diff --git a/configs/config-xshield_stellar.yaml b/configs/config-xshield_stellar.yaml
new file mode 100644
index 0000000..82c750d
--- /dev/null
+++ b/configs/config-xshield_stellar.yaml
@@ -0,0 +1,68 @@
+#what kind of directory structure to expect? 
+#For a directory structure like /archive/am5/am5/am5f3b1r0/c96L65_am5f3b1r0_pdclim1850F/gfdl.ncrc5-deploy-prod-openmp/pp
+# the output_path_template is set as follows.
+#We have NA in those values that do not match up with any of the expected headerlist (CSV columns), otherwise we
+#simply specify the associated header name in the appropriate place. E.g. The third directory in the PP path example
+#above is the model (source_id), so the third list value in output_path_template is set to 'source_id'. We make sure
+#this is a valid value in headerlist as well.
+#The fourth directory is am5f3b1r0 which does not map to an existing header value. So we simply NA in output_path_template
+#for the fourth value.
+
+#catalog headers
+#The headerlist is expected column names in your catalog/csv file. This is usually determined by the users in conjuction
+#with the ESM collection specification standards and the appropriate workflows.
+
+# default, failed because standard_name not compatible with X-SHiELD output
+# may be okay with updated diag table that uses cmip variable names
+#headerlist: ["activity_id", "institution_id", "source_id", "experiment_id",
+#                  "frequency", "realm", "table_id",
+#                  "member_id", "grid_label", "variable_id",
+#                  "time_range", "chunk_freq","platform","dimensions","cell_methods","standard_name","path"]
+
+# working prototype v1
+#headerlist: ["activity_id", "institution_id", "source_id", "experiment_id",
+#                  "frequency", "realm", "table_id",
+#                  "member_id", "grid_label", "variable_id",
+#                  "time_range", "chunk_freq","platform","dimensions","cell_methods","path"]
+
+# eliminated some unused headers, but
+# eliminating frequency, realm, table_id, chunk_freq, causes a problem
+# when col.search is called
+headerlist: ["source_id", "experiment_id",
+                  "frequency", "realm", "table_id",
+                  "member_id", "grid_label", "variable_id",
+                  "time_range", "chunk_freq","platform","path"]
+
+#headerlist: ["source_id","platform","activity_id", "experiment_id",
+#                  "frequency", "realm", "table_id",
+#                  "member_id", "grid_label", "variable_id",
+#                  "time_range", "chunk_freq","platform","dimensions","cell_methods","path"]
+
+#output_path_template: ['NA','NA','source_id','platform','activity_id','experiment_id','custom_pp','time_range']
+
+#what kind of directory structure to expect?
+#For a directory structure like /archive/am5/am5/am5f3b1r0/c96L65_am5f3b1r0_pdclim1850F/gfdl.ncrc5-deploy-prod-openmp/pp
+# the output_path_template is set as follows.
+#We have NA in those values that do not match up with any of the expected headerlist (CSV columns), otherwise we
+#simply specify the associated header name in the appropriate place. E.g. The third directory in the PP path example
+#above is the model (source_id), so the third list value in output_path_template is set to 'source_id'. We make sure
+#this is a valid value in headerlist as well.
+#The fourth directory is am5f3b1r0 which does not map to an existing header value. So we simply NA in output_path_template
+#for the fourth value.
+
+output_path_template: ['NA','NA','NA','source_id','platform','member_id','experiment_id','custom_pp','time_range']
+
+output_file_template: ['variable_id','NA']
+
+#OUTPUT FILE INFO is currently passed as command-line argument.
+#We will revisit adding a csvfile, jsonfile and logfile configuration to the builder configuration file in the future.
+#csvfile =  #jsonfile =  #logfile =
+
+#######################################################
+
+# note: this input path is built from softlinks to the directory /scratch/cimes/GLOBALFV3/stellar_run/
+# cp -as /scratch/cimes/GLOBALFV3/stellar_run/processed/  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/processed
+# cp -as /scratch/cimes/GLOBALFV3/stellar_run/processed_new/  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/processed_new
+# this avoids the other directories that contain other experiments that have not been 'processed'
+input_path:  "/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/"
+output_path: "/home/tmerlis/hackathon/catbuild/pire4" # ENTER NAME OF THE CSV AND JSON, THE SUFFIX ALONE. e.g catalog (the builder then generates catalog.csv and catalog.json. This can also be an absolute path)
diff --git a/examples/build_xshield_catalog.ipynb b/examples/build_xshield_catalog.ipynb
new file mode 100644
index 0000000..4fab86f
--- /dev/null
+++ b/examples/build_xshield_catalog.ipynb
@@ -0,0 +1,102 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "2a5a9746-b56f-4462-b938-ae17f7129a8d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import catalogbuilder\n",
+    "from catalogbuilder.scripts import gen_intake_gfdl\n",
+    "import sys, os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1b0f5306-0032-4e0a-8c4a-b5bcb1d2ab7f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#This is an example call to run catalog builder using a yaml config file.\n",
+    "\n",
+    "configyaml = '/home/tmerlis/hackathon/catbuild/config-xshield_stellar.yaml' \n",
+    "# soft link to processed and processed_new **only** from within '/scratch/cimes/GLOBALFV3/stellar_run/' \n",
+    "input_path = '/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/' \n",
+    "output_path = '/home/tmerlis/hackathon/catbuild/xshield_cat' "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e8d89aec-655e-4729-820b-a37ffb60454e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:local:[Mostly] silent log activated\n",
+      "INFO:local:Default schema: catalogbuilder/cats/gfdl_template.json\n",
+      "INFO:local:input path: /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/\n",
+      "INFO:local: output path: /home/tmerlis/hackathon/catbuild/xshield_cat\n",
+      "JSON generated at: /home/tmerlis/hackathon/catbuild/xshield_cat.json\n",
+      "CSV generated at: /home/tmerlis/hackathon/catbuild/xshield_cat.csv\n",
+      "INFO:local:CSV generated at/home/tmerlis/hackathon/catbuild/xshield_cat.csv\n",
+      "CPU times: user 4.76 s, sys: 12.6 s, total: 17.3 s\n",
+      "Wall time: 2min 5s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "def create_catalog_from_config(input_path=input_path,output_path=output_path,configyaml=configyaml):\n",
