diff --git a/data_pre_processing.ipynb b/data_pre_processing.ipynb
index 04fe864..0d48f0b 100644
--- a/data_pre_processing.ipynb
+++ b/data_pre_processing.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "7be84f55-a429-467a-b01a-fd64cc949edb",
    "metadata": {},
    "outputs": [],
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 43,
    "id": "8aafdcf1-df25-4b8d-8ec1-6b43a186672a",
    "metadata": {},
    "outputs": [],
@@ -60,8 +60,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "f4701774-c590-40cd-a550-de635d96ae07",
+   "execution_count": 15,
+   "id": "a754c167-ea55-460c-bb56-25e0c9964f3d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 16,
    "id": "81039646-9085-4061-bbea-65bbfba3c74d",
    "metadata": {},
    "outputs": [],
@@ -138,7 +138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 17,
    "id": "1426df34-d486-4cfe-91a4-8d7d213c459a",
    "metadata": {},
    "outputs": [],
@@ -165,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 18,
    "id": "9dbbb757-c1b1-4924-a055-178506e23330",
    "metadata": {},
    "outputs": [],
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 3,
    "id": "05af817e-923b-4356-8ad3-21bc81c51ae8",
    "metadata": {},
    "outputs": [],
@@ -209,12 +209,63 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 6,
    "id": "14d2024b-13b9-42ae-a063-ac5bc94d6cd5",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "masked_array(\n",
+       "  data=[[246.4697 , 246.4697 , 246.4697 , ..., 246.4697 , 246.4697 ,\n",
+       "         246.4697 ],\n",
+       "        [247.39708, 247.33827, 247.28154, ..., 247.57051, 247.51707,\n",
+       "         247.45937],\n",
+       "        [248.11905, 248.00008, 247.88597, ..., 248.44518, 248.33568,\n",
+       "         248.23036],\n",
+       "        ...,\n",
+       "        [242.17198, 242.29324, 242.40303, ..., 241.7135 , 241.89888,\n",
+       "         242.02023],\n",
+       "        [241.2053 , 241.24907, 241.28726, ..., 241.02998, 241.06673,\n",
+       "         241.13202],\n",
+       "        [240.66132, 240.66132, 240.66132, ..., 240.66132, 240.66132,\n",
+       "         240.66132]],\n",
+       "  mask=False,\n",
+       "  fill_value=1e+20,\n",
+       "  dtype=float32)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n",
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n",
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n",
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n",
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n",
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n"
+     ]
+    }
+   ],
    "source": [
-    "# cube_esm1_5"
+    "cube_esm1_5"
    ]
   },
   {
@@ -493,42 +544,74 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "021ad0d0-4338-4bf6-b6a0-accde93b86b4",
+   "execution_count": 4,
+   "id": "9ea9db9a-f637-4d07-967c-a2cdb900d827",
    "metadata": {},
    "outputs": [],
    "source": [
-    "## "
+    "# def calc_trend(xarr, start,end,length):\n",
+    "#     #loop over years\n",
+    "#     for i in np.arange(start,end,1):\n",
+    "#         startyear=i\n",
+    "#         endyear=i+length\n",
+    "#         #extract window\n",
+    "#         arr = xarr.sel(year=slice(str(startyear),str(endyear)))\n",
+    "    \n",
+    "#         timedim=np.arange(0,len(arr.year))\n",
+    "#         arr['year'] = timedim\n",
+    "#         #call polyfit to calculate trend over the window. multiply by 10 so we get units of trend per decade\n",
+    "#         trnd = ((arr.polyfit(dim='year',deg=1,skipna=True)).polyfit_coefficients.isel(degree=0))*10\n",
+    " \n",
+    "#         #if it's the first year, copy the trend to trnarr\n",
+    "#         if i == start:\n",
+    "#             trnarr = trnd\n",
+    "#         #if it's the subsequent years, concatenate the trend to trnarr\n",
+    "#         else:\n",
+    "#             trnarr = xr.concat([trnarr,trnd],dim='year')\n",
+    "\n",
+    "#     trnarr['year'] = np.arange(start,end,1)\n",
+    "\n",
+    "#     return trnarr"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "9ea9db9a-f637-4d07-967c-a2cdb900d827",
+   "execution_count": 7,
+   "id": "021ad0d0-4338-4bf6-b6a0-accde93b86b4",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def calc_trend(xarr, start,end,length):\n",
-    "    #loop over years\n",
-    "    for i in np.arange(start,end,1):\n",
-    "        startyear=i\n",
-    "        endyear=i+length\n",
-    "        #extract window\n",
-    "        arr = xarr.sel(year=slice(str(startyear),str(endyear)))\n",
+    "##  updated calc trend 6/02/26\n",
+    "def calc_trend(xarr, start, end, length):\n",
+    "    \"\"\"\n",
+    "    Compute running linear trends over windows of size `length` (years)\n",
+    "    from `start` to `end - 1`, returning trend per decade.\n",
+    "\n",
+    "    xarr must have a coordinate \"year\".\n",
+    "    \"\"\"\n",
     "    \n",
-    "        timedim=np.arange(0,len(arr.year))\n",
