0.0  0.0  0.050068    0.062124   \n",
       "\n",
       "        UTC_15-18h  UTC_18-21h  UTC_21-24h  UTC_3-6h  UTC_6-9h  UTC_9-12h  \\\n",
       "346680    0.054151    0.033291    0.031302  0.168124  0.356744   0.228148   \n",
       "346681    0.054151    0.033291    0.031302  0.168124  0.356744   0.228148   \n",
       "346682    0.054151    0.033291    0.031302  0.168124  0.356744   0.228148   \n",
       "346683    0.054151    0.033291    0.031302  0.168124  0.356744   0.228148   \n",
       "346684    0.054151    0.033291    0.031302  0.168124  0.356744   0.228148   \n",
       "...            ...         ...         ...       ...       ...        ...   \n",
       "460515    0.034230    0.013260    0.011477  0.258091  0.405644   0.165106   \n",
       "460516    0.034230    0.013260    0.011477  0.258091  0.405644   0.165106   \n",
       "460517    0.034230    0.013260    0.011477  0.258091  0.405644   0.165106   \n",
       "460518    0.034230    0.013260    0.011477  0.258091  0.405644   0.165106   \n",
       "460519    0.034230    0.013260    0.011477  0.258091  0.405644   0.165106   \n",
       "\n",
       "         DM_AGRI  DM_BORF  DM_DEFO  DM_PEAT   DM_SAVA  DM_TEMF  \n",
       "346680  0.030389      0.0      0.0      0.0  0.969611      0.0  \n",
       "346681  0.030389      0.0      0.0      0.0  0.969611      0.0  \n",
       "346682  0.030389      0.0      0.0      0.0  0.969611      0.0  \n",
       "346683  0.000000      0.0      0.0      0.0  1.000000      0.0  \n",
       "346684  0.030389      0.0      0.0      0.0  0.969611      0.0  \n",
       "...          ...      ...      ...      ...       ...      ...  \n",
       "460515  0.000000      0.0      0.0      0.0  0.000000      0.0  \n",
       "460516  0.000000      0.0      0.0      0.0  0.000000      0.0  \n",
       "460517  0.000000      0.0      0.0      0.0  0.000000      0.0  \n",
       "460518  0.000000      0.0      0.0      0.0  0.000000      0.0  \n",
       "460519  0.000000      0.0      0.0      0.0  0.000000      0.0  \n",
       "\n",
       "[153600 rows x 20 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "months = ['01','02','03','04','05','06','07','08','09','10','11','12']\n",
    "\n",
    "columns = ['lat', 'lon', 'year', 'month', 'C', 'DM', 'UTC_0-3h', 'UTC_12-15h',\n",
    "       'UTC_15-18h', 'UTC_18-21h', 'UTC_21-24h', 'UTC_3-6h', 'UTC_6-9h',\n",
    "       'UTC_9-12h', 'DM_AGRI', 'DM_BORF', 'DM_DEFO', 'DM_PEAT', 'DM_SAVA',\n",
    "       'DM_TEMF']\n",
    "\n",
    "gfed = pd.DataFrame(columns = columns)\n",
    "\n",
    "for yearEmi in GFEDlis:\n",
    "    corr = xr.open_dataset(yearEmi, engine=\"netcdf4\").to_dataframe()\n",
    "    for mon in months:\n",
    "        try:\n",
    "            emis = xr.open_dataset(yearEmi, engine=\"netcdf4\", group = 'emissions/'+mon).to_dataframe()\n",
    "#             print(1)\n",
    "            partitioning = xr.open_dataset(yearEmi, engine=\"netcdf4\", group = 'emissions/'+mon+'/partitioning').to_dataframe()\n",
    "            diurnal = xr.open_dataset(yearEmi, engine=\"netcdf4\", group = 'emissions/'+mon+'/diurnal_cycle').to_dataframe()\n",
    "#             print(2)\n",
    "            gfedT = pd.concat([emis, corr, partitioning, diurnal], axis=1).reset_index()\n",
    "            gfedT['year'] = str(yearEmi)[-14:-10]\n",
    "            gfedT['month'] = mon\n",
    "            gfedT = gfedT[columns]\n",
    "            gfedT = gfedT[(gfedT['lat']>10)&(gfedT['lat']<30)&(gfedT['lon']>90)&(gfedT['lon']<110)]\n",
    "#             print(3)\n",
    "\n",
    "            gfed = pd.concat([gfed,gfedT])\n",
    "        except:\n",
    "            print(yearEmi + '?' + mon)\n",
    "gfed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9de52d72",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>C</th>\n",
       "      <th>DM</th>\n",
       "      <th>UTC_0-3h</th>\n",
       "      <th>UTC_12-15h</th>\n",
       "      <th>UTC_15-18h</th>\n",
       "      <th>UTC_18-21h</th>\n",