+    "    csv, json = gen_intake_gfdl.create_catalog(input_path=input_path,output_path=output_path,config=configyaml)\n",
+    "    return(csv,json)\n",
+    "\n",
+    "if __name__ == '__main__':\n",
+    "    create_catalog_from_config(input_path,output_path,configyaml)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "69de4f3a-c622-444f-9bdf-cb3459d3261c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "No traceback available to show.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%tb"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "catalogbuilder [~/.conda/envs/catalogbuilder/]",
+   "language": "python",
+   "name": "conda_catalogbuilder"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/use_xshield_catalog.ipynb b/examples/use_xshield_catalog.ipynb
new file mode 100644
index 0000000..344ff8e
--- /dev/null
+++ b/examples/use_xshield_catalog.ipynb
@@ -0,0 +1,2459 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "23ee3b8c-346d-4ee7-b799-6f8216c24149",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import intake,yaml,os\n",
+    "import intake_esm\n",
+    "import matplotlib\n",
+    "from matplotlib import pyplot as plt\n",
+    "%matplotlib inline\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e2259f47-ef15-45ab-a160-de25296ee9be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# result of build_xshield_cat.ipynb\n",
+    "col_url = \"/home/tmerlis/hackathon/catbuild/xshield_cat.json\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c78e92a7-d6bd-4df5-8fb2-a2f2ecc3e887",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "col = intake.open_esm_datastore(col_url)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b60cb89e-7545-483f-9832-74d717c664a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>source_id</th>\n",
+       "      <th>experiment_id</th>\n",
+       "      <th>frequency</th>\n",
+       "      <th>realm</th>\n",
+       "      <th>table_id</th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>grid_label</th>\n",
+       "      <th>variable_id</th>\n",
+       "      <th>time_range</th>\n",
+       "      <th>chunk_freq</th>\n",
+       "      <th>platform</th>\n",
+       "      <th>path</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C384.L79x2_pire_CO2_1270ppmv</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>v500_C384_1440x720</td>\n",
+       "      <td>2020011300</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C384.L79x2_pire_CO2_1270ppmv</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>u_dt_phys_C384_1440x720</td>\n",
+       "      <td>2020011300</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C384.L79x2_pire_CO2_1270ppmv</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>u_dt_sg_C384_1440x720</td>\n",
+       "      <td>2020011300</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C384.L79x2_pire_CO2_1270ppmv</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>int_tendency_of_air_temperature_due_to_deep_co...</td>\n",
+       "      <td>2020011300</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C384.L79x2_pire_CO2_1270ppmv</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>int_tendency_of_air_temperature_due_to_longwav...</td>\n",
+       "      <td>2020011300</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>299513</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C3072.L79x2_pire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed_new</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>int_u_dt_phys_coarse_C3072_1440x720</td>\n",
+       "      <td>2021081700</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>299514</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C3072.L79x2_pire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed_new</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>omT_coarse_C3072_1440x720</td>\n",
+       "      <td>2021081700</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>299515</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C3072.L79x2_pire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed_new</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>int_tendency_of_air_temperature_due_to_shortwa...</td>\n",
+       "      <td>2021081700</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>299516</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C3072.L79x2_pire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed_new</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>int_tendency_of_specific_humidity_due_to_turbu...</td>\n",
+       "      <td>2021081700</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>299517</th>\n",
+       "      <td>GLOBALFV3</td>\n",
+       "      <td>20191020.00Z.C3072.L79x2_pire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>processed_new</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>t925_coarse_C3072_1440x720</td>\n",
+       "      <td>2021081700</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>stellar_run</td>\n",
+       "      <td>/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>299518 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        source_id                              experiment_id  frequency  \\\n",
+       "0       GLOBALFV3  20191020.00Z.C384.L79x2_pire_CO2_1270ppmv        NaN   \n",
+       "1       GLOBALFV3  20191020.00Z.C384.L79x2_pire_CO2_1270ppmv        NaN   \n",
+       "2       GLOBALFV3  20191020.00Z.C384.L79x2_pire_CO2_1270ppmv        NaN   \n",
+       "3       GLOBALFV3  20191020.00Z.C384.L79x2_pire_CO2_1270ppmv        NaN   \n",
+       "4       GLOBALFV3  20191020.00Z.C384.L79x2_pire_CO2_1270ppmv        NaN   \n",
+       "...           ...                                        ...        ...   \n",
+       "299513  GLOBALFV3              20191020.00Z.C3072.L79x2_pire        NaN   \n",
+       "299514  GLOBALFV3              20191020.00Z.C3072.L79x2_pire        NaN   \n",
+       "299515  GLOBALFV3              20191020.00Z.C3072.L79x2_pire        NaN   \n",
+       "299516  GLOBALFV3              20191020.00Z.C3072.L79x2_pire        NaN   \n",
+       "299517  GLOBALFV3              20191020.00Z.C3072.L79x2_pire        NaN   \n",
+       "\n",
+       "        realm  table_id      member_id  grid_label  \\\n",
+       "0         NaN       NaN      processed         NaN   \n",
+       "1         NaN       NaN      processed         NaN   \n",
+       "2         NaN       NaN      processed         NaN   \n",
+       "3         NaN       NaN      processed         NaN   \n",
+       "4         NaN       NaN      processed         NaN   \n",
+       "...       ...       ...            ...         ...   \n",
+       "299513    NaN       NaN  processed_new         NaN   \n",
+       "299514    NaN       NaN  processed_new         NaN   \n",