-    "        arr['year'] = timedim\n",
-    "        #call polyfit to calculate trend over the window. multiply by 10 so we get units of trend per decade\n",
-    "        trnd = ((arr.polyfit(dim='year',deg=1,skipna=True)).polyfit_coefficients.isel(degree=0))*10\n",
-    " \n",
-    "        #if it's the first year, copy the trend to trnarr\n",
-    "        if i == start:\n",
-    "            trnarr = trnd\n",
-    "        #if it's the subsequent years, concatenate the trend to trnarr\n",
-    "        else:\n",
-    "            trnarr = xr.concat([trnarr,trnd],dim='year')\n",
+    "    trend_list = []\n",
+    "\n",
+    "    for yr in range(start, end):\n",
+    "        # window\n",
+    "        win = xarr.sel(year=slice(str(yr), str(yr + length-1)))\n",
+    "\n",
+    "        # replace year coordinate with integers 0..N-1 for polyfit\n",
+    "        t = np.arange(win.year.size)\n",
+    "        win = win.assign_coords(year=t)\n",
+    "\n",
+    "        # polyfit: slope * 10 for trend per decade\n",
+    "        tr = (win.polyfit(dim=\"year\", deg=1, skipna=True)\n",
+    "                 .polyfit_coefficients\n",
+    "                 .isel(degree=0) * 10)\n",
+    "        \n",
+    "        trend_list.append(tr)\n",
     "\n",
-    "    trnarr['year'] = np.arange(start,end,1)\n",
+    "    # concatenate trends along a new \"year\" dimension\n",
+    "    trnarr = xr.concat(trend_list, dim=\"year\")\n",
+    "\n",
+    "    # restore actual years\n",
+    "    trnarr = trnarr.assign_coords(year=np.arange(start, end))\n",
     "\n",
     "    return trnarr"
    ]
@@ -548,7 +631,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "id": "714ca1de-2063-4cca-9ee6-1dcb421f4ee7",
    "metadata": {},
    "outputs": [],
@@ -588,11 +671,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 9,
    "id": "8565ae54-f3fa-4bfa-a16c-b10bcb55f755",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
+      "cannot be safely cast to variable data type\n",
+      "  var = variable[keys]\n"
+     ]
+    }
+   ],
    "source": [
+    "\n",
     "pre_processing_trend_write(cube_esm1_5,\"ACCESS_ESM1_5\", output_path=\"/g/data/kj13/datasets/visualisation_projects/uncharted_future/trend\")    "
    ]
   },
@@ -648,43 +742,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "id": "84001a80-ec2e-4503-b725-1bd7afea0a5a",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n",
-      "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/iris/fileformats/netcdf/_thread_safe_nc.py:340: UserWarning: WARNING: missing_value not used since it\n",
-      "cannot be safely cast to variable data type\n",
-      "  var = variable[keys]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "path=\"/g/data/kj13/datasets/visualisation_projects/uncharted_future/trend\"\n",
+    "\n",
     "dataset_list={\n",
     "    \"CESM2\":cube_cesm2,\n",
     "    \"NORESM2\":cube_noresm2,\n",
@@ -1486,11 +1550,1787 @@
     "path=\"/g/data/kj13/datasets/visualisation_projects/uncharted_future/Rolling_SSTA/\"\n",
     "pre_processing_SSTA_annually_rolling_write_ear5_monthly(cube_era5, \"ERA5-025\", output_path=path, start_year=\"1959\", end_year=\"2009\")"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c6bd1d3b-8cb2-4d96-8d85-bd56e34b8f3b",
+   "metadata": {},
+   "source": [
+    "### mean for multiple model trends"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "5762d47b-17e7-4311-a5bf-2301553342b4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "}\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",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\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) !important;\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",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\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",
+       "  border-color: var(--xr-background-color-row-even);\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",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\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-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\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",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 420MB\n",
+       "Dimensions:                (lon: 360, lat: 180, year: 54)\n",
+       "Coordinates:\n",
+       "  * lon                    (lon) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5\n",
+       "  * lat                    (lat) float64 1kB -89.5 -88.5 -87.5 ... 88.5 89.5\n",
+       "  * year                   (year) int64 432B 2015 2016 2017 ... 2066 2067 2068\n",
+       "    degree                 int64 8B 1\n",
+       "Data variables: (12/15)\n",
