diag_climo.ipynb

{
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   "cell_type": "markdown",
   "id": "e7f50c21-feb3-4d68-b9ec-971f8fdb84d5",
   "metadata": {},
   "source": [
    "# diagnostics of iHesp climatology"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f2ad8b83-9fa4-4c0c-ab2e-6e5abb774e51",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import pop_tools \n",
    "from geocat.viz import util as gvutil\n",
    "import datetime\n",
    "import cf_units as cf\n",
    "import cmocean\n",
    "import dask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bf3dceac-6bdb-4088-95e6-4bc0a3ede9ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask_jobqueue import PBSCluster\n",
    "from dask.distributed import Client\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "248640e5-8146-40aa-b75a-9f003de751e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# method: 0 for difference 1 for mean\n",
    "# note that xarray.copy, if you are copying the variable's data to the new data, the origial array will be affected\n",
    "# i.e.. b=a.copy(data=a.data), then b=a[2]-a[1], will change a[2] value\n",
    "\n",
    "def get_anoms(variable, index, istart, iend, bdays,adays, method, climo=None):\n",
    "    ncases = iend - istart\n",
    "    anoms = variable[istart:iend+1, :,:].copy(data=np.array(variable[istart:iend+1,:,:].data))\n",
    "    anoms.data = np.zeros(anoms.shape)\n",
    "    j = 0\n",
    "    print(j)\n",
    "    for i in np.arange(istart, iend):\n",
    "        hit_day = index[i]\n",
    "        before = index[i] - pd.to_timedelta(bdays,'D')     # 3 days before and maximum 7 days after\n",
    "        after = index[i] + pd.to_timedelta(adays,'D')\n",
    "      \n",
    "        if (variable.time.dt.date.isin(before.dt.date).any()) & (variable.time.dt.date.isin(after.dt.date).any()):\n",
    "            if method == 0:\n",
    "                anoms[j,:,:] = np.array(variable.sel(time=after) - variable.sel(time=before))\n",
    "            if method == 1:\n",
    "                ar_range = variable.sel(time=slice(before,after))\n",
    "                anoms[j,:,:] = ar_range.mean('time') - climo.sel(month=before.dt.month)\n",
    "            anoms[j,:,:] = anoms[j].where(np.isfinite(anoms[j]),-99999)\n",
    "            anoms[j,:,:]['time'] = index[i]\n",
    "#        print(index[i])\n",
    "            j = j + 1                                 \n",
    "    anoms = anoms.assign_attrs({'units':variable.units})\n",
    "    return anoms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "90c2b82d-37cc-43a8-aa7c-32a5d6ca60d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/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 41180 instead\n",
      "  expected, actual\n"
     ]
    }
   ],
   "source": [
    "cluster = PBSCluster(\n",
    "    cores=1, # The number of cores you want\n",
    "    memory='20GB', # Amount of memory\n",
    "    processes=1, # How many processes\n",
    "    queue='casper', # The type of queue to utilize (/glade/u/apps/dav/opt/usr/bin/execcasper)\n",
    "    local_directory='$TMPDIR', # Use your local directory\n",
    "    resource_spec='select=1:ncpus=1:mem=25GB', # Specify resources\n",
    "    project='P93300313', # Input your project ID here\n",
    "    walltime='04:00:00', # Amount of wall time\n",
    "    interface='ib0', # Interface to use\n",
    ")\n",
    "\n",
    "# Scale up\n",
    "cluster.scale(12)\n",
    "\n",
    "# Change your url to the dask dashboard so you can see it\n",
    "dask.config.set({'distributed.dashboard.link':'https://jupyterhub.hpc.ucar.edu/stable/user/huili7/proxy/127.0.0.1:8787/status'})\n",
    "\n",
    "# Setup your client\n",
    "client = Client(cluster)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e8f7fc9d-a7c0-4c8e-af61-c8610c6a0eba",
   "metadata": {},
   "outputs": [
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       "                    <strong>Dashboard:</strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/huili7/proxy/127.0.0.1:8787/status\">https://jupyterhub.hpc.ucar.edu/stable/user/huili7/proxy/127.0.0.1:8787/status</a>\n",
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       "<Client: 'tcp://10.12.206.56:37549' processes=0 threads=0, memory=0 B>"
