Published April 13, 2023 | Version v1
Dataset Open

Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models

  • 1. University of Valencia
  • 2. Universidad Rey Juan Carlos

Description

This repository contains several datasets of spectral atmospheric transfer functions (i.e. path radiance, transmittances, spherical albedo) simulated with MODTRAN6 atmospheric radiative transfer model. The simulations are stored in hdf5 files using the Atmospheric Look-up table Generator (ALG) toolbox (https://doi.org/10.5194/gmd-13-1945-2020). Each dataset has an associated .xml file that includes the configuration of ALG/MODTRAN6 executions. All datasets include the input atmospheric/geometric variables that are summarized in the following table. Each dataset file has a random distribution (based on latin hypercube sampling) these input variables with varying number of points (e.g. train500.h5 contains 500 samples). The reference dataset contains 10000 samples and was used as reference for evaluating Gaussian Processes emulators.

Input Variables Units Min Max
O3 column concentration atm-cm 0.25 0.45
Columnar Water Vapor g/cm2 0.2 4
Aerosol Optical Thickness - 0.04 0.6
Asymmetry parameter - 0.5 0.85
Angstrom exponent - 0.1 2
Single Scattering Albedo - 0.8 1
Surface elevation km 0 2.5
Solar Zenith Angle deg 0 70
Relative Zenith Angle deg 0 180

 

Files

reference.xml

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Additional details

Funding

European Commission
iMIRACLI - innovative MachIne leaRning to constrain Aerosol-cloud CLimate Impacts (iMIRACLI) 860100
European Commission
SENTIFLEX - Fluorescence-based photosynthesis estimates for vegetation productivity monitoring from space 755617
European Commission
USMILE - Understanding and Modelling the Earth System with Machine Learning 855187

References

  • J. Vicent et al.: Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0), Geosci. Model Dev., 13, 1945–1957, https://doi.org/10.5194/gmd-13-1945-2020, 2020.
  • J. Vicent et al.: Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models, IEEE Trans. on Geosci. and Rem. Sens., 2023 (in review)