{
"cells": [
{
"cell_type": "markdown",
"id": "f373e554",
"metadata": {
"tags": [
"papermill-error-cell-tag"
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"source": [
"An Exception was encountered at 'In [8]'."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "864e13c1-5879-4940-9f1d-0288c77992fd",
"metadata": {
"editable": true,
"execution": {
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"papermill": {
"duration": 0.01893,
"end_time": "2025-03-26T20:36:26.792560",
"exception": false,
"start_time": "2025-03-26T20:36:26.773630",
"status": "completed"
},
"slideshow": {
"slide_type": ""
},
"tags": [
"parameters"
]
},
"outputs": [],
"source": [
"from IPython.display import display, Markdown\n",
"\n",
"# Parameters injected by Papermill\n",
"variable = 'tos'"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "861ad674",
"metadata": {
"execution": {
"iopub.execute_input": "2025-03-26T20:36:26.798477Z",
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"exception": false,
"start_time": "2025-03-26T20:36:26.795374",
"status": "completed"
},
"tags": [
"injected-parameters"
]
},
"outputs": [],
"source": [
"# Parameters\n",
"variable = \"heat_content_lprec\"\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "dce4db04-3953-4356-b4cd-7f811e6ac563",
"metadata": {
"execution": {
"iopub.execute_input": "2025-03-26T20:36:26.806281Z",
"iopub.status.busy": "2025-03-26T20:36:26.806174Z",
"iopub.status.idle": "2025-03-26T20:36:26.809483Z",
"shell.execute_reply": "2025-03-26T20:36:26.809231Z"
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"status": "completed"
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"tags": []
},
"outputs": [
{
"data": {
"text/markdown": [
"# heat_content_lprec \n",
" This notebook compares area-weighted mean time series for heat_content_lprec in different basins."
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Dynamically generate markdown content\n",
"markdown_text = f\"# {variable} \\n This notebook compares area-weighted mean time series for {variable} in different basins.\"\n",
"\n",
"# Display the updated markdown content\n",
"display(Markdown(markdown_text))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "13834ab8-5413-4cd4-8b72-d02389459983",
"metadata": {
"editable": true,
"execution": {
"iopub.execute_input": "2025-03-26T20:36:26.817915Z",
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},
"papermill": {
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"end_time": "2025-03-26T20:36:26.838909",
"exception": false,
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"status": "completed"
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"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "ca374cc2",
"metadata": {
"editable": true,
"execution": {
"iopub.execute_input": "2025-03-26T20:36:26.845040Z",
"iopub.status.busy": "2025-03-26T20:36:26.844847Z",
"iopub.status.idle": "2025-03-26T20:36:41.064652Z",
"shell.execute_reply": "2025-03-26T20:36:41.064346Z"
},
"papermill": {
"duration": 14.223961,
"end_time": "2025-03-26T20:36:41.065674",
"exception": false,
"start_time": "2025-03-26T20:36:26.841713",
"status": "completed"
},
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": [
"%%capture \n",
"# comment above line to see details about the run(s) displayed\n",
"from misc import *\n",
"import glob\n",
"from mom6_tools.m6toolbox import weighted_temporal_mean\n",
"print(\"Last update:\", date.today())\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "9f7b0baf-fc8c-42a2-8f85-394752748d3c",
"metadata": {
"editable": true,
"execution": {
"iopub.execute_input": "2025-03-26T20:36:41.075040Z",
"iopub.status.busy": "2025-03-26T20:36:41.073997Z",
"iopub.status.idle": "2025-03-26T20:36:41.132057Z",
"shell.execute_reply": "2025-03-26T20:36:41.131784Z"
},
"papermill": {
"duration": 0.062307,
"end_time": "2025-03-26T20:36:41.132966",
"exception": false,
"start_time": "2025-03-26T20:36:41.070659",
"status": "completed"
},
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": [
"# figure size\n",
"fs = (10,4)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "7a76c19e-4617-421e-9912-6e37b8b411cd",
"metadata": {
"execution": {
"iopub.execute_input": "2025-03-26T20:36:41.139822Z",
"iopub.status.busy": "2025-03-26T20:36:41.139315Z",
"iopub.status.idle": "2025-03-26T20:36:41.203979Z",
"shell.execute_reply": "2025-03-26T20:36:41.203707Z"
},
"papermill": {
"duration": 0.068851,
"end_time": "2025-03-26T20:36:41.204871",
"exception": false,
"start_time": "2025-03-26T20:36:41.136020",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# load data\n",
"ds = []\n",
"#variable = 'tos'\n",
"for c, p in zip(casename, ocn_path):\n",
" file = glob.glob(p+'{}.native.{}.??????-??????.nc'.format(c, variable))[0]\n",
" ds.append(xr.open_dataset(file))"
]
},
{
"cell_type": "markdown",
"id": "502465ab-ff8d-4a56-82eb-96eb140f2fb9",
"metadata": {
"papermill": {
"duration": 0.002706,
"end_time": "2025-03-26T20:36:41.210746",
"exception": false,
"start_time": "2025-03-26T20:36:41.208040",
"status": "completed"
},
"tags": []
},
"source": [
"## Global"
]
},
{
"cell_type": "markdown",
"id": "c0fe1f07",
"metadata": {
"tags": [
"papermill-error-cell-tag"
]
},
"source": [
