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Untitled.ipynb
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"%matplotlib inline\n",
"\n",
"import cartopy.crs as ccrs\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"import xarray as xr"
]
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"</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'air'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 730</li><li><span class='xr-has-index'>lat</span>: 25</li><li><span class='xr-has-index'>lon</span>: 53</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6b8144c9-1804-426f-a34a-35758056d9d9' class='xr-array-in' type='checkbox' ><label for='section-6b8144c9-1804-426f-a34a-35758056d9d9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-31.2775 -30.849998 -30.475002 ... 23.065002 22.715004 22.390007</span></div><pre class='xr-array-data'>array([[[-31.2775 , -30.849998 , -30.475002 , ..., -39.7775 ,\n",
" -37.975 , -35.475002 ],\n",
" [-28.575005 , -28.5775 , -28.874996 , ..., -41.9025 ,\n",
" -40.324997 , -36.85 ],\n",
" [-19.149998 , -19.927498 , -21.3275 , ..., -41.675 ,\n",
" -39.454998 , -34.524998 ],\n",
" ...,\n",
" [ 23.15001 , 22.824997 , 22.849998 , ..., 22.747505 ,\n",
" 22.170013 , 21.795006 ],\n",
" [ 23.174995 , 23.574997 , 23.592514 , ..., 23.022507 ,\n",
" 22.850006 , 22.397507 ],\n",
" [ 23.470009 , 23.845001 , 23.950005 , ..., 23.872505 ,\n",
" 23.897507 , 23.82251 ]],\n",
"\n",
" [[-29.550003 , -29.650005 , -29.849998 , ..., -34.177498 ,\n",
" -32.3525 , -30.0775 ],\n",
" [-25.3275 , -25.95 , -26.927498 , ..., -37.225 ,\n",
" -36.552498 , -34.550003 ],\n",
" [-19.627502 , -21.0775 , -22.852497 , ..., -35.452496 ,\n",
" -34.277496 , -31.25 ],\n",
" ...,\n",
" [ 22.972504 , 22.24501 , 22.049995 , ..., 22.99501 ,\n",
" 22.720001 , 22.0225 ],\n",
" [ 23.972504 , 23.647507 , 22.9225 , ..., 23.497498 ,\n",
" 23.622505 , 23.070007 ],\n",
" [ 24.545006 , 24.372513 , 23.875 , ..., 23.975006 ,\n",
" 23.997505 , 24.100006 ]],\n",
"\n",
" [[-29.2775 , -29.1525 , -29.177502 , ..., -33.6525 ,\n",
" -31.599998 , -29.25 ],\n",
" [-27.552498 , -26.900002 , -26.729996 , ..., -36.727497 ,\n",
" -35.5275 , -33.125 ],\n",
" [-20.975002 , -20.474998 , -20.649998 , ..., -32.127495 ,\n",
" -30.350002 , -27.454998 ],\n",
" ...,\n",
" [ 23.395004 , 22.57251 , 22.425003 , ..., 22.625 ,\n",
" 21.850006 , 21.150002 ],\n",
" [ 24.222504 , 23.674995 , 23.07251 , ..., 23.092514 ,\n",
" 22.850006 , 22.345009 ],\n",
" [ 24.625 , 24.345001 , 24.095001 , ..., 24.174995 ,\n",
" 24.1725 , 24.32251 ]],\n",
"\n",
" ...,\n",
"\n",
" [[-13.055 , -13.154995 , -13.682495 , ..., -23.23 ,\n",
" -24.5075 , -25.780003 ],\n",
" [ -6.6524963, -6.207489 , -6.404991 , ..., -20.155003 ,\n",
" -20.005001 , -19.477505 ],\n",
" [ -6.757492 , -6.8074875, -6.8799896, ..., -16.435001 ,\n",
" -14.129997 , -11.229996 ],\n",
" ...,\n",
" [ 21.519997 , 20.870003 , 20.9225 , ..., 24.322502 ,\n",
" 23.895004 , 22.920006 ],\n",
" [ 22.792511 , 22.897507 , 22.7725 , ..., 24.6175 ,\n",
" 24.097504 , 22.967506 ],\n",
" [ 24.297493 , 24.620003 , 24.2975 , ..., 24.947502 ,\n",
" 24.542496 , 23.970001 ]],\n",
"\n",
" [[-25.130001 , -24.405003 , -23.755005 , ..., -24.1325 ,\n",
" -24.807495 , -25.685001 ],\n",
" [-21.93 , -20.805 , -19.805004 , ..., -29.032505 ,\n",
" -28.0075 , -26.382504 ],\n",
" [-14.830006 , -14.380005 , -13.959999 , ..., -28.579998 ,\n",