       "      <th>...</th>\n",
       "      <th>DM_BORF</th>\n",
       "      <th>DM_DEFO</th>\n",
       "      <th>DM_PEAT</th>\n",
       "      <th>DM_SAVA</th>\n",
       "      <th>DM_TEMF</th>\n",
       "      <th>HCHO</th>\n",
       "      <th>Days</th>\n",
       "      <th>HCHO_Daily</th>\n",
       "      <th>HCHO_Daily_KG_KM2</th>\n",
       "      <th>HCHO_VCD_e15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>346685</th>\n",
       "      <td>29.875</td>\n",
       "      <td>91.375</td>\n",
       "      <td>2021</td>\n",
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       "      <th>348124</th>\n",
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       "      <td>2022</td>\n",
       "      <td>12</td>\n",
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       "      <td>105.875</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>1.086189</td>\n",
       "      <td>0.002255</td>\n",
       "      <td>0.048746</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>460500</th>\n",
       "      <td>10.125</td>\n",
       "      <td>105.125</td>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>1.155333</td>\n",
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       "      <td>0.048746</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31766 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           lat      lon  year month         C        DM  UTC_0-3h  UTC_12-15h  \\\n",
       "346685  29.875   91.375  2021    01  0.109643  0.000225  0.031380    0.096860   \n",
       "346736  29.875  104.125  2021    01  0.382805  0.000797  0.038497    0.093727   \n",
       "348123  29.625   90.875  2021    01  1.273078  0.002610  0.031380    0.096860   \n",
       "348124  29.625   91.125  2021    01  0.112572  0.000231  0.031380    0.096860   \n",
       "348125  29.625   91.375  2021    01  0.477641  0.000979  0.031380    0.096860   \n",
       "...        ...      ...   ...   ...       ...       ...       ...         ...   \n",
       "457626  10.625  106.625  2022    12  1.305593  0.002714  0.030017    0.065588   \n",
       "457628  10.625  107.125  2022    12  1.150456  0.002371  0.042911    0.067887   \n",
       "459059  10.375  104.875  2022    12  0.204219  0.000421  0.031986    0.066139   \n",
       "459063  10.375  105.875  2022    12  1.086189  0.002255  0.048746    0.070489   \n",
       "460500  10.125  105.125  2022    12  1.155333  0.002401  0.048746    0.070489   \n",
       "\n",
       "        UTC_15-18h  UTC_18-21h  ...  DM_BORF   DM_DEFO  DM_PEAT   DM_SAVA  \\\n",
       "346685    0.054151    0.033291  ...      0.0  0.000000      0.0  0.887337   \n",
       "346736    0.058009    0.032116  ...      0.0  0.000000      0.0  0.028849   \n",
       "348123    0.054151    0.033291  ...      0.0  0.000000      0.0  0.946959   \n",
       "348124    0.054151    0.033291  ...      0.0  0.000000      0.0  0.923240   \n",
       "348125    0.054151    0.033291  ...      0.0  0.000000      0.0  0.976130   \n",
       "...            ...         ...  ...      ...       ...      ...       ...   \n",
       "457626    0.031697    0.005690  ...      0.0  0.000000      0.0  0.081239   \n",
       "457628    0.035014    0.006652  ...      0.0  0.000000      0.0  0.606723   \n",
       "459059    0.033398    0.005953  ...      0.0  0.313909      0.0  0.202042   \n",
       "459063    0.037722    0.007484  ...      0.0  0.000000      0.0  0.164680   \n",
       "460500    0.037722    0.007484  ...      0.0  0.000000      0.0  0.117334   \n",
       "\n",
       "        DM_TEMF      HCHO  Days  HCHO_Daily  HCHO_Daily_KG_KM2  HCHO_VCD_e15  \n",
       "346685      0.0  0.000198  31.0    0.000006           0.006401      0.012850  \n",
       "346736      0.0  0.001626  31.0    0.000052           0.052445      0.105277  \n",
       "348123      0.0  0.002092  31.0    0.000067           0.067478      0.135455  \n",
       "348124      0.0  0.000192  31.0    0.000006           0.006208      0.012461  \n",