+       "    ACCESS-CM2ssp370       (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    ACCESS-ESM1-5ssp370    (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    BCC-CSM2-MRssp370      (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    CAS-ESM2-0ssp370       (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    CESM2-WACCMssp370      (year, lat, lon) float64 28MB dask.array&lt;chunksize=(9, 180, 360), meta=np.ndarray&gt;\n",
+       "    CMCC-CM2-SR5ssp370     (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    ...                     ...\n",
+       "    MIROC6ssp370           (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    MPI-ESM-1-2-HAMssp370  (year, lat, lon) float64 28MB dask.array&lt;chunksize=(9, 180, 360), meta=np.ndarray&gt;\n",
+       "    MRI-ESM2-0ssp370       (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    NorESM2-LMssp370       (year, lat, lon) float64 28MB dask.array&lt;chunksize=(8, 180, 360), meta=np.ndarray&gt;\n",
+       "    NorESM2-MMssp370       (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;\n",
+       "    TaiESM1ssp370          (year, lat, lon) float64 28MB dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</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-edf56101-cd33-4826-b4d7-664af53e481c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-edf56101-cd33-4826-b4d7-664af53e481c' 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'>lon</span>: 360</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>year</span>: 54</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8c8a86c5-5b73-4b08-bae8-dc426a35f34e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c8a86c5-5b73-4b08-bae8-dc426a35f34e' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-c7ac2a91-e6ad-4558-89d2-ba06fdbe68d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7ac2a91-e6ad-4558-89d2-ba06fdbe68d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f84b3efc-5cbd-4023-a93e-92992bdf98bd' class='xr-var-data-in' type='checkbox'><label for='data-f84b3efc-5cbd-4023-a93e-92992bdf98bd' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-287e368b-6ab2-4dfd-9851-4d4ceea7f0ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-287e368b-6ab2-4dfd-9851-4d4ceea7f0ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a30cf8f5-9007-454b-bea9-153e87364c07' class='xr-var-data-in' type='checkbox'><label for='data-a30cf8f5-9007-454b-bea9-153e87364c07' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>2015 2016 2017 ... 2066 2067 2068</div><input id='attrs-7ca0d7c0-7e98-48f2-9c83-edad5ce7e350' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ca0d7c0-7e98-48f2-9c83-edad5ce7e350' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8fa7edb-908b-4e70-992d-b13a6737ca5c' class='xr-var-data-in' type='checkbox'><label for='data-b8fa7edb-908b-4e70-992d-b13a6737ca5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026,\n",
+       "       2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038,\n",
+       "       2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050,\n",
+       "       2051, 2052, 2053, 2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062,\n",
+       "       2063, 2064, 2065, 2066, 2067, 2068])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>degree</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-6df1f4d9-ed99-4d8c-9d1e-f960580977d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6df1f4d9-ed99-4d8c-9d1e-f960580977d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25289096-bfa1-4dd2-8309-4569e55a7445' class='xr-var-data-in' type='checkbox'><label for='data-25289096-bfa1-4dd2-8309-4569e55a7445' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6c6523bd-01d6-49da-9cc2-0c50866c7519' class='xr-section-summary-in' type='checkbox'  ><label for='section-6c6523bd-01d6-49da-9cc2-0c50866c7519' class='xr-section-summary' >Data variables: <span>(15)</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>ACCESS-CM2ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-70fb7100-bb99-4632-82f6-38111c47e2e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70fb7100-bb99-4632-82f6-38111c47e2e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fafca0b-10f5-4fb6-824b-52cfa66f42f2' class='xr-var-data-in' type='checkbox'><label for='data-2fafca0b-10f5-4fb6-824b-52cfa66f42f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"203\" height=\"133\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "\n",
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+       "  <text x=\"11.972462\" y=\"91.972462\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.972462,91.972462)\">54</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACCESS-ESM1-5ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-0305129f-4a44-4463-bf2e-aa06f00c2aca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0305129f-4a44-4463-bf2e-aa06f00c2aca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79b14ca8-9a56-4ce1-81f7-7691a546bd6d' class='xr-var-data-in' type='checkbox'><label for='data-79b14ca8-9a56-4ce1-81f7-7691a546bd6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"203\" height=\"133\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"33\" y1=\"23\" x2=\"153\" y2=\"23\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