+       "299515    NaN       NaN  processed_new         NaN   \n",
+       "299516    NaN       NaN  processed_new         NaN   \n",
+       "299517    NaN       NaN  processed_new         NaN   \n",
+       "\n",
+       "                                              variable_id  time_range  \\\n",
+       "0                                      v500_C384_1440x720  2020011300   \n",
+       "1                                 u_dt_phys_C384_1440x720  2020011300   \n",
+       "2                                   u_dt_sg_C384_1440x720  2020011300   \n",
+       "3       int_tendency_of_air_temperature_due_to_deep_co...  2020011300   \n",
+       "4       int_tendency_of_air_temperature_due_to_longwav...  2020011300   \n",
+       "...                                                   ...         ...   \n",
+       "299513                int_u_dt_phys_coarse_C3072_1440x720  2021081700   \n",
+       "299514                          omT_coarse_C3072_1440x720  2021081700   \n",
+       "299515  int_tendency_of_air_temperature_due_to_shortwa...  2021081700   \n",
+       "299516  int_tendency_of_specific_humidity_due_to_turbu...  2021081700   \n",
+       "299517                         t925_coarse_C3072_1440x720  2021081700   \n",
+       "\n",
+       "        chunk_freq     platform  \\\n",
+       "0              NaN  stellar_run   \n",
+       "1              NaN  stellar_run   \n",
+       "2              NaN  stellar_run   \n",
+       "3              NaN  stellar_run   \n",
+       "4              NaN  stellar_run   \n",
+       "...            ...          ...   \n",
+       "299513         NaN  stellar_run   \n",
+       "299514         NaN  stellar_run   \n",
+       "299515         NaN  stellar_run   \n",
+       "299516         NaN  stellar_run   \n",
+       "299517         NaN  stellar_run   \n",
+       "\n",
+       "                                                     path  \n",
+       "0       /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "1       /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "2       /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "3       /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "4       /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "...                                                   ...  \n",
+       "299513  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "299514  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "299515  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "299516  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "299517  /scratch/cimes/tmerlis/GLOBALFV3/stellar_run/p...  \n",
+       "\n",
+       "[299518 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "col.df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "0ec86ef1-478b-47fa-a110-751507f1e974",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# note member_id is used for the different simulation years that are in the 'processed' and 'processed_new' directories\n",
+    "#cat = col.search(variable_id = 't925_coarse_C3072_1440x720', experiment_id = '20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv', member_id = 'processed')\n",
+    "cat = col.search(variable_id = 't925_coarse_C3072_1440x720', experiment_id = '20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bfdbe249-dc24-4901-939d-666ca83ffb01",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>esm_catalog_ESM4 catalog with 2 dataset(s) from 487 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frequency</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>realm</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time_range</th>\n",
+       "      <td>477</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>chunk_freq</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>platform</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>path</th>\n",
+       "      <td>487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1f27eb85-8ab1-4244-92db-399bb4f8c790",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/scratch/cimes/tmerlis/GLOBALFV3/stellar_run/processed/20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv/pp/2020071400/t925_coarse_C3072_1440x720.fre.nc'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.df['path'][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7f2e7a0f-ca94-4ca1-81a4-8fb78fd7e7b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
+      "\t'source_id.experiment_id.member_id'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
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+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='2' class='' max='2' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [2/2 00:24&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dset_dict = cat.to_dataset_dict(cdf_kwargs={'chunks': {'time':5}, 'decode_times': True})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "1403c046-b980-4d9d-9d8c-6c0eb4582c2f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GLOBALFV3.20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv.processed_new\n",
+      "GLOBALFV3.20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv.processed\n"
+     ]
+    }
+   ],
+   "source": [
+    "for k in dset_dict.keys(): \n",
+    "    print(k)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a2c00574-af0e-473e-9885-a0a60d819137",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# year 1 in ds, year 2 in ds2\n",
+    "ds = dset_dict['GLOBALFV3.20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv.processed']\n",
+    "ds2 = dset_dict['GLOBALFV3.20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv.processed_new']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5e73cd3e-c658-4b6a-8cad-2fe81e34552d",
+   "metadata": {},
+   "outputs": [
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+       "\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-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\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",
+       ".xr-index-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",
+       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-no-icon {\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; Size: 15GB\n",
+       "Dimensions:              (time: 3640, grid_yt_coarse: 720, bnds: 2,\n",
+       "                          grid_xt_coarse: 1440)\n",
+       "Coordinates:\n",
+       "  * time                 (time) object 29kB 2019-10-20 03:00:00 ... 2021-01-1...\n",
+       "  * grid_yt_coarse       (grid_yt_coarse) float32 3kB -89.88 -89.62 ... 89.88\n",
+       "    grid_yt_coarse_bnds  (grid_yt_coarse, bnds) float32 6kB dask.array&lt;chunksize=(720, 2), meta=np.ndarray&gt;\n",
