{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d9b0d201",
   "metadata": {},
   "source": [
    "# CO<sub>2</sub> Flux\n",
    "\n",
    "Compare monthly climatologies of the CO<sub>2</sub> Flux with observations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e61bcda-4b17-4ff5-88cf-40b690fe623f",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3bc12e7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e103a5fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "\n",
    "from itertools import product\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "import matplotlib.colors as colors\n",
    "import cmocean\n",
    "\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "\n",
    "import xpersist as xp\n",
    "cache_dir = '/glade/p/cgd/oce/projects/cesm2-marbl/xpersist_cache/3d_fields'\n",
    "if (os.path.isdir(cache_dir)):\n",
    "    xp.settings['cache_dir'] = cache_dir\n",
    "os.makedirs(cache_dir, exist_ok=True)\n",
    "\n",
    "import pop_tools\n",
    "\n",
    "\n",
    "import climo_utils as cu\n",
    "import utils\n",
    "import discrete_obs \n",
    "\n",
    "import plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af7cd57b-f12e-4a40-8ed0-fcad8bcc968d",
   "metadata": {},
   "source": [
    "## Spin up a Cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "66f09305",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/u/home/mgrover/miniconda3/envs/cesm2-marbl/lib/python3.7/site-packages/distributed/node.py:164: UserWarning: Port 8787 is already in use.\n",
      "Perhaps you already have a cluster running?\n",
      "Hosting the HTTP server on port 46185 instead\n",
      "  expected, actual\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://10.12.206.51:43632</li>\n",
       "  <li><b>Dashboard: </b><a href='https://jupyterhub.hpc.ucar.edu/stable/user/mgrover/proxy/46185/status' target='_blank'>https://jupyterhub.hpc.ucar.edu/stable/user/mgrover/proxy/46185/status</a></li>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>0</li>\n",
       "  <li><b>Cores: </b>0</li>\n",
       "  <li><b>Memory: </b>0 B</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: 'tcp://10.12.206.51:43632' processes=0 threads=0, memory=0 B>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster, client = utils.get_ClusterClient()\n",
    "cluster.scale(12) #adapt(minimum_jobs=0, maximum_jobs=24)\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29c7a916-3953-43dd-b70a-7910fe1d05ec",
   "metadata": {},
   "source": [
    "## Read in the Grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ea8eb98e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ba40310d250>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_grid = pop_tools.get_grid('POP_gx1v7')\n",
    "masked_area = ds_grid.TAREA.where(ds_grid.REGION_MASK > 0).fillna(0.).expand_dims('region')\n",
    "masked_area.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4d832cc-d051-4fb2-87a4-715a686a4999",
   "metadata": {},
   "source": [
    "## Compute Monthly Climatologies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cdcfe201",
   "metadata": {},
   "outputs": [],
   "source": [
    "def monthly_clim(ds):\n",
    "    vars_time_dep = [v for v in ds.variables if 'time' in ds[v].dims]\n",
    "    vars_other = list(set(ds.variables) - set(vars_time_dep))   \n",
    "    \n",
    "    encoding = {v: ds[v].encoding for v in vars_time_dep}\n",
    "    dso =  ds[vars_time_dep].groupby('time.month').mean('time').rename({'month': 'time'})\n",
    "    for v in vars_time_dep:\n",
    "        dso[v].encoding = encoding[v]\n",
    "    return xr.merge([dso, ds[vars_other]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "32090069",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "assuming cache is correct\n",
      "reading cached file: /glade/p/cgd/oce/projects/cesm2-marbl/xpersist_cache/3d_fields/co2-flux-FG_CO2.nc\n"
     ]
    },
    {
     "data": {
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       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (nlat: 384, nlon: 320, time: 12, z_t: 60)\n",
       "Coordinates:\n",
       "    TLONG        (nlat, nlon) float64 ...\n",
       "    TLAT         (nlat, nlon) float64 ...\n",
       "    ULONG        (nlat, nlon) float64 ...\n",
       "    ULAT         (nlat, nlon) float64 ...\n",
       "  * time         (time) int32 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "  * z_t          (z_t) float32 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n",
       "Dimensions without coordinates: nlat, nlon\n",
       "Data variables:\n",
       "    FG_CO2       (time, nlat, nlon) float32 nan nan nan nan ... nan nan nan nan\n",
       "    TAREA        (nlat, nlon) float64 ...\n",
       "    dz           (z_t) float32 1e+03 1e+03 1e+03 ... 2.499e+04 2.5e+04 2.5e+04\n",
       "    KMT          (nlat, nlon) float64 ...\n",
