Updating Docs for commit d593cf3 made on 2024-09-18T13:09:01+00:00 fr…

…om refs/heads/main by slarosa

README.md

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+# GitHub Pages Cache
+Nothing to see here. The contents of this branch are essentially a cache that's not intended to be viewed on github.com.
+If you're looking to update our documentation, check the relevant development branch's 'docs/' dir.

en/main/.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 89cee837b0976258984cb53dbc57f17c
+tags: 645f666f9bcd5a90fca523b33c5a78b7

en/main/_downloads/022ea1c8a367f324a3b651e5af565388/plot_bt_igra2.py

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+"""
+Performing Upwelling Brightness Temperature calculation using IGRA2 Upper Air Observations (with Extrapolation).
+================================================================================================================
+"""
+
+# %%
+# This example shows how to use the
+# :py:class:`pyrtlib.tb_spectrum.TbCloudRTE` method to calculate brightness temperature from satellite (upwelling) using
+# observations from IGRA2 Upper Air Archive and comparison of BT with the extrapoletd profile.
+
+import numpy as np
+from datetime import datetime
+
+import matplotlib.pyplot as plt
+plt.rcParams.update({'font.size': 15})
+
+from pyrtlib.tb_spectrum import TbCloudRTE
+from pyrtlib.climatology import ProfileExtrapolation
+from pyrtlib.utils import dewpoint2rh, to_kelvin
+from pyrtlib.absorption_model import H2OAbsModel
+from pyrtlib.apiwebservices import IGRAUpperAir
+
+date = datetime(2020, 6, 1, 12)
+station = 'SPM00008221'
+df_igra2, header = IGRAUpperAir.request_data(date, station)
+
+df_igra2 = df_igra2[df_igra2.pressure.notna() & 
+                    df_igra2.temperature.notna() & 
+                    df_igra2.dewpoint.notna() & 
+                    df_igra2.height.notna()]
+
+z, p, t = df_igra2.height.values / 1000, df_igra2.pressure.values, to_kelvin(df_igra2.temperature.values)
+
+rh = dewpoint2rh(df_igra2.dewpoint, df_igra2.temperature).values
+
+mdl = 'R21SD'
+frq = np.arange(20, 201, 1)
+nf = len(frq)
+
+rte = TbCloudRTE(z, p, t, rh, frq)
+rte.init_absmdl('R20')
+H2OAbsModel.model = 'R21SD'
+H2OAbsModel.set_ll()
+df = rte.execute()
+df = df.set_index(frq)
+
+# %%
+# Extrapolation of profile
+ex = ProfileExtrapolation()
+zz, pp, tt, rhh = ex.profile_extrapolation(header.latitude.values[0], 6, z, (p, t, rh))
+
+rte = TbCloudRTE(zz, pp, tt, rhh, frq)
+rte.init_absmdl('R20')
+H2OAbsModel.model = 'R21SD'
+H2OAbsModel.set_ll()
+dff = rte.execute()
+dff = dff.set_index(frq)
+
+#%%
+# Plotting
+fig, ax = plt.subplots(1, 1, figsize=(12, 8))
+plt.suptitle("{}, {}, {} - {}".format(header.site_id.values[0], header.latitude.values[0], header.longitude.values[0], header.date.values[0]), y=0.96)
+plt.title("IGRA2 UpperAir Radiosonde Archive", fontsize=10, ha='center')
+ax.set_xlabel('Frequency [GHz]')
+ax.set_ylabel('${T_B}$ [K]')
+df.tbtotal.plot(ax=ax, linewidth=2, label='{} - {}'.format(header.site_id.values[0], mdl))
+dff.tbtotal.plot(ax=ax, linewidth=2, label='Extrap {} - {}'.format(header.site_id.values[0], mdl))
+ax.grid(True, 'both')
+ax.legend()
+plt.show()
+
+#%%
+# Difference BT
+
+df['delta'] = dff.tbtotal - df.tbtotal
+df.delta.plot(linewidth=2, xlabel='Frequency [GHz]', ylabel='$\Delta T_B$ [K]', grid=True, figsize=(12, 8))

