Skip to content

Instantly share code, notes, and snippets.

@jbusecke

jbusecke/interpolate_or_combine.ipynb

Created July 13, 2021 17:54
Show Gist options
  • Save jbusecke/f8bad77e7957ab011d4c83fac37dc8e2 to your computer and use it in GitHub Desktop.
Save jbusecke/f8bad77e7957ab011d4c83fac37dc8e2 to your computer and use it in GitHub Desktop.
Download ZIP
Comparison between reconstruction methods for ocean metrics using GFDL OM025
Display the source blob
Display the rendered blob
Raw
interpolate_or_combine.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "gross-spyware",
"metadata": {},
"source": [
"# Quick example to compare if interpolation of combination of grid metrics is more accurate"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "gross-lover",
"metadata": {},
"outputs": [],
"source": [
"# get gfdl grid data\n",
"# !wget -r ftp://ftp.gfdl.noaa.gov/perm/Alistair.Adcroft/MOM6-testing/OM4_025/ocean_static.nc"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "neutral-arthritis",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=dark],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1F1F1F;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block;\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 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\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: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-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",
" 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",
" 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-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-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",
" 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;\n",
"Dimensions: (time: 1, xh: 1440, xq: 1440, yh: 1080, yq: 1080)\n",
"Coordinates:\n",
" * xh (xh) float64 -299.7 -299.5 -299.2 -299.0 ... 59.53 59.78 60.03\n",
" * yh (yh) float64 -80.39 -80.31 -80.23 -80.15 ... 89.73 89.84 89.95\n",
" * time (time) object 1900-01-01 00:00:00\n",
" * xq (xq) float64 -299.6 -299.3 -299.1 -298.9 ... 59.66 59.91 60.16\n",
" * yq (yq) float64 -80.35 -80.27 -80.19 -80.11 ... 89.78 89.89 90.0\n",
"Data variables:\n",
" areacello (yh, xh) float32 ...\n",
" deptho (yh, xh) float32 ...\n",
" hfgeou (yh, xh) float32 ...\n",
" sftof (yh, xh) float32 ...\n",
" Coriolis (yq, xq) float32 ...\n",
" geolon (yh, xh) float32 ...\n",
" geolat (yh, xh) float32 ...\n",
" geolon_c (yq, xq) float32 ...\n",
" geolat_c (yq, xq) float32 ...\n",
" geolon_u (yh, xq) float32 ...\n",
" geolat_u (yh, xq) float32 ...\n",
" geolon_v (yq, xh) float32 ...\n",
" geolat_v (yq, xh) float32 ...\n",
" wet (yh, xh) float32 ...\n",
" wet_c (yq, xq) float32 ...\n",
" wet_u (yh, xq) float32 ...\n",
" wet_v (yq, xh) float32 ...\n",
" dxt (yh, xh) float32 ...\n",
" dyt (yh, xh) float32 ...\n",
" dxCu (yh, xq) float32 ...\n",
" dyCu (yh, xq) float32 ...\n",
" dxCv (yq, xh) float32 ...\n",
" dyCv (yq, xh) float32 ...\n",
" areacello_cu (yh, xq) float32 ...\n",
" areacello_cv (yq, xh) float32 ...\n",
" areacello_bu (yq, xq) float32 ...\n",
" basin (yh, xh) int32 ...\n",
"Attributes:\n",
" filename: 19000101.ocean_static.nc\n",
" title: OM4_SIS2_cgrid_025\n",
" grid_type: regular\n",
" grid_tile: N/A</pre><div class='xr-wrap' hidden><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-895a4dd8-b751-4a25-8f22-93d20cecae1d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-895a4dd8-b751-4a25-8f22-93d20cecae1d' 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>: 1</li><li><span class='xr-has-index'>xh</span>: 1440</li><li><span class='xr-has-index'>xq</span>: 1440</li><li><span class='xr-has-index'>yh</span>: 1080</li><li><span class='xr-has-index'>yq</span>: 1080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b48b8147-20dd-481a-9e40-d2ec310e53c2' class='xr-section-summary-in' type='checkbox' checked><label for='section-b48b8147-20dd-481a-9e40-d2ec310e53c2' class='xr-section-summary' >Coordinates: <span>(5)</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'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.7 -299.5 ... 59.78 60.03</div><input id='attrs-ecf301f5-227d-48eb-89cb-a90e4910e73f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecf301f5-227d-48eb-89cb-a90e4910e73f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76092885-a41e-40d1-b1e2-dd4c94bc3570' class='xr-var-data-in' type='checkbox'><label for='data-76092885-a41e-40d1-b1e2-dd4c94bc3570' 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>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.724244, -299.476198, -299.22815 , ..., 59.531631, 59.77967 ,\n",