"Execution using papermill encountered an exception here and stopped:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ea77f10f-3d7e-4191-a3d1-8bcd7318125c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-03-26T20:36:41.217257Z",
"iopub.status.busy": "2025-03-26T20:36:41.216733Z",
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"shell.execute_reply": "2025-03-26T20:36:41.747500Z"
},
"papermill": {
"duration": 0.5354,
"end_time": "2025-03-26T20:36:41.748783",
"exception": true,
"start_time": "2025-03-26T20:36:41.213383",
"status": "failed"
},
"tags": []
},
"outputs": [
{
"ename": "KeyError",
"evalue": "\"No variable named 'heat_content_lprec'. Variables on the dataset include ['time', 'region', 'heat_content_lprec_mean', 'heat_content_lprec_int']\"",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/glade/work/gmarques/conda-envs/mom6-tools/lib/python3.11/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 1475\u001b[0m \u001b[0mvariable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1476\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1477\u001b[0;31m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvariable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_virtual_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variables\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msizes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'heat_content_lprec'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/glade/work/gmarques/conda-envs/mom6-tools/lib/python3.11/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1574\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct_dataarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1575\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1576\u001b[0;31m raise KeyError(\n\u001b[0m\u001b[1;32m 1577\u001b[0m \u001b[0;34mf\"No variable named {key!r}. Variables on the dataset include {shorten_list_repr(list(self.variables.keys()), max_items=10)}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/glade/work/gmarques/conda-envs/mom6-tools/lib/python3.11/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 1475\u001b[0m \u001b[0mvariable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1476\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1477\u001b[0;31m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvariable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_virtual_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variables\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msizes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/glade/work/gmarques/conda-envs/mom6-tools/lib/python3.11/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(variables, key, dim_sizes)\u001b[0m\n\u001b[1;32m 208\u001b[0m \u001b[0msplit_key\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\".\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 209\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msplit_key\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 210\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 211\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'heat_content_lprec'",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/glade/derecho/scratch/gmarques/tmp/ipykernel_125188/847476785.py\u001b[0m in \u001b[0;36m?\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mreg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Global'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mncols\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mvariable\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mregion\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlw\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;31m#ax.set_ylabel(ds[variable].attrs['units'])\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/glade/work/gmarques/conda-envs/mom6-tools/lib/python3.11/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1572\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhashable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1573\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1574\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct_dataarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1575\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1576\u001b[0;31m raise KeyError(\n\u001b[0m\u001b[1;32m 1577\u001b[0m \u001b[0;34mf\"No variable named {key!r}. Variables on the dataset include {shorten_list_repr(list(self.variables.keys()), max_items=10)}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1578\u001b[0m ) from e\n\u001b[1;32m 1579\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: \"No variable named 'heat_content_lprec'. Variables on the dataset include ['time', 'region', 'heat_content_lprec_mean', 'heat_content_lprec_int']\""