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6ab9fe0-a82d-4830-b995-0b37e43a6eb0",
   "metadata": {},
   "source": [
    "## 1. read in data 1950-1969"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b803a09d-add7-4f68-91bc-8b532fe711c3",
   "metadata": {},
   "source": [
    "## 1.1 Get regrided surface heat flux"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1b1bd0e6-5a3a-4a0e-acde-dc7e3fe91d72",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob as _glob\n",
    "import os as _os\n",
    "\n",
    "ocn_dir = \"/glade/scratch/huili7/AR_cases/data/\"\n",
    "ocn_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SHF.19[56]*\"\n",
    "shf_files = sorted(_glob.glob(ocn_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "70a7b711-149b-4c51-b197-eff392917e57",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='SHF'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b81ef42b-f61f-4751-9522-384bf055e8e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsh0 = xr.open_mfdataset(shf_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7cc303f6-896f-4933-9337-66689a6dee26",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/xarray/core/dataarray.py:3224: FutureWarning: roll_coords will be set to False in the future. Explicitly set roll_coords to silence warning.\n",
      "  shifts=shifts, roll_coords=roll_coords, **shifts_kwargs\n"
     ]
    }
   ],
   "source": [
    "shf0 = dsh0.SHF\n",
    "shf_new = shf0.roll(lon=180)             #lonflip \n",
    "shf_new['lon'] = np.arange(-180,180,1)\n",
    "del(shf0)\n",
    "shf_1950 = shf_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(shf_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "15e4b1e8-30a3-461e-9eea-2990f01fa6d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:1: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "shf_1950['time'] = shf_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d489926f-3a1b-485a-96d4-952897e2eba2",
   "metadata": {},
   "outputs": [],
   "source": [
    "ocn_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SHF.20[34]*\"\n",
    "shf_files = sorted(_glob.glob(ocn_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bc2c6560-b0c2-4286-8c82-932a84f66846",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsh1 = xr.open_mfdataset(shf_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "31fab576-3e02-46a3-bf15-bd2122b0160a",
   "metadata": {},
   "outputs": [],
   "source": [
    "shf1 = dsh1.SHF\n",
    "shf_new = shf1.roll(lon=180)             #lonflip \n",
    "shf_new['lon'] = np.arange(-180,180,1)\n",
    "del(shf1)\n",
    "shf_2050 = shf_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(shf_new)\n",
    "shf_2050['time'] = shf_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22d62436-daea-4eae-a66a-9356bb1ee56f",
   "metadata": {},
   "source": [
    "### 1.2 get regridded daily SSH"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f371269-1b63-4d21-8370-7af19b3b8447",
   "metadata": {},
   "source": [
    "<h1 style=\"red' now find timing AR \\>\n",
    "### 1. \n",
    "           from AR case  -- ar_date\n",
    "\n",
    "The original date from the netcdf files are just integers. We will need to convert them to datetime class for easy manipulation and indexing\n",
    "\n",
    "We use the datetim.datetime()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ed307e20-9561-494d-927c-9d9cbbd38831",
   "metadata": {},
   "outputs": [],
   "source": [
    "ssh_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SSH.19[56]*\"\n",
    "ssh_files = sorted(_glob.glob(ssh_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "07dfffd9-cd55-44fb-baf2-384987f29ece",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='SSH'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d8715835-e1ad-4dba-999f-2d192e0a99db",
   "metadata": {},
   "outputs": [],
   "source": [
    "dshh0 = xr.open_mfdataset(ssh_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1991f82a-3c04-4886-bb7d-5fadefe061c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "ssh0 = dshh0.SSH\n",
    "ssh_new = ssh0.roll(lon=180)             #lonflip \n",
    "ssh_new['lon'] = np.arange(-180,180,1)\n",
    "#del(ssh0)\n",
    "ssh_1950 = ssh_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(ssh_new)\n",
    "ssh_1950['time'] = ssh_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "38bc7579-1253-4d56-85fe-4fed094eca35",
