diff --git a/notebooks/Calc_cloud_base_and_top.ipynb b/notebooks/Calc_cloud_base_and_top.ipynb new file mode 100644 index 0000000..9d2861e --- /dev/null +++ b/notebooks/Calc_cloud_base_and_top.ipynb @@ -0,0 +1,1016 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Clouds over SGP for April 4, 2019\n", + "\n", + "Looking at LASSO data for April 4, 2019 to see meterological data and calculate cloud base and cloud top." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime\n", + "import numpy as np\n", + "import xarray as xr\n", + "import xwrf\n", + "\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bring in the data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here is the raw model output from LASSO." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "path_shcu_root = \"/data/project/ARM_Summer_School_2024_Data/lasso_tutorial/ShCu/untar\" # on Jupyter\n", + "\n", + "case_date = datetime(2019, 4, 4)\n", + "sim_id = 7\n", + "\n", + "ds_stat = xr.open_dataset(f\"{path_shcu_root}/{case_date:%Y%m%d}/sim{sim_id:04d}/raw_model/wrfstat_d01_{case_date:%Y-%m-%d_12:00:00}.nc\")\n", + "ds_stat\n", + "\n", + "ds_stat[\"Time\"] = ds_stat[\"XTIME\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Find the indices of the boundary layer depth - in case we happen to care about that later" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.DataArray 'bottom_top' (Time: 91)> Size: 728B\n",
+       "array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  1.,  1.,\n",
+       "        2.,  2.,  2.,  3.,  3.,  3.,  2.,  2.,  2.,  3.,  3.,  3.,  4.,\n",
+       "        4.,  4.,  5.,  5.,  5.,  5.,  5.,  6.,  6.,  7.,  7.,  7.,  7.,\n",
+       "        8., 10., 12., 13., 13., 12., 12., 12., 11., 11., 11., 10., 11.,\n",
+       "       11., 11., 10., 11., 10., 10., 10., 10., 10., 10., 10.,  9.,  9.,\n",
+       "        9.,  9.,  8.,  8.,  7.,  7.,  6.,  6.,  4.,  3.,  0.,  0.,  0.,\n",
+       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.])\n",
+       "Coordinates:\n",
+       "    XTIME    (Time) datetime64[ns] 728B 2019-04-04T12:00:00 ... 2019-04-05T03...\n",
+       "Dimensions without coordinates: Time
" + ], + "text/plain": [ + " Size: 728B\n", + "array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1.,\n", + " 2., 2., 2., 3., 3., 3., 2., 2., 2., 3., 3., 3., 4.,\n", + " 4., 4., 5., 5., 5., 5., 5., 6., 6., 7., 7., 7., 7.,\n", + " 8., 10., 12., 13., 13., 12., 12., 12., 11., 11., 11., 10., 11.,\n", + " 11., 11., 10., 11., 10., 10., 10., 10., 10., 10., 10., 9., 9.,\n", + " 9., 9., 8., 8., 7., 7., 6., 6., 4., 3., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])\n", + "Coordinates:\n", + " XTIME (Time) datetime64[ns] 728B 2019-04-04T12:00:00 ... 2019-04-05T03...\n", + "Dimensions without coordinates: Time" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_stat[\"bottom_top\"] = ds_stat.bottom_top\n", + "ds_stat\n", + "ki = ds_stat['CSP_THL'].idxmin(dim='bottom_top')\n", + "ki" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Let's look at some meteorological info for this date" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_ql = ds_stat['CSP_QL'].assign_coords(height = (ds_stat[\"CSP_Z\"]))\n", + "plot_ql.isel(Time=slice(6,None)).plot(x = 'Time',y = 'height', ylim=[0,7000])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_lwc = ds_stat['CSP_LWC'].assign_coords(height = (ds_stat[\"CSP_Z\"]))\n", + "plot_lwc.isel(Time=slice(6,None)).plot(x = 'Time',y = 'height', ylim=[0,7000])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_thl = ds_stat['CSP_TH'].assign_coords(height = (ds_stat[\"CSP_Z\"]))\n", + "plot_thl.isel(Time=slice(6,None)).plot(x = 'Time',y = 'height', ylim=[0,7000],vmin=298,vmax=320)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Fix some height things so that we can plot...