       "348125      0.0  0.000746  31.0    0.000024           0.024062      0.048301  \n",
       "...         ...       ...   ...         ...                ...           ...  \n",
       "457626      0.0  0.005348   NaN         NaN                NaN           NaN  \n",
       "457628      0.0  0.002990   NaN         NaN                NaN           NaN  \n",
       "459059      0.0  0.000714   NaN         NaN                NaN           NaN  \n",
       "459063      0.0  0.004189   NaN         NaN                NaN           NaN  \n",
       "460500      0.0  0.004613   NaN         NaN                NaN           NaN  \n",
       "\n",
       "[31766 rows x 25 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://www.geo.vu.nl/~gwerf/GFED/GFED4/ancill/GFED4_Emission_Factors.txt\n",
    "# emission factor (g HCHO per kg DM burned)\n",
    "# DM emissions (kg DM per m2 per month)\n",
    "gfed['HCHO'] = gfed['DM'] * (gfed['DM_AGRI']*2.08 + gfed['DM_BORF']*1.86 + gfed['DM_DEFO']*1.73 + gfed['DM_PEAT']*1.4 + gfed['DM_SAVA']*0.73 + gfed['DM_TEMF']*2.09)\n",
    "# g HCHO per m2 per month TO daily\n",
    "gfed['Days'] = gfed['month'].map({'01':31,'02':28,'03':31,'04':30})\n",
    "gfed['HCHO_Daily'] = gfed['HCHO'] / gfed['Days'] \n",
    "gfed['HCHO_Daily_KG_KM2'] = gfed['HCHO_Daily'] * 1e3 \n",
    "\n",
    "# HCHO Molecular Mass: 30\n",
    "gfed['HCHO_VCD_e15'] = gfed['HCHO_Daily'] * 6.02214*10000/30 # scaling factor: 1e15 \n",
    "gfed[gfed['HCHO']>0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f69b2db8",
   "metadata": {},
   "outputs": [],
   "source": [
    "GEMSlisD = [\n",
    " 'Fire/GEMS/GEMS_2022m2021_03_0245.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_03_0445.nc',\n",
    " 'Fire/GEMS/GEMS_2022m2021_03_0645.nc',\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0db87a21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# UTC 7\n",
    "int(str(GEMSlisD[0])[-7:-5]) + 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d3215ceb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/4y/knznw84s4p5d2d77tb6wyq6h0000gn/T/ipykernel_29924/972897903.py:17: UserWarning: This figure was using a layout engine that is incompatible with subplots_adjust and/or tight_layout; not calling subplots_adjust.\n",
      "  plt.subplots_adjust(wspace=0.1, hspace=0,top=0.935)\n",
      "/Users/weitao/anaconda3/lib/python3.10/site-packages/cartopy/mpl/style.py:76: UserWarning: facecolor will have no effect as it has been defined as \"never\".\n",
      "  warnings.warn('facecolor will have no effect as it has been '\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 629.921x708.661 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# cmap = mpl.cm.bwr\n",
    "bounds = [-10, -8, -6, -4, -2,  2, 4, 6, 8, 10]\n",
    "# bounds = [-10, -7.5, -5, -2.5,  2.5, 5, 7.5, 10]\n",
    "# norm = mpl.colors.BoundaryNorm(bounds, cmap.N, extend='both')\n",
    "\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=False)\n",
    "lat_formatter = LatitudeFormatter()\n",
    "alp = ['a','b','c','d','e','f','g','h','i','j','k','l','m','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\n",
    "\n",
    "monthLable = ['January', 'February', 'March' ,'April']\n",
    "\n",
    "cm = 1/2.54  # centimeters in inches\n",
    "plt.rcParams['figure.dpi']=600\n",
    "plt.style.use('default')\n",
    "\n",
    "fig = plt.figure(layout=\"constrained\", figsize=(16*cm, 18*cm))\n",
    "plt.subplots_adjust(wspace=0.1, hspace=0,top=0.935)\n",
    "\n",
    "gs = GridSpec(3, 2, figure=fig, height_ratios=[4, 4, 0.5])\n",
    "\n",
    "\n",
    "ax1 = fig.add_subplot(gs[0, 0], projection=cartopy.crs.PlateCarree())\n",
    "ax2 = fig.add_subplot(gs[0, 1], projection=cartopy.crs.PlateCarree())\n",
    "ax3 = fig.add_subplot(gs[1, 0], projection=cartopy.crs.PlateCarree())\n",
    "ax4 = fig.add_subplot(gs[1, 1], projection=cartopy.crs.PlateCarree())\n",
    "\n",
    "axs = [ax1, ax2, ax3, ax4, \n",
    "\n",
    "      ]\n",
    "\n",
    "bx1 = fig.add_subplot(gs[2, 0])\n",