" 60.027712])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.39 -80.31 ... 89.84 89.95</div><input id='attrs-589e0a3a-a6d5-481e-a127-d1ced61cdbc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-589e0a3a-a6d5-481e-a127-d1ced61cdbc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f101344-5ac4-4e18-a393-070d92b12334' class='xr-var-data-in' type='checkbox'><label for='data-5f101344-5ac4-4e18-a393-070d92b12334' 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>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.389238, -80.308075, -80.226911, ..., 89.729781, 89.837868,\n",
" 89.945956])</pre></div></li><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'>1900-01-01 00:00:00</div><input id='attrs-5a59b45a-a26d-4f27-b87c-1f950c143a54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a59b45a-a26d-4f27-b87c-1f950c143a54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16b89c4f-bc4d-4053-b7ac-15437d9721a8' class='xr-var-data-in' type='checkbox'><label for='data-16b89c4f-bc4d-4053-b7ac-15437d9721a8' 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>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>NOLEAP</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1900, 1, 1, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.6 -299.3 ... 59.91 60.16</div><input id='attrs-2b954ee5-e907-419c-8449-6ac17e6f4cdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b954ee5-e907-419c-8449-6ac17e6f4cdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f3b6d37-1b09-4516-a79f-8eae2d14d9f3' class='xr-var-data-in' type='checkbox'><label for='data-0f3b6d37-1b09-4516-a79f-8eae2d14d9f3' 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>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.594355, -299.346385, -299.098412, ..., 59.661746, 59.90971 ,\n",
" 60.157676])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.35 -80.27 -80.19 ... 89.89 90.0</div><input id='attrs-e738f02e-bf4e-4cec-b94f-c08a36dc78b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e738f02e-bf4e-4cec-b94f-c08a36dc78b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd33e146-4329-46d8-9fd7-41037ccf3bdf' class='xr-var-data-in' type='checkbox'><label for='data-cd33e146-4329-46d8-9fd7-41037ccf3bdf' 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>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.348657, -80.267493, -80.186329, ..., 89.783825, 89.891912,\n",
" 90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-60992650-7b76-4808-a9ed-3b43d8b90997' class='xr-section-summary-in' type='checkbox' ><label for='section-60992650-7b76-4808-a9ed-3b43d8b90997' class='xr-section-summary' >Data variables: <span>(27)</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>areacello</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-31257a1f-ed42-438e-8c8d-05a10ee2034f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31257a1f-ed42-438e-8c8d-05a10ee2034f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90ded206-335b-482c-8472-8d60a0ae84e9' class='xr-var-data-in' type='checkbox'><label for='data-90ded206-335b-482c-8472-8d60a0ae84e9' 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>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>deptho</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-513892c2-4943-4c4c-a0b8-72d2ea2d77f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-513892c2-4943-4c4c-a0b8-72d2ea2d77f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04db0442-ea21-453e-a092-415774d58fb1' class='xr-var-data-in' type='checkbox'><label for='data-04db0442-ea21-453e-a092-415774d58fb1' 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>Sea Floor Depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>standard_name :</span></dt><dd>sea_floor_depth_below_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hfgeou</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2641e44b-244f-4058-b2fd-ded5307e5b45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2641e44b-244f-4058-b2fd-ded5307e5b45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac5889b5-5671-4a8d-bcab-51fab3b9815b' class='xr-var-data-in' type='checkbox'><label