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+       "  <line x1=\"153\" y1=\"23\" x2=\"153\" y2=\"83\" style=\"stroke-width:2\" />\n",
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+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
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+       "  <text x=\"173.944923\" y=\"53.944923\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,173.944923,53.944923)\">180</text>\n",
+       "  <text x=\"11.972462\" y=\"91.972462\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.972462,91.972462)\">54</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BCC-CSM2-MRssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-576dfaf5-e3f9-43cb-902b-e01705ad0c43' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-576dfaf5-e3f9-43cb-902b-e01705ad0c43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c1a95d6-f22e-417d-88d0-19ab1e43f43d' class='xr-var-data-in' type='checkbox'><label for='data-6c1a95d6-f22e-417d-88d0-19ab1e43f43d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"203\" height=\"133\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"33\" y2=\"23\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAS-ESM2-0ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-97c50541-8403-42c1-a6fc-4dad74191ba9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-97c50541-8403-42c1-a6fc-4dad74191ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f14a27c8-53fb-427a-9115-376bb6014ff4' class='xr-var-data-in' type='checkbox'><label for='data-f14a27c8-53fb-427a-9115-376bb6014ff4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"203\" height=\"133\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CESM2-WACCMssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(9, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-b22329ee-1fc7-4baa-ae7e-787fa5b36bf3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b22329ee-1fc7-4baa-ae7e-787fa5b36bf3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4bec88c-cc05-407f-8e2b-b22f5cfe4d2f' class='xr-var-data-in' type='checkbox'><label for='data-a4bec88c-cc05-407f-8e2b-b22f5cfe4d2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 4.45 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (9, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 6 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CMCC-CM2-SR5ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-d0b52d5a-d802-475b-8042-68179f73f33a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0b52d5a-d802-475b-8042-68179f73f33a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fde99552-711f-4e2e-81c1-a1ec3e7af5b1' class='xr-var-data-in' type='checkbox'><label for='data-fde99552-711f-4e2e-81c1-a1ec3e7af5b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (54, 180, 360) </td>\n",
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+       "                    <tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CMCC-ESM2ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-616d6aaf-2a01-4ad6-8a20-c2539a161823' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-616d6aaf-2a01-4ad6-8a20-c2539a161823' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cac64b33-ae0b-4e06-b568-a1a7d66ea5c6' class='xr-var-data-in' type='checkbox'><label for='data-cac64b33-ae0b-4e06-b568-a1a7d66ea5c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (54, 180, 360) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CanESM5ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-ae532e54-f01f-4ab8-b994-7e64f01e7b5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae532e54-f01f-4ab8-b994-7e64f01e7b5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef4b1e9a-9dc1-4be9-b1b3-9801a3fb3a45' class='xr-var-data-in' type='checkbox'><label for='data-ef4b1e9a-9dc1-4be9-b1b3-9801a3fb3a45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "                        <td> (54, 180, 360) </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>FGOALS-g3ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-d76a51aa-e6a9-44da-9c67-e8c82ae0ac9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d76a51aa-e6a9-44da-9c67-e8c82ae0ac9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-972a33a9-be71-48e3-80f9-fcd668831a44' class='xr-var-data-in' type='checkbox'><label for='data-972a33a9-be71-48e3-80f9-fcd668831a44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
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+       "                        <td> (54, 180, 360) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MIROC6ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-ff1960e1-bf25-4ae8-92fb-7f9f9207a93b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff1960e1-bf25-4ae8-92fb-7f9f9207a93b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2385bf6f-95d8-4213-a8a5-5f26643c5acc' class='xr-var-data-in' type='checkbox'><label for='data-2385bf6f-95d8-4213-a8a5-5f26643c5acc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
