Development of the Fast and Accurate Vector PCRTM Radiative Transfer Model
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hyperspectral↗
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Development of the Principal Component Based Accurate Fast Vector Radiative Transfer Model with Fine Resolution in the UV to NIR Wavelength Range
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Vector PCRTM↗
Using Polarized PCRTM-Solar Model to Validate EMIT Surface Reflectance L2A Product
Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer scattering code, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate hyperspectral radiation fields from visible to shortwave infrared (VSWIR), i.e., 250 nm to 2500 nm. Since only limited accurate line-by-line calculation using VLIDORT is needed, this coupled PCRTM-VLIDORT approach is very efficient for simulating hyperspectral VSWIR spectra. These simulations incorporate accurately defined optical properties (gas absorptions, molecular and aerosol/cloud particle scattering) and detailed surface reflectance inputs. In this study we used the current L2A products of the Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer as the inputs to PCRTM-VLIDORT to simulate EMIT spectra. Comparing the simulated spectra with EMIT measurements provides an efficient method to validate the current EMIT product.
Xiaozhen Xiong↗
Data Simulation Using VLIDORT and PCRTM and its Use for Radiometric Calibration of Hyperspectral UV-NIR-SWIR Sensors
Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer discrete ordinate scattering codes, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate the radiation fields for hyperspectral UV-NIR-SWIR sensors from 250nm to 2500nm with a very high speed. Since the accurate gas absorptions, molecules and aerosol/cloud particle scatterings, and the surface reflectance have been considered in these simulations, these model data can be used for satellite or airborne sensor design, characterization, or end-to-end system level uncertainty assessment. Comparison of the modelled data with measured results has been a general practice for operational satellite sensor calibrations, such as the Ozone Mapping and Profiler Suite (OMPS) onboard on SNPP and NOAA-20. This presentation will give more details of this simulation system and models. Some examples of the generation of simulations data for CLARREO PathFinder (CPF) and the Surface Biology and Geology (SBG), as well as some examples to use these data for CPF and OMPS radiometric calibration will be presented.
Xiaozhen Xiong↗
Forward and Inverse Models for Satellite Remote Sensors using Principal Component Analysis
Satellite remote sensors such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C make millions of observations each day with thousands of spectral channels for each observation; this poses challenges for efficiently inversion of the inherently large dataset as needed to retrieve atmospheric and surface properties. This presentation will illustrate the use of Principal Component Analysis (PCA) to speed up radiative transfer forward model calculations and to stabilize the inversion algorithms. A Principal Component-based radiative transfer model (PCRTM) developed at NASA Langley Research Center can simulate top of atmosphere (TOA) radiance or reflectance spectra from 50 cm-1 to 50000 cm-1 (200 m to 0.20 m quickly and accurately. PCRTM demonstrated very high accuracy relative to reference line-by-line radiative transfer models and it saves orders of magnitude computational time. Examples of the PCRTM model developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, CPF, TEMPO, SBG, OMI, and SCIAMACHY will be presented. In addition to using the PCRTM as forward model, the NASA Langley developed inversion algorithm also uses PCA to compress the state vector into a compressed dimension to speed up and stabilize the inversion process. Examples of retrieved atmospheric temperature, water vapor, CO2, CO, CH4, N2O, and O3 profiles, cloud properties (optical depth, size, phase, and height), and surface properties (surface emissivity spectra and skin temperatures) will be presented. This algorithm is being transitioned to the NASA Sounder SIPS and NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC).
forward model↗
A New BRDF Hotspot Model and its Use in Improving Radiative Transfer Model Efficiency and Application to VLIDORT-based PCRTM Model
The term “hotspot” refers to the sharp increase of reflectance occurring when incident (solar) and reflected (viewing) directions almost coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications. The RossThick-LiSparse-Reciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is widely used in radiative transfer simulations, and the hotspot model mostly used is from Maignan- Bréon but it typically requires large values of numerical quadrature and Fourier expansion terms in order to represent the hotspot accurately. To improve its use in atmospheric radiative transfer (RT) model simulations, we have developed a modified version based on the Maignan-Bréon’s hotspot BRDF model that converge much faster numerically, making it more practical for use in RT models that require Fourier expansion of BRDF to simulate the top-of-atmosphere (TOA) hotspot signatures. On basis of the vector linearized discrete ordinate radiative transfer model (VLIDORT), we have built a line-by-line based simulation system that can simulate the TOA radiance for atmospheres with 26 gases, different aerosols, dust and clouds, and surface with different BRDF. Using simulated results under diverse atmospheric conditions, we have developed VLIDORT-PCRTM model.
Xiaozhen Xiong↗