{ "cells": [ { "cell_type": "markdown", "id": "aea4bf41-6a02-40b8-8906-c168abb5fc0f", "metadata": {}, "source": [ "# Mars: UV nadir-viewing measurement \n", "\n", "In this notebook, we show an example of how to compute a forward model of the atmosphere of Mars with archNEMESIS in the UV-visible spectral range, including absorption by the Hartley band of ozone and scattering by dust particles in the atmosphere. This is similar to the measurements made by the NOMAD-UVIS spectrometer aboard the ExoMars Trace Gas Orbiter [(Mason et al., 2024)](https://doi.org/10.1029/2023JE008270).\n", "\n", "In addition, we perform a comparison of the foward model outputs against the DISORT radiative transfer code [(Stamnes et al., 1988)](https://doi.org/10.1364/AO.27.002502)." ] }, { "cell_type": "code", "execution_count": 1, "id": "95eaaa78-5ea2-4a01-b436-9a3e8d83b120", "metadata": {}, "outputs": [], "source": [ "import os\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import archnemesis as ans\n", "import h5py" ] }, { "cell_type": "markdown", "id": "e88f1be2-23bb-436e-9b62-327a77741cfc", "metadata": {}, "source": [ "## 1. Inspecting the input files" ] }, { "cell_type": "code", "execution_count": 2, "id": "deb3e3ba", "metadata": {}, "outputs": [], "source": [ "# Read the archNemesis hdf5 input file\n", "inp_dir = './'\n", "runname = 'archnemesis_disort_comparison_input'\n", "Atmosphere,Measurement,Spectroscopy,Scatter,Stellar,Surface,CIA,Layer,Variables,Retrieval,Telluric = ans.Files.read_input_files_hdf5(inp_dir+runname)" ] }, { "cell_type": "markdown", "id": "2541eb99-7574-452d-a9be-931d0c58d824", "metadata": {}, "source": [ "### Normalising the ozone abundance\n", "\n", "In this example, we want to calculate the spectra of the Martian atmosphere at different ozone column densities. The units of the column density are generally m$^{-2}$, but ozone measurements are often reported in $\\mu$m-atm, which correspond to 1 $\\mu$m-atm = 2.689 $\\times$ 10$^{19}$ m$^{-2}$. Since in our example we want to vary the ozone density in these units, we are going to normalise the column density of ozone to 1 $\\mu$m-atm so that it is later on easy to apply a scaling factor and get our desired ozone amounts." ] }, { "cell_type": "code", "execution_count": null, "id": "63b106d0-7181-4d35-903a-e15de6166333", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.0\n", "Ozone column density = 2.689e+19 m-2 = 1.0 um-atm\n" ] } ], "source": [ "#Estimating the atmospheric column density from the Atmosphere\n", "coldens = Atmosphere.calc_coldens()\n", "\n", "#Locating the index of ozone\n", "iO3 = np.where((Atmosphere.ID==3) & (Atmosphere.ISO==0))[0][0] \n", "\n", "#Normalising the O3 column density to 1 um-atm\n", "ozone_coldens = coldens[iO3]\n", "print(ozone_coldens/2.689e19)\n", "Atmosphere.update_gas(3,0,Atmosphere.VMR[:,iO3]/ozone_coldens*2.689e19) \n", "\n", "#Calculating again the column density to make sure it is normalised to 1 um-atm\n", "coldens = Atmosphere.calc_coldens()\n", "print(f\"Ozone column density = {(coldens[iO3],'m-2 = ',coldens[iO3]/2.689e19,' um-atm')}\")" ] }, { "cell_type": "markdown", "id": "4dec214f-697d-4b53-9d97-e24da1c29fde", "metadata": {}, "source": [ "### Normalising the dust optical depth to 0.67 $\\mu$m\n", "\n", "The units of the aerosol density profiles in archNEMESIS are generally m$^{-3}$ (if working with the HDF5 files), meaning that the column density of dust will be calculated in m$^{-2}$. Similarly, the units of the extinction cross section in the Scatter class are generally cm$^{2}$, so that when the extinction cross section is multiplied by the dust column density, we calculate the optical depth.