" -25.085 , -20.382504 ],\n",
" ...,\n",
" [ 23.215004 , 22.265 , 22.015007 , ..., 23.740005 ,\n",
" 23.195007 , 22.195 ],\n",
" [ 24.3675 , 24.514992 , 23.895012 , ..., 23.415 ,\n",
" 22.995003 , 22.269997 ],\n",
" [ 25.417496 , 25.592499 , 25.192497 , ..., 23.642502 ,\n",
" 23.190002 , 22.720001 ]],\n",
"\n",
" [[-28.935001 , -29.535 , -30.385002 , ..., -29.410004 ,\n",
" -28.960003 , -28.46 ],\n",
" [-23.834995 , -24.060001 , -24.559998 , ..., -32.585 ,\n",
" -31.635002 , -30.035004 ],\n",
" [-10.209999 , -10.784988 , -11.434998 , ..., -33.684998 ,\n",
" -31.035 , -27.135002 ],\n",
" ...,\n",
" [ 21.69001 , 21.990005 , 23.489998 , ..., 22.265007 ,\n",
" 22.015 , 21.415009 ],\n",
" [ 23.390007 , 24.439995 , 24.94001 , ..., 22.415009 ,\n",
" 22.315002 , 21.640007 ],\n",
" [ 24.840012 , 25.590004 , 25.54 , ..., 23.065002 ,\n",
" 22.715004 , 22.390007 ]]], dtype=float32)</pre></div></li><li class='xr-section-item'><input id='section-89f12d56-40d3-4895-a976-47de1d022174' class='xr-section-summary-in' type='checkbox' checked><label for='section-89f12d56-40d3-4895-a976-47de1d022174' class='xr-section-summary' >Coordinates: <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-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2013-01-01 ... 2014-12-31</div><input id='attrs-446dd3cc-7f74-4a7a-9a79-efb3ad1f87cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-446dd3cc-7f74-4a7a-9a79-efb3ad1f87cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90a7a585-aafa-411a-b0fb-c2f700e46604' class='xr-var-data-in' type='checkbox'><label for='data-90a7a585-aafa-411a-b0fb-c2f700e46604' 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><pre class='xr-var-data'>array([&#x27;2013-01-01T00:00:00.000000000&#x27;, &#x27;2013-01-02T00:00:00.000000000&#x27;,\n",
" &#x27;2013-01-03T00:00:00.000000000&#x27;, ..., &#x27;2014-12-29T00:00:00.000000000&#x27;,\n",
" &#x27;2014-12-30T00:00:00.000000000&#x27;, &#x27;2014-12-31T00:00:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>75.0 72.5 70.0 ... 20.0 17.5 15.0</div><input id='attrs-9bd3e928-156b-49f2-8f58-f2b9d6d00739' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bd3e928-156b-49f2-8f58-f2b9d6d00739' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49d76d92-9e98-4ee5-affb-669382baab06' class='xr-var-data-in' type='checkbox'><label for='data-49d76d92-9e98-4ee5-affb-669382baab06' 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>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><pre class='xr-var-data'>array([75. , 72.5, 70. , 67.5, 65. , 62.5, 60. , 57.5, 55. , 52.5, 50. , 47.5,\n",
" 45. , 42.5, 40. , 37.5, 35. , 32.5, 30. , 27.5, 25. , 22.5, 20. , 17.5,\n",
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" 225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
" 250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
" 275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
" 300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
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"Coordinates:\n",
" * time (time) datetime64[ns] 2013-01-01 2013-01-02 ... 2014-12-31\n",
" * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n",
" * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds = xr.tutorial.load_dataset(\"air_temperature\")\n",
"\n",
"# to celsius\n",
"air = ds.air - 273.15\n",
"\n",
"# resample from 6-hourly to daily values\n",
"air = air.resample(time=\"D\").mean()\n",
"\n",