+       "  * grid_xt_coarse       (grid_xt_coarse) float32 6kB 0.125 0.375 ... 359.9\n",
+       "    grid_xt_coarse_bnds  (grid_xt_coarse, bnds) float32 12kB dask.array&lt;chunksize=(1440, 2), meta=np.ndarray&gt;\n",
+       "    t925_coarse          (time, grid_yt_coarse, grid_xt_coarse) float32 15GB dask.array&lt;chunksize=(5, 720, 1440), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    *empty*\n",
+       "Attributes: (12/13)\n",
+       "    title:                           PIRE_production_202103.20191020.00Z.C307...\n",
+       "    grid_type:                       regular\n",
+       "    grid_tile:                       N/A\n",
+       "    code_release_version:            19.1\n",
+       "    git_hash:                        c97c1f6afab0df3545ee82c337d51accc4205bc3\n",
+       "    intake_esm_vars:                 [&#x27;t925_coarse_C3072_1440x720&#x27;]\n",
+       "    ...                              ...\n",
+       "    intake_esm_attrs:experiment_id:  20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO...\n",
+       "    intake_esm_attrs:member_id:      processed\n",
+       "    intake_esm_attrs:variable_id:    t925_coarse_C3072_1440x720\n",
+       "    intake_esm_attrs:platform:       stellar_run\n",
+       "    intake_esm_attrs:_data_format_:  netcdf\n",
+       "    intake_esm_dataset_key:          GLOBALFV3.20191020.00Z.C3072.L79x2_pire_...</pre><div class='xr-wrap' style='display:none'><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-448c8b4f-2323-460b-b678-fb056e704733' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-448c8b4f-2323-460b-b678-fb056e704733' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3640</li><li><span class='xr-has-index'>grid_yt_coarse</span>: 720</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>grid_xt_coarse</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b6bdeafe-c257-42d5-ad85-5dc04e26475d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b6bdeafe-c257-42d5-ad85-5dc04e26475d' 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 class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2019-10-20 03:00:00 ... 2021-01-...</div><input id='attrs-8efd0fc2-660c-4f1d-ad8c-c91fb248bc2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8efd0fc2-660c-4f1d-ad8c-c91fb248bc2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a89e7be1-1110-4e66-802f-2f51d42967f2' class='xr-var-data-in' type='checkbox'><label for='data-a89e7be1-1110-4e66-802f-2f51d42967f2' 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>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeJulian(2019, 10, 20, 3, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 6, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 9, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 18, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 21, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 17, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>grid_yt_coarse</span></div><div class='xr-var-dims'>(grid_yt_coarse)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.88 -89.62 ... 89.62 89.88</div><input id='attrs-e724e470-1087-4aba-8b94-d5feaadf2652' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e724e470-1087-4aba-8b94-d5feaadf2652' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba7bd940-bafa-413c-a5b2-5b5ff0b032da' class='xr-var-data-in' type='checkbox'><label for='data-ba7bd940-bafa-413c-a5b2-5b5ff0b032da' 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>index</dd><dt><span>long_name :</span></dt><dd>y-index of cell center points</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>grid_yt_coarse_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-89.875, -89.625, -89.375, ...,  89.375,  89.625,  89.875],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>grid_yt_coarse_bnds</span></div><div class='xr-var-dims'>(grid_yt_coarse, bnds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(720, 2), meta=np.ndarray&gt;</div><input id='attrs-7a58a8ae-fb96-4df6-b237-068bb7976b87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a58a8ae-fb96-4df6-b237-068bb7976b87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfbaf255-3f03-4107-b455-40da78ffbdde' class='xr-var-data-in' type='checkbox'><label for='data-cfbaf255-3f03-4107-b455-40da78ffbdde' 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>index</dd><dt><span>long_name :</span></dt><dd>y-index of cell center points</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 5.62 kiB </td>\n",
+       "                        <td> 5.62 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (720, 2) </td>\n",
+       "                        <td> (720, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 1450 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">720</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>grid_xt_coarse</span></div><div class='xr-var-dims'>(grid_xt_coarse)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 359.6 359.9</div><input id='attrs-79c3cf22-1e4d-4d80-be7e-b0aaad45df7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79c3cf22-1e4d-4d80-be7e-b0aaad45df7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79738041-3eb7-4321-a6c0-62b19253a0c8' class='xr-var-data-in' type='checkbox'><label for='data-79738041-3eb7-4321-a6c0-62b19253a0c8' 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>index</dd><dt><span>long_name :</span></dt><dd>x-index of cell center points</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>grid_xt_coarse_bnds</dd></dl></div><div class='xr-var-data'><pre>array([1.25000e-01, 3.75000e-01, 6.25000e-01, ..., 3.59375e+02, 3.59625e+02,\n",
+       "       3.59875e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>grid_xt_coarse_bnds</span></div><div class='xr-var-dims'>(grid_xt_coarse, bnds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1440, 2), meta=np.ndarray&gt;</div><input id='attrs-e1f556d5-97a5-4d54-a398-3fb538b72b9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1f556d5-97a5-4d54-a398-3fb538b72b9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cbe4c4b-e191-4a28-ae71-eb92fd3cdeea' class='xr-var-data-in' type='checkbox'><label for='data-9cbe4c4b-e191-4a28-ae71-eb92fd3cdeea' 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>index</dd><dt><span>long_name :</span></dt><dd>x-index of cell center points</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 11.25 kiB </td>\n",
+       "                        <td> 11.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1440, 2) </td>\n",
