analyze.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import cmocean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "OUTPUT_FILES = {\n",
    "    \"snapshot\": \"acc.snapshot.nc\",\n",
    "    \"averages\": \"acc.averages.nc\",\n",
    "    \"overturning\": \"acc.overturning.nc\",\n",
    "    \"energy\": \"acc.energy.nc\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_avg = xr.open_dataset(OUTPUT_FILES[\"averages\"])\n",
    "ds_avg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_avg[\"psi\"] = ds_avg.psi / 1e6\n",
    "ds_avg[\"psi\"].attrs[\"units\"] = \"Sv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_avg[\"psi\"].isel(Time=-1).plot.contourf(levels=50, cmap=\"cmo.balance\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "(\n",
    "    ds_avg[\"salt\"]\n",
    "    .isel(Time=slice(-1,None))\n",
    "    .mean(dim=(\"Time\", \"xt\"))\n",
    "    .plot.contourf(levels=50, cmap=\"cmo.haline\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_snap = xr.open_dataset(OUTPUT_FILES[\"snapshot\"])\n",
    "weights = ds_snap[\"area_t\"].fillna(0)\n",
    "\n",
    "temp_weighted = (\n",
    "    ds_avg[\"temp\"]\n",
    "    .isel(Time=-1)\n",
    "    .weighted(weights)\n",
    "    .mean(dim=\"yt\")\n",
    "    .plot.contourf(vmin=-2, vmax=22, levels=25, cmap=\"cmo.thermal\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_ovr = xr.open_dataset(OUTPUT_FILES[\"overturning\"])\n",
    "\n",
    "ds_ovr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_ovr[\"vsf_depth\"] = ds_ovr.vsf_depth / 1e6\n",
    "\n",
    "ds_ovr.vsf_depth.attrs[\"long_name\"] = \"MOC\"\n",
    "\n",
    "ds_ovr.vsf_depth.attrs[\"units\"] = \"Sv\"\n",
    "\n",
    "ds_ovr.vsf_depth.isel(Time=-1).plot.contourf(levels=50, cmap=\"cmo.balance\")"
   ]
  }
 ],
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