   "metadata": {},
   "outputs": [],
   "source": [
    "ssh_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-2015-2050.013.pop.h.nday1.SSH.20[34]*\"\n",
    "ssh_files = sorted(_glob.glob(ssh_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d42ced7e-68fd-46d3-8fdb-e55e1ddbdc06",
   "metadata": {},
   "outputs": [],
   "source": [
    "dshh = xr.open_mfdataset(ssh_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7796609a-68a4-4efc-a209-30c3a7c2782a",
   "metadata": {},
   "outputs": [],
   "source": [
    "ssh0 = dshh.SSH\n",
    "ssh_new = ssh0.roll(lon=180)             #lonflip \n",
    "ssh_new['lon'] = np.arange(-180,180,1)\n",
    "del(ssh0)\n",
    "ssh_2050 = ssh_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(ssh_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e9620204-9795-489f-b117-7eaa7a1c22ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:1: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "ssh_2050['time'] = ssh_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d040beae-ec25-4fc6-bf69-7debb4698e9d",
   "metadata": {},
   "source": [
    "## 1.3 get SST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "533c272a-a9fe-4c9f-a739-cebfad0d28a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "sst_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SST.19[56]*\"\n",
    "sst_files = sorted(_glob.glob(sst_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5c6be915-ac36-474a-96ff-4b190312105c",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='SST'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6881e474-7892-4c8b-ba6f-26e9fccc70df",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsst0 = xr.open_mfdataset(sst_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "946ee004-83d2-4136-b35c-d091d3731a4a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "sst0 = dsst0.SST\n",
    "sst_new = sst0.roll(lon=180)             #lonflip \n",
    "sst_new['lon'] = np.arange(-180,180,1)\n",
    "#del(sst0)\n",
    "sst_1950 = sst_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(sst_new)\n",
    "sst_1950['time'] = sst_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "68416711-b5a4-4ab5-b679-07c1faef699b",
   "metadata": {},
   "outputs": [],
   "source": [
    "sst_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SST.20[34]*\"\n",
    "sst_files = sorted(_glob.glob(sst_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "42be4136-b2d5-443b-b0d4-8d9d8dc24797",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsst = xr.open_mfdataset(sst_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3a58a307-d70e-4b7a-9cae-c271fdb5754b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "sst0 = dsst.SST\n",
    "sst_new = sst0.roll(lon=180)             #lonflip \n",
    "sst_new['lon'] = np.arange(-180,180,1)\n",
    "#del(sst0)\n",
    "sst_2050 = sst_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(sst_new)\n",
    "sst_2050['time'] = sst_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffb8fd64-d58a-4c7e-9ada-72a0d713aa8a",
   "metadata": {},
   "source": [
    "## 1.4 read in evaporation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f92f1118-c5d2-4c91-96ee-fbab4e00e51a",
   "metadata": {},
   "outputs": [],
   "source": [
    "evap_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.EVAP_F.19[56]*\"\n",
    "evap_files = sorted(_glob.glob(evap_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e68a8727-21dd-45fd-a7d5-c3914472f74d",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='EVAP_F'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "eaf9e790-df33-42ab-8932-5efd7850b6f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsev0 = xr.open_mfdataset(evap_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3726681f-4b98-473b-b906-defe7f4aaf37",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "evap0 = dsev0.EVAP_F\n",
    "evap_new = evap0.roll(lon=180)             #lonflip e\n",
    "evap_new['lon'] = np.arange(-180,180,1)\n",
    "del(evap0)\n",
    "evap_1950 = evap_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(evap_new)\n",
    "evap_1950['time'] = evap_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "9495d898-fa9d-485e-a3a3-a2b258e4ca5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "evap_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.EVAP_F.20[34]*\"\n",