for='data-ac5889b5-5671-4a8d-bcab-51fab3b9815b' 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>Upward geothermal heat flux at sea floor</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>upward_geothermal_heat_flux_at_sea_floor</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftof</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2d8d7cb3-8f07-4514-b963-8bf8c62df198' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d8d7cb3-8f07-4514-b963-8bf8c62df198' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbd22ee5-2131-4405-bc35-3dd3c971b870' class='xr-var-data-in' type='checkbox'><label for='data-dbd22ee5-2131-4405-bc35-3dd3c971b870' 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>Sea Area Fraction</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>SeaAreaFraction</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Coriolis</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-345d68b0-b3c4-45d5-8630-3ebcbf99828b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-345d68b0-b3c4-45d5-8630-3ebcbf99828b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29d3cc4a-6a0b-49f0-baff-0a8af1191111' class='xr-var-data-in' type='checkbox'><label for='data-29d3cc4a-6a0b-49f0-baff-0a8af1191111' 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>Coriolis parameter at corner (Bu) points</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-19c8ba7b-a0e5-4cf0-8166-08d1fb8b59be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19c8ba7b-a0e5-4cf0-8166-08d1fb8b59be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f652ea9c-2647-461b-89a8-b547944a8735' class='xr-var-data-in' type='checkbox'><label for='data-f652ea9c-2647-461b-89a8-b547944a8735' 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>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b170e7d-9a2f-44ff-a770-9af8a9dda6d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b170e7d-9a2f-44ff-a770-9af8a9dda6d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f2338ac-e4ed-44be-ae0a-2a0dd1fa4d72' class='xr-var-data-in' type='checkbox'><label for='data-0f2338ac-e4ed-44be-ae0a-2a0dd1fa4d72' 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>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-efa9369c-08d3-4b95-b5e7-13a4edf2cc00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efa9369c-08d3-4b95-b5e7-13a4edf2cc00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24908e26-6aa4-48cb-a0e7-24af9a8176e9' class='xr-var-data-in' type='checkbox'><label for='data-24908e26-6aa4-48cb-a0e7-24af9a8176e9' 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>Longitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96544896-b333-408c-adad-77cd66050247' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96544896-b333-408c-adad-77cd66050247' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f4f63d1-738b-4567-b2c4-c0e6dcf4db5c' class='xr-var-data-in' type='checkbox'><label for='data-1f4f63d1-738b-4567-b2c4-c0e6dcf4db5c' 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>Latitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5edf931f-f9ef-4e16-8b9e-5b7c9adfa058' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5edf931f-f9ef-4e16-8b9e-5b7c9adfa058' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e971a55f-2bab-49ef-b010-61a12655761e' class='xr-var-data-in' type='checkbox'><label for='data-e971a55f-2bab-49ef-b010-61a12655761e' 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>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-88bcfd6a-0f22-48b2-8e0b-cfc4614aa61e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88bcfd6a-0f22-48b2-8e0b-cfc4614aa61e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-077a5c60-6c5b-4ba3-b6bf-94a0f5fa7ec9' class='xr-var-data-in' type='checkbox'><label for='data-077a5c60-6c5b-4ba3-b6bf-94a0f5fa7ec9' 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>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5e20c0a2-34da-4486-b295-fa99a7d159fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e20c0a2-34da-4486-b295-fa99a7d159fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-136a70df-dadf-4098-a2fd-e5ffc05ca277' class='xr-var-data-in' type='checkbox'><label for='data-136a70df-dadf-4098-a2fd-e5ffc05ca277' 