"air"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
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"</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'weights'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 25</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-36cebf50-fdbf-4a63-aeb5-4e0908301f59' class='xr-array-in' type='checkbox' ><label for='section-36cebf50-fdbf-4a63-aeb5-4e0908301f59' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.25881907 0.30070582 0.34202015 ... 0.9396926 0.95371693 0.9659258</span></div><pre class='xr-array-data'>array([0.25881907, 0.30070582, 0.34202015, 0.38268346, 0.42261827,\n",
" 0.4617486 , 0.49999997, 0.5372996 , 0.57357645, 0.6087614 ,\n",
" 0.6427876 , 0.67559016, 0.70710677, 0.7372773 , 0.76604444,\n",
" 0.7933533 , 0.81915206, 0.8433914 , 0.8660254 , 0.8870108 ,\n",
" 0.90630776, 0.9238795 , 0.9396926 , 0.95371693, 0.9659258 ],\n",
" dtype=float32)</pre></div></li><li class='xr-section-item'><input id='section-6ce7b6ad-6485-494b-8226-70cf8adfda19' class='xr-section-summary-in' type='checkbox' checked><label for='section-6ce7b6ad-6485-494b-8226-70cf8adfda19' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>75.0 72.5 70.0 ... 20.0 17.5 15.0</div><input id='attrs-59977ec7-6e5b-4e0a-8a3f-9fea2470b61b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59977ec7-6e5b-4e0a-8a3f-9fea2470b61b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94c5e246-f705-48c2-9d48-86d6385e93a5' class='xr-var-data-in' type='checkbox'><label for='data-94c5e246-f705-48c2-9d48-86d6385e93a5' 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>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><pre class='xr-var-data'>array([75. , 72.5, 70. , 67.5, 65. , 62.5, 60. , 57.5, 55. , 52.5, 50. , 47.5,\n",
" 45. , 42.5, 40. , 37.5, 35. , 32.5, 30. , 27.5, 25. , 22.5, 20. , 17.5,\n",
" 15. ], dtype=float32)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-0916112f-bbfc-490b-a478-ca05485b45b5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0916112f-bbfc-490b-a478-ca05485b45b5' 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.DataArray 'weights' (lat: 25)>\n",
"array([0.25881907, 0.30070582, 0.34202015, 0.38268346, 0.42261827,\n",
" 0.4617486 , 0.49999997, 0.5372996 , 0.57357645, 0.6087614 ,\n",
" 0.6427876 , 0.67559016, 0.70710677, 0.7372773 , 0.76604444,\n",
" 0.7933533 , 0.81915206, 0.8433914 , 0.8660254 , 0.8870108 ,\n",
" 0.90630776, 0.9238795 , 0.9396926 , 0.95371693, 0.9659258 ],\n",
" dtype=float32)\n",
"Coordinates:\n",
" * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weights = np.cos(np.deg2rad(air.lat))\n",
"weights.name = \"weights\"\n",
"weights"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1240de7d0>]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"air.weighted(weights).mean('lat').mean('lon').plot()\n",
"\n",
"air.weighted(weights).mean(('lat', 'lon')).plot()\n",
"\n",
"air.mean(('lat', 'lon')).plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1247e9650>]"
]
},
"execution_count": 11,
"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": [
"tmp = air.weighted(weights).mean('lat')\n",
"timeseries1 = tmp.mean('lon')\n",
"\n",
"(timeseries1 - air.weighted(weights).mean('lat').mean('lon')).plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.7"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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