\n", + "\n", + "The z values are time dependent, so we need to deal with the height values by assuming that the first time step is close enough\n", + "\n", + "We also need to make bottom_top a coordinate so that we aren't yelled at by errors" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "ds_stat[\"bottom_top\"] = ds_stat.bottom_top" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "ds_stat['bottom_top'] = ds_stat['CSP_Z'].isel(Time = 1).values" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 15.215184, 45.605114, 75.94632 , 106.27506 ,\n", + " 136.59618 , 166.91183 , 197.23079 , 227.55254 ,\n", + " 257.86115 , 288.1541 , 318.44684 , 348.74237 ,\n", + " 379.03595 , 409.33054 , 439.62314 , 469.91293 ,\n", + " 500.20493 , 530.4964 , 560.79016 , 591.11 ,\n", + " 621.4132 , 651.6837 , 681.9462 , 712.2066 ,\n", + " 742.4813 , 772.7549 , 803.0155 , 833.27167 ,\n", + " 863.53253 , 893.79333 , 924.05646 , 954.3343 ,\n", + " 984.625 , 1014.9191 , 1045.2263 , 1075.5452 ,\n", + " 1105.8611 , 1136.1669 , 1166.4724 , 1196.7739 ,\n", + " 1227.061 , 1257.3391 , 1287.613 , 1317.8835 ,\n", + " 1348.1545 , 1378.427 , 1408.7014 , 1438.9777 ,\n", + " 1469.2583 , 1499.5316 , 1529.7927 , 1560.058 ,\n", + " 1590.3406 , 1620.6185 , 1650.8711 , 1681.1194 ,\n", + " 1711.373 , 1741.6282 , 1771.863 , 1802.084 ,\n", + " 1832.3059 , 1862.5199 , 1892.7288 , 1922.9358 ,\n", + " 1953.1406 , 1983.3519 , 2013.5719 , 2043.8057 ,\n", + " 2074.0422 , 2104.2583 , 2134.4634 , 2164.6702 ,\n", + " 2194.8755 , 2225.0752 , 2255.268 , 2285.4622 ,\n", + " 2315.6643 , 2345.861 , 2376.0405 , 2406.2173 ,\n", + " 2436.3982 , 2466.58 , 2496.766 , 2526.9626 ,\n", + " 2557.1538 , 2587.3315 , 2617.5088 , 2647.6782 ,\n", + " 2677.8381 , 2708.0024 , 2738.185 , 2768.3545 ,\n", + " 2798.5044 , 2828.6675 , 2858.8428 , 2889.018 ,\n", + " 2919.1719 , 2949.3062 , 2979.443 , 3009.5776 ,\n", + " 3039.703 , 3069.83 , 3099.9514 , 3130.066 ,\n", + " 3160.1882 , 3190.3154 , 3220.4434 , 3250.5742 ,\n", + " 3280.702 , 3310.8237 , 3340.931 , 3371.0188 ,\n", + " 3401.102 , 3431.1902 , 3461.293 , 3491.3945 ,\n", + " 3521.4683 , 3551.5403 , 3581.6167 , 3611.6907 ,\n", + " 3641.769 , 3671.8528 , 3701.933 , 3732.0137 ,\n", + " 3762.0945 , 3792.1685 , 3822.2473 , 3852.3481 ,\n", + " 3882.4512 , 3912.5269 , 3942.5942 , 3972.6646 ,\n", + " 4002.7378 , 4032.811 , 4062.8813 , 4092.9517 ,\n", + " 4123.02 , 4153.09 , 4183.161 , 4213.229 ,\n", + " 4243.2993 , 4273.3696 , 4303.4385 , 4333.5093 ,\n", + " 4363.5786 , 4393.6553 , 4423.735 , 4453.8096 ,\n", + " 4483.88 , 4513.9585 , 4544.05 , 4574.1533 ,\n", + " 4604.2773 , 4634.3887 , 4664.45 , 4694.4854 ,\n", + " 4724.5103 , 4754.531 , 4784.547 , 4814.564 ,\n", + " 4844.583 , 4874.598 , 4904.608 , 4934.618 ,\n", + " 4964.6323 , 4994.6475 , 5024.664 , 5055.481 ,\n", + " 5087.9473 , 5122.214 , 5158.3315 , 5196.3467 ,\n", + " 5236.46 , 5278.7236 , 5323.2344 , 5370.1943 ,\n", + " 5419.6626 , 5471.841 , 5526.9717 , 5585.007 ,\n", + " 5646.068 , 5710.3896 , 5778.146 , 5849.596 ,\n", + " 5924.9067 , 6004.247 , 6087.865 , 6176.043 ,\n", + " 6268.9814 , 6366.915 , 6470.13 , 