\n", "\n", "In some cases, it is useful to normalise our profiles so that we can easily define the column-integrated optical depth of the aerosol at a given wavelength. To do so, we need to do some transformations so that all the calculations stay consistent throughout the code.\n", "\n", "In particular, we need to normalise the extinction cross section (Scatter.KEXT) to a wavelength of our choice. Then, we need to normalise our aerosol density profile (Atmosphere.DUST), so that the calculations are correctly performed. \n", "\n", "In this example, we show how to easily perform this normalisation in archNEMESIS with our example: we will normalise the profile to an optical depth of 1 at 0.67 $\\mu$m." ] }, { "cell_type": "code", "execution_count": 4, "id": "50dca5e7-cf14-4173-937b-ab48ebf8bec7", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Normalising the extinction coefficient to 1 at 0.67 um\n", "idust = 0 #We select the index of the aerosol population we want to normalise\n", "vnorm = 0.67\n", "kext_norm = np.interp(vnorm,Scatter.WAVE,Scatter.KEXT[:,idust])\n", "Scatter.KEXT[:,idust] /= kext_norm\n", "\n", "#Normalising the aerosol density\n", "Atmosphere.normalise_dust(idust=idust)\n", "\n", "#Making summary plot\n", "fig,(ax1,ax2) = plt.subplots(2,1,figsize=(6,4),sharex=True)\n", "\n", "for i in range(Scatter.NDUST):\n", " \n", " ax1.plot(Scatter.WAVE,Scatter.KEXT[:,i],label='Dust population '+str(i+1))\n", " ax2.plot(Scatter.WAVE,Scatter.SGLALB[:,i])\n", "\n", "ax1.axvline(vnorm,c='black',linestyle='--')\n", "ax1.legend()\n", "ax1.set_facecolor('lightgray')\n", "ax2.set_facecolor('lightgray')\n", "ax1.grid()\n", "ax2.grid()\n", "ax2.set_xlabel('Wavenumber (cm$^{-1}$)')\n", "ax1.set_ylabel('k$_{ext}$')\n", "ax2.set_ylabel('$\\omega$')\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "6f67a6ea-1ef6-4762-8b79-497b68de4ae7", "metadata": {}, "source": [ "## 2. Loading the DISORT modelled spectra\n", "\n", "Here, we read the file with the outputs from DISORT. The spectra for DISORT was calculated using the information from the archNEMESIS HDF5 file, so that the calculations from the two codes are comparable. Here, we read the file and plot the outputs to inspect the information about the cases that were run with DISORT." ] }, { "cell_type": "code", "execution_count": null, "id": "517f0916-c640-400c-aefc-0ae900fd979f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Ozone amounts in DISORT calculations [1.0e-02 5.0e+00 1.5e+01 3.0e+01] um-atm\n", "Dust optical depths in DISORT calculations [0.01 0.5 1. 2. ] um-atm\n" ] } ], "source": [ "# Load the DISORT file that contains the output from the DISORT raidative transfer model\n", "with h5py.File('archNEMEIS-DISORT_spectra.h5','r') as f:\n", " WAVE = f['OZONE']['WAVE'][:] #Wavelength array (um)\n", " DUST_TAU_ARRAY = f['DUST']['DUST_ARRAY'][:] #Optical depths at which the spectra were computed\n", " OZONE_ARRAY = f['OZONE']['OZONE_ARRAY'][:] #Ozone densities at which the spectra were computed (um-atm)\n", " DISORT_OZONE = f['OZONE']['SPECTRA'][:] #Spectra for the different ozone cases (I/F)\n", " DISORT_DUST = f['DUST']['SPECTRA'][:] #Spectra for the different dust cases (I/F)\n", " SOLSPEC = f['OZONE']['SOLAR_SPECTRUM'][:] #Solar spectrum used in the calculations\n", "\n", "print(f\"Ozone amounts in DISORT calculations {(OZONE_ARRAY,'um-atm')}\")\n", "print(f\"Dust optical depths in DISORT calculations {(DUST_TAU_ARRAY,'um-atm')}\")" ] }, { "cell_type": "code", "execution_count": 6, "id": "1cd6b544-8007-4c55-ad9a-74255fa92880", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,(ax1,ax2) = plt.subplots(1,2,figsize=(12,4),sharey=True)\n", "\n", "for i in range(len(OZONE_ARRAY)):\n", " ax1.plot(WAVE[:,0],DISORT_OZONE[:,i],label='O$_3$ = '+str(OZONE_ARRAY[i])+' $\\mu$m-atm')\n", "\n", "for i in range(len(DUST_TAU_ARRAY)):\n", " ax2.plot(WAVE[:,0],DISORT_DUST[:,i],label=r'$\\tau$ = '+str(DUST_TAU_ARRAY[i]))\n", "\n", "ax1.set_ylim(bottom=0.0)\n", "ax1.grid()\n", "ax1.set_facecolor('lightgray')\n", "ax1.set_xlabel('Wavelength ($\\mu$m)')\n", "ax1.set_ylabel('I/F')\n", "ax1.legend()\n", "\n", "ax2.set_ylim(bottom=0.0)\n", "ax2.grid()\n", "ax2.set_facecolor('lightgray')\n", "ax2.set_xlabel('Wavelength ($\\mu$m)')\n", "ax2.legend()\n", "\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "e9399305-9275-49a0-a304-5ffef58bb76f", "metadata": {}, "source": [ "## 3. Running forward model for varying ozone amounts\n", "\n", "In this section, we are going to run the forward model of archNEMESIS and vary the ozone column density to compare the outputs against DISORT. In particular, since we have normalised our ozone profile to a column density of 1 $\\mu$-atm, we can easily modify the column density by using model parameterisation 2 (i.e., scaling factor of atmospheric profile). In particular, since we want to apply this to ozone, Variables.VARIDENT should be (3,0,2). \n", "\n", "Similarly, since we have normalised the optical depth of the dust column to 1, we can easily modify it by applying a scaling factor to the dust (i.e., Variables.VARIDENT = (-1,0,2)). In this part, we are going to set this scaling factor to zero to focus on the variation of the spectrum with ozone." ] }, { "cell_type": "code", "execution_count": 7, "id": "6fb63605-f0e9-47ad-9c69-4187251b64dd", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[-1 0 2]\n", " [ 3 0 2]]\n" ] } ], "source": [ "#Checking the model parameterisations chosen in our .apr file\n", "print(Variables.VARIDENT)" ] }, { "cell_type": "code", "execution_count": 8, "id": "bba673e6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n", "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n", "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n", "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n" ] } ], "source": [ "# Define the output arrays\n", "SPECONV_ozone = np.zeros((Measurement.VCONV.shape[0],len(OZONE_ARRAY))) #NEMESIS spectrum in I/F units\n", "for i in range(len(OZONE_ARRAY)):\n", "\n", " #Changing the parameters in the state vector to our desired scaling factor\n", " Variables.XA[0] = 0.0 ; Variables.XN[0] = 0.0 #We set the dust optical depth to 0.01 \n", " Variables.XA[1] = OZONE_ARRAY[i] ; Variables.XN[1] = OZONE_ARRAY[i] # Update the ozone abundance in the Variables class\n", "\n", " #Load ForwardModel class\n", " ForwardModel = ans.ForwardModel_0(runname=runname, Atmosphere=Atmosphere,Surface=Surface,Measurement=Measurement,Spectroscopy=Spectroscopy,Stellar=Stellar,Scatter=Scatter,CIA=CIA,Layer=Layer,Variables=Variables)\n", "\n", " # Setup the archNemesis forward model\n", " SPECONVx = ForwardModel.nemesisfm() # Run the archNemesis foward model\n", " SPECONV_ozone[:,i] = np.pi * SPECONVx[:,0] / SOLSPEC[:,i] # Compute the radiance factor by dividing by the solar spectrum (Loaded from the DISORT file)" ] }, { "cell_type": "code", "execution_count": 9, "id": "7171c8a0-866d-4c8b-8334-772c31cc55cb", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#fig,(ax1,ax2) = plt.subplots(2,1,figsize=(7,6))\n", "fig,ax1 = plt.subplots(1,1,figsize=(6,4))\n", "\n", "for i in range(len(OZONE_ARRAY)):\n", "\n", " if i==0:\n", " ax1.plot(Measurement.VCONV[:,0],SPECONV_ozone[:,i],c='tab:red',label='archNEMESIS',linewidth = 3.)\n", " ax1.plot(WAVE[:,0],DISORT_OZONE[:,i],c='black',label='DISORT')\n", " else:\n", " ax1.plot(Measurement.VCONV[:,0],SPECONV_ozone[:,i],c='tab:red',linewidth = 3.)\n", " ax1.plot(WAVE[:,0],DISORT_OZONE[:,i],c='black')\n", "\n", "# ax2.plot(Measurement.VCONV[:,0],(SPECONV_ozone[:,i]-DISORT_OZONE[:,i])/DISORT_OZONE[:,i]*100.)\n", "\n", "ax1.set_ylim(bottom=0.0)\n", "ax1.grid()\n", "ax1.set_facecolor('lightgray')\n", "ax1.set_xlabel('Wavelength ($\\mu$m)')\n", "ax1.set_ylabel('I/F')\n", "ax1.legend()\n", "\n", "#ax2.set_ylim(-5.,5.)