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Xu Liu

Publications and source records attributed to Xu Liu.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Fusion of Hyperspectral Sounder Products Via Spectral Fingerprinting Methodology

Satellite based measurements of top-of-atmosphere (TOA) spectral radiances in the infrared (IR) region have been in existence for almost two decades and are expected to be continued in the following decades. The data from multiple hyper-spectral IR sounders can therefore be combined to build a long-term data record to further global scale climate trend research. Challenges associated with the fusion of data from different sensors come from the stability and consistency requirement on the climate record. The direct radiance observations from different sounders need to be homogenized by reconciling the differences in calibration, spectral response function (SRF), and spatial-temporal sampling. When geophysical variables derived from radiances measured by different sounders are combined to form long-term climate records, the impacts of any inconsistencies between overlapping measurements on the retrieval must be carefully assessed in order to estimate the uncertainty of the corresponding climate anomalies/trends derived. This paper presents a novel climate fingerprinting methodology and establishes a rigorously-defined inverse relationship that allows us to efficiently evaluate the change in essential climate variables from the change in spectral radiances measured in prescribed spatial and temporal averaging scales. The inverse spectral fingerprinting relationship is constructed based on a unified spectral kernel scheme, providing a direct means for quantifying the potential discontinuity in the derived climate anomalies due to inconsistencies between overlapping measurements. We show in this paper a sample application of using the spectral fingerprinting scheme to derive long-term, global-scale surface temperatures from the Climate Hyperspectral Infrared Radiance Product (CHIRP) and quantify the inter-satellite biases.

Wan Wu↗
NASA NTRSDate not supplied

The PACE-MAPP Algorithm: Simultaneous Aerosol and Ocean Products From Combined Polarimeter and Shortwave Infrared Measurements

PACE-MAPP collaborative algorithm project - Produce accurate aerosol optical and microphysical properties and ocean properties - Use a coupled atmosphere-ocean vector radiative transfer (VRT) model - Use accurate but fast Mie/SS/T-matrix LUTs - Use scientific machine learning to speed-up retrievals by 1000x (PACE-MAPP Neural Network) - PACE-MAPP is a multi-instrument polarimeter algorithm for SPEXone, HARP2, OCI shortwave infrared channels

Snorre Alfred Moen Stamnes↗
NASA NTRSDate not supplied

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.

pcrtm↗
NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗
NASA NTRSDate not supplied

Climate Data Record Derived from Hyperspectral Sounders on AQUA, S-NPP and NOAA 20

Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a 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 accurate data climate data fusion products from multiple satellite sensors. It eliminates or reduces the errors due to inconsistent L2 algorithms. 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.

climate data record↗
NASA NTRSDate not supplied

Hyper-Spectral Infrared Remote Sensing for Wildfire-Related Research and Air Quality Monitoring

The National Airborne Sounder Testbed-Interferometer (NAST-I) is an airborne FTS remote sensor that nominally flies on NASA high-altitude aircraft to serve as a spaceborne instrument simulator. NAST-I continues to serve as a pathfinder for future satellite FTS systems and the next generation advanced atmospheric sounders in general. NAST-I provides high resolution spectrally resolved infrared radiances. NAST-I retrieval products characterizing the surface (i.e., skin temperature and spectral emissivity), atmosphere (i.e., profiles of temperature, moisture, ozone, carbon monoxide, and other trace species), and clouds (e.g., optical depth, particle size, temperature, and height) can be used to support fire-related monitoring and research. NAST-I provided 3-d characterizations of wildfire-induced plumes of CO during the FIREX-AQ field campaign (conducted during 2019) which showed the intensity and size evolution of wildfire plumes at high spatial and temporal resolutions. Wildfire-induced CO plumes, in conjunction with their evolution, transport, and age have been identified and recently published in scientific journals. Other research applications, such as surface emissivity changes due to fire burning of ground landscape, have been under investigation. These products could be used in support of wildfire management to better inform decision making and operations for pre-, active, and post-fire environments.

remote sensing↗
NASA NTRSDate not supplied

Update on Earth Skin Temperature Monitoring From 16 Years of IASI Satellite Observations

Surface parameters such as emissivity and skin temperature have been retrieved from IASI measurements of last 16 years. Monthly and spatially gridded surface skin temperature is produced to show the phenomena of its natural variability, which is also reflected in the surface emissivity and/or soil moisture content derived from the same time series of measurements. The anomalies of surface skin temperature are used to estimate its trend. The IASI global surface skin temperature trend is comparable with the NASA GISTEMP5 global surface air temperature trend. The trend of IASI global surface skin temperature reports that an approximate 0.027 K/yr. increase has evolved during 2007–2023. Attention has been given to the arctic region where an average warming rate is near 3 times higher than the global average. In some arctic regions, the rapid warming rate has reached 0.2-0.3 K/yr. which is about 10 times higher than the global average. Geophysical distribution of the surface temperature trend in the arctic region is emphasized and reported.

Global warming↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

CLARREO Pathfinder as a SI-traceable Reference for Satellite Intercalibration

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) consists of an Earthviewing reflected solar (RS) spectrometer that will measure the Earth-reflected solar radiation from International Space Station with an SI-traceable radiometric uncertainty of 0.3% (1-sigma). The high-accuracy CPF measurements will provide an in-orbit reference for intercalibrating other spaceflight RS instruments. The CPF intercalibration team has been tasked to develop a state-of-the-art approach to calibrate the shortwave channel (300-5000 nm) of the Clouds and the Earth’s Radiant Energy System (CERES) instrument and the reflective solar bands (RSB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, both onboard the NOAA-20 satellite, against the CPF benchmark measurements. The aimed intercalibration methodology uncertainty for both the target instruments is also 0.3%. To meet this stringent intercalibration accuracy, the CPF team has developed methods for mitigating the impacts of spatial, spectral, and angular differences between the intercalibration footprints from the CPF and target instruments. To further alleviate uncertainty, the CPF team will employ Polarization Distribution Models (PDMs) to characterize the polarization state of the Earth-reflected radiance as a function of the intercalibration footprint scene type, solar and viewing geometry, and wavelength. The PDMs will assist in identifying low-polarized scene radiances for meticulously intercalibrating the polarization sensitive VIIRS instrument against the significantly-less polarization-sensitive CPF instrument. This paper will highlight the CPF mission overview, the details of the CPF intercalibration approach, and additional outcomes of the CPF intercalibration studies that may benefit the broader remote sensing community.community.