+       "                        <td> (1440, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 1450 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1440</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t925_coarse</span></div><div class='xr-var-dims'>(time, grid_yt_coarse, grid_xt_coarse)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(5, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-80f8c96f-ec61-40b1-90c5-785424e7028a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80f8c96f-ec61-40b1-90c5-785424e7028a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b8369a8-bd9a-4e24-88b8-493006f8c7a4' class='xr-var-data-in' type='checkbox'><label for='data-0b8369a8-bd9a-4e24-88b8-493006f8c7a4' 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>K</dd><dt><span>long_name :</span></dt><dd>coarse-grained 925-mb temperature</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>conserve_order1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 14.06 GiB </td>\n",
+       "                        <td> 19.78 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "                        <th> Dask graph </th>\n",
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+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2969e196-d8f8-4072-aa4a-cb6e0e2234ae' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2969e196-d8f8-4072-aa4a-cb6e0e2234ae' class='xr-section-summary'  title='Expand/collapse section'>Data variables: <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-03469d81-0dbb-4544-a1e1-0142f7618ebc' class='xr-section-summary-in' type='checkbox'  ><label for='section-03469d81-0dbb-4544-a1e1-0142f7618ebc' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-26940fe1-e2ec-47ff-81ea-c75b37a70030' class='xr-index-data-in' type='checkbox'/><label for='index-26940fe1-e2ec-47ff-81ea-c75b37a70030' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2019-10-20 03:00:00, 2019-10-20 06:00:00, 2019-10-20 09:00:00,\n",
+       "             2019-10-20 12:00:00, 2019-10-20 15:00:00, 2019-10-20 18:00:00,\n",
+       "             2019-10-20 21:00:00, 2019-10-21 00:00:00, 2019-10-21 03:00:00,\n",
+       "             2019-10-21 06:00:00,\n",
+       "             ...\n",
+       "             2021-01-15 21:00:00, 2021-01-16 00:00:00, 2021-01-16 03:00:00,\n",
+       "             2021-01-16 06:00:00, 2021-01-16 09:00:00, 2021-01-16 12:00:00,\n",
+       "             2021-01-16 15:00:00, 2021-01-16 18:00:00, 2021-01-16 21:00:00,\n",
+       "             2021-01-17 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=3640, calendar=&#x27;julian&#x27;, freq=&#x27;3h&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>grid_yt_coarse</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-24092239-be0c-495a-930d-b82eb68856c4' class='xr-index-data-in' type='checkbox'/><label for='index-24092239-be0c-495a-930d-b82eb68856c4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n",
+       "       -87.875, -87.625,\n",
+       "       ...\n",
+       "        87.625,  87.875,  88.125,  88.375,  88.625,  88.875,  89.125,  89.375,\n",
+       "        89.625,  89.875],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;grid_yt_coarse&#x27;, length=720))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>grid_xt_coarse</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-df013707-d2e2-4695-9bf2-524af3f19e64' class='xr-index-data-in' type='checkbox'/><label for='index-df013707-d2e2-4695-9bf2-524af3f19e64' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.125,   0.375,   0.625,   0.875,   1.125,   1.375,   1.625,   1.875,\n",
+       "         2.125,   2.375,\n",
+       "       ...\n",
+       "       357.625, 357.875, 358.125, 358.375, 358.625, 358.875, 359.125, 359.375,\n",
+       "       359.625, 359.875],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;grid_xt_coarse&#x27;, length=1440))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-220a3112-4a54-4e5e-bb34-f88e172bac84' class='xr-section-summary-in' type='checkbox'  ><label for='section-220a3112-4a54-4e5e-bb34-f88e172bac84' class='xr-section-summary' >Attributes: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>PIRE_production_202103.20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>code_release_version :</span></dt><dd>19.1</dd><dt><span>git_hash :</span></dt><dd>c97c1f6afab0df3545ee82c337d51accc4205bc3</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;t925_coarse_C3072_1440x720&#x27;]</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>GLOBALFV3</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>processed</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>t925_coarse_C3072_1440x720</dd><dt><span>intake_esm_attrs:platform :</span></dt><dd>stellar_run</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>netcdf</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>GLOBALFV3.20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO2_1270ppmv.processed</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 15GB\n",
+       "Dimensions:              (time: 3640, grid_yt_coarse: 720, bnds: 2,\n",
+       "                          grid_xt_coarse: 1440)\n",
+       "Coordinates:\n",
+       "  * time                 (time) object 29kB 2019-10-20 03:00:00 ... 2021-01-1...\n",
+       "  * grid_yt_coarse       (grid_yt_coarse) float32 3kB -89.88 -89.62 ... 89.88\n",
+       "    grid_yt_coarse_bnds  (grid_yt_coarse, bnds) float32 6kB dask.array<chunksize=(720, 2), meta=np.ndarray>\n",
+       "  * grid_xt_coarse       (grid_xt_coarse) float32 6kB 0.125 0.375 ... 359.9\n",
+       "    grid_xt_coarse_bnds  (grid_xt_coarse, bnds) float32 12kB dask.array<chunksize=(1440, 2), meta=np.ndarray>\n",
+       "    t925_coarse          (time, grid_yt_coarse, grid_xt_coarse) float32 15GB dask.array<chunksize=(5, 720, 1440), meta=np.ndarray>\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    *empty*\n",
+       "Attributes: (12/13)\n",
+       "    title:                           PIRE_production_202103.20191020.00Z.C307...\n",
+       "    grid_type:                       regular\n",
+       "    grid_tile:                       N/A\n",
+       "    code_release_version:            19.1\n",
+       "    git_hash:                        c97c1f6afab0df3545ee82c337d51accc4205bc3\n",
+       "    intake_esm_vars:                 ['t925_coarse_C3072_1440x720']\n",
+       "    ...                              ...\n",
+       "    intake_esm_attrs:experiment_id:  20191020.00Z.C3072.L79x2_pire_PLUS_4K_CO...\n",
+       "    intake_esm_attrs:member_id:      processed\n",
+       "    intake_esm_attrs:variable_id:    t925_coarse_C3072_1440x720\n",
+       "    intake_esm_attrs:platform:       stellar_run\n",
+       "    intake_esm_attrs:_data_format_:  netcdf\n",
+       "    intake_esm_dataset_key:          GLOBALFV3.20191020.00Z.C3072.L79x2_pire_..."