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>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9954e2ef-7b1a-4b7f-bc8a-8f69764617fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9954e2ef-7b1a-4b7f-bc8a-8f69764617fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-366a045f-0c67-455f-bba6-0f4d779351b3' class='xr-var-data-in' type='checkbox'><label for='data-366a045f-0c67-455f-bba6-0f4d779351b3' 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>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2ed0a67c-cc4d-4d0f-ac8c-1952127e954d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ed0a67c-cc4d-4d0f-ac8c-1952127e954d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ccd80d4-a0c1-47f3-834f-7427ac0ccfef' class='xr-var-data-in' type='checkbox'><label for='data-2ccd80d4-a0c1-47f3-834f-7427ac0ccfef' 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>0 if land, 1 if ocean at tracer points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0480b3c-13f3-46c8-bb66-c062ea92eed2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0480b3c-13f3-46c8-bb66-c062ea92eed2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2a2a2e-0043-4ce5-b8b5-3cae311b338e' class='xr-var-data-in' type='checkbox'><label for='data-6d2a2a2e-0043-4ce5-b8b5-3cae311b338e' 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>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e2e7795e-ceb5-49fa-b075-fbbcd933052c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2e7795e-ceb5-49fa-b075-fbbcd933052c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be228330-1fda-4e3f-b6a6-4ccf2b75484f' class='xr-var-data-in' type='checkbox'><label for='data-be228330-1fda-4e3f-b6a6-4ccf2b75484f' 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>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3e91e696-23ab-4075-ad96-01e9fd409ffb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e91e696-23ab-4075-ad96-01e9fd409ffb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efab2a4d-344e-4a6c-b79b-1a50c5393850' class='xr-var-data-in' type='checkbox'><label for='data-efab2a4d-344e-4a6c-b79b-1a50c5393850' 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>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6de58990-4c13-4e1f-9616-16c4b186ce61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6de58990-4c13-4e1f-9616-16c4b186ce61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79614ddc-4d51-4296-816f-82d3cdded8c8' class='xr-var-data-in' type='checkbox'><label for='data-79614ddc-4d51-4296-816f-82d3cdded8c8' 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>Delta(x) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-44fcb18c-13d8-47c4-931a-cdc4ad769bf5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44fcb18c-13d8-47c4-931a-cdc4ad769bf5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b8eedde-5400-4ed3-8743-1ef18ccce995' class='xr-var-data-in' type='checkbox'><label for='data-2b8eedde-5400-4ed3-8743-1ef18ccce995' 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>Delta(y) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5bba39da-28a5-415a-98b2-43ab2ab2a7fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bba39da-28a5-415a-98b2-43ab2ab2a7fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54cb888f-b474-43ad-94ff-3b6b5a9a0183' class='xr-var-data-in' type='checkbox'><label for='data-54cb888f-b474-43ad-94ff-3b6b5a9a0183' 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>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-65d36ceb-27f2-4820-9ca1-b17d0795d914' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65d36ceb-27f2-4820-9ca1-b17d0795d914' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b7e4143-13df-4743-915c-ff18ba376cb5' class='xr-var-data-in' type='checkbox'><label for='data-7b7e4143-13df-4743-915c-ff18ba376cb5' 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>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8de0afe3-7ae8-4c91-9d25-5a700264a5c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8de0afe3-7ae8-4c91-9d25-5a700264a5c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f13c3b5-7060-4026-9af0-bc8912b38f26' class='xr-var-data-in' type='checkbox'><label for='data-2f13c3b5-7060-4026-9af0-bc8912b38f26' 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>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-643d7866-aa90-49dc-810c-1136add7b68e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-643d7866-aa90-49dc-810c-1136add7b68e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4703d073-973a-45f6-bd4a-d383968577d3' class='xr-var-data-in' type='checkbox'><label