Hyperspectral↗
NASA NTRSDate not supplied

20-Years of Atmospheric Temperature, Water Vapor, Cloud, and Surface Temperature Anomalies and Trends Derived From Operational Hyperspectral Ir Sounders

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. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. 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 SiFSAP retrieval algorithm also uses the same climatology a priori and associated covariances, which makes it ideal for generating high quality products for both weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our 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. 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. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

Homogenization of Satellite Based Hyperspectral Infrared Sounder Data To Build Long Term Climate Record

Building long term climate record using data from multiple hyperspectral Infrared (IR)sounders requires the homogenization of different data record to ensure the consistency andcontinuity. Such a requirement comes from two perspectives: 1) the need to adjust theoverlapping measurements of different sounders to ensure the radiometric consistency in thespectral radiance domain; 2) the need for a rigorously defined scheme to ensure the radiometricconsistency being transferred to the essential climate variables derived from the radiance record.We develop a solution that uses a spectral fingerprinting scheme to derive anomalies of keyclimate variables from long term spectral radiance data record constructed using both AIRS andCrIS observations aboard AQUA, SNPP and JPSS satellites. The fingerprinting scheme usescommon radiative kernels for all sounder measurements and therefore effectively avoids thealgorithm introduced inconsistency in retrieved geophysical variables. Our approach uses aunified sampling scheme to match AIRS and CrIS observations in both spectral and spatial-temporal domain, facilitating the intercomparison of spectral radiances from different sensors(platforms). The optimized liner inversion scheme allows the direct quantification and thereforethe adjustment for the impact on the derived climate anomalies imposed by potential radiometricinconsistency between the overlapping measurements. Such a scheme also enables the low-latency data processing of long term hyperspectral sounder data records. This paper provides a detailed introduction of the spectral fingerprinting methodology.Also introduced here is the climate fingerprinting Sounder Product (ClimFiSP) developed basedon the fingerprinting methodology. ClimFiSP products include the space-time averagedproperties of key climate variables that are derived from the long-term, space-time averagedradiances from AQUA-AIRS, SNPP-CrIS, and JPSS1-CrIS. ClimFiSP will be available to usersthrough NASA'sGoddard Earth Sciences Data and Information Services Center (GES DISC).

Wan Wu↗
NASA NTRSDate not supplied

Deriving a Suite of Climate Data Records from 21-years of Sounder Observations

Two retrieval algorithms, a Single Field-of-view Sounder Atmospheric Product (SiFSAP) Level 2 algorithm and a Climate Fingerprinting Sounder Product (ClimFiSP) Level 3 algorithm, have been developed at NASA Langley Research Center. In this presentation, we will demonstrate the radiance closure build into these two algorithms. This is possible due to the use of a principal-component-based radiative transfer model (PCRTM). The PCRTM enables the inclusion of all available spectral information from hyperspectral IR sounders. It also has fast and accurate capability of modeling observed cloudy radiance spectra directly. The SiFSAP, which fits sounder radiance spectra using PCRTM as forward model and an optimal estimation as inverse model, has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. With great support from NASA sounder SIPS, the SiFSAP algorithm has been delivered to NASA GES DISC for L2 and L3 data generation and releasing. The ClimFiSP uses a spectral fingerprinting method to directly generate L3 data products from spatiotemporally averaged L1 data. The goal of ClimFiSP is to generate high-quality climate data records (CDRs) from multiple IR sounders (e.g. Aqua AIRS, SNPP CrIS, NOAA-20 and NOAA-21 CrIS) using a consistent retrieval methodology. Using CHIRP L1 data, we have generated 20-years of CDRs for atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties. The algorithm will be transitioned to Sounder SIPS soon and eventually to NASA GES DISC.

Xu Liu↗
NASA NTRSDate not supplied

Newly Available Single Field-of-view Sounder Atmospheric Product (SiFSAP) and Its Derivative Product

The Single Field-of-view Sounder Atmospheric product (SiFSAP) has been developed and delivered to NASA GES DISC. The SiFSAP Algorithm Theoretical Basis Documents (ATBD) and users manuals are ready to be released to public. This novel data product supplements other operational products such as AIRS version 7 and the Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) from two main perspectives: 1) improving the spatial resolution of sounder Level-2 data to extend its usage in weather and dynamics focus area; 2) establishing radiance closure between Level-2 data and directly measured Level-1 radiances to facilitate the climate trend analysis. SiFSAP has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. SiFSAP is derived using the optimal estimation method based physical retrieval algorithm. The Principal Component-based Radiative Transfer Model (PCRTM) which includes the cloud scattering simulation is used for the forward model so that the solution can fit the spectral radiances under all-sky conditions for individual single field-of-view (SFOV) measurements. A general introduction of the SiFSAP algorithm and corresponding validation work will be presented. Also introduced here is the Climate Fingerprinting Sounder product (ClimFiSP) that is the derivative product of SiFSAP and will be released in the near future. The ClimFiSP algorithm uses pre-constructed fingerprinting relationship to achieve a low-latency Level-3 data production and facilitate the