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"reg = 'Global'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "b8b4dc27-3be0-4973-8bdd-4a0de25e4316",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## PersianGulf"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "11b61be4-fdcf-475c-a524-2a3ac8c76ecf",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'PersianGulf'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "fa711e4f-4e29-4094-ada2-4ae38e234a82",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## RedSea"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a40d43fe-7d25-414c-8d87-79517880d35f",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'RedSea'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "88ad3620-a8da-4180-83d1-f39edfd5aae2",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## BlackSea"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6e85f68d-eb4e-44fe-acba-84c08de56905",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'BlackSea'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "9c5641d3-c954-411b-abee-d4825c4208ab",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## MedSea"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "67297917-8d56-4a6d-9d59-a478035429a1",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'MedSea'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "0543bf55-997b-4ac3-b22b-76c7f52ee97b",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## BalticSea"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "198da03e-467e-49f3-b8a5-2a31ad3b9711",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'BalticSea'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "44aa11d1-830c-45a8-9235-0a03ec35daa6",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## HudsonBay"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0fa02937-1b4e-4ade-a803-d2994b12545f",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'HudsonBay'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "e29ef839-e162-4ceb-927a-d82b7a59277e",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## Arctic"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "64880ae9-0688-4c3a-ab45-0e76d5284852",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'Arctic'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "1de03483-3233-4881-86a7-06813ce0211f",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## PacificOcean"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d8be41b0-a06e-4bac-ad2f-72b3dc32a3c1",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'PacificOcean'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "1b5bb92f-04ee-4edb-844a-dc32285a3017",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## AtlanticOcean "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c7a7a1b2-7665-4f42-aa57-3e8ccf255528",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'AtlanticOcean'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "bfa1406b-88fb-4638-a11c-9b530c50e48b",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## IndianOcean"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "674dc694-f91c-48d8-8cf9-18a9dc35dd87",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'IndianOcean'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "36a07721-9d05-42e2-b24d-a559f814478b",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## SouthernOcean"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5f6bc7ed-e959-49ad-8916-e307249b43fc",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'SouthernOcean'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "0b23cca5-e9a3-477a-a387-1c653c04989b",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## LabSea"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "51e70d80-7a39-4989-aecc-bd5016b324fa",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'LabSea'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "8f01e1c4-7a2b-491f-a311-1c52f299f45b",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## BaffinBay"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "64bdc239-6eef-4838-93d4-340528c4cde1",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'BaffinBay'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "5a24685a-397b-4381-bdfa-4bacdde702a8",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## Maritime"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9215bd4f-3bb8-41b7-a4b5-98d228cedfc6",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'Maritime'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
},
{
"cell_type": "markdown",
"id": "248dd205-fc5c-486c-b405-87109b2bf2f4",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## SouthernOcean60S"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1bed67b9-8a1a-4852-b49d-9c646f161e85",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"reg = 'SouthernOcean60S'\n",
"fig, ax = plt.subplots(nrows=1,ncols=1,figsize=fs)\n",
"for l, i in zip(label, range(len(label))):\n",
" ds[i][variable].sel(region=reg).plot(ax=ax, label=l, lw=3)\n",
"\n",
"#ax.set_ylabel(ds[variable].attrs['units'])\n",
"ax.set_xlabel('Year')\n",
"ax.grid()\n",
"ax.legend(ncol=3,loc=1);"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (mom6-tools)",
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"name": "mom6-tools"
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"end_time": "2025-03-26T20:36:44.367607",
"environment_variables": {},
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"input_path": "template.ipynb",
"output_path": "heat_content_lprec.ipynb",
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"nbformat_minor": 5
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