6578.867 ,\n", + " 6693.4404 , 6814.2485 , 6941.7056 , 7076.026 ,\n", + " 7217.5884 , 7366.8086 , 7524.0337 , 7689.741 ,\n", + " 7864.397 , 8048.4517 , 8242.3955 , 8446.839 ,\n", + " 8662.638 , 8890.157 , 9130.356 , 9383.886 ,\n", + " 9650.805 , 9932.354 , 10227.337 , 10527.948 ,\n", + " 10828.727 , 11129.923 , 11431.03 , 11731.875 ,\n", + " 12032.737 , 12333.832 , 12635.557 , 12937.003 ,\n", + " 13237.864 , 13538.295 , 13838.356 , 14138.922 ,\n", + " 14440.3545 , 14719.19 ], dtype=float32)" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_stat['bottom_top'].values # make sure that these are heights and not indicies" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Calculate cloud base and top from the liquid water conent and the liquid water mixing ratio\n" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Size: 364B\n", + "array([ nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, 742.4813 , 772.7549 ,\n", + " 772.7549 , 803.0155 , 833.27167, 863.53253, 893.79333,\n", + " 833.27167, 863.53253, 863.53253, 863.53253, 833.27167,\n", + " 651.6837 , 742.4813 , 772.7549 , 651.6837 , 469.91293,\n", + " 681.9462 , 893.79333, 803.0155 , 984.625 , 651.6837 ,\n", + " 954.3343 , 621.4132 , 1075.5452 , 1075.5452 , 1105.8611 ,\n", + " 1105.8611 , 1136.1669 , 1136.1669 , 1136.1669 , 1166.4724 ,\n", + " 1166.4724 , 1166.4724 , 1166.4724 , 1196.7739 , 1196.7739 ,\n", + " 1196.7739 , 1196.7739 , 1196.7739 , 1227.061 , 1257.3391 ,\n", + " 1227.061 , 1317.8835 , 1348.1545 , 1348.1545 , 1348.1545 ,\n", + " 1348.1545 , 1348.1545 , 1348.1545 , 1348.1545 , 1348.1545 ,\n", + " nan, nan, nan, nan, nan,\n", + " nan], dtype=float32)\n", + "Coordinates:\n", + " XTIME (Time) datetime64[ns] 728B ...\n", + " * Time (Time) datetime64[ns] 728B 2019-04-04T12:00:00 ... 2019-04-05T03...\n", + " Size: 364B\n", + "array([ nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, 803.0155, 954.3343, 1075.5452,\n", + " 1227.061 , 1378.427 , 1499.5316, 1560.058 , 1620.6185, 1741.6282,\n", + " 1741.6282, 1802.084 , 1862.5199, 1892.7288, 1922.9358, 1922.9358,\n", + " 2074.0422, 2043.8057, 1983.3519, 1983.3519, 1953.1406, 1953.1406,\n", + " 1983.3519, 2013.5719, 2013.5719, 2013.5719, 1983.3519, 2013.5719,\n", + " 2013.5719, 1953.1406, 1983.3519, 1953.1406, 1953.1406, 1953.1406,\n", + " 2043.8057, 1953.1406, 1983.3519, 1862.5199, 1892.7288, 1862.5199,\n", + " 1832.3059, 1771.863 , 1741.6282, 1681.1194, 1681.1194, 1650.8711,\n", + " 1620.6185, 1560.058 , 1529.7927, 1469.2583, 1438.9777, 1408.7014,\n", + " 1378.427 , nan, nan, nan, nan, nan,\n", + " nan], dtype=float32)\n", + "Coordinates:\n", + " XTIME (Time) datetime64[ns] 728B ...\n", + " * Time (Time) datetime64[ns] 728B 2019-04-04T12:00:00 ... 2019-04-05T03...\n" + ] + } + ], + "source": [ + "ds_stat['cb_lwc'] = (ds_stat['CSP_LWC']>0).idxmax(dim = 'bottom_top')\n", + "ds_stat['cb_lwc'] = ds_stat['cb_lwc'].where(ds_stat['cb_lwc']>ds_stat['bottom_top'][0])\n", + "print(ds_stat['cb_lwc'])\n", + "\n", + "ds_stat['ct_lwc'] = ((ds_stat['CSP_LWC'].isel(bottom_top = slice(None, None, -1)))>0).idxmax(dim='bottom_top')\n", + "ds_stat['ct_lwc'] = ds_stat['ct_lwc'].where(ds_stat['ct_lwc']" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ds_stat['cb_lwc'].plot(label='base',ylim = (0,7000),xlim = (ds_stat['CSP_Z'].Time[6],ds_stat['CSP_Z'].Time[-1]))\n", + "ds_stat['ct_lwc'].plot(label='top',ylim = (0,7000),xlim = (ds_stat['CSP_Z'].Time[6],ds_stat['CSP_Z'].Time[-1]))\n", + "plt.legend()\n", + "plt.ylabel('Height (m)')\n", + "plt.xlabel('Time (UTC)')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Size: 364B\n", + "array([ nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan,\n", + " nan, nan, nan, 742.4813 , 772.7549 ,\n", + " 772.7549 , 803.0155 , 833.27167, 863.53253, 893.79333,\n", + " 833.27167, 863.53253, 863.53253, 863.53253, 833.27167,\n", + " 651.6837 , 742.4813 , 772.7549 , 651.6837 , 469.91293,\n", + " 681.9462 , 893.79333, 803.0155 , 984.625 , 651.6837 ,\n", + " 954.3343 , 621.4132 , 1075.5452 , 1075.5452 , 1105.8611 ,\n", + " 1105.8611 , 1136.1669 , 1136.1669 , 1136.1669 , 1166.4724 ,\n", + " 1166.4724 , 1166.4724 , 1166.4724 , 1196.7739 , 1196.7739 ,\n", + " 1196.7739 , 1196.7739 , 1196.7739 , 1227.061 , 1257.3391 ,\n", + " 1227.061 , 1317.8835 , 1348.1545 , 1348.1545 , 1348.1545 ,\n", + " 1348.1545 , 1348.1545 , 1348.1545 , 1348.1545 , 1348.1545 ,\n", + " nan, nan, nan, nan, nan,\n", + " nan], dtype=float32)\n", + "Coordinates:\n", + " XTIME (Time) datetime64[ns] 728B ...\n", + " * Time (Time) datetime64[ns] 728B 2019-04-04T12:00:00 ... 2019-04-05T03...\n", + " Size: 364B\n", + "array([ nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, nan, nan, nan,\n", + " nan, nan, nan, 803.0155, 954.3343, 1075.5452,\n", + " 1227.061 , 1378.427 , 1499.5316, 1560.058 , 1620.6185, 1741.6282,\n", + " 1741.6282, 1802.084 , 1862.5199, 1892.7288, 1922.9358, 1922.9358,\n", + " 2074.0422, 2043.8057, 1983.3519, 1983.3519, 1953.1406, 1953.1406,\n", + " 1983.3519, 2013.5719, 2013.5719, 2013.5719, 1983.3519, 2013.5719,\n", + " 2013.5719, 1953.1406, 1983.3519, 1953.1406, 1953.1406, 1953.1406,\n", + " 2043.8057, 1953.1406, 1983.3519, 1862.5199, 1892.7288, 1862.5199,\n", + " 1832.3059, 1771.863 , 1741.6282, 1681.1194, 1681.1194, 1650.8711,\n", + " 1620.6185, 1560.058 , 1529.7927, 1469.2583, 1438.9777, 1408.7014,\n", + " 1378.427 , nan, nan, nan, nan, nan,\n", + " nan], dtype=float32)\n", + "Coordinates:\n", + " XTIME (Time) datetime64[ns] 728B ...\n", + " * Time (Time) datetime64[ns] 728B 2019-04-04T12:00:00 ... 2019-04-05T03...\n" + ] + } + ], + "source": [ + "ds_stat['cb_ql'] = (ds_stat['CSP_LWC']>0).idxmax(dim = 'bottom_top')\n", + "ds_stat['cb_ql'] = ds_stat['cb_ql'].where(ds_stat['cb_ql']>ds_stat['bottom_top'][0])\n", + "print(ds_stat['cb_ql'])\n", + "\n", + "ds_stat['ct_ql'] = ((ds_stat['CSP_LWC'].isel(bottom_top = slice(None, None, -1)))>0).idxmax(dim='bottom_top')\n", + "ds_stat['ct_ql'] = ds_stat['ct_ql'].where(ds_stat['ct_ql']" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ds_stat['cb_ql'].plot(label='base',ylim = (0,7000),xlim = (ds_stat['CSP_Z'].Time[6],ds_stat['CSP_Z'].Time[-1]))\n", + "ds_stat['ct_ql'].plot(label='top',ylim = (0,7000),xlim = (ds_stat['CSP_Z'].Time[6],ds_stat['CSP_Z'].Time[-1]))\n", + "plt.legend()\n", + "plt.ylabel('Height (m)')\n", + "plt.xlabel('Time (UTC)')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## They're the same - how fun!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.9" + }, + "nbdime-conflicts": { + "local_diff": [ + { + "diff": [ + { + "diff": [ + { + "key": 0, + "op": "addrange", + "valuelist": [ + "Python 3" + ] + }, + { + "key": 0, + "length": 1, + "op": "removerange" + } + ], + "key": "display_name", + "op": "patch" + } + ], + "key": "kernelspec", + "op": "patch" + } + ], + "remote_diff": [ + { + "diff": [ + { + "diff": [ + { + "key": 0, + "op": 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