\n", "#ax2.grid()\n", "#ax2.set_facecolor('lightgray')\n", "#ax2.set_xlabel('Wavelength ($\\mu$m)')\n", "#ax2.set_ylabel('Difference (%)')\n", "\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "6d733928-4578-4ec1-9b7e-8ee889d6725c", "metadata": {}, "source": [ "## 4. Running forward model for varying dust optical depths\n", "\n", "Similar to the previous section, we can run the forward model at different dust optical depths by applying a varying scaling factor for the dust, given that we have normalised our profiles to an optical depth of 1 at 0.67 $\\mu$m. The ozone column in this case is set to 2 $\\mu$m-atm." ] }, { "cell_type": "code", "execution_count": 10, "id": "27e6c6cb-a425-47d9-80df-2f49d1afed18", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.00947053]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n", "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.47352657]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n", "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [0.94705315]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n", "CIRSrad :: CIA not included in calculations\n", "CIRSrad :: Aerosol optical depths at 0.2014500037766993 :: [1.89410629]\n", "CIRSrad :: Performing multiple scattering calculation\n", "CIRSrad :: NF = 20 ; NMU = 16 ; NPHI = 201\n" ] } ], "source": [ "# Define the output arrays\n", "SPECONV_dust = np.zeros((Measurement.VCONV.shape[0],len(DUST_TAU_ARRAY))) #NEMESIS spectrum in I/F units\n", "for i in range(len(OZONE_ARRAY)):\n", "\n", " #Changing the parameters in the state vector to our desired scaling factor\n", " Variables.XA[0] = DUST_TAU_ARRAY[i] ; Variables.XN[0] = DUST_TAU_ARRAY[i] # Update the dust optical depth in the Variables class\n", " Variables.XA[1] = 2. ; Variables.XN[1] = 2. #We set the ozone column to 2. um-atm\n", " #Load ForwardModel class\n", " ForwardModel = ans.ForwardModel_0(runname=runname, Atmosphere=Atmosphere,Surface=Surface,Measurement=Measurement,Spectroscopy=Spectroscopy,Stellar=Stellar,Scatter=Scatter,CIA=CIA,Layer=Layer,Variables=Variables)\n", "\n", " # Setup the archNemesis forward model\n", " SPECONVx = ForwardModel.nemesisfm() # Run the archNemesis foward model\n", " SPECONV_dust[:,i] = np.pi * SPECONVx[:,0] / SOLSPEC[:,i] # Compute the radiance factor by dividing by the solar spectrum (Loaded from the DISORT file)" ] }, { "cell_type": "code", "execution_count": 11, "id": "bf6b5e13-e444-43ee-93c9-6dabf5227f65", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#fig,(ax1,ax2) = plt.subplots(2,1,figsize=(7,6))\n", "fig,ax1 = plt.subplots(1,1,figsize=(6,4))\n", "for i in range(len(DUST_TAU_ARRAY)):\n", "\n", " if i==0:\n", " ax1.plot(Measurement.VCONV[:,0],SPECONV_dust[:,i],c='tab:red',label='archNEMESIS',linewidth = 3.)\n", " ax1.plot(WAVE[:,0],DISORT_DUST[:,i],c='black',label='DISORT')\n", " else:\n", " ax1.plot(Measurement.VCONV[:,0],SPECONV_dust[:,i],c='tab:red',linewidth = 3.)\n", " ax1.plot(WAVE[:,0],DISORT_DUST[:,i],c='black')\n", "\n", "# ax2.plot(Measurement.VCONV[:,0],(SPECONV_dust[:,i]-DISORT_DUST[:,i])/DISORT_DUST[:,i]*100.)\n", "\n", "ax1.set_ylim(bottom=0.0)\n", "ax1.grid()\n", "ax1.set_facecolor('lightgray')\n", "ax1.set_xlabel('Wavelength ($\\mu$m)')\n", "ax1.set_ylabel('I/F')\n", "ax1.legend()\n", "\n", "#ax2.set_ylim(-5.,5.)\n", "#ax2.grid()\n", "#ax2.set_facecolor('lightgray')\n", "#ax2.set_xlabel('Wavelength ($\\mu$m)')\n", "#ax2.set_ylabel('Difference (%)')\n", "\n", "plt.tight_layout()" ] }, { "cell_type": "code", "execution_count": null, "id": "6bfeef35-8c67-415d-8995-4fbdd0a27428", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "pyenv", "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": "3.11.10" } }, "nbformat": 4, "nbformat_minor": 5 }