notebooks/pypsa-eur.py.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pypsa\n",
    "import geopandas as gpd\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "from matplotlib.lines import Line2D\n",
    "import atlite\n",
    "\n",
    "plt.style.use([\"bmh\", \"matplotlibrc\"])\n",
    "xr.set_options(display_style=\"html\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH = \"../workflows/pypsa-eur/\"\n",
    "CLUSTERS = 181\n",
    "OUTPUT = \"../results/graphics-20221227/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions = gpd.read_file(PATH + f\"resources/regions_onshore_elec_s_{CLUSTERS}.geojson\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Electricity Network Topology"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = pypsa.Network(PATH + \"networks/elec.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(n.buses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "n.lines.query(\"num_parallel == 0.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = pypsa.Network(PATH + \"networks/elec_s_181.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={\"projection\": ccrs.EqualEarth()})\n",
    "x.plot(ax=ax, boundaries=[-9, 28, 72, 35])\n",
    "\n",
    "handles = [\n",
    "    Line2D([0], [0], color=\"rosybrown\", lw=2),\n",
    "    Line2D([0], [0], color=\"darkseagreen\", lw=2),\n",
    "]\n",
    "plt.legend(handles, [\"HVAC\", \"HVDC\"], frameon=False, loc=[0.15, 0.85], fontsize=18)\n",
    "\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "plt.savefig(OUTPUT + \"network-s.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(n.buses.loc[n.buses.substation_lv == False])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(n.buses.loc[n.buses.substation_lv == True])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(n.lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(n.links)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "w = n.lines.v_nom.div(380)\n",
    "c = n.lines.v_nom.map({220: \"teal\", 300: \"orange\", 380: \"firebrick\"})\n",
    "\n",
    "fig, ax = plt.subplots(subplot_kw={\"projection\": ccrs.EqualEarth()})\n",
    "fig.set_size_inches(13, 13)\n",
    "n.plot(\n",
    "    ax=ax,\n",
    "    bus_sizes=0,\n",
    "    line_widths=w,\n",
    "    line_colors=c,\n",
    "    link_colors=\"royalblue\",\n",
    "    link_widths=1,\n",
    "    color_geomap=None,\n",
    ")\n",
    "\n",
    "handles = [\n",
    "    Line2D([0], [0], color=\"teal\", lw=2),\n",
    "    Line2D([0], [0], color=\"orange\", lw=2),\n",
    "    Line2D([0], [0], color=\"firebrick\", lw=2),\n",
    "    Line2D([0], [0], color=\"royalblue\", lw=2),\n",
    "]\n",
    "plt.legend(\n",
    "    handles,\n",
    "    [\"HVAC 220 kV\", \"HVAC 300 kV\", \"HVAC 380 kV\", \"HVDC\"],\n",
    "    frameon=False,\n",
    "    loc=[0.2, 0.85],\n",
    "    fontsize=14,\n",
    ")\n",
    "ax.set_frame_on(False)\n",
    "plt.savefig(OUTPUT + \"network.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Renewable Potentials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions = gpd.read_file(PATH + \"resources/regions_onshore.geojson\").append(\n",
    "    gpd.read_file(PATH + \"resources/regions_offshore.geojson\")\n",
    ")\n",
    "regions = regions.dissolve(\"name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions[\"Area\"] = regions.to_crs(epsg=3035).area.div(1e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "onregions = gpd.read_file(PATH + \"resources/regions_onshore.geojson\").set_index(\"name\")\n",
    "onregions[\"Area\"] = onregions.to_crs(epsg=3035).area.div(1e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "wind = pd.Series()\n",
    "for profile in [\"onwind\", \"offwind-ac\", \"offwind-dc\"]:\n",
    "    ds = xr.open_dataset(PATH + f\"resources/profile_{profile}.nc\")\n",