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
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+  {
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+   "execution_count": 12,
+   "id": "2f22d787-7d0e-47c2-b347-3e7046ef8fdb",
+   "metadata": {},
+   "outputs": [
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+       "}\n",
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+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
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+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
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+       "\n",
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+       "\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",
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+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
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+       "\n",
+       ".xr-section-summary,\n",
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+       "  padding-bottom: 4px;\n",
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+       "\n",
+       ".xr-array-wrap {\n",
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+       "  display: grid;\n",
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+       ".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",
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+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
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+       "  list-style: none;\n",
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+       "}\n",
+       "\n",
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+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
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+       "  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",
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+       ".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",
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+       "}\n",
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+       "  color: var(--xr-font-color2);\n",
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+       "\n",
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+       ".xr-var-dims,\n",
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+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
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+       "  overflow: visible;\n",
+       "  width: auto;\n",
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+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-no-icon {\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 &#x27;time&#x27; (time: 3640)&gt; Size: 29kB\n",
+       "array([cftime.DatetimeJulian(2019, 10, 20, 3, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 6, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 9, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 18, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 21, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 17, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)\n",
+       "Coordinates:\n",
+       "  * time     (time) object 29kB 2019-10-20 03:00:00 ... 2021-01-17 00:00:00\n",
+       "Attributes:\n",
+       "    long_name:      time\n",
+       "    axis:           T\n",
+       "    calendar_type:  JULIAN</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3640</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9230c195-e9c3-4ba6-9320-3a3d26fa85b2' class='xr-array-in' type='checkbox' checked><label for='section-9230c195-e9c3-4ba6-9320-3a3d26fa85b2' 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>2019-10-20 03:00:00 2019-10-20 06:00:00 ... 2021-01-17 00:00:00</span></div><div class='xr-array-data'><pre>array([cftime.DatetimeJulian(2019, 10, 20, 3, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 6, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 9, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 18, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 21, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 17, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)</pre></div></div></li><li class='xr-section-item'><input id='section-33601805-5311-448d-b7d6-dd266cb5ce35' class='xr-section-summary-in' type='checkbox'  checked><label for='section-33601805-5311-448d-b7d6-dd266cb5ce35' 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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2019-10-20 03:00:00 ... 2021-01-...</div><input id='attrs-c7014434-d894-42be-9e38-c40d3709f98e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7014434-d894-42be-9e38-c40d3709f98e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf3275f9-19a1-4c8b-8af2-9280b255f16a' class='xr-var-data-in' type='checkbox'><label for='data-bf3275f9-19a1-4c8b-8af2-9280b255f16a' 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>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeJulian(2019, 10, 20, 3, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 6, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 9, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 18, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 21, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 17, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4802ab7-ebb6-4938-bf83-4362f469019d' class='xr-section-summary-in' type='checkbox'  ><label for='section-f4802ab7-ebb6-4938-bf83-4362f469019d' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5fe53789-d82f-4005-8ac0-9ae8e9896e3d' class='xr-index-data-in' type='checkbox'/><label for='index-5fe53789-d82f-4005-8ac0-9ae8e9896e3d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2019-10-20 03:00:00, 2019-10-20 06:00:00, 2019-10-20 09:00:00,\n",
+       "             2019-10-20 12:00:00, 2019-10-20 15:00:00, 2019-10-20 18:00:00,\n",
+       "             2019-10-20 21:00:00, 2019-10-21 00:00:00, 2019-10-21 03:00:00,\n",
+       "             2019-10-21 06:00:00,\n",
+       "             ...\n",
+       "             2021-01-15 21:00:00, 2021-01-16 00:00:00, 2021-01-16 03:00:00,\n",
+       "             2021-01-16 06:00:00, 2021-01-16 09:00:00, 2021-01-16 12:00:00,\n",
+       "             2021-01-16 15:00:00, 2021-01-16 18:00:00, 2021-01-16 21:00:00,\n",
