Deriving High-quality Climate Data Records from Two Decades of Satellite Hyperspectral Remote Sensors
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Xu Liu↗
Engineering topics
Allen M Larar
Publications and source records attributed to Allen M Larar.
Recent Algorithm updates on Generating Weather and Climate Products from More Than 20 Years of Hyperspectral Sounders Data
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PCRTM↗
Observation of Deep Convective Cloud-Top Height and Vertical Temperature Structure of Hurricane Using Hyperspectral Infrared Sounder and its Single-Field-View Retrieval Products
Hurricanes, severe tropical cyclones (TC), or typhoons are significant natural disasters that often result in substantial loss of life and property damage. Numerous studies have indicated that changes in TC intensity are closely linked to deep convective clouds (DCC), with stronger TCs typically exhibiting higher cloud top heights (CTH) compared to weaker TCs. The CTH can help determine if a tropical depression is at the onset of rapid intensification based on case studies. Therefore, accurate determination of TC CTH will be greatly helpful for monitoring TC development and studying TC dynamics. One traditional and most common method to derive CHT from satellite observations is using the thermal brightness temperature in atmospheric channels to match the sounding temperature profile. However, it was found that thermally derived CTH has a lower bias of approximately 1 km, and this bias tends to worsen for the tallest clouds. A new method using the hyperspectral infrared sounder will be presented. From the measurements of Cross-track Infrared Sounder (CrIS) on S-NPP and J-1, along with radiative transfer simulations, we identified the inverted-V spectral feature in the ozone (O3) band (near 9.6 μm) corresponding to high clouds. The depth of the inverted-V can be used to estimate the CTH. Since the depth is computed using the peak absorption O3 channel and the nearby most transparent O3 channel in this O3 band, the uncertainties associated with cloud emissivity and scattering by cloud particles in the traditional method can be ignored. From several hurricane case studies, we found that the CHT derived using this method can accurately capture the structure of the cloud tops in the eyewall, spiral rainbands, and surrounding regions. For example, Hurricane Dorian on September 2, 2019, showed a nicely outward-sloping and circular shape eye cloud in the early morning, but the circular shape of the eyewall cloud became distorted in the afternoon. For various hurricanes we examined, the distribution of CHT for the eyewall clouds differed significantly. To better study the thermodynamic structure of hurricane clouds, this research will analyze the vertical temperature profiles from a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP), derived using CrIS and the Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1. SiFSAP has a spatial resolution of 15 km at nadir, which surpasses most global weather and climate models and other current operational sounding products. The combined use of ATMS and CrIS allows for retrievals near hurricane eyewalls and spiral rainbands. Wind fields from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize transport, and comparisons between the model temperature and water vapor profiles with the corresponding SiFSAP products will also be provided.
SiFSAP↗
Observation of Deep Convective Cloud-Top Height and Vertical Temperature Structure of Hurricane Using Hyperspectral Infrared Sounder and its Single-Field-View Retrieval Products
A new method utilizing hyperspectral infrared sounders is developed to estimate cloud top height (CTH) for deep convective clouds from hurricane, or tropical cyclone (TC). By analyzing measurements from the Cross-track Infrared Sounder (CrIS), and further validating with radiative transfer simulations, we identified an inverted-V spectral feature in the ozone (O3) band near 9.6 μm, which correlates with deep convective clouds. The depth of this feature can be used to estimate the CTH of a TC's eyewall and surrounding rain bands. This approach effectively captures the cloud structure of the TC. Additionally, a new single Field of View sounder products (SiFSAP), derived from CrIS and the Advanced Technology Microwave Sounder (ATMS), will be used to analyze the vertical temperature and water vapor structure, offering more insights into TC dynamics.
Single-field-view retrieval↗
PBL Thermodynamic Characterization and Its Variability From NAST-I During the Wh2yMSIE Field Campaign
The National Airborne Sounder Testbed-Interferometer (NAST‑I) suborbital system (<2.6 km IFOV; 0.25 cm-1 within 645–2700 cm‑1) serves as a spaceborne instrument simulator and pathfinder for future satellite capabilities and airborne science experiments. The NAST‑I measurements are made to advance understanding of science critical for weather, climate, chemistry, and radiation applications. Here we present some groundbreaking capabilities of NAST-I measurements and corresponding geophysical retrievals and their potential benefits toward improved atmospheric state and composition characterizations needed for science applications of particular importance toward enhancing characterization and understanding of the Planetary Boundary Layer (PBL). Initial results of PBL height estimation and thermodynamic characterization and their time evolution from NAST-I measurements during the WH2yMSIE field campaign are presented.
Daniel K Zhou↗
Developing Fast and Accurate Radiative Transfer Models to Meet the Needs of Modern Satellite Remote Sensing Applications
Modern hyperspectral satellite remote sensors provide highly accurate measurements the Earth’s Top-of-Atmosphere (TOA) radiance, reflectance, or polarized spectra with hundreds to thousands of spectral channels and with millions of observations per day. The large data volume and high spectral dimensionality of the data pose challenges for retrieval algorithms. To process the satellite Level-1 data (e.g. calibrated TOA spectra) into Level-2 products (e.g. atmospheric and surface properties) using physical-based retrieval algorithms, accurate and fast Radiative Transfer Models (RTMs) are needed. RTMs are usually the limiting factor in determining the speed of a level-2 algorithm. For example, more than one million Line-by-Line (LBL) radiative transfer (RT) calculations are needed in order to properly capture the spectral contributions of important atmospheric molecules for an IR hyperspectral sensor with a spectral coverage from 3.5 m to 15 m or a solar hyperspectral sensor with spectral coverage from 0.25 m to 2.5 m. In this presentation, we will discuss advantages and disadvantages of different ways (e.g. correlated k and effective transmittance) to accelerate the speed of a fast RTM. We finally describe a Principal Component-based Radiative Transfer Model (PCRTM), which can calculate TOA radiance or reflectance spectra from 50 cm-1 to 40,000 cm-1 (200 m to 0.25 m). It has demonstrated very good accuracy relative to reference LBL RTMs and saves orders of magnitude in computational time. The PCRTM has been used in many satellite remote sensing applications. Examples include forward modeling in Level-2 and Level-3 retrieval algorithms, high fidelity satellite instrument simulators and instrument performance trade studies, spectral and radiometric accuracy characterizations of satellite Level-1 data, tools for inter-satellite calibrations, tools for satellite RTM lookup table generations, and tools for generating physically based training datasets for Artificial Intelligence (AI) algorithms.
climate data record↗
Explore Information Content Efficiently from Current and Future Hyperspectral Satellite Missions using a Spectral Fingerprinting Method
Hyperspectral remote sensors from current and future missions provide measurements of the Top of Atmosphere (TOA) radiance or reflectance spectra with high information content. For example, the Atmospheric Infrared Sounder (AIRS), together with the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI) have provided more than 20 years radiance measurements with thousands of spectral channels. These measurements will be continued for the next two decades with the same or more advanced hyperspectral sensors. The upcoming missions such as NASA’s CLARREO Pathfinder (CPF) and ESA’s TRUTHS will provide unprecedented accurate TOA hyperspectral radiance measurements in solar spectral region. Traditional ways to derive Climate Data Records (CDRs) from these measurements are performing spatial and temporal averages of the retrieved Level-2 products. However, it is a time-consuming process to generate decades of Level-2 data from Level-1 data. Furthermore, the differences in Level-2 algorithms used for different satellite sensors will introduce errors in derived CDRs. In this presentation, we will describe a spectral fingerprinting method to generate high-quality CDRs directly from spatiotemporally averaged Level-1 data. By using consistent radiative kernels which contain the spectral information of various atmospheric and surface CDRs, we can reduce the errors due to algorithm inconsistency. Additionally, the spectral fingerprinting method reduces the time needed to generate CDRs by more than three orders of magnitude. This makes it easy to reprocess CDRs once the Level-1 data from different satellites have been improved via either re-calibrations or inter-satellite calibrations. We will present results of applying spectral fingerprinting method to 20-years of AIRS and CrIS data. The resulting CDRs include: 1) vertical profiles of atmospheric temperature and water vapor, 2) cloud properties such as optical depth, effective size, and height, 3) vertical profiles or column amounts for atmospheric trace gases such as O3 and CO, and 4) surface emissivity spectra and skin temperatures. These CDRs will be publicly available at NASA GES DISC in late 2024. The same fingerprinting method is planned to be applied to future CPF and TRUTHS data for solar spectral region.
hyperspectral remote sensing↗