       "    REGION_MASK  (nlat, nlon) float64 ...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-89c4f203-e938-409a-81d1-883ea2e1b376' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-89c4f203-e938-409a-81d1-883ea2e1b376' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nlat</span>: 384</li><li><span>nlon</span>: 320</li><li><span class='xr-has-index'>time</span>: 12</li><li><span class='xr-has-index'>z_t</span>: 60</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3cefd0ce-ee04-40d0-a8a6-ede39174fe2d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3cefd0ce-ee04-40d0-a8a6-ede39174fe2d' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9f993690-39a6-4a45-b444-83dc6c8042f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f993690-39a6-4a45-b444-83dc6c8042f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34c5a47d-9da9-420f-8b0b-6caa0f83547b' class='xr-var-data-in' type='checkbox'><label for='data-34c5a47d-9da9-420f-8b0b-6caa0f83547b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a7e26477-cca1-40b6-8812-7fddb254546f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7e26477-cca1-40b6-8812-7fddb254546f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65080d7e-4ab6-4cbc-9126-9df13fec0bbe' class='xr-var-data-in' type='checkbox'><label for='data-65080d7e-4ab6-4cbc-9126-9df13fec0bbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-afc91130-21dc-468b-a8ef-03db5332ba03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afc91130-21dc-468b-a8ef-03db5332ba03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cc56218-b1e1-4f98-bc7e-ff650758380a' class='xr-var-data-in' type='checkbox'><label for='data-5cc56218-b1e1-4f98-bc7e-ff650758380a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4639700e-76a1-4135-8c7b-15112a857aa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4639700e-76a1-4135-8c7b-15112a857aa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43d84cc1-b271-4cdf-8252-ad04ceea9a2a' class='xr-var-data-in' type='checkbox'><label for='data-43d84cc1-b271-4cdf-8252-ad04ceea9a2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-4a365ff4-fe9f-42bd-9efa-a0494f270e5b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a365ff4-fe9f-42bd-9efa-a0494f270e5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6e271c8-3fcc-4760-8b8c-f0ac3c68625b' class='xr-var-data-in' type='checkbox'><label for='data-a6e271c8-3fcc-4760-8b8c-f0ac3c68625b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_t</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.375e+05</div><input id='attrs-44f19fc8-7577-4ca6-9af6-cd7e577406a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44f19fc8-7577-4ca6-9af6-cd7e577406a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d7965ae-40d6-4a49-92bb-9c4a6da6aaa5' class='xr-var-data-in' type='checkbox'><label for='data-2d7965ae-40d6-4a49-92bb-9c4a6da6aaa5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>depth from surface to midpoint of layer</dd><dt><span>units :</span></dt><dd>centimeters</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>500.0</dd><dt><span>valid_max :</span></dt><dd>537500.0</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
       "       5.500000e+03, 6.500000e+03, 7.500000e+03, 8.500000e+03, 9.500000e+03,\n",
       "       1.050000e+04, 1.150000e+04, 1.250000e+04, 1.350000e+04, 1.450000e+04,\n",
       "       1.550000e+04, 1.650984e+04, 1.754790e+04, 1.862913e+04, 1.976603e+04,\n",
       "       2.097114e+04, 2.225783e+04, 2.364088e+04, 2.513702e+04, 2.676542e+04,\n",
       "       2.854837e+04, 3.051192e+04, 3.268680e+04, 3.510935e+04, 3.782276e+04,\n",
       "       4.087846e+04, 4.433777e+04, 4.827367e+04, 5.277280e+04, 5.793729e+04,\n",
       "       6.388626e+04, 7.075633e+04, 7.870025e+04, 8.788252e+04, 9.847059e+04,\n",
       "       1.106204e+05, 1.244567e+05, 1.400497e+05, 1.573946e+05, 1.764003e+05,\n",
       "       1.968944e+05, 2.186457e+05, 2.413972e+05, 2.649001e+05, 2.889385e+05,\n",
       "       3.133405e+05, 3.379793e+05, 3.627670e+05, 3.876452e+05, 4.125768e+05,\n",
       "       4.375392e+05, 4.625190e+05, 4.875083e+05, 5.125028e+05, 5.375000e+05],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a40cc59e-f6c2-4c8e-9684-472f112c9cc4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a40cc59e-f6c2-4c8e-9684-472f112c9cc4' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>FG_CO2</span></div><div class='xr-var-dims'>(time, nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5190e063-f4be-4165-8274-16568e2cf1b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5190e063-f4be-4165-8274-16568e2cf1b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dedc91a2-94ba-47fb-839e-439bf1fddcaf' class='xr-var-data-in' type='checkbox'><label for='data-dedc91a2-94ba-47fb-839e-439bf1fddcaf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mol m$^{-2}$ yr$^{-1}$</dd></dl></div><div class='xr-var-data'><pre>array([[[           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-4.8583554e-04, -5.7094818e-04, -4.7134905e-04, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-3.4481292e-03, -4.1879923e-03, -3.5189423e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "...\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-6.2478946e-05, -7.6542361e-05, -6.9390946e-05, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAREA</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9e02763a-6501-4385-b9d2-e3499f3c9dc9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e02763a-6501-4385-b9d2-e3499f3c9dc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd7fd213-5111-4c82-9925-3a1f341e144f' class='xr-var-data-in' type='checkbox'><label for='data-dd7fd213-5111-4c82-9925-3a1f341e144f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of T cells</dd><dt><span>units :</span></dt><dd>centimeter^2</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dz</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-81eb2f1a-d4e8-4052-80fb-2f0f520aa5a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81eb2f1a-d4e8-4052-80fb-2f0f520aa5a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5daa1659-6871-4ebc-8ab5-d8e8a064e189' class='xr-var-data-in' type='checkbox'><label for='data-5daa1659-6871-4ebc-8ab5-d8e8a064e189' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>thickness of layer k</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>array([ 1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,\n",