+       "             2021-01-17 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=3640, calendar=&#x27;julian&#x27;, freq=&#x27;3h&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ff355a5-8ff7-429e-8dc9-2553b47b4c8d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2ff355a5-8ff7-429e-8dc9-2553b47b4c8d' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'time' (time: 3640)> Size: 29kB\n",
+       "array([cftime.DatetimeJulian(2019, 10, 20, 3, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 6, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 9, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 18, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 21, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 17, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)\n",
+       "Coordinates:\n",
+       "  * time     (time) object 29kB 2019-10-20 03:00:00 ... 2021-01-17 00:00:00\n",
+       "Attributes:\n",
+       "    long_name:      time\n",
+       "    axis:           T\n",
+       "    calendar_type:  JULIAN"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds.time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "c31565a4-438f-463d-a997-49834c6a3279",
+   "metadata": {},
+   "outputs": [
+    {
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+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\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 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\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:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\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-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\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",
+       ".xr-index-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",
+       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-no-icon {\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 &#x27;t925_coarse&#x27; (time: 3640, grid_yt_coarse: 720,\n",
+       "                                 grid_xt_coarse: 1440)&gt; Size: 15GB\n",
+       "dask.array&lt;concatenate, shape=(3640, 720, 1440), dtype=float32, chunksize=(5, 720, 1440), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * time            (time) object 29kB 2019-10-20 03:00:00 ... 2021-01-17 00:...\n",
+       "  * grid_yt_coarse  (grid_yt_coarse) float32 3kB -89.88 -89.62 ... 89.62 89.88\n",
+       "  * grid_xt_coarse  (grid_xt_coarse) float32 6kB 0.125 0.375 ... 359.6 359.9\n",
+       "    t925_coarse     (time, grid_yt_coarse, grid_xt_coarse) float32 15GB dask.array&lt;chunksize=(5, 720, 1440), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    units:          K\n",
+       "    long_name:      coarse-grained 925-mb temperature\n",
+       "    cell_methods:   time: point\n",
+       "    interp_method:  conserve_order1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'t925_coarse'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3640</li><li><span class='xr-has-index'>grid_yt_coarse</span>: 720</li><li><span class='xr-has-index'>grid_xt_coarse</span>: 1440</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a7a8f2e2-848f-4681-b104-4c126902c34a' class='xr-array-in' type='checkbox' checked><label for='section-a7a8f2e2-848f-4681-b104-4c126902c34a' 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>dask.array&lt;chunksize=(5, 720, 1440), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 14.06 GiB </td>\n",
+       "                        <td> 19.78 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3640, 720, 1440) </td>\n",
+       "                        <td> (5, 720, 1440) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 828 chunks in 583 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-10c30178-6b66-47b4-b7b9-9da04a72aa08' class='xr-section-summary-in' type='checkbox'  checked><label for='section-10c30178-6b66-47b4-b7b9-9da04a72aa08' class='xr-section-summary' >Coordinates: <span>(4)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2019-10-20 03:00:00 ... 2021-01-...</div><input id='attrs-7d224fed-d604-4f38-af45-7a8bd36a52e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d224fed-d604-4f38-af45-7a8bd36a52e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3be65a34-7682-4fa3-95ad-4cd7efc6b202' class='xr-var-data-in' type='checkbox'><label for='data-3be65a34-7682-4fa3-95ad-4cd7efc6b202' 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>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeJulian(2019, 10, 20, 3, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 6, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2019, 10, 20, 9, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 18, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 16, 21, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeJulian(2021, 1, 17, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>grid_yt_coarse</span></div><div class='xr-var-dims'>(grid_yt_coarse)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.88 -89.62 ... 89.62 89.88</div><input id='attrs-1259f251-2fd5-4e81-9458-2ce092775869' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1259f251-2fd5-4e81-9458-2ce092775869' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-433e9c72-77a8-4404-87b5-587ec8c9a945' class='xr-var-data-in' type='checkbox'><label for='data-433e9c72-77a8-4404-87b5-587ec8c9a945' 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>index</dd><dt><span>long_name :</span></dt><dd>y-index of cell center points</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>grid_yt_coarse_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-89.875, -89.625, -89.375, ...,  89.375,  89.625,  89.875],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>grid_xt_coarse</span></div><div class='xr-var-dims'>(grid_xt_coarse)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 359.6 359.9</div><input id='attrs-8cd05db4-b6b2-4e7f-b527-3e8caa458a1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cd05db4-b6b2-4e7f-b527-3e8caa458a1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c9c32f1-df1a-4d52-bcdb-d791626c7e26' class='xr-var-data-in' type='checkbox'><label for='data-3c9c32f1-df1a-4d52-bcdb-d791626c7e26' 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>index</dd><dt><span>long_name :</span></dt><dd>x-index of cell center points</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>grid_xt_coarse_bnds</dd></dl></div><div class='xr-var-data'><pre>array([1.25000e-01, 3.75000e-01, 6.25000e-01, ..., 3.59375e+02, 3.59625e+02,\n",
