Engineering topics
D K Zhou
Publications and source records attributed to D K Zhou.
Hyperspectral Radiatve Transfer Modeling and its Applications
We will describe a fast radiative transfer model that is specifically designed for hyperspectral remote sensing applications. The fast radiative transfer model is capable of performing efficient and accurate calculations under cloudy condition and in the presence of solar radiations. The model uses a Principal Component Analysis to speed up computational speed. The PCRTM model is capable of simulating top of atmospheric radiance or reflectance spectral from 50 wavenumber to 30000 wavenumber. The PCRTM has a very good accuracy relative to reference line-by-line radiative transfer models and it saves orders of magnitude computational time. We will show comparisons of the PCRTM model to AIRS, CrIS, IASI, NAST-I, and SCIAMACHY data. We will further show results of applying the PCRTM retrieval algorithm to these remote sensing data to retrieve atmospheric temperature and moisture profiles, CO2, CO, CH4, N2O, and O3 profiles, cloud optical depth, size, phase, and height. Surface properties such as surface emissivity spectra and surface skin temperatures are also retrieved simultaneously.
TPSAS-NF1676L-27604-DND
Satellite-based hyperspectral observations provide high information content for the Earth's atmospheric and surface properties; however, in order to analyze hyperspectral data efficiently, fast and accurate radiative transfer model is needed. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate radiative transfer in the cloudy atmosphere from far IR to visible and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5 and LBLRTM. The PCRTM calculated radiance spectra agree with the Modtran and LBLRTM within 0.02%. We will demonstrate the application of the PCRTM forward model for atmospheric and surface property inversions and for climate observation studies.
Polar Vortex Outbreak Air Transport: Observation using Satellite IR Sounder Derived Ozone Product and Comparison with Model
The Single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP) derived from Cross-track Infrared Sounder (CrIS) on SNPP and JPSS have a spatial resolution ( ~14.5 km) better than most global weather and climate models. Most recent significant improvement in the quality of these products enables us to use these high-resolution observation-based sounding data for weather studies and model evaluation. The aim of this study is to explore the value to use these SFOV products for studying the dynamic transport associated with polar vortex outbreak. In a few cases studies, we used SiFSAP products, especially ozone, as well as the data of wind, geopotential height (GPH) and potential velocity (PV) from the fifth-generation ECMWF reanalysis (ERA5) data, to analyze the variation of total ozone, relative humidity and ozone in different layers, as well as their correlation with GPH and PV. Some comparison of the retrieved temperature and water vapor with ERA5 data, and ozone with the Ozone Mapping and Profiler Suite (OMPS) measurements have also been made. It is found (1) the transport of O3-riched polar air accompanying the polar vortex breakup to lower latitude and lower atmosphere, and (2) the transport path of O3 agreeing well with the path of polar cold air (illustrated using the retrieved RH, wind fields and GPH). These results demonstrate the 3-D structure of O3 distribution as derived from CrIS measurements provides some insights of the cold air transport, and can be used to track the dynamic transport of polar cold air following the outbreak of polar vortex. The observed enhancement of O3 following the polar vortex outbreak also suggests some possible linkage between the tropospheric cold air advected with stratospheric air source.
Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Remote Sensors for UV, VVIS, NIR, IR, and FIR Spectral Regions
Fast and accurate radiative transfer models are needed to efficiently process satellite hyperspectral remote sensors. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate TOA radiance or reflectance spectra in the cloudy atmosphere for far IR, IR, NIR, VIS, and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. Polarization components can also be calculated. The computation speed is 3 to 4 orders of magnitude faster than MODTRAN5, LBLRTM, and VLIDORT. The PCRTM calculated radiance spectra agree with reference RTM calculated radiance spectra very well (0.03 K in IR and 0.05% in solar). Comparisons of the PCRTM model calculations with observed AIRS, CrIS, IASI, NAST-I, and SCIAMACHY data will be presented. The solar-PCRTM has been developed for CLARREO PathFinder (CPF) and has been extensively used for CPF science algorithms. The PCRTM can also be used for many current and future NASA future missions such as EMIT, SBG, TEMPO, and PACE.
All-sky Retrieval of Atmospheric Temperature, Water Vapor, Clouds, Trace Gases, and Surface Properties from Operational Hyperspectral IR Sounders
Operational IR sounders such AIRS, CrIS, and IASI provide high quality hyperspectral measurements for weather and climate applications. We will describe a new all-sky Single Field-of-view Sounder Atmospheric Product (SiFSAP). The uniqueness of this product is that it uses all available channels from hyperspectral sounders and the optimal estimation retrieval is done at a single FOV spatial resolution. The SiFSAP includes atmospheric temperature, water vapor, clouds, trace gases, surface skin, and surface emissivity and will be produced operationally at NASA GES DISC. We will describe the core component of the SiFSAP algorithm, which is the Principal Component-based Radiative Transfer Model (PCRTM), and will show example applications of the SiFSAP product for various atmospheric weather and dynamics studies. We also describe a new Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.
Remote Sensing of Atmospheric Temperature, Water Vapor, Trace Gases, Cloud, and Surface Properties on Daily and Decadal Time Scales
Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.