    "    wind = wind.append((ds.p_nom_max * ds.profile.sum(\"time\")).to_pandas())\n",
    "wind = wind.sum(level=0).reindex(regions.index, fill_value=0)\n",
    "wind_per_skm = wind / regions.Area / 1e3  # GWh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "proj = ccrs.EqualEarth()\n",
    "regions = regions.to_crs(proj.proj4_init)\n",
    "fig, ax = plt.subplots(figsize=(7, 7), subplot_kw={\"projection\": proj})\n",
    "regions.plot(\n",
    "    ax=ax,\n",
    "    column=wind_per_skm,\n",
    "    cmap=\"Blues\",\n",
    "    linewidths=0,\n",
    "    legend=True,\n",
    "    legend_kwds={\"label\": r\"Renewable Potential [GWh/a/km$^2$]\", \"shrink\": 0.7},\n",
    ")\n",
    "ax.add_feature(cartopy.feature.COASTLINE.with_scale(\"50m\"), linewidth=0.2, zorder=4)\n",
    "ax.add_feature(cartopy.feature.BORDERS.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.set_frame_on(False)\n",
    "ax.set_facecolor(\"white\")\n",
    "plt.savefig(OUTPUT + \"wind-energy-density.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset(PATH + \"resources/profile_solar.nc\")\n",
    "solar = (ds.p_nom_max * ds.profile.sum(\"time\")).to_pandas()\n",
    "\n",
    "solar = solar.sum(level=0).reindex(onregions.index, fill_value=0)\n",
    "solar_per_skm = solar / onregions.Area / 1e3  # GWh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "proj = ccrs.EqualEarth()\n",
    "onregions = onregions.to_crs(proj.proj4_init)\n",
    "fig, ax = plt.subplots(figsize=(7, 7), subplot_kw={\"projection\": proj})\n",
    "onregions.plot(\n",
    "    ax=ax,\n",
    "    column=solar_per_skm,\n",
    "    cmap=\"Reds\",\n",
    "    linewidths=0,\n",
    "    legend=True,\n",
    "    legend_kwds={\"label\": r\"Renewable Potential [GWh/a/km$^2$]\", \"shrink\": 0.7},\n",
    ")\n",
    "ax.add_feature(cartopy.feature.COASTLINE.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.add_feature(cartopy.feature.BORDERS.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.set_frame_on(False)\n",
    "ax.set_facecolor(\"white\")\n",
    "plt.savefig(OUTPUT + \"solar-energy-density.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "elec = pypsa.Network(PATH + \"networks/elec.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "wind = (\n",
    "    elec.generators_t.p_max_pu.filter(like=\"onwind\")\n",
    "    .groupby(elec.generators.bus.map(elec.buses.country), axis=1)\n",
    "    .mean()[\"DE\"]\n",
    ")\n",
    "solar = (\n",
    "    elec.generators_t.p_max_pu.filter(like=\"solar\")\n",
    "    .groupby(elec.generators.bus.map(elec.buses.country), axis=1)\n",
    "    .mean()[\"DE\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sel = (\n",
    "    (wind.index >= \"2013-02-01\") & (wind.index < \"2013-02-03\")\n",
    "    | (wind.index >= \"2013-05-01\") & (wind.index < \"2013-05-03\")\n",
    "    | (wind.index >= \"2013-08-01\") & (wind.index < \"2013-08-03\")\n",
    "    | (wind.index >= \"2013-11-01\") & (wind.index < \"2013-11-03\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sel = (wind.index >= \"2013-01-01\") & (wind.index < \"2014-01-01\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 3))\n",
    "\n",
    "solar.where(sel).plot(\n",
    "    ax=ax, c=\"#f9d002\", alpha=0.5, linewidth=0.75, label=\"Germany Solar\"\n",
    ")\n",
    "wind.where(sel).plot(ax=ax, c=\"#235ebc\", label=\"Germany Wind\")\n",
    "\n",
    "plt.ylabel(\"Capacity Factor [-]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.legend(ncol=3, frameon=False, loc=\"upper center\")\n",
    "plt.ylim([0, 1])\n",
    "plt.xlabel(None)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(OUTPUT + \"temporal-fullyear.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "time = \"03-2013\"\n",
    "i = elec.generators_t.p_max_pu.loc[time, \"5710 onwind\"]\n",
    "c = (\n",
    "    elec.generators_t.p_max_pu.filter(like=\"onwind\")\n",
    "    .groupby(elec.generators.bus.map(elec.buses.country), axis=1)\n",
    "    .mean()\n",
    "    .loc[time, \"DE\"]\n",
    ")\n",
    "a = elec.generators_t.p_max_pu.filter(like=\"onwind\").mean(axis=1).loc[time]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 2))\n",
    "plt.plot(i, label=\"Flensburg\", linewidth=1.5, color=\"teal\")\n",
    "plt.plot(c, label=\"Germany\", linewidth=1.5, color=\"orange\")\n",
    "plt.plot(a, label=\"Europe\", linewidth=1.5, color=\"mediumpurple\")\n",
    "plt.legend(ncol=3, frameon=False, loc=[0, 1])\n",
    "plt.xticks(rotation=30)\n",
    "plt.ylabel(\"Capacity Factor [-]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.savefig(OUTPUT + \"ts-wind.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 2))\n",
    "i.plot(ax=ax, label=\"Flensburg (Northern Germany)\", linewidth=1.5, color=\"#235ebc\")\n",
    "plt.legend(ncol=3, frameon=False, loc=[0, 1])\n",
    "plt.ylabel(\"Capacity Factor [-]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.xlabel(None)\n",
    "plt.savefig(OUTPUT + \"ts-wind-reduced.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# time = \"01-03-2013\":\"05-03-2013\"\n",
    "start = \"06-28-2013\"\n",
    "end = \"07-07-2013\"\n",
    "i = elec.generators_t.p_max_pu.loc[start:end, \"5710 solar\"]\n",
    "c = (\n",
    "    elec.generators_t.p_max_pu.filter(like=\"solar\")\n",
    "    .groupby(elec.generators.bus.map(elec.buses.country), axis=1)\n",
    "    .mean()\n",
    "    .loc[start:end, \"DE\"]\n",
    ")\n",
    "a = elec.generators_t.p_max_pu.filter(like=\"solar\").mean(axis=1).loc[start:end]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 2))\n",
    "plt.plot(i, label=\"Flensburg\", linewidth=1.5, color=\"teal\")\n",
    "plt.plot(c, label=\"Germany\", linewidth=1.5, color=\"orange\")\n",
    "plt.plot(a, label=\"Europe\", linewidth=1.5, color=\"mediumpurple\")\n",
    "plt.legend(ncol=3, frameon=False, loc=[0, 1])\n",
    "plt.xticks(rotation=30)\n",
    "plt.ylabel(\"Capacity Factor [-]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.savefig(OUTPUT + \"ts-solar.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 2))\n",
    "i.plot(ax=ax, label=\"Flensburg (Northern Germany)\", linewidth=1.5, color=\"#f9d002\")\n",
    "plt.legend(ncol=3, frameon=False, loc=[0, 1])\n",
    "plt.ylabel(\"Capacity Factor [-]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.xlabel(None)\n",
    "plt.savefig(OUTPUT + \"ts-solar-reduced.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "load = (\n",
    "    elec.loads_t.p_set.groupby(elec.loads.bus.map(elec.buses.country), axis=1)\n",
    "    .sum()\n",
    "    .div(1e3)\n",
    "    .loc[\"03-2013\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "load.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 2))\n",
    "plt.plot(load.ES, label=\"Spain\", linewidth=1.5, color=\"teal\")\n",
    "plt.plot(load.DE, label=\"Germany\", linewidth=1.5, color=\"orange\")\n",
    "plt.plot(load.NO, label=\"Norway\", linewidth=1.5, color=\"mediumpurple\")\n",
    "# plt.plot(load.IE, label=\"Ireland\",  linewidth=1.5, color=\"royalblue\")\n",
    "# plt.plot(load.IT, label=\"Estonia\",  linewidth=1.5, color=\"darksalmon\")\n",
    "plt.legend(ncol=3, frameon=False, loc=[0, 1])\n",
    "plt.xticks(rotation=30)\n",
    "plt.ylabel(\"Electricity Load [GW]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.ylim([0, 80])\n",
    "plt.savefig(OUTPUT + \"ts-load.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 2))\n",
    "load.DE.plot(ax=ax, label=\"Germany\", linewidth=1.5, color=\"green\")\n",
    "plt.legend(ncol=3, frameon=False, loc=[0, 1])\n",
    "plt.ylabel(\"Electricity Load [GW]\")\n",
    "plt.box(None)\n",
    "plt.grid(False)\n",
    "plt.ylim([0, 80])\n",
    "plt.xlabel(None)\n",