for='data-4703d073-973a-45f6-bd4a-d383968577d3' 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>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed515beb-5564-4451-a70c-118eddf559b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed515beb-5564-4451-a70c-118eddf559b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f73551b2-562e-4c0a-b81e-0e616da83894' class='xr-var-data-in' type='checkbox'><label for='data-f73551b2-562e-4c0a-b81e-0e616da83894' 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>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0e15bf47-0b97-4ff7-932b-1ba5a5699dcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e15bf47-0b97-4ff7-932b-1ba5a5699dcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb01ef82-03de-42b2-9539-42b185a4f544' class='xr-var-data-in' type='checkbox'><label for='data-cb01ef82-03de-42b2-9539-42b185a4f544' 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>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_bu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-140fae10-9b46-4ff7-8a68-4ffd3644262c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-140fae10-9b46-4ff7-8a68-4ffd3644262c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f19d8d43-0a58-44b9-aefb-448813073837' class='xr-var-data-in' type='checkbox'><label for='data-f19d8d43-0a58-44b9-aefb-448813073837' 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>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>basin</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dc30e234-ea1f-4849-9ec1-e0d59b80017c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc30e234-ea1f-4849-9ec1-e0d59b80017c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7dd2d01-613f-48ba-8ad5-c4cfc62adb76' class='xr-var-data-in' type='checkbox'><label for='data-c7dd2d01-613f-48ba-8ad5-c4cfc62adb76' 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>Region Selection Index</dd><dt><span>standard_name :</span></dt><dd>region</dd><dt><span>units :</span></dt><dd>1.0</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>flag_values :</span></dt><dd>0 1 2 3 4 5 6 7 8 9 10</dd><dt><span>flag_meanings :</span></dt><dd>global_land southern_ocean atlantic_ocean pacific_ocean arctic_ocean indian_ocean mediterranean_sea black_sea hudson_bay baltic_sea red_sea</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=int32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cdda15d9-d3a7-44ff-9c2d-8fcc0787303d' class='xr-section-summary-in' type='checkbox' checked><label for='section-cdda15d9-d3a7-44ff-9c2d-8fcc0787303d' 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>filename :</span></dt><dd>19000101.ocean_static.nc</dd><dt><span>title :</span></dt><dd>OM4_SIS2_cgrid_025</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 1, xh: 1440, xq: 1440, yh: 1080, yq: 1080)\n",
"Coordinates:\n",
" * xh (xh) float64 -299.7 -299.5 -299.2 -299.0 ... 59.53 59.78 60.03\n",
" * yh (yh) float64 -80.39 -80.31 -80.23 -80.15 ... 89.73 89.84 89.95\n",
" * time (time) object 1900-01-01 00:00:00\n",
" * xq (xq) float64 -299.6 -299.3 -299.1 -298.9 ... 59.66 59.91 60.16\n",
" * yq (yq) float64 -80.35 -80.27 -80.19 -80.11 ... 89.78 89.89 90.0\n",
"Data variables:\n",
" areacello (yh, xh) float32 ...\n",
" deptho (yh, xh) float32 ...\n",
" hfgeou (yh, xh) float32 ...\n",
" sftof (yh, xh) float32 ...\n",
" Coriolis (yq, xq) float32 ...\n",
" geolon (yh, xh) float32 ...\n",
" geolat (yh, xh) float32 ...\n",
" geolon_c (yq, xq) float32 ...\n",
" geolat_c (yq, xq) float32 ...\n",
" geolon_u (yh, xq) float32 ...\n",
" geolat_u (yh, xq) float32 ...\n",
" geolon_v (yq, xh) float32 ...\n",
" geolat_v (yq, xh) float32 ...\n",
" wet (yh, xh) float32 ...\n",
" wet_c (yq, xq) float32 ...\n",
" wet_u (yh, xq) float32 ...\n",
" wet_v (yq, xh) float32 ...\n",
" dxt (yh, xh) float32 ...\n",
" dyt (yh, xh) float32 ...\n",
" dxCu (yh, xq) float32 ...\n",
" dyCu (yh, xq) float32 ...\n",
" dxCv (yq, xh) float32 ...\n",
" dyCv (yq, xh) float32 ...\n",
" areacello_cu (yh, xq) float32 ...\n",
" areacello_cv (yq, xh) float32 ...\n",
" areacello_bu (yq, xq) float32 ...\n",
" basin (yh, xh) int32 ...\n",
"Attributes:\n",
" filename: 19000101.ocean_static.nc\n",
" title: OM4_SIS2_cgrid_025\n",
" grid_type: regular\n",
" grid_tile: N/A"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import xarray as xr\n",