+       "       3.59875e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t925_coarse</span></div><div class='xr-var-dims'>(time, grid_yt_coarse, grid_xt_coarse)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(5, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-ee990b3e-7fd7-40f4-ab31-08afbc8f9383' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee990b3e-7fd7-40f4-ab31-08afbc8f9383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39eb0455-33fd-4379-9282-83ba249b7954' class='xr-var-data-in' type='checkbox'><label for='data-39eb0455-33fd-4379-9282-83ba249b7954' 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>K</dd><dt><span>long_name :</span></dt><dd>coarse-grained 925-mb temperature</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>conserve_order1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 14.06 GiB </td>\n",
+       "                        <td> 19.78 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3640, 720, 1440) </td>\n",
+       "                        <td> (5, 720, 1440) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 828 chunks in 583 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"178\" height=\"162\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"104.324499\" y=\"132.551296\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
+       "  <text x=\"148.060763\" y=\"91.569765\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,148.060763,91.569765)\">720</text>\n",
+       "  <text x=\"35.294118\" y=\"97.257178\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,97.257178)\">3640</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f52ca922-802b-4bac-b1a0-7639578ab6dd' class='xr-section-summary-in' type='checkbox'  ><label for='section-f52ca922-802b-4bac-b1a0-7639578ab6dd' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dd8f0385-fd1b-4a73-ba84-79774890b915' class='xr-index-data-in' type='checkbox'/><label for='index-dd8f0385-fd1b-4a73-ba84-79774890b915' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2019-10-20 03:00:00, 2019-10-20 06:00:00, 2019-10-20 09:00:00,\n",
+       "             2019-10-20 12:00:00, 2019-10-20 15:00:00, 2019-10-20 18:00:00,\n",
+       "             2019-10-20 21:00:00, 2019-10-21 00:00:00, 2019-10-21 03:00:00,\n",
+       "             2019-10-21 06:00:00,\n",
+       "             ...\n",
+       "             2021-01-15 21:00:00, 2021-01-16 00:00:00, 2021-01-16 03:00:00,\n",
+       "             2021-01-16 06:00:00, 2021-01-16 09:00:00, 2021-01-16 12:00:00,\n",
+       "             2021-01-16 15:00:00, 2021-01-16 18:00:00, 2021-01-16 21:00:00,\n",
+       "             2021-01-17 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=3640, calendar=&#x27;julian&#x27;, freq=&#x27;3h&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>grid_yt_coarse</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-886f3df6-536c-4ab8-9bde-034c1374def4' class='xr-index-data-in' type='checkbox'/><label for='index-886f3df6-536c-4ab8-9bde-034c1374def4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.875, -89.625, -89.375, -89.125, -88.875, -88.625, -88.375, -88.125,\n",
+       "       -87.875, -87.625,\n",
+       "       ...\n",
+       "        87.625,  87.875,  88.125,  88.375,  88.625,  88.875,  89.125,  89.375,\n",
+       "        89.625,  89.875],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;grid_yt_coarse&#x27;, length=720))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>grid_xt_coarse</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2c3b5593-5106-401f-afa7-153ce8c2d9fc' class='xr-index-data-in' type='checkbox'/><label for='index-2c3b5593-5106-401f-afa7-153ce8c2d9fc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.125,   0.375,   0.625,   0.875,   1.125,   1.375,   1.625,   1.875,\n",
+       "         2.125,   2.375,\n",
+       "       ...\n",
+       "       357.625, 357.875, 358.125, 358.375, 358.625, 358.875, 359.125, 359.375,\n",
+       "       359.625, 359.875],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;grid_xt_coarse&#x27;, length=1440))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e2cbaaef-0d9b-42eb-bafc-77ceae98ea65' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2cbaaef-0d9b-42eb-bafc-77ceae98ea65' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>coarse-grained 925-mb temperature</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>conserve_order1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 't925_coarse' (time: 3640, grid_yt_coarse: 720,\n",
+       "                                 grid_xt_coarse: 1440)> Size: 15GB\n",
+       "dask.array<concatenate, shape=(3640, 720, 1440), dtype=float32, chunksize=(5, 720, 1440), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * time            (time) object 29kB 2019-10-20 03:00:00 ... 2021-01-17 00:...\n",
+       "  * grid_yt_coarse  (grid_yt_coarse) float32 3kB -89.88 -89.62 ... 89.62 89.88\n",
+       "  * grid_xt_coarse  (grid_xt_coarse) float32 6kB 0.125 0.375 ... 359.6 359.9\n",
+       "    t925_coarse     (time, grid_yt_coarse, grid_xt_coarse) float32 15GB dask.array<chunksize=(5, 720, 1440), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    units:          K\n",
+       "    long_name:      coarse-grained 925-mb temperature\n",
+       "    cell_methods:   time: point\n",
+       "    interp_method:  conserve_order1"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds.t925_coarse"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "01a873d4-b212-4447-9ec4-62c8ad8680a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 1.85 s, sys: 1.16 s, total: 3.01 s\n",
+      "Wall time: 7.08 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# monthly mean over May, where the chunking of the nc files is irregular\n",
+    "ds.t925_coarse.sel(time=slice('2020-05-01', '2020-05-31')).mean(dim='time').plot()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "6b3b80f3-fc78-4e5e-bff7-e494f37e4d7b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 3.09 s, sys: 1.06 s, total: 4.15 s\n",
+      "Wall time: 8.69 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# difference between year 1 May and year 2 May\n",
+    "(ds.t925_coarse.sel(time=slice('2020-05-01', '2020-05-31')).mean(dim='time') - ds2.t925_coarse.sel(time=slice('2021-05-01', '2021-05-31')).mean(dim='time') ).plot()\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "catalogbuilder [~/.conda/envs/catalogbuilder/]",
+   "language": "python",
+   "name": "conda_catalogbuilder"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}