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+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (54, 180, 360) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
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+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MPI-ESM-1-2-HAMssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(9, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-f67bc8f8-4381-4493-86fb-380474e1e72a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f67bc8f8-4381-4493-86fb-380474e1e72a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab28cea7-bb13-4ac3-955c-d1a31e275b69' class='xr-var-data-in' type='checkbox'><label for='data-ab28cea7-bb13-4ac3-955c-d1a31e275b69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
+       "                        <td> </td>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                        <td> 4.45 MiB </td>\n",
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+       "                    <tr>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRI-ESM2-0ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-e32d5c60-fb07-4d95-928e-0d2994bc7ca6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e32d5c60-fb07-4d95-928e-0d2994bc7ca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5268e686-9d5c-4c6c-bea8-0fbaf8ddfbae' class='xr-var-data-in' type='checkbox'><label for='data-5268e686-9d5c-4c6c-bea8-0fbaf8ddfbae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NorESM2-LMssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(8, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-ea981f8b-87c9-4cc9-ba92-3c332524cf54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea981f8b-87c9-4cc9-ba92-3c332524cf54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71fa88d5-be3b-4ab6-b83f-af99b0bc91fa' class='xr-var-data-in' type='checkbox'><label for='data-71fa88d5-be3b-4ab6-b83f-af99b0bc91fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 3.96 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (8, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 7 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NorESM2-MMssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-3a29092e-3c3e-4350-9655-65c415759e60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a29092e-3c3e-4350-9655-65c415759e60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1003b2a5-8a08-4f91-946e-e4c923791889' class='xr-var-data-in' type='checkbox'><label for='data-1003b2a5-8a08-4f91-946e-e4c923791889' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (54, 180, 360) </td>\n",
+       "                        <td> (54, 180, 360) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TaiESM1ssp370</span></div><div class='xr-var-dims'>(year, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(54, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-1784c864-575c-4260-b806-df14c607f156' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1784c864-575c-4260-b806-df14c607f156' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc7dab35-6870-4db4-8985-a5fdfd06c5c6' class='xr-var-data-in' type='checkbox'><label for='data-dc7dab35-6870-4db4-8985-a5fdfd06c5c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><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> 26.70 MiB </td>\n",
+       "                        <td> 26.70 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (54, 180, 360) </td>\n",
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+       "                    <tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "  <line x1=\"33\" y1=\"83\" x2=\"153\" y2=\"83\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"153\" y1=\"23\" x2=\"153\" y2=\"83\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"93.944923\" y=\"103.944923\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >360</text>\n",
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+       "  <text x=\"11.972462\" y=\"91.972462\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.972462,91.972462)\">54</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7b2bf2fc-ecce-43c6-85c0-3dd0cb49310a' class='xr-section-summary-in' type='checkbox'  ><label for='section-7b2bf2fc-ecce-43c6-85c0-3dd0cb49310a' 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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-a1bb1e80-a2f6-4f71-9ae7-397704ff0103' class='xr-index-data-in' type='checkbox'/><label for='index-a1bb1e80-a2f6-4f71-9ae7-397704ff0103' 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([  0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "       ...\n",