    "evap_files = sorted(_glob.glob(evap_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "38c998dc-d419-4b13-8607-f195a766593b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsev = xr.open_mfdataset(evap_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bf0e17aa-fc7b-457c-99c6-2022b22c1d2c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "evap0 = dsev.EVAP_F\n",
    "evap_new = evap0.roll(lon=180)             #lonflip e\n",
    "evap_new['lon'] = np.arange(-180,180,1)\n",
    "del(evap0)\n",
    "evap_2050 = evap_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(evap_new)\n",
    "evap_2050['time'] = evap_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "249eb8e2-0c64-41e3-afc5-8ee314ecf784",
   "metadata": {},
   "source": [
    "## 1.5 get sensible heat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b7a82079-8f3d-4e72-82fc-c67155d1b3b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "sen_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SENH_F.19[56]*\"\n",
    "sen_files = sorted(_glob.glob(sen_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9539aa78-719f-4c33-8569-9531e925b403",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='SENH_F'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "cb5c3d0d-07db-4260-b7d0-4d723c043044",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsen0 = xr.open_mfdataset(sen_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "152479c9-dac2-4f7d-b106-e2cb39e69cb5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "sen0 = dsen0.SENH_F\n",
    "sen_new = sen0.roll(lon=180)             #lonflip \n",
    "sen_new['lon'] = np.arange(-180,180,1)\n",
    "#del(ssh0)\n",
    "sen_1950 = sen_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(sen_new)\n",
    "sen_1950['time'] = sen_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "8391edd1-89eb-4856-85c7-773096841ef6",
   "metadata": {},
   "outputs": [],
   "source": [
    "sen_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.SENH_F.20[34]*\"\n",
    "sen_files = sorted(_glob.glob(sen_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "1a3b20de-a5f8-46d5-bc86-9493b18e7991",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsen = xr.open_mfdataset(sen_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ff2cc7e0-0db2-4f88-95ea-0db60906ac60",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "sen0 = dsen.SENH_F\n",
    "sen_new = sen0.roll(lon=180)             #lonflip \n",
    "sen_new['lon'] = np.arange(-180,180,1)\n",
    "del(sen0)\n",
    "sen_2050 = sen_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(sen_new)\n",
    "sen_2050['time'] = sen_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c900386-164a-4c25-9d2f-f4d7b45b7744",
   "metadata": {},
   "source": [
    "## 1.7.get HMXL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "9d40f36c-d3cf-4b07-a813-a6612359a367",
   "metadata": {},
   "outputs": [],
   "source": [
    "h_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.HMXL.19[56]*\"\n",
    "h_files = sorted(_glob.glob(h_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6888732f-b44d-4a2d-b8eb-fe485c97cb43",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='HMXL'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "944dd336-2476-490b-b8f8-5bc0e63d071b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dshm0 = xr.open_mfdataset(h_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "759aa5df-4dc8-4651-861a-7b9a65085aec",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "h0 = dshm0.HMXL\n",
    "h0_new = h0.roll(lon=180)             #lonflip \n",
    "h0_new['lon'] = np.arange(-180,180,1)\n",
    "del(h0)\n",
    "hmxl_1950 = h0_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(h0_new)\n",
    "hmxl_1950['time'] = hmxl_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "8cf9de6d-aa25-4123-8e06-9bf305e713bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "h_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.HMXL.20[34]*\"\n",
    "h_files = sorted(_glob.glob(h_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "5514f675-2af3-499a-aa6e-29b4077806ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "dshm = xr.open_mfdataset(h_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "d3f5b488-1063-4931-858f-804d45b4e10d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "h0 = dshm.HMXL\n",
    "h0_new = h0.roll(lon=180)             #lonflip \n",
    "h0_new['lon'] = np.arange(-180,180,1)\n",
    "del(h0)\n",
    "hmxl_2050 = h0_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(h0_new)\n",
    "hmxl_2050['time'] = hmxl_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "457b8d8f-c51c-4751-ac12-f2962b4a3b95",
   "metadata": {},
   "source": [
    "## 1.7 get taux, tauy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "be2c071e-210b-4ae1-ba6b-5f145538d161",
   "metadata": {},
   "outputs": [],
   "source": [
    "t_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.TAUX.19[56]*\"\n",
    "t_files = sorted(_glob.glob(t_path))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "3f937871-44a2-49af-9384-5b14cfa40153",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='TAUX'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ac2b63c1-6df3-4a88-8681-ccb7c0770e4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "dtau0 = xr.open_mfdataset(t_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "53d845e0-53bc-42a9-9b90-e7a8671efed3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "taux0 = dtau0.TAUX\n",
    "taux_new = taux0.roll(lon=180)             #lonflip \n",
    "taux_new['lon'] = np.arange(-180,180,1)\n",
    "del(taux0)\n",
    "taux_1950 = taux_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(taux_new)\n",
    "taux_1950['time'] = taux_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "d201fc8b-6c9f-49f3-95c2-6a5fc520a05a",
   "metadata": {},
   "outputs": [],
   "source": [
    "t_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-2015-2050.013.pop.h.nday1.TAUX.20[34]*\"\n",
    "t_files = sorted(_glob.glob(t_path))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "4116a8b0-8743-4eb3-aa37-be74c4c23995",
   "metadata": {},
   "outputs": [],
   "source": [
    "dtau = xr.open_mfdataset(t_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "2e35fa80-ace2-4fd9-b106-f0b0446fac87",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "taux0 = dtau.TAUX\n",
    "taux_new = taux0.roll(lon=180)             #lonflip \n",
    "taux_new['lon'] = np.arange(-180,180,1)\n",
    "del(taux0)\n",
    "taux_2050 = taux_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(taux_new)\n",
    "taux_2050['time'] = taux_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01271356-9451-4b19-b863-2f0215d46a5a",
   "metadata": {},
   "source": [
    "#### now tauy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "77d532c5-0ff9-492b-968f-47f06b7791f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "ty_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-1950-2050.013.pop.h.nday1.TAUY.19[56]*\"\n",
    "ty_files = sorted(_glob.glob(ty_path))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "e18c66cd-dd6b-43b4-acd7-8994387d75c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "var='TAUY'\n",
    "def preprocess_var(ds):\n",
    "    return ds[var].to_dataset(name=var).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c76c7f9f-3aa0-442f-91e3-94c9d3a1995e",
   "metadata": {},
   "outputs": [],
   "source": [
    "dtauy0 = xr.open_mfdataset(ty_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "2ba5937e-0a72-425c-bdd6-b25e0aebb07d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "tauy0 = dtauy0.TAUY\n",
    "tauy_new = tauy0.roll(lon=180)             #lonflip \n",
    "tauy_new['lon'] = np.arange(-180,180,1)\n",
    "del(tauy0)\n",
    "tauy_1950 = tauy_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(tauy_new)\n",
    "tauy_1950['time'] = tauy_1950.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0418731d-8fe8-463f-ad43-6e984827ed8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "ty_path = f\"{ocn_dir}/B.E.13.B1950TRC5.ne120_t12.cesm-ihesp-2015-2050.013.pop.h.nday1.TAUY.20[34]*\"\n",
    "ty_files = sorted(_glob.glob(ty_path))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "e073c748-0a14-46d8-b654-aa3a9796ebad",
   "metadata": {},
   "outputs": [],
   "source": [
    "dtauy = xr.open_mfdataset(ty_files,\n",
    "                    combine=\"nested\",\n",
    "                    concat_dim=\"time\",\n",
    "                    preprocess=preprocess_var,\n",
    "                    parallel=True,\n",
    "                    engine=None,\n",
    "                    coords=\"minimal\",  # expecting identical coords\n",
    "                    data_vars=\"minimal\",  # expecting identical vars\n",
    "                    compat=\"override\",  # speed up\n",
    "                    #chunks = {'time':365}\n",
    "                    ).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "db63dc83-cc93-4179-8dc0-4ced63a762ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/huili7/miniconda3/envs/geocat_env/lib/python3.7/site-packages/ipykernel_launcher.py:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "tauy0 = dtauy.TAUY\n",
    "tauy_new = tauy0.roll(lon=180)             #lonflip \n",
    "tauy_new['lon'] = np.arange(-180,180,1)\n",
    "del(tauy0)\n",
    "tauy_2050 = tauy_new.sel(lat=slice(15,55),lon=slice(-160,-110))\n",
    "del(tauy_new)\n",
    "tauy_2050['time'] = tauy_2050.indexes['time'].to_datetimeindex()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ba7cdc9-98f5-4383-8366-348aaa77095b",
   "metadata": {},
   "source": [
    "## 2 get climatology"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97630e46-58ae-412c-93ce-7f0864237040",
   "metadata": {},
   "source": [
    "### 2.1 for 1950"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "d2b02feb-c61f-4bf5-88be-dbd2cc825a21",
   "metadata": {},
   "outputs": [],
   "source": [
    "sst_climo = sst_1950.groupby(sst_1950.time.dt.month).mean(keep_attrs=True)\n",
    "hmxl_climo = hmxl_1950.groupby(hmxl_1950.time.dt.month).mean(keep_attrs=True)\n",
    "taux_climo = taux_1950.groupby(taux_1950.time.dt.month).mean(keep_attrs=True)\n",
    "tauy_climo = tauy_1950.groupby(tauy_1950.time.dt.month).mean(keep_attrs=True)\n",
    "ssh_climo = ssh_1950.groupby(ssh_1950.time.dt.month).mean(keep_attrs=True)\n",
    "evap_climo = evap_1950.groupby(evap_1950.time.dt.month).mean(keep_attrs=True)\n",
    "sen_climo = sen_1950.groupby(sen_1950.time.dt.month).mean(keep_attrs=True)\n",
    "shf_climo = shf_1950.groupby(shf_1950.time.dt.month).mean(keep_attrs=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f62d051d-b3d9-49d0-aded-87def07af134",
   "metadata": {},
   "source": [
    "### 2.2 for 2050"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "eb74ae6b-ddc1-44e8-bf91-706e9dd9157f",
   "metadata": {},
   "outputs": [],
   "source": [
    "sst_climo2 = sst_2050.groupby(sst_2050.time.dt.month).mean(keep_attrs=True)\n",
    "hmxl_climo2 = hmxl_2050.groupby(hmxl_2050.time.dt.month).mean(keep_attrs=True)\n",
    "taux_climo2 = taux_2050.groupby(taux_2050.time.dt.month).mean(keep_attrs=True)\n",
    "tauy_climo2 = tauy_2050.groupby(tauy_2050.time.dt.month).mean(keep_attrs=True)\n",
    "ssh_climo2 = ssh_2050.groupby(ssh_2050.time.dt.month).mean(keep_attrs=True)\n",
    "evap_climo2 = evap_2050.groupby(evap_2050.time.dt.month).mean(keep_attrs=True)\n",
    "sen_climo2 = sen_2050.groupby(sen_2050.time.dt.month).mean(keep_attrs=True)\n",
    "shf_climo2 = shf_2050.groupby(shf_2050.time.dt.month).mean(keep_attrs=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66ebe37e-7245-4bdd-9975-bb15d57ec5ee",
   "metadata": {},
   "source": [
    "### 2.3 get differences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "3de073f7-2c6e-4e01-9a1c-6a6c728d4439",
   "metadata": {},
   "outputs": [],
   "source": [
    "sst_diff = sst_climo.copy(data=sst_climo2.data - sst_climo.data)\n",
    "hmxl_diff = hmxl_climo.copy(data=hmxl_climo2.data - hmxl_climo.data)\n",
    "taux_diff = taux_climo.copy(data=taux_climo2.data - taux_climo.data)\n",
    "tauy_diff =tauy_climo.copy(data=tauy_climo2.data - tauy_climo.data)\n",
    "ssh_diff = ssh_climo.copy(data=ssh_climo2.data - ssh_climo.data)\n",
    "evap_diff = evap_climo.copy(data=evap_climo2.data - evap_climo.data)\n",
    "sen_diff = sen_climo.copy(data=sen_climo2.data - sen_climo.data)\n",
    "shf_diff = shf_climo.copy(data=shf_climo2.data - shf_climo.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "bb4e0a61-698a-40d9-99a5-d1295091fd46",
   "metadata": {},
   "outputs": [],
   "source": [
    "from cartopy.mpl.gridliner import LongitudeFormatter, LatitudeFormatter\n",
    "import cartopy.feature as cfeature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "a4f5de34-7e60-4eac-9e88-74cfa4c9ad63",
   "metadata": {},
   "outputs": [],