    "plt.savefig(OUTPUT + \"ts-load-reduced.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Voronoi Cells Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "smregions = gpd.read_file(PATH + \"resources/regions_onshore.geojson\").set_index(\"name\")\n",
    "elecs = pypsa.Network(PATH + \"networks/elec_s.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(4, 4))\n",
    "smregions.plot(ax=ax, facecolor=\"steelblue\", edgecolor=\"white\")\n",
    "plt.scatter(x=smregions.x, y=smregions.y, color=\"white\", s=5)\n",
    "plt.axis(\"off\")\n",
    "plt.ylim([52, 53])\n",
    "plt.xlim([9, 13])\n",
    "plt.savefig(OUTPUT + \"voronoi.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cutouts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "era5 = atlite.Cutout(PATH + \"cutouts/europe-2013-era5.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sarah = atlite.Cutout(PATH + \"cutouts/europe-2013-sarah.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(7, 7), subplot_kw={\"projection\": ccrs.EqualEarth(), \"facecolor\": \"white\"}\n",
    ")\n",
    "\n",
    "sarah.data.influx_direct.mean(\"time\").plot(\n",
    "    ax=ax,\n",
    "    transform=ccrs.PlateCarree(),\n",
    "    cmap=\"Oranges\",\n",
    "    linewidths=0,\n",
    "    cbar_kwargs={\"label\": r\"Mean Direct Solar Irradiance [W/m$^2$]\", \"shrink\": 0.6},\n",
    ")\n",
    "\n",
    "ax.add_feature(cartopy.feature.COASTLINE.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.add_feature(cartopy.feature.BORDERS.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "plt.savefig(OUTPUT + \"irradiation.png\", dpi=400, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(7, 7), subplot_kw={\"projection\": ccrs.EqualEarth(), \"facecolor\": \"white\"}\n",
    ")\n",
    "\n",
    "era5.data.wnd100m.mean(\"time\").plot(\n",
    "    ax=ax,\n",
    "    transform=ccrs.PlateCarree(),\n",
    "    cmap=\"Blues\",\n",
    "    linewidths=0,\n",
    "    cbar_kwargs={\"label\": r\"Mean Wind Speeds [m/s]\", \"shrink\": 0.7},\n",
    ")\n",
    "\n",
    "ax.add_feature(cartopy.feature.COASTLINE.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.add_feature(cartopy.feature.BORDERS.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "plt.savefig(OUTPUT + \"windspeeds.png\", dpi=400, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(7, 7), subplot_kw={\"projection\": ccrs.EqualEarth(), \"facecolor\": \"white\"}\n",
    ")\n",
    "\n",
    "(era5.data.temperature.mean(\"time\") - 273.15).plot(\n",
    "    ax=ax,\n",
    "    transform=ccrs.PlateCarree(),\n",
    "    cmap=\"Reds\",\n",
    "    linewidths=0,\n",
    "    vmin=-5,\n",
    "    vmax=30,\n",
    "    cbar_kwargs={\"label\": r\"Mean Temperatures [°C]\", \"shrink\": 0.7},\n",
    ")\n",
    "\n",
    "\n",
    "ax.add_feature(cartopy.feature.COASTLINE.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.add_feature(cartopy.feature.BORDERS.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "plt.savefig(OUTPUT + \"temperatures.png\", dpi=400, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(7, 7), subplot_kw={\"projection\": ccrs.EqualEarth(), \"facecolor\": \"white\"}\n",
    ")\n",
    "\n",
    "era5.data.runoff.sum(\"time\").plot(\n",
    "    ax=ax,\n",
    "    transform=ccrs.PlateCarree(),\n",
    "    cmap=\"Greens\",\n",
    "    linewidths=0,\n",
    "    vmin=0,\n",
    "    vmax=2,\n",
    "    cbar_kwargs={\"label\": r\"Total Runoff [m]\", \"shrink\": 0.7},\n",
    ")\n",
    "\n",
    "\n",
    "ax.add_feature(cartopy.feature.COASTLINE.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.add_feature(cartopy.feature.BORDERS.with_scale(\"50m\"), linewidth=0.2, zorder=2)\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "plt.savefig(OUTPUT + \"runoff.png\", dpi=400, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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