+       "       350.5, 351.5, 352.5, 353.5, 354.5, 355.5, 356.5, 357.5, 358.5, 359.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=360))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b98e13e0-4c39-4dc1-bfa0-a14c50a93cd4' class='xr-index-data-in' type='checkbox'/><label for='index-b98e13e0-4c39-4dc1-bfa0-a14c50a93cd4' 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([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       ...\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7369d347-a6a6-4bce-aa42-c93a3108c1e2' class='xr-index-data-in' type='checkbox'/><label for='index-7369d347-a6a6-4bce-aa42-c93a3108c1e2' 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([2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026,\n",
+       "       2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038,\n",
+       "       2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050,\n",
+       "       2051, 2052, 2053, 2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062,\n",
+       "       2063, 2064, 2065, 2066, 2067, 2068],\n",
+       "      dtype=&#x27;int64&#x27;, name=&#x27;year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9a8fc20a-1d03-455e-8e3c-3eea7af320b6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9a8fc20a-1d03-455e-8e3c-3eea7af320b6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 420MB\n",
+       "Dimensions:                (lon: 360, lat: 180, year: 54)\n",
+       "Coordinates:\n",
+       "  * lon                    (lon) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5\n",
+       "  * lat                    (lat) float64 1kB -89.5 -88.5 -87.5 ... 88.5 89.5\n",
+       "  * year                   (year) int64 432B 2015 2016 2017 ... 2066 2067 2068\n",
+       "    degree                 int64 8B 1\n",
+       "Data variables: (12/15)\n",
+       "    ACCESS-CM2ssp370       (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    ACCESS-ESM1-5ssp370    (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    BCC-CSM2-MRssp370      (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    CAS-ESM2-0ssp370       (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    CESM2-WACCMssp370      (year, lat, lon) float64 28MB dask.array<chunksize=(9, 180, 360), meta=np.ndarray>\n",
+       "    CMCC-CM2-SR5ssp370     (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    ...                     ...\n",
+       "    MIROC6ssp370           (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    MPI-ESM-1-2-HAMssp370  (year, lat, lon) float64 28MB dask.array<chunksize=(9, 180, 360), meta=np.ndarray>\n",
+       "    MRI-ESM2-0ssp370       (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    NorESM2-LMssp370       (year, lat, lon) float64 28MB dask.array<chunksize=(8, 180, 360), meta=np.ndarray>\n",
+       "    NorESM2-MMssp370       (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>\n",
+       "    TaiESM1ssp370          (year, lat, lon) float64 28MB dask.array<chunksize=(54, 180, 360), meta=np.ndarray>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import xarray as xr\n",
+    "\n",
+    "# dir_trends = '/g/data/kj13/datasets/visualisation_projects/uncharted_future/trend/models/*.nc'\n",
+    "dir_trends = '/g/data/kj13/datasets/visualisation_projects/uncharted_future/trend/models/future/*.nc'\n",
+    "\n",
+    "def _name_var(x):\n",
+    "    name = x.encoding['source'].split('/')[-1]\n",
+    "    name = ''.join(name.split('_')[:2])\n",
+    "    x.assign_coords({'source':name})\n",
+    "    return x.rename_vars({'polyfit_coefficients':name})\n",
+    "\n",
+    "mfds = xr.open_mfdataset(dir_trends, preprocess=_name_var)\n",
+    "mfds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "1194718a-40a9-484f-9a8e-fce91b9df380",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mean = mfds.to_array(dim='trend').mean('trend')\n",
+    "start = mean.year[0].values\n",
+    "end = mean.year[-1].values\n",
+    "\n",
+    "output_path = '/g/data/kj13/datasets/visualisation_projects/uncharted_future/trend'\n",
+    "mean.to_netcdf(f\"{output_path}/future_cmip6_model_ts_31years_trend_{start}_{end}.nc\")"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:analysis3-25.09] *",
+   "display_name": "Python [conda env:analysis3-25.09]",
    "language": "python",
    "name": "conda-env-analysis3-25.09-py"
   },
diff --git a/esmval_recipe_trends/recipe_cmip6_ts_trend.yml b/esmval_recipe_trends/recipe_cmip6_ts_trend.yml
new file mode 100644
index 0000000..b241521
--- /dev/null
+++ b/esmval_recipe_trends/recipe_cmip6_ts_trend.yml
@@ -0,0 +1,79 @@
+# ESMValTool
+# 
+---
+documentation:
+  description: multi model cmip6 statistics
+  title: CMIP6 ts trends
+  authors:
+    - chun_felicity
+  maintainer:
+    - chun_felicity
+
+# datasets:
+  # - project: CMIP6
+  #   exp: SSP370
+  #   dataset: '*'
+  #   institute: '*'
+  #   ensemble: 'r*i1p1f1'
+  #   grid: gn
+
+overlap: &models
+  - {dataset: ACCESS-ESM1-5, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: ACCESS-CM2, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: BCC-CSM2-MR, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: CAS-ESM2-0, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: CESM2-WACCM, project: CMIP6, ensemble: '*', grid: gn} # missing years in ensembles r2,3