       "        1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,\n",
       "        1000.    ,  1000.    ,  1000.    ,  1000.    ,  1019.6808,  1056.4484,\n",
       "        1105.9951,  1167.807 ,  1242.4133,  1330.9678,  1435.141 ,  1557.1259,\n",
       "        1699.6796,  1866.2124,  2060.9023,  2288.852 ,  2556.247 ,  2870.575 ,\n",
       "        3240.8372,  3677.7725,  4194.031 ,  4804.2236,  5524.7544,  6373.192 ,\n",
       "        7366.945 ,  8520.893 ,  9843.658 , 11332.466 , 12967.199 , 14705.344 ,\n",
       "       16480.709 , 18209.135 , 19802.234 , 21185.957 , 22316.51  , 23186.494 ,\n",
       "       23819.45  , 24257.217 , 24546.78  , 24731.014 , 24844.328 , 24911.975 ,\n",
       "       24951.291 , 24973.594 , 24985.96  , 24992.674 , 24996.244 , 24998.11  ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KMT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5985901f-73b7-4828-a70e-cdb122e8b413' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5985901f-73b7-4828-a70e-cdb122e8b413' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67b8909e-3989-4fd9-b792-bd40a6b9ebfd' class='xr-var-data-in' type='checkbox'><label for='data-67b8909e-3989-4fd9-b792-bd40a6b9ebfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>k Index of Deepest Grid Cell on T Grid</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>REGION_MASK</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-35a6038a-b082-4026-96ed-e7bc3d00a1fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35a6038a-b082-4026-96ed-e7bc3d00a1fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10dba774-31e6-44a8-bce2-be406a788294' class='xr-var-data-in' type='checkbox'><label for='data-10dba774-31e6-44a8-bce2-be406a788294' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>basin index number (signed integers)</dd></dl></div><div class='xr-var-data'><pre>[122880 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5972b2d9-e778-40be-b56b-86112cb02f9d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5972b2d9-e778-40be-b56b-86112cb02f9d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (nlat: 384, nlon: 320, time: 12, z_t: 60)\n",
       "Coordinates:\n",
       "    TLONG        (nlat, nlon) float64 ...\n",
       "    TLAT         (nlat, nlon) float64 ...\n",
       "    ULONG        (nlat, nlon) float64 ...\n",
       "    ULAT         (nlat, nlon) float64 ...\n",
       "  * time         (time) int32 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "  * z_t          (z_t) float32 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n",
       "Dimensions without coordinates: nlat, nlon\n",
       "Data variables:\n",
       "    FG_CO2       (time, nlat, nlon) float32 nan nan nan nan ... nan nan nan nan\n",
       "    TAREA        (nlat, nlon) float64 ...\n",
       "    dz           (z_t) float32 ...\n",
       "    KMT          (nlat, nlon) float64 ...\n",
       "    REGION_MASK  (nlat, nlon) float64 ..."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nmolcm2s_to_molm2yr = 1e-9 * 1e4 * 86400. * 365.\n",
    "\n",
    "time_slice = slice(\"1990-01-15\", \"2015-01-15\")\n",
    "varlist = [\n",
    "    'FG_CO2',\n",
    "]\n",
    "ds_list = []\n",
    "for variable in varlist:\n",
    "    xp_func = xp.persist_ds(cu.read_CESM_var, name=f'co2-flux-{variable}', trust_cache=True,)\n",
    "    ds_list.append(xp_func(\n",
    "        time_slice, \n",
    "        variable, \n",
    "        postprocess=monthly_clim,\n",
    "        mean_dims=['member_id'],\n",
    "    ))\n",
    "    \n",
    "ds = xr.merge(ds_list)\n",
    "\n",
    "#ds['TAREA'] = grid.TAREA\n",
    "\n",
    "convert_glb = dict(\n",
    "    FG_CO2=(-1.0) * 1e-9 * 86400. * 365. * 12e-15,\n",
    ")\n",
    "\n",
    "ds_glb = xr.Dataset()\n",
    "for v in convert_glb.keys():\n",
    "    ds_glb[v] = (masked_area * ds[v].mean('time')).sum(['nlat', 'nlon']) * convert_glb[v]\n",
    "    ds_glb[v].attrs['units'] = 'Pg C yr$^{-1}$'\n",
    "    \n",
    "    \n",
    "from netCDF4 import default_fillvals    \n",
    "ds.FG_CO2.data = ds.FG_CO2 * nmolcm2s_to_molm2yr * (-1.0) # reverse sign\n",
    "ds.FG_CO2.attrs['units'] = 'mol m$^{-2}$ yr$^{-1}$'\n",
    "ds.FG_CO2.encoding['coordinates'] = 'TLONG TLAT time'\n",
    "ds.FG_CO2.encoding['_FillValue'] = default_fillvals['f4']\n",
    "ds['time'] = ds.time.astype(np.int32)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a522c67d",
   "metadata": {},
   "outputs": [
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       ".xr-attrs dd {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (region: 1)\n",
       "Dimensions without coordinates: region\n",
       "Data variables:\n",
       "    FG_CO2   (region) float64 -2.039</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-28fd5026-15be-495e-a548-24a6cd816276' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-28fd5026-15be-495e-a548-24a6cd816276' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>region</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b37cb4b7-22cd-4c83-ae37-658f023f5eb0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b37cb4b7-22cd-4c83-ae37-658f023f5eb0' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-5cafbb15-714b-43ae-b591-c75790b22db2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5cafbb15-714b-43ae-b591-c75790b22db2' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>FG_CO2</span></div><div class='xr-var-dims'>(region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.039</div><input id='attrs-045ff8e0-eb33-4f00-ae0b-848faf4dfa34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-045ff8e0-eb33-4f00-ae0b-848faf4dfa34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99d14ab3-581b-4ce2-b595-205945cbf7d5' class='xr-var-data-in' type='checkbox'><label for='data-99d14ab3-581b-4ce2-b595-205945cbf7d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pg C yr$^{-1}$</dd></dl></div><div class='xr-var-data'><pre>array([-2.03923908])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd8ae321-4af8-4aef-a526-e80e4d4ac44a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dd8ae321-4af8-4aef-a526-e80e4d4ac44a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (region: 1)\n",
       "Dimensions without coordinates: region\n",
       "Data variables:\n",
       "    FG_CO2   (region) float64 -2.039"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_glb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d383358-09d3-49c2-86df-881fd6d10023",
   "metadata": {},
   "source": [
    "### After the computation is done, spin down the cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e3cfccdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "del client\n",
    "del cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9bcc74f-a304-4474-9b3a-1eddbc7c13cf",
   "metadata": {},
   "source": [
    "## Open the Gridded Observational Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1e50c721",
   "metadata": {},
   "outputs": [],
   "source": [
    "with xr.open_dataset('/glade/p/cgd/oce/projects/cesm2-marbl/fgco2-MPI-SOM-FFN_POP_gx1v7.nc') as ds_obs:\n",
    "    with xr.set_options(keep_attrs=True):\n",
    "        ds_obs = monthly_clim(ds_obs.sel(time=slice('1990', '2014'))).load()\n",
    "\n",
    "ds_obs_glb = (masked_area * ds_obs['fgco2_smoothed'].mean('time')).sum(['nlat', 'nlon']) * 12e-15 * 1e-4\n",
    "\n",
    "import intake\n",
    "cat = intake.open_catalog('catalogs/fgco2_MPI-SOM-FFN.yml')\n",
    "with xr.set_options(keep_attrs=True):\n",
    "    ds_tmp = monthly_clim(cat.fgco2_MPI_SOM_FFN().to_dask()[['fgco2_smoothed']].sel(time=slice('1990', '2014'))).compute()\n",
    "    ds_obs_za = ds_tmp.mean('lon')\n",
    "\n",
    "#for v in ['fgco2_smoothed', 'fgco2_raw']:\n",
    "#     ds_obs[v].encoding['_FillValue'] = -1e36\n",
    "         \n",
    "#ds_obs['time'] = ds_obs.time.astype(np.int32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "75d15341",
   "metadata": {},
   "outputs": [
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       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (region: 1)&gt;\n",
       "array([-1.4174079])\n",
       "Dimensions without coordinates: region</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>region</span>: 1</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f831677e-a4f4-4787-b9c9-dfe4b50e2d55' class='xr-array-in' type='checkbox' checked><label for='section-f831677e-a4f4-4787-b9c9-dfe4b50e2d55' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-1.417</span></div><div class='xr-array-data'><pre>array([-1.4174079])</pre></div></div></li><li class='xr-section-item'><input id='section-1ccbf094-6582-4894-ac66-66f3e31d6495' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1ccbf094-6582-4894-ac66-66f3e31d6495' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b5c8be4c-8ea4-4b39-a293-625d171b594f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b5c8be4c-8ea4-4b39-a293-625d171b594f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (region: 1)>\n",
       "array([-1.4174079])\n",
       "Dimensions without coordinates: region"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_obs_glb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4223b159",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ba403c909d0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_obs.fgco2_raw.isel(time=-1).plot() #('time').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0e7dabcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ba52a1c15d0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.FG_CO2.mean('time').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ecabe34e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ba52a2d5a90>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask2d = utils.get_pop_region_mask_za(mask_type='2D')\n",
    "mask2d.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "801a1285-8e9e-43cc-9cee-421319ed2a2f",
   "metadata": {},
   "source": [
    "## Compute the Zonal Mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5d7f2f01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "za ran successfully, writing netcdf output\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (basins: 4, lat_t: 394, lat_t_edges: 395, time: 12)\n",
       "Coordinates:\n",
       "  * lat_t        (lat_t) float32 -79.22 -78.69 -78.15 ... 88.84 89.37 89.9\n",
       "  * lat_t_edges  (lat_t_edges) float32 -79.49 -78.95 -78.42 ... 89.1 89.64 90.0\n",
       "  * time         (time) int32 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Dimensions without coordinates: basins\n",
       "Data variables:\n",