   "source": [
    "## define plotting funcition\n",
    "def var_plot_panels(variable, x, y,u, v, scale, nrows, ncols, i, levels, colormap, title):\n",
    "    ax1= fig.add_subplot(nrows, ncols, i, projection=ccrs.PlateCarree(central_longitude=0))\n",
    "    ax1.add_feature(cfeature.LAND, facecolor='lightgray', zorder=1)\n",
    "    ax1.add_feature(cfeature.COASTLINE, linewidth=0.5, zorder=1)\n",
    "    contour = variable.plot.contourf(ax=ax1,\n",
    "                           transform=ccrs.PlateCarree(),\n",
    "                           levels=levels,\n",
    "                           extend='both',\n",
    "                            cmap = colormap,\n",
    "                           add_colorbar=False,\n",
    "                           add_labels=False,\n",
    "                            zorder=0)\n",
    "\n",
    "    plt.colorbar(contour,\n",
    "                     ax=ax1,\n",
    "#                     ticks=ticks,\n",
    "                     orientation='horizontal',\n",
    "                     pad=0.1,\n",
    "                     drawedges=True,\n",
    "                     shrink=0.9,\n",
    "                     label=variable.units)\n",
    "    \n",
    "    csq = ax1.quiver(x, y, u, v,scale=scale)\n",
    "\n",
    "\n",
    "    gvutil.set_titles_and_labels(ax1,maintitle=title,\n",
    "                             maintitlefontsize=15)\n",
    "    gvutil.set_axes_limits_and_ticks(ax1, xlim=(-160, -110),\n",
    "                                 ylim=(15, 55),\n",
    "                                 xticks=np.linspace(-160, -110, 3),\n",
    "                                 yticks=np.linspace(15, 55, 5))\n",
    "\n",
    "    gvutil.add_major_minor_ticks(ax1, labelsize=12)\n",
    "    gvutil.add_lat_lon_ticklabels(ax1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "02453282-7886-4e48-af7e-bb0a78d7cd39",
   "metadata": {},
   "outputs": [],
   "source": [
    "evap_diff_e5 = evap_diff * 1e5\n",
    "evap_diff_e5 = evap_diff_e5.assign_attrs({'units':evap_diff.units})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "1451ebc5-d084-4411-815d-658ccf4a6a24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x5760 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(20,80))\n",
    "\n",
    "veclon = taux_climo.lon[::3]\n",
    "veclat = taux_climo.lat[::3]\n",
    "\n",
    "taux_space = taux_diff[:,::3,::3].mean('month')\n",
    "tauy_space = tauy_diff[:,::3,::3].mean('month')\n",
    "\n",
    "levels=np.arange(-0.5, 2.1, 0.1)\n",
    "var_plot_panels(sst_diff.sel(month=[1,2,11,12]).mean('month',keep_attrs=True), veclon, veclat, taux_space, tauy_space,5, 8, 3, 1, levels, cmocean.cm.thermal,\"SST diff\")\n",
    "var_plot_panels(shf_diff.sel(month=[1,2,11,12]).mean('month',keep_attrs=True), veclon, veclat, taux_space, tauy_space,5, 8, 3, 2, np.arange(-15, 16, 1), cmocean.cm.balance,\"SHF diff\")\n",
    "var_plot_panels(sen_diff.sel(month=[1,2,11,12]).mean('month',keep_attrs=True), veclon, veclat, taux_space, tauy_space,5, 8, 3, 3, np.arange(-12, 13, 1), cmocean.cm.balance,\"SENH diff\")\n",
    "var_plot_panels(evap_diff_e5.sel(month=[1,2,11,12]).mean('month',keep_attrs=True), veclon, veclat, taux_space, tauy_space,5, 8, 3, 4, np.arange(-1, 1.1, 0.1), cmocean.cm.balance,\"EVAP diff\")\n",
    "var_plot_panels(hmxl_diff.sel(month=[1,2,11,12]).mean('month',keep_attrs=True), veclon, veclat, taux_space, tauy_space,5, 8, 3, 5, np.arange(-2000, 2100, 100), cmocean.cm.balance,\"HMXL diff\")\n",
    "var_plot_panels(ssh_diff.sel(month=[1,2,11,12]).mean('month',keep_attrs=True), veclon, veclat, taux_space, tauy_space,5, 8, 3, 6, np.arange(-12, 13, 1), cmocean.cm.balance,\"SSH diff\")\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "b21b2dc2-a25f-452a-9665-9076fccf345f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2b19c43ab210>"
      ]
     },
     "execution_count": 146,
     "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": [
    "hmxl_diff.sel(month=[1,2,11,12]).mean('month').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "318e7230-17c0-4df4-b2bc-b26aead290cf",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:miniconda3-geocat_env]",
   "language": "python",
   "name": "conda-env-miniconda3-geocat_env-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
}