    "bx2 = fig.add_subplot(gs[2, 1])\n",
    "bxs = [bx1, bx2,\n",
    "      ]\n",
    "\n",
    "extent = [90, 110, 10, 30]\n",
    "\n",
    "yr = '2021'\n",
    "gfedHCHO = gfed[gfed['year']==yr]\n",
    "DiurLis = ['Morning', 'Midday', 'Afternoon']\n",
    "\n",
    "def adjustFig(f):\n",
    "    f.set_xlabel('', labelpad = 0.1,color='white')\n",
    "    f.set_ylabel('', labelpad = 0.1,color='white')\n",
    "    f.add_feature(cfeature.COASTLINE, linewidth=1, alpha=1,color='black', zorder=11)    \n",
    "    f.set_extent(extent)\n",
    "    f.set_yticks(np.arange(15,29,5), crs=ccrs.PlateCarree())\n",
    "\n",
    "    f.yaxis.set_major_formatter(lat_formatter)\n",
    "    f.set_xticks(np.arange(95,106,5), crs=ccrs.PlateCarree())\n",
    "    f.xaxis.set_major_formatter(lon_formatter)\n",
    "    for pos in ['right', 'top', 'bottom', 'left']:\n",
    "        f.spines[pos].set_visible(False) \n",
    "\n",
    "for count in range(4):\n",
    "    count2 = count\n",
    "\n",
    "\n",
    "    if (count<3):    \n",
    "\n",
    "        try:\n",
    "            gg = xr.open_dataset(GEMSlisD[count])['HCHO_column']\n",
    "        except:\n",
    "            print(count)\n",
    "        im = gg.plot(ax=axs[count]\n",
    "                                 ,vmin = -10, vmax = 10\n",
    "                                     ,cmap = \"bwr\"\n",
    "            ,levels=bounds\n",
    "                                 ,transform = ccrs.PlateCarree()\n",
    "                                 ,add_colorbar=False\n",
    "                                )\n",
    "        axs[count].set_title('('+alp[count]+') GEMS '+str(int(str(GEMSlisD[count])[-7:-5]) + 8)+':00 HCHO Change',size=11)\n",
    "        axs[count].add_feature(cfeature.OCEAN, zorder=1,color='white')\n",
    "\n",
    "        adjustFig(axs[count])\n",
    "\n",
    "        cbar = fig.colorbar(im, cax=bx1, orientation='horizontal',label='GEMS: 10$^{15}$ molecules cm$^{-2}$')\n",
    "    \n",
    "        \n",
    "    elif (count==3):           \n",
    "\n",
    "            \n",
    "        try:\n",
    "            count2 = count\n",
    "            gfedHCHO = gfed[gfed['month']=='03']\n",
    "            gfedHCHO21 = gfedHCHO[gfedHCHO['year']=='2021'].set_index(['lat','lon']).to_xarray()['HCHO_Daily_KG_KM2']\n",
    "            gfedHCHO22 = gfedHCHO[gfedHCHO['year']=='2022'].set_index(['lat','lon']).to_xarray()['HCHO_Daily_KG_KM2']\n",
    "            gfedHCHOdelta = gfedHCHO22 - gfedHCHO21\n",
    "            im = gfedHCHOdelta.plot(ax=axs[count]\n",
    "                                 ,vmin = -5, vmax = 5\n",
    "                                     ,cmap = \"seismic\"\n",
    "                                 ,transform = ccrs.PlateCarree()\n",
    "                                 ,add_colorbar=False\n",
    "                                )\n",
    "\n",
    "            axs[count].set_title('('+alp[count]+') GFED4s HCHO Change',size=11)\n",
    "\n",
    "\n",
    "            \n",
    "            adjustFig(axs[count])\n",
    "            cbar = fig.colorbar(im, cax=bx2, orientation='horizontal',label='GFED4s: kg km$^{-2}$ day$^{-1}$')\n",
    "\n",
    "        except:\n",
    "            print(months[count]+'?')    \n",
    "    \n",
    "\n",
    "    try:\n",
    "        axs[count].tick_params(axis='both', which='major', labelsize=10, direction = 'in',color='black')\n",
    "        axs[count].bbox_inches=\"tight\"\n",
    "    except:\n",
    "        continue\n",
    "\n",
    "    if (count%2!=0) or count ==12:\n",
    "        axs[count].tick_params(axis='y',labelleft=False) \n",
    "\n",
    "    if (count<2):\n",
    "        axs[count].tick_params(axis='x',label1On=False)\n",
    "        \n",
    "    count = count + 1\n",
    "    \n",
    "    \n",
    "\n",
    "\n",
    "plt.rcParams['figure.constrained_layout.use'] = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a6d4c6c7",
   "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}