       "    FG_CO2       (basins, time, lat_t) float32 nan nan -1.236 ... nan nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e3db87eb-3d59-4eea-b52c-adc5146effa7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e3db87eb-3d59-4eea-b52c-adc5146effa7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>basins</span>: 4</li><li><span class='xr-has-index'>lat_t</span>: 394</li><li><span class='xr-has-index'>lat_t_edges</span>: 395</li><li><span class='xr-has-index'>time</span>: 12</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-dcbcf909-81a6-4ca0-9491-eebebd4cd507' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dcbcf909-81a6-4ca0-9491-eebebd4cd507' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat_t</span></div><div class='xr-var-dims'>(lat_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-79.22 -78.69 -78.15 ... 89.37 89.9</div><input id='attrs-7941f61f-dbb7-4155-88ca-7e2481ca80f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7941f61f-dbb7-4155-88ca-7e2481ca80f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-017af5a7-b7c0-4618-836a-5b5bf5006477' class='xr-var-data-in' type='checkbox'><label for='data-017af5a7-b7c0-4618-836a-5b5bf5006477' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude Cell Centers</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>edges :</span></dt><dd>lat_t_edges</dd></dl></div><div class='xr-var-data'><pre>array([-79.22052 , -78.68631 , -78.15209 , ...,  88.836334,  89.370575,\n",
       "        89.904816], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat_t_edges</span></div><div class='xr-var-dims'>(lat_t_edges)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-79.49 -78.95 -78.42 ... 89.64 90.0</div><input id='attrs-45edfa6f-9def-4350-9055-1a71b9719cc6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45edfa6f-9def-4350-9055-1a71b9719cc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecd849f2-7cbb-47fc-afda-3f9d6fc10399' class='xr-var-data-in' type='checkbox'><label for='data-ecd849f2-7cbb-47fc-afda-3f9d6fc10399' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-79.48714 , -78.952896, -78.418655, ...,  89.103455,  89.637695,\n",
       "        90.      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-b0bc63ee-6a71-4447-a7b3-65d86dba5c61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b0bc63ee-6a71-4447-a7b3-65d86dba5c61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08fe63ea-4134-4858-8819-e364829a9fae' class='xr-var-data-in' type='checkbox'><label for='data-08fe63ea-4134-4858-8819-e364829a9fae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c31d496e-9a82-484b-b2f6-596dc11ae9b5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c31d496e-9a82-484b-b2f6-596dc11ae9b5' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>FG_CO2</span></div><div class='xr-var-dims'>(basins, time, lat_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cfe5b2c1-86e2-41ec-a1a6-406311b47550' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfe5b2c1-86e2-41ec-a1a6-406311b47550' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2468a59e-6057-415a-9847-186332485190' class='xr-var-data-in' type='checkbox'><label for='data-2468a59e-6057-415a-9847-186332485190' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mol m$^{-2}$ yr$^{-1}$</dd></dl></div><div class='xr-var-data'><pre>array([[[      nan,       nan, ..., -0.00894 , -0.008547],\n",
       "        [      nan,       nan, ..., -0.014722, -0.01433 ],\n",
       "        ...,\n",
       "        [      nan,       nan, ..., -0.067452, -0.064322],\n",
       "        [      nan,       nan, ..., -0.006892, -0.006435]],\n",
       "\n",
       "       [[      nan,       nan, ..., -0.00894 , -0.008547],\n",
       "        [      nan,       nan, ..., -0.014722, -0.01433 ],\n",
       "        ...,\n",
       "        [      nan,       nan, ..., -0.067452, -0.064322],\n",
       "        [      nan,       nan, ..., -0.006892, -0.006435]],\n",
       "\n",
       "       [[      nan,       nan, ...,       nan,       nan],\n",
       "        [      nan,       nan, ...,       nan,       nan],\n",
       "        ...,\n",
       "        [      nan,       nan, ...,       nan,       nan],\n",
       "        [      nan,       nan, ...,       nan,       nan]],\n",
       "\n",
       "       [[      nan,       nan, ...,       nan,       nan],\n",
       "        [      nan,       nan, ...,       nan,       nan],\n",
       "        ...,\n",
       "        [      nan,       nan, ...,       nan,       nan],\n",
       "        [      nan,       nan, ...,       nan,       nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b31ae0e7-fe94-4b84-8db1-509444e01c24' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b31ae0e7-fe94-4b84-8db1-509444e01c24' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (basins: 4, lat_t: 394, lat_t_edges: 395, time: 12)\n",
       "Coordinates:\n",
       "  * lat_t        (lat_t) float32 -79.22 -78.69 -78.15 ... 88.84 89.37 89.9\n",
       "  * lat_t_edges  (lat_t_edges) float32 -79.49 -78.95 -78.42 ... 89.1 89.64 90.0\n",
       "  * time         (time) int32 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Dimensions without coordinates: basins\n",
       "Data variables:\n",
       "    FG_CO2       (basins, time, lat_t) float32 ..."
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#\n",
    "ds_za = utils.zonal_mean_via_fortran(ds, grid='POP_gx1v7', region_mask=mask2d,)\n",
    "ds_za"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7281ee1-e5c6-40d0-bd91-33058eb7fca9",
   "metadata": {},
   "source": [