"\n",
"ds = xr.open_dataset(\n",
" \"ftp.gfdl.noaa.gov/perm/Alistair.Adcroft/MOM6-testing/OM4_025/ocean_static.nc\"\n",
")\n",
"ds"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "through-empire",
"metadata": {},
"outputs": [],
"source": [
"from xgcm import Grid"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "isolated-messaging",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xgcm.Grid>\n",
"X Axis (periodic, boundary=None):\n",
" * center xh --> left\n",
" * left xq --> center\n",
"Y Axis (periodic, boundary=None):\n",
" * center yh --> left\n",
" * left yq --> center"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grid = Grid(ds, coords={'X':{'center':'xh', 'left':'xq'}, 'Y':{'center':'yh', 'left':'yq'}})\n",
"grid"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "fatal-albert",
"metadata": {},
"outputs": [],
"source": [
"# lets erode the mask to only see open ocean stuff\n",
"import scipy.ndimage as ndim \n",
"\n",
"\n",
"mask_t = ds.wet.copy()\n",
"mask_t.data = ndim.morphology.binary_erosion(mask_t, iterations=20)\n",
"\n",
"mask_u = ds.wet_u.copy()\n",
"mask_u.data = ndim.morphology.binary_erosion(mask_u, iterations=20)\n",
"\n",
"mask_v = ds.wet_v.copy()\n",
"mask_v.data = ndim.morphology.binary_erosion(mask_v, iterations=20)"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "headed-penalty",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f013a01fa30>"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ds.wet.plot()"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "hawaiian-novel",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f013ad88490>"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"mask_v.plot()"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "activated-remark",
"metadata": {},
"outputs": [],
"source": [
"groundtruth = ds.areacello.where(mask_t)\n",
"interpolated_area = grid.interp(ds.areacello_cu.where(mask_u),'X')\n",
"interpolated_then_combined_area = grid.interp(ds.dxCu.where(mask_u),'X') * grid.interp(ds.dyCv.where(mask_v),'Y')\n",
"combined_area = ds.dxt * ds.dyt"
]
},
{
"cell_type": "code",
"execution_count": 78,
"id": "studied-craps",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f013b42ca60>"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"interpolated_then_combined_area.plot()"
]
},
{
"cell_type": "code",
"execution_count": 82,
"id": "healthy-bristol",
"metadata": {},
"outputs": [],
"source": [
"interpolated_error = (interpolated_area - groundtruth) / groundtruth *100\n",
"interpolated_then_combined_error = (\n",
" interpolated_then_combined_area - groundtruth\n",
") / groundtruth *100\n",
"combined_error = (combined_area - groundtruth) / groundtruth *100"
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "valued-truck",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f013ab404c0>"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"interpolated_error.plot(robust=True)"
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "united-wheel",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f00faef9550>"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"combined_error.plot(robust=True)"
]
},
{
"cell_type": "code",
"execution_count": 84,
"id": "unlike-clone",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f0139f943d0>"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"interpolated_then_combined_error.plot(robust=True)"
]
},
{
"cell_type": "markdown",
"id": "marked-denver",
"metadata": {},
"source": [
"Seems like the combo works best!"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "intended-danger",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f00fb2411f0>"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot results\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"bins = np.linspace(-1, 1, 100)\n",
"interpolated_error.plot.hist(bins=bins, label='interpolated')\n",
"combined_error.plot.hist(bins=bins, alpha=0.5, label='combined');\n",
"interpolated_then_combined_error.plot.hist(bins=bins, alpha=0.5, label='interpolated_then_combined');\n",
"plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "going-outdoors",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "cosmetic-cologne",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:notebook] *",
"language": "python",
"name": "conda-env-notebook-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment