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kuchaale/SSW_detection_ERA5.ipynb

Created June 25, 2021 11:07
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Split and discplament detection in ERA5
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SSW_detection_ERA5.ipynb
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"cells": [
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"cell_type": "markdown",
"id": "cabb5209",
"metadata": {},
"source": [
"# Libraries"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "0ab55978",
"metadata": {
"execution": {
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"source": [
"import numpy as np\n",
"#import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import xarray as xr\n",
"from pathlib import Path\n",
"import pandas as pd\n",
"#from scipy.stats import gaussian_kde, percentileofscore\n",
"import scipy.ndimage as ndimage\n",
"from datetime import timedelta\n",
"xr.set_options(display_style='html')"
]
},
{
"cell_type": "markdown",
"id": "7c3e0849",
"metadata": {},
"source": [
"# Functions"
]
},
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"cell_type": "code",
"execution_count": 2,
"id": "aaa06cb1",
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"execution": {
"iopub.execute_input": "2021-06-25T10:59:03.230680Z",
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"shell.execute_reply": "2021-06-25T10:59:03.241979Z",
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"def find_consecutive_exceedences_above_threshold(events, n_events, minDuration, t, timescale = None):\n",
" \"\"\"Find all MHW events of duration >= minDuration\n",
" Updates the mhw dictionary object.\n",
" \n",
" \"\"\"\n",
" mhw = {}\n",
" mhw['time_start'] = [] # datetime format\n",
" mhw['time_end'] = [] # datetime format\n",
" mhw['event_duration'] = []\n",
" for ev in range(1, n_events + 1): # for each event\n",
" event_duration = (events == ev).sum()\n",
" #print(event_duration)\n",
" if event_duration < minDuration: # is it longer than threshold?\n",
" continue\n",
" # extract the t where event starts and ends\n",
" #print(type(t[np.where(events == ev)]))\n",
" #print(type(t[np.where(events == ev)[0]]))\n",
" start = t[np.where(events == ev)[0][0]]\n",
" end = t[np.where(events == ev)[0][-1]]\n",
" #print(end.month)\n",
" mhw[\"time_start\"].append(start)\n",
" mhw[\"time_end\"].append(end)\n",
" mhw['event_duration'].append(event_duration)\n",
" \n",
" mhw = pd.DataFrame(mhw)\n",
" #print(mhw.empty)\n",
" # filter according to radiative timescale\n",
" if timescale is not None and not mhw.empty:\n",
" mask = mhw.time_start.diff(1) > pd.Timedelta(str(timescale)+' days')\n",
" mask[0] = True # include first event\n",
" mhw = mhw[mask]\n",
" \n",
" return mhw"
]
},
{
"cell_type": "markdown",
"id": "1274b5a1",
"metadata": {},
"source": [
"# Open data"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4acfb37e",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T10:59:03.244396Z",
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"shell.execute_reply": "2021-06-25T10:59:04.123778Z",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 7671)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2000-01-01T11:30:00 ... 2020-12-...\n",
"Data variables:\n",
" aspect_ratio (time) float64 1.464 1.491 1.493 ... 1.381 1.537 1.737\n",
" centroid_latitude (time) float64 82.62 83.48 83.71 ... 73.83 75.22 76.01</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-8bd50e86-1c9b-4cb6-a533-8833eb7c00d3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8bd50e86-1c9b-4cb6-a533-8833eb7c00d3' 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>: 7671</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2429d761-4e7d-4db5-a50f-c57e21f46b56' class='xr-section-summary-in' type='checkbox' checked><label for='section-2429d761-4e7d-4db5-a50f-c57e21f46b56' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01T11:30:00 ... 2020-12-...</div><input id='attrs-e428f7cb-e954-4e50-b865-894439f79dde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e428f7cb-e954-4e50-b865-894439f79dde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0df4f6e5-257d-46ec-ac16-f0ac75dad4ef' class='xr-var-data-in' type='checkbox'><label for='data-0df4f6e5-257d-46ec-ac16-f0ac75dad4ef' 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>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T11:30:00.000000000&#x27;, &#x27;2000-01-02T11:30:00.000000000&#x27;,\n",
" &#x27;2000-01-03T11:30:00.000000000&#x27;, ..., &#x27;2020-12-29T11:30:00.000000000&#x27;,\n",
" &#x27;2020-12-30T11:30:00.000000000&#x27;, &#x27;2020-12-31T11:30:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-70ea5cdb-12af-401c-bd25-9f5d2b8daae1' class='xr-section-summary-in' type='checkbox' checked><label for='section-70ea5cdb-12af-401c-bd25-9f5d2b8daae1' class='xr-section-summary' >Data variables: <span>(2)</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>aspect_ratio</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ab8965d6-cd34-4e77-85ac-424a569ae403' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab8965d6-cd34-4e77-85ac-424a569ae403' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbab2572-7c24-4501-95a8-36704c5e4910' class='xr-var-data-in' type='checkbox'><label for='data-fbab2572-7c24-4501-95a8-36704c5e4910' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.464039, 1.490872, 1.492935, ..., 1.380819, 1.536664, 1.7372 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centroid_latitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-15926426-9ff9-4cca-9ae4-36d7e457bb15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-15926426-9ff9-4cca-9ae4-36d7e457bb15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1beac03e-f040-4768-9bc7-a561ae31bbea' class='xr-var-data-in' type='checkbox'><label for='data-1beac03e-f040-4768-9bc7-a561ae31bbea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([82.624449, 83.481868, 83.707622, ..., 73.826339, 75.220947, 76.012344])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3046671a-aaec-4c5a-97bb-0805c2684156' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3046671a-aaec-4c5a-97bb-0805c2684156' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 7671)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2000-01-01T11:30:00 ... 2020-12-...\n",
"Data variables:\n",
" aspect_ratio (time) float64 ...\n",
" centroid_latitude (time) float64 ..."
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inpath = '/projekt4/hochatm/ERA5/'\n",
"ds = xr.open_adataset(f'{inpath}moment_calculation_ERA5.nc')\n",
"ds"
]
},
{
"cell_type": "markdown",
"id": "2a9a1ec5",
"metadata": {},
"source": [
"## DJF only"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "a8788151",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T11:01:32.849624Z",
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"shell.execute_reply": "2021-06-25T11:01:32.889359Z",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 1896)\n",
"Coordinates:\n",
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"Data variables:\n",
" aspect_ratio (time) float64 1.464 1.491 1.493 ... 1.381 1.537 1.737\n",
" centroid_latitude (time) float64 82.62 83.48 83.71 ... 73.83 75.22 76.01</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-a278b1f9-6730-4395-a697-3b0c050e6bbe' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a278b1f9-6730-4395-a697-3b0c050e6bbe' 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>: 1896</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3f44c855-7695-4986-991d-68ff6e877bff' class='xr-section-summary-in' type='checkbox' checked><label for='section-3f44c855-7695-4986-991d-68ff6e877bff' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01T11:30:00 ... 2020-12-...</div><input id='attrs-44cfcf96-2c4c-4029-8ad3-1c57c9bd69ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44cfcf96-2c4c-4029-8ad3-1c57c9bd69ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8e8f73f-b0aa-40f6-ae20-9d758a49a82c' class='xr-var-data-in' type='checkbox'><label for='data-e8e8f73f-b0aa-40f6-ae20-9d758a49a82c' 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>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T11:30:00.000000000&#x27;, &#x27;2000-01-02T11:30:00.000000000&#x27;,\n",
" &#x27;2000-01-03T11:30:00.000000000&#x27;, ..., &#x27;2020-12-29T11:30:00.000000000&#x27;,\n",
" &#x27;2020-12-30T11:30:00.000000000&#x27;, &#x27;2020-12-31T11:30:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-20b87e20-e118-4112-9e4e-82e63092aa6b' class='xr-section-summary-in' type='checkbox' checked><label for='section-20b87e20-e118-4112-9e4e-82e63092aa6b' class='xr-section-summary' >Data variables: <span>(2)</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>aspect_ratio</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.464 1.491 1.493 ... 1.537 1.737</div><input id='attrs-f4c658a7-7362-4c74-adab-9c0f1a43548d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f4c658a7-7362-4c74-adab-9c0f1a43548d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c0cb23f-c525-4ae0-83e8-e593d7546273' class='xr-var-data-in' type='checkbox'><label for='data-0c0cb23f-c525-4ae0-83e8-e593d7546273' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.464039, 1.490872, 1.492935, ..., 1.380819, 1.536664, 1.7372 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centroid_latitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>82.62 83.48 83.71 ... 75.22 76.01</div><input id='attrs-af97ff4d-d1d5-4b95-b26e-3cb35fb74964' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af97ff4d-d1d5-4b95-b26e-3cb35fb74964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f12ddc2b-b525-47d8-bf0b-71891d72b682' class='xr-var-data-in' type='checkbox'><label for='data-f12ddc2b-b525-47d8-bf0b-71891d72b682' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([82.624449, 83.481868, 83.707622, ..., 73.826339, 75.220947, 76.012344])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-54028ca9-c921-4ba8-8ac9-4df669552fd7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-54028ca9-c921-4ba8-8ac9-4df669552fd7' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 1896)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2000-01-01T11:30:00 ... 2020-12-...\n",
"Data variables:\n",
" aspect_ratio (time) float64 1.464 1.491 1.493 ... 1.381 1.537 1.737\n",
" centroid_latitude (time) float64 82.62 83.48 83.71 ... 73.83 75.22 76.01"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mask = (ds.time.dt.month == 12) | \\\n",
" (ds.time.dt.month == 1) | (ds.time.dt.month == 2) #| (ds.time.dt.month == 3)(ds.time.dt.month == 11) |\n",
"ds_sel = ds.sel(time = mask)\n",
"ds_sel"
]
},
{
"cell_type": "markdown",
"id": "e3357075",
"metadata": {},
"source": [
"## Analysis"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "dbe24ead",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T11:01:34.699228Z",
"iopub.status.busy": "2021-06-25T11:01:34.698675Z",
"iopub.status.idle": "2021-06-25T11:01:34.713944Z",
"shell.execute_reply": "2021-06-25T11:01:34.713005Z",
"shell.execute_reply.started": "2021-06-25T11:01:34.699161Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"aspect ratio threshold: [2.79789406] centroid latitude threshold: [64.22916133]\n"
]
}
],
"source": [
"nc_days = 7 # number of consecutive days below or above threshold\n",
"timescale = 30 # gap between events\n",
"perc = 5/100. # percentile to estimate thresholds below\n",
"ar_threshold= ds_sel['aspect_ratio'].quantile([1-perc], dim = ['time']).values\n",
"cl_threshold= ds_sel['centroid_latitude'].quantile([perc], dim = ['time']).values\n",
"print('aspect ratio threshold: ', ar_threshold, 'centroid latitude threshold: ', cl_threshold)"
]
},
{
"cell_type": "markdown",
"id": "58e0b403",
"metadata": {},
"source": [
"### Splits"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "81d3a87a",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T11:01:49.515080Z",
"iopub.status.busy": "2021-06-25T11:01:49.514508Z",
"iopub.status.idle": "2021-06-25T11:01:49.612772Z",
"shell.execute_reply": "2021-06-25T11:01:49.611612Z",
"shell.execute_reply.started": "2021-06-25T11:01:49.515012Z"
}
},
"outputs": [],
"source": [
"temp = ds['aspect_ratio']\n",
"exceed_bool = temp - ar_threshold # or 2.3999 from Seviour et al\n",
"exceed_bool[exceed_bool <= 0] = False\n",
"exceed_bool[exceed_bool > 0] = True\n",
"\n",
"# Find contiguous regions of exceed_bool = True\n",
"events, n_events = ndimage.label(exceed_bool)\n",
"mhw_split = find_consecutive_exceedences_above_threshold(events, n_events, nc_days, \\\n",
" temp.time.to_index(), timescale = timescale)\n",
"\n",
"mask2drop = (mhw_split.time_start.dt.month == 1) | \\\n",
" (mhw_split.time_start.dt.month == 12) | \\\n",
" (mhw_split.time_start.dt.month == 2)\n",
"mhw_split = mhw_split[mask2drop]\n",
"\n",
"counted = mhw_split.groupby(mhw_split.time_start.dt.month).count().reindex([12,1,2])['event_duration']\n",
"#counted.name = ens\n",
"counted.index.name = 'month'\n",
"\n",
"\n",
"ed = mhw_split['event_duration']\n",
"#ave_duration_ls.append(ed.mean())\n",
"#std_duration_ls.append(ed.std())"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "f5b60db8",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T11:01:51.710661Z",
"iopub.status.busy": "2021-06-25T11:01:51.710112Z",
"iopub.status.idle": "2021-06-25T11:01:51.774666Z",
"shell.execute_reply": "2021-06-25T11:01:51.773526Z",
"shell.execute_reply.started": "2021-06-25T11:01:51.710595Z"
}
},
"outputs": [
{
"data": {
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" vertical-align: top;\n",
" }\n",
"\n",
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" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>time_start</th>\n",
" <th>time_end</th>\n",
" <th>event_duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2003-01-17 11:30:00</td>\n",
" <td>2003-01-23 11:30:00</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2009-01-19 11:30:00</td>\n",
" <td>2009-01-27 11:30:00</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2013-01-06 11:30:00</td>\n",
" <td>2013-01-12 11:30:00</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2014-02-03 11:30:00</td>\n",
" <td>2014-02-10 11:30:00</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2019-01-08 11:30:00</td>\n",
" <td>2019-01-20 11:30:00</td>\n",
" <td>13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" time_start time_end event_duration\n",
"0 2003-01-17 11:30:00 2003-01-23 11:30:00 7\n",
"1 2009-01-19 11:30:00 2009-01-27 11:30:00 9\n",
"2 2013-01-06 11:30:00 2013-01-12 11:30:00 7\n",
"3 2014-02-03 11:30:00 2014-02-10 11:30:00 8\n",
"4 2019-01-08 11:30:00 2019-01-20 11:30:00 13"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mhw_split.reset_index(drop = True)"
]
},
{
"cell_type": "markdown",
"id": "6da06d85",
"metadata": {},
"source": [
"### Displacements"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "0756ba2f",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T11:02:51.069396Z",
"iopub.status.busy": "2021-06-25T11:02:51.068806Z",
"iopub.status.idle": "2021-06-25T11:02:51.101770Z",
"shell.execute_reply": "2021-06-25T11:02:51.100951Z",
"shell.execute_reply.started": "2021-06-25T11:02:51.069327Z"
}
},
"outputs": [],
"source": [
"temp = ds['centroid_latitude']\n",
"exceed_bool = temp - cl_threshold # or 66.0000001 from Seviour et al\n",
"exceed_bool[exceed_bool >= 0] = False\n",
"exceed_bool[exceed_bool < 0] = True\n",
"\n",
"# Find contiguous regions of exceed_bool = True\n",
"events, n_events = ndimage.label(exceed_bool)\n",
"mhw_displ = find_consecutive_exceedences_above_threshold(events, n_events, nc_days, \\\n",
" temp.time.to_index(), timescale = timescale)\n",
"\n",
"mask2drop = (mhw_displ.time_start.dt.month == 1) | \\\n",
" (mhw_displ.time_start.dt.month == 12) | \\\n",
" (mhw_displ.time_start.dt.month == 2)\n",
"mhw_displ = mhw_displ[mask2drop]\n",
"\n",
"counted = mhw_displ.groupby(mhw_displ.time_start.dt.month).count().reindex([12,1,2])['event_duration']\n",
"counted.index.name = 'month'\n",
"\n",
"ed = mhw_displ['event_duration']"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d44200ea",
"metadata": {
"execution": {
"iopub.execute_input": "2021-06-25T11:02:52.281956Z",
"iopub.status.busy": "2021-06-25T11:02:52.281399Z",
"iopub.status.idle": "2021-06-25T11:02:52.296582Z",
"shell.execute_reply": "2021-06-25T11:02:52.295606Z",
"shell.execute_reply.started": "2021-06-25T11:02:52.281890Z"
}
},
"outputs": [
{
"data": {
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" <thead>\n",
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" <th>time_end</th>\n",
" <th>event_duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2001-02-13 11:30:00</td>\n",
" <td>2001-02-23 11:30:00</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2004-01-02 11:30:00</td>\n",
" <td>2004-01-17 11:30:00</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2006-01-19 11:30:00</td>\n",
" <td>2006-02-10 11:30:00</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2009-01-28 11:30:00</td>\n",
" <td>2009-02-28 11:30:00</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2013-01-13 11:30:00</td>\n",
" <td>2013-01-20 11:30:00</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2018-02-12 11:30:00</td>\n",
" <td>2018-02-22 11:30:00</td>\n",
" <td>11</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" time_start time_end event_duration\n",
"0 2001-02-13 11:30:00 2001-02-23 11:30:00 11\n",
"1 2004-01-02 11:30:00 2004-01-17 11:30:00 16\n",
"2 2006-01-19 11:30:00 2006-02-10 11:30:00 23\n",
"3 2009-01-28 11:30:00 2009-02-28 11:30:00 32\n",
"4 2013-01-13 11:30:00 2013-01-20 11:30:00 8\n",
"5 2018-02-12 11:30:00 2018-02-22 11:30:00 11"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mhw_displ.reset_index(drop = True)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:.conda-moje] *",
"language": "python",
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