+  - {dataset: CMCC-CM2-SR5, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: CMCC-ESM2, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: CanESM5, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: FGOALS-g3, project: CMIP6, ensemble: '*', grid: gn}
+  # - {dataset: IITM-ESM, project: CMIP6, ensemble: '*', grid: gn, start_year: '*', end_year: 2098} ##not in historical
+  - {dataset: MIROC6, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: MPI-ESM-1-2-HAM, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: MRI-ESM2-0, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: NorESM2-LM, project: CMIP6, ensemble: '*', grid: gn} # missing years in ensembles r2,3
+  - {dataset: NorESM2-MM, project: CMIP6, ensemble: '*', grid: gn}
+  - {dataset: TaiESM1, project: CMIP6, ensemble: '*', grid: gn}
+
+
+preprocessors:
+  all_preprocessor:
+    regrid:
+      target_grid: 1x1
+      scheme: linear
+    ensemble_statistics:
+      statistics: [mean]
+
+
+diagnostics:
+  diagnostic_metrics:
+    description: run ts in groups future, historical and obs
+    variables:
+      ts_future:
+        short_name: ts
+        mip: Amon
+        activity: ScenarioMIP
+        exp: ssp370
+        timerange: '*'
+        preprocessor: all_preprocessor
+        additional_datasets: *models
+
+      ts_obs:
+        short_name: ts
+        mip: Amon
+        timerange: '*'
+        additional_datasets:
+          - {dataset: HadISST, project: OBS, type: reanaly, tier: 2, version: 1}
+
+      ts:
+        mip: Amon
+        exp: historical
+        timerange: '*'
+        preprocessor: all_preprocessor
+        additional_datasets: *models
+
+    scripts:
+      trends:
+        script: trends.py #update filepath or run in folder
+
+
diff --git a/esmval_recipe_trends/trends.py b/esmval_recipe_trends/trends.py
new file mode 100755
index 0000000..89eeb4c
--- /dev/null
+++ b/esmval_recipe_trends/trends.py
@@ -0,0 +1,91 @@
+"""diagnostic script to plot"""
+
+import iris
+import os
+import logging
+import numpy as np
+import xarray as xr
+
+from esmvaltool.diag_scripts.shared import (
+    run_diagnostic,
+    save_figure,
+    group_metadata,
+    select_metadata,
+)
+from esmvalcore.preprocessor import (
+    climate_statistics,
+    regrid,
+    concatenate
+)
+
+
+# This part sends debug statements to stdout
+logger = logging.getLogger(os.path.basename(__file__))
+
+
+def calc_trend(xarr, start, end, length):
+    """
+    Compute running linear trends over windows of size `length` (years)
+    from `start` to `end - 1`, returning trend per decade.
+
+    xarr must have a coordinate "year".
+    """
+    
+    trend_list = []
+
+    for yr in range(start, end):
+        # window
+        win = xarr.sel(year=slice(str(yr), str(yr + length-1)))
+
+        # replace year coordinate with integers 0..N-1 for polyfit
+        t = np.arange(win.year.size)
+        win = win.assign_coords(year=t)
+
+        # polyfit: slope * 10 for trend per decade
+        tr = (win.polyfit(dim="year", deg=1, skipna=True)
+                 .polyfit_coefficients
+                 .isel(degree=0) * 10)
+        
+        trend_list.append(tr)
+
+    # concatenate trends along a new "year" dimension
+    trnarr = xr.concat(trend_list, dim="year")
+
+    # restore actual years
+    trnarr = trnarr.assign_coords(year=np.arange(start, end))
+
+    return trnarr
+
+
+def main(cfg):
+    """run on all datasets"""
+
+    input_data = cfg["input_data"].values()
+    ## group by dataset to concatenate future to historical after ensemble means
+    # for dataset, attributes in group_metadata(input_data,"dataset", sort='exp').items():
+    #     in_files = [d['filename'] for d in attributes]
+    #     cubes = iris.load(in_files)
+    #     start_year = min([d['start_year'] for d in attributes]) 
+    #     end_year = max([d['end_year'] for d in attributes])
+        
+    #     logger.info(f"Loaded {len(cubes)} cubes for {dataset}, {start_year} - {end_year}")
+    #     iris.util.equalise_attributes(cubes)
+    #     cube = concatenate(cubes)
+
+    ## keep future variable separate 
+    for dataset in input_data:
+        input_file = dataset['filename']
+        name = dataset['dataset'] + '_' + dataset['exp']
+        cube = iris.load_cube(input_file)
+        start_year, end_year = dataset['start_year'], dataset['end_year']
+        ##
+
+        data = xr.DataArray.from_iris(cube)
+        ds_model_ann = data.groupby('time.year').mean('time')
+        ds_model_ann_trend_31 = calc_trend(ds_model_ann, start_year, end_year-31, 31)
+
+        ds_model_ann_trend_31.to_netcdf(os.path.join(cfg["work_dir"], f"{dataset}_trend_31yr{start_year}_{end_year-31}.nc"))
+
+if __name__ == "__main__":
+    with run_diagnostic() as config:
+        main(config)