en/main/_downloads/04ebb85e301429d7cb4d63349c11cf97/generic_tutorial.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Generic Example\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "This example shows how to use calculate the upwelling brigthness temperature by using R16 and R03 absorption model\nand then plotting them difference.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\n\nplt.rcParams.update({'font.size': 15})\nimport matplotlib.ticker as ticker\nfrom matplotlib.ticker import ScalarFormatter\nimport numpy as np"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Import pyrtlib package\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "from pyrtlib.climatology import AtmosphericProfiles as atmp\nfrom pyrtlib.tb_spectrum import TbCloudRTE\nfrom pyrtlib.utils import ppmv2gkg, mr2rh"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "atm = ['Tropical',\n       'Midlatitude Summer',\n       'Midlatitude Winter',\n       'Subarctic Summer',\n       'Subarctic Winter',\n       'U.S. Standard']"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Load standard atmosphere (low res at lower levels, only 1 level within 1 km) and define which absorption model will be used.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "z, p, d, t, md = atmp.gl_atm(atmp.TROPICAL)\ngkg = ppmv2gkg(md[:, atmp.H2O], atmp.H2O)\nrh = mr2rh(p, t, gkg)[0] / 100\n\nmdl = 'R16'"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Performing upwelling brightness temperature calculation\n\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Default calculatoin consideres no cloud\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "ang = np.array([90.])\nfrq = np.arange(20, 201, 1)\nnf = len(frq)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Setup matplotlib plot\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, ax = plt.subplots(1, 1, figsize=(12,8))\nax.set_xlabel('Frequency [GHz]')\nax.set_ylabel('${T_B}$ [K]')\n\nrte = TbCloudRTE(z, p, t, rh, frq, ang)\nrte.init_absmdl(mdl)\ndf = rte.execute()\n\ndf = df.set_index(frq)\ndf.tbtotal.plot(ax=ax, linewidth=1, label='{} - {}'.format(atm[atmp.TROPICAL], mdl))\n\nax.legend()\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Print dataframe\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "df"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Performing calculation for R03 absorption model\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "mdl = 'R03'\nrte.init_absmdl(mdl)\ndf_r03 = rte.execute()\ndf_r03 = df_r03.set_index(frq)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Add brigthness temperature values as new column\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "df['delta'] = df.tbtotal - df_r03.tbtotal"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "df"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Difference between R16 and R03 brightness temperature\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, ax = plt.subplots(1, 1, figsize=(12,8))\nax.set_xlabel('Frequency [GHz]')\nax.set_ylabel('$\\Delta {T_B}$ [K]')\ndf.delta.plot(ax=ax, figsize=(12,8), label='$\\Delta {T_B}$ (R16-R03)')\nax.legend()\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Performing downwelling brightness temperature calculation\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, ax = plt.subplots(1, 1, figsize=(12,8))\nax.set_xlabel('Frequency [GHz]')\nax.set_ylabel('${T_B}$ [K]')\n\nrte.satellite = False\ndf_from_ground = rte.execute()\n\ndf_from_ground = df_from_ground.set_index(frq)\ndf_from_ground.tbtotal.plot(ax=ax, linewidth=1, label='{} - {}'.format(atm[atmp.TROPICAL], mdl))\nax.legend()\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "df_from_ground"
+      ]
+    }
+  ],
+  "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": "3.10.12"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

en/main/_downloads/05da99fceea7871dd6706a0148d79a7e/plot_model_cloudy.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Performing Downwelling Brightness Temperature calculation in cloudy condition.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "This example shows how to use the\n:py:class:`pyrtlib.tb_spectrum.TbCloudRTE` method to calculate brightness temperature from ground (downwelling) in cloudy condition\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\nfrom matplotlib.ticker import FixedLocator, FormatStrFormatter\nplt.rcParams.update({'font.size': 15})\nimport numpy as np\nnp.seterr('raise')\n\nfrom pyrtlib.climatology import AtmosphericProfiles as atmp\nfrom pyrtlib.tb_spectrum import TbCloudRTE\nfrom pyrtlib.utils import ppmv2gkg, mr2rh\n\natm = ['Tropical',\n       'Midlatitude Summer',\n       'Midlatitude Winter',\n       'Subarctic Summer',\n       'Subarctic Winter',\n       'U.S. Standard']\n\nfig, ax = plt.subplots(1, 1, figsize=(12, 8))\n\nz, p, d, t, md = atmp.gl_atm(atmp.MIDLATITUDE_SUMMER)\ngkg = ppmv2gkg(md[:, atmp.H2O], atmp.H2O)\nrh = mr2rh(p, t, gkg)[0] / 100\n\nmdl = 'R19SD'\n\nang = np.array([90.])\nfrq = np.arange(20, 61, 1)\nnf = len(frq)\n\ndenliq = np.zeros(z.shape)\ndenice = np.zeros(z.shape)\ncldh = np.empty((2, 2))\n\nfor i in [False, True]:\n    if not i:\n        text_plot = 'clear-sky'\n    else:\n        # build a cloud\n        ib = 1\n        it = 3\n        denliq[ib:it + 1] = 10 * np.ones((it - ib + 1))\n        cldh[:, 0] = np.array([z[ib], z[it]])\n        ib = 29\n        it = 31\n        denice[ib:it + 1] = 0.1 * np.ones((it - ib + 1))\n        cldh[:, 1] = np.array([z[ib], z[it]])\n        text_plot = 'cloudy'\n\n    ax.set_xlabel('Frequency (GHz)')\n    ax.set_ylabel('BT (K)')\n\n    rte = TbCloudRTE(z, p, t, rh, frq, ang)\n    rte.satellite = False\n    rte.cloudy = i\n    rte.init_cloudy(cldh, denice, denliq)\n    rte.init_absmdl(mdl)\n    df = rte.execute()\n\n    df = df.set_index(frq)\n    df.tbtotal.plot(x=frq, ax=ax, linewidth=1,\n                    label='{} - {} ({})'.format(atm[atmp.MIDLATITUDE_SUMMER], mdl, text_plot))\n\nax.grid(True, 'both')\nax.legend()\nplt.show()"
+      ]
+    }
+  ],
+  "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": "3.10.12"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}