    "## Plot the Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "090d2aea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ba52a44f5d0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_za.FG_CO2.isel(basins=0).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ff9693c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ba52a5eae90>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_obs_za.fgco2_smoothed.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e553981e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
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       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (nlat: 384, nlon: 321, z_t: 60)\n",
       "Coordinates:\n",
       "  * z_t          (z_t) float32 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n",
       "Dimensions without coordinates: nlat, nlon\n",
       "Data variables:\n",
       "    TLAT         (nlat, nlon) float64 -79.22 -79.22 -79.22 ... 80.31 80.31 80.31\n",
       "    TLONG        (nlat, nlon) float64 -220.6 -219.4 -218.3 ... -39.57 -39.86\n",
       "    fgco2        (nlat, nlon) float32 nan nan nan nan nan ... nan nan nan nan\n",
       "    TAREA        (nlat, nlon) float64 8.592e+12 8.592e+12 ... 3.341e+12\n",
       "    dz           (z_t) float32 1e+03 1e+03 1e+03 ... 2.499e+04 2.5e+04 2.5e+04\n",
       "    KMT          (nlat, nlon) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    REGION_MASK  (nlat, nlon) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    fgco2_obs    (nlat, nlon) float64 nan nan nan nan nan ... nan nan nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-08958da3-6150-45d8-9176-323f76f808b2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-08958da3-6150-45d8-9176-323f76f808b2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nlat</span>: 384</li><li><span>nlon</span>: 321</li><li><span class='xr-has-index'>z_t</span>: 60</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-183c006c-cea4-48aa-a16d-9775f2b385c3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-183c006c-cea4-48aa-a16d-9775f2b385c3' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_t</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.375e+05</div><input id='attrs-336fbed4-fb56-447f-b017-fcd9171e6b6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-336fbed4-fb56-447f-b017-fcd9171e6b6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2ac9acd-db99-4a62-9e9a-6155dc50a719' class='xr-var-data-in' type='checkbox'><label for='data-f2ac9acd-db99-4a62-9e9a-6155dc50a719' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>depth from surface to midpoint of layer</dd><dt><span>units :</span></dt><dd>centimeters</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>500.0</dd><dt><span>valid_max :</span></dt><dd>537500.0</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
       "       5.500000e+03, 6.500000e+03, 7.500000e+03, 8.500000e+03, 9.500000e+03,\n",
       "       1.050000e+04, 1.150000e+04, 1.250000e+04, 1.350000e+04, 1.450000e+04,\n",
       "       1.550000e+04, 1.650984e+04, 1.754790e+04, 1.862913e+04, 1.976603e+04,\n",
       "       2.097114e+04, 2.225783e+04, 2.364088e+04, 2.513702e+04, 2.676542e+04,\n",
       "       2.854837e+04, 3.051192e+04, 3.268680e+04, 3.510935e+04, 3.782276e+04,\n",
       "       4.087846e+04, 4.433777e+04, 4.827367e+04, 5.277280e+04, 5.793729e+04,\n",
       "       6.388626e+04, 7.075633e+04, 7.870025e+04, 8.788252e+04, 9.847059e+04,\n",
       "       1.106204e+05, 1.244567e+05, 1.400497e+05, 1.573946e+05, 1.764003e+05,\n",
       "       1.968944e+05, 2.186457e+05, 2.413972e+05, 2.649001e+05, 2.889385e+05,\n",
       "       3.133405e+05, 3.379793e+05, 3.627670e+05, 3.876452e+05, 4.125768e+05,\n",
       "       4.375392e+05, 4.625190e+05, 4.875083e+05, 5.125028e+05, 5.375000e+05],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2cee497-0769-4403-8b1c-c57a369bec64' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f2cee497-0769-4403-8b1c-c57a369bec64' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-79.22 -79.22 ... 80.31 80.31</div><input id='attrs-78d29a2c-3019-4d4e-b3cc-868d77fba014' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78d29a2c-3019-4d4e-b3cc-868d77fba014' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-743e3419-e076-48c7-9e00-502cd63f1684' class='xr-var-data-in' type='checkbox'><label for='data-743e3419-e076-48c7-9e00-502cd63f1684' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-79.22052261, -79.22052261, -79.22052261, ..., -79.22052261,\n",
       "        -79.22052261, -79.22052261],\n",
       "       [-78.68630626, -78.68630626, -78.68630626, ..., -78.68630626,\n",
       "        -78.68630626, -78.68630626],\n",
       "       [-78.15208992, -78.15208992, -78.15208992, ..., -78.15208992,\n",
       "        -78.15208992, -78.15208992],\n",
       "       ...,\n",
       "       [ 81.44584238,  81.44584238,  81.44466079, ...,  81.44229771,\n",
       "         81.44466079,  81.44584238],\n",
       "       [ 80.87803543,  80.87803543,  80.87705778, ...,  80.87510244,\n",
       "         80.87705778,  80.87803543],\n",
       "       [ 80.31321311,  80.31321311,  80.31241206, ...,  80.31080987,\n",
       "         80.31241206,  80.31321311]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-220.6 -219.4 ... -39.57 -39.86</div><input id='attrs-2a73f464-48ac-43f5-88ac-c90a120fbee3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a73f464-48ac-43f5-88ac-c90a120fbee3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5ba595a-3023-4765-b822-61c5737b2c37' class='xr-var-data-in' type='checkbox'><label for='data-f5ba595a-3023-4765-b822-61c5737b2c37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-220.56249613, -219.43749609, -218.31249606, ...,  137.18750382,\n",
       "         138.31250385,  139.43750388],\n",
       "       [-220.56249613, -219.43749609, -218.31249606, ...,  137.18750382,\n",
       "         138.31250385,  139.43750388],\n",
       "       [-220.56249613, -219.43749609, -218.31249606, ...,  137.18750382,\n",
       "         138.31250385,  139.43750388],\n",
       "       ...,\n",
       "       [ -39.7932723 ,  -40.20670806,  -40.62006565, ...,  -38.96679888,\n",
       "         -39.37991654,  -39.79327229],\n",
       "       [ -39.82753619,  -40.17244447,  -40.51730173, ...,  -39.13798089,\n",
       "         -39.48268046,  -39.82753618],\n",
       "       [ -39.85740526,  -40.14257567,  -40.42771349, ...,  -39.28723255,\n",
       "         -39.5722687 ,  -39.85740525]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fgco2</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-106c900d-457c-4662-aee0-34552b1c07fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-106c900d-457c-4662-aee0-34552b1c07fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6550b79d-b506-4050-84ac-316882ce126f' class='xr-var-data-in' type='checkbox'><label for='data-6550b79d-b506-4050-84ac-316882ce126f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAREA</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.592e+12 8.592e+12 ... 3.341e+12</div><input id='attrs-e70be3ca-f8d3-4ba2-a0da-5cb727c5d572' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e70be3ca-f8d3-4ba2-a0da-5cb727c5d572' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0179d19-9822-4957-802c-a936fde10873' class='xr-var-data-in' type='checkbox'><label for='data-e0179d19-9822-4957-802c-a936fde10873' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[8.59217065e+12, 8.59217065e+12, 8.59235345e+12, ...,\n",
       "        8.59271911e+12, 8.59235345e+12, 8.59217065e+12],\n",
       "       [1.45745047e+13, 1.45745047e+13, 1.45745047e+13, ...,\n",
       "        1.45745047e+13, 1.45745047e+13, 1.45745047e+13],\n",
       "       [1.52530781e+13, 1.52530781e+13, 1.52530781e+13, ...,\n",
       "        1.52530781e+13, 1.52530781e+13, 1.52530781e+13],\n",
       "       ...,\n",
       "       [4.32754786e+12, 4.32754786e+12, 4.32799292e+12, ...,\n",
       "        4.32888316e+12, 4.32799292e+12, 4.32754786e+12],\n",
       "       [3.82798578e+12, 3.82798578e+12, 3.82839189e+12, ...,\n",
       "        3.82920421e+12, 3.82839189e+12, 3.82798578e+12],\n",
       "       [3.34119240e+12, 3.34119240e+12, 3.34155788e+12, ...,\n",
       "        3.34228893e+12, 3.34155788e+12, 3.34119240e+12]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dz</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1e+03 1e+03 ... 2.5e+04 2.5e+04</div><input id='attrs-d6e103b0-1dcc-4a43-bd5c-6d59e26d6e85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6e103b0-1dcc-4a43-bd5c-6d59e26d6e85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3998f7e8-95bd-4f18-b33d-ab83a7676a44' class='xr-var-data-in' type='checkbox'><label for='data-3998f7e8-95bd-4f18-b33d-ab83a7676a44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,\n",
       "        1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,\n",
       "        1000.    ,  1000.    ,  1000.    ,  1000.    ,  1000.    ,\n",
       "        1000.    ,  1019.6808,  1056.4484,  1105.9951,  1167.807 ,\n",
       "        1242.4133,  1330.9678,  1435.141 ,  1557.1259,  1699.6796,\n",
       "        1866.2124,  2060.9023,  2288.852 ,  2556.247 ,  2870.575 ,\n",
       "        3240.8372,  3677.7725,  4194.031 ,  4804.2236,  5524.7544,\n",
       "        6373.192 ,  7366.945 ,  8520.893 ,  9843.658 , 11332.466 ,\n",
       "       12967.199 , 14705.344 , 16480.709 , 18209.135 , 19802.234 ,\n",
       "       21185.957 , 22316.51  , 23186.494 , 23819.45  , 24257.217 ,\n",
       "       24546.78  , 24731.014 , 24844.328 , 24911.975 , 24951.291 ,\n",
       "       24973.594 , 24985.96  , 24992.674 , 24996.244 , 24998.11  ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KMT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-7db29596-8b3b-4305-9f8e-5a4958116a6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7db29596-8b3b-4305-9f8e-5a4958116a6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4095fd88-2eee-43a9-9fd0-004c0a431ad5' class='xr-var-data-in' type='checkbox'><label for='data-4095fd88-2eee-43a9-9fd0-004c0a431ad5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>REGION_MASK</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3e949ef9-1ab3-4874-8aa9-170be7f82bfc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e949ef9-1ab3-4874-8aa9-170be7f82bfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09c1405d-d817-4b71-a9c8-28027c806dae' class='xr-var-data-in' type='checkbox'><label for='data-09c1405d-d817-4b71-a9c8-28027c806dae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fgco2_obs</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-57ceceac-1036-4048-b013-495f833030ac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57ceceac-1036-4048-b013-495f833030ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-432b9c9f-adec-46fd-b0bc-7008383e6e14' class='xr-var-data-in' type='checkbox'><label for='data-432b9c9f-adec-46fd-b0bc-7008383e6e14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93e405ab-e910-40c5-b356-71ddc043ea69' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-93e405ab-e910-40c5-b356-71ddc043ea69' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (nlat: 384, nlon: 321, z_t: 60)\n",
       "Coordinates:\n",
       "  * z_t          (z_t) float32 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n",
       "Dimensions without coordinates: nlat, nlon\n",
       "Data variables:\n",
       "    TLAT         (nlat, nlon) float64 -79.22 -79.22 -79.22 ... 80.31 80.31 80.31\n",
       "    TLONG        (nlat, nlon) float64 -220.6 -219.4 -218.3 ... -39.57 -39.86\n",
       "    fgco2        (nlat, nlon) float32 nan nan nan nan nan ... nan nan nan nan\n",
       "    TAREA        (nlat, nlon) float64 8.592e+12 8.592e+12 ... 3.341e+12\n",
       "    dz           (z_t) float32 1e+03 1e+03 1e+03 ... 2.499e+04 2.5e+04 2.5e+04\n",
       "    KMT          (nlat, nlon) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    REGION_MASK  (nlat, nlon) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    fgco2_obs    (nlat, nlon) float64 nan nan nan nan nan ... nan nan nan nan"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dsa = ds.mean('time').rename({'FG_CO2': 'fgco2'})\n",
    "dsa['fgco2_obs'] = ds_obs.fgco2_smoothed.mean('time')\n",
    "dsa = utils.pop_add_cyclic(dsa)\n",
    "dsa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ddcfd8a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/u/home/mgrover/miniconda3/envs/cesm2-marbl/lib/python3.7/site-packages/ipykernel_launcher.py:66: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 6))\n",
    "prj = ccrs.Robinson(central_longitude=305.0)\n",
    "\n",
    "gs = gridspec.GridSpec(\n",
    "    nrows=2, ncols=6, \n",
    "    width_ratios=(1, 0.01, 0.3, 0.3, 0.25, 0.02),\n",
    "    wspace=0.1, \n",
    "    hspace=0.15,\n",
    ")\n",
    "\n",
    "axs = np.empty((2, 6)).astype(object)\n",
    "\n",
    "axs_map = [\n",
    "    plt.subplot(gs[0, 0], projection=prj),\n",
    "    plt.subplot(gs[1, 0], projection=prj),\n",
    "]\n",
    "cax = plt.subplot(gs[:, -1])\n",
    "\n",
    "axs_za = [\n",
    "    plt.subplot(gs[:, 2]),\n",
    "    plt.subplot(gs[:, 3]),\n",
    "]\n",
    "\n",
    "ax_za_mean = plt.subplot(gs[:, 4])\n",
    "\n",
    "cmap = cmocean.cm.balance\n",
    "\n",
    "levels = np.arange(-3.6, 3.8, 0.2)\n",
    "\n",
    "for field, ax in zip(['fgco2', 'fgco2_obs'], axs_map):\n",
    "       \n",
    "    cf = ax.contourf(\n",
    "        dsa.TLONG, dsa.TLAT, dsa[field],\n",
    "        levels=levels,\n",
    "        extend='both',\n",
    "        cmap=cmap, \n",
    "        norm=colors.BoundaryNorm(levels, ncolors=cmap.N),\n",
    "        transform=ccrs.PlateCarree(),\n",
    "    )\n",
    "    \n",
    "    land = ax.add_feature(\n",
    "        cartopy.feature.NaturalEarthFeature(\n",
    "            'physical','land','110m',\n",
    "            edgecolor='face',\n",
    "            facecolor='gray'\n",
    "        )\n",
    "    )      \n",
    "    \n",
    "    \n",
    "axs_map[0].set_title(f'CESM: {ds_glb.FG_CO2.values[0]:0.2f} Pg C yr$^{{-1}}$')\n",
    "axs_map[1].set_title(f'SOM-FFN: {ds_obs_glb.values[0]:0.2f} Pg C yr$^{{-1}}$')\n",
    "\n",
    "axs_za[0].pcolormesh(\n",
    "    np.arange(0, 13, 1), \n",
    "    ds_za.lat_t_edges, \n",
    "    ds_za.FG_CO2.isel(basins=0).T, \n",
    "    cmap=cmap, \n",
    "    norm=colors.BoundaryNorm(levels, ncolors=cmap.N),\n",
    ")\n",
    "\n",
    "axs_za[1].pcolormesh(\n",
    "    np.arange(0, 13, 1), \n",
    "    ds_obs_za.lat,\n",
    "    ds_obs_za.fgco2_smoothed.T,\n",
    "    cmap=cmap, \n",
    "    norm=colors.BoundaryNorm(levels, ncolors=cmap.N),\n",
    ")\n",
    "\n",
    "ax_za_mean.plot(ds_za.FG_CO2.isel(basins=0).mean('time'), ds_za.lat_t, '-', color='tab:blue', label='CESM2')\n",
    "ax_za_mean.plot(ds_obs_za.fgco2_smoothed.mean('time'), ds_obs_za.lat, '-', color='tab:red', label='SOM-FFN')\n",
    "\n",
    "monlabs = np.array([\"J\", \"F\", \"M\", \"A\", \"M\", \"J\", \"J\", \"A\", \"S\", \"O\", \"N\", \"D\"])\n",
    "\n",
    "for ax in axs_za:\n",
    "    ax.set_ylim([-80, 90.])\n",
    "    ax.set_yticks(np.arange(-75, 90, 15))\n",
    "    ax.set_xticks(np.arange(0, 13))\n",
    "    ax.set_xticklabels([f'   {m}' for m in monlabs]+['']);\n",
    "axs_za[0].set_ylabel('Latitude [°N]')\n",
    "axs_za[1].set_yticklabels([])\n",
    "\n",
    "axs_za[0].set_title('CESM')\n",
    "axs_za[1].set_title('SOM-FFN')\n",
    "\n",
    "ax_za_mean.set_ylim([-80, 90.])\n",
    "ax_za_mean.set_yticks(np.arange(-75, 90, 15))\n",
    "ax_za_mean.set_yticklabels([])\n",
    "ax_za_mean.set_xticks(np.arange(-2.5, 1.5, 0.5))\n",
    "ax_za_mean.set_xticklabels(['', '-2', '', -1, '', '0', '', '1'])\n",
    "ax_za_mean.axvline(0., linewidth=0.5, color='k',)\n",
    "ax_za_mean.set_xlabel('mol m$^{-2}$ yr$^{-1}$')\n",
    "\n",
    "ax_za_mean.legend(loc=(0.03, 0.45), frameon=False, handlelength=1.0, fontsize=8, handletextpad=0.5)\n",
    "\n",
    "utils.label_plots(fig, [ax for ax in axs_map], xoff=0.02, yoff=0)       \n",
    "utils.label_plots(fig, [ax for ax in axs_za + [ax_za_mean]], xoff=-0.01, start=2)\n",
    "\n",
    "plt.colorbar(cf, cax=cax)\n",
    "cax.set_title('mol m$^{-2}$ yr$^{-1}$')\n",
    "\n",
    "utils.savefig('fgco2.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca07f4c6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:miniconda3-cesm2-marbl]",
   "language": "python",
   "name": "conda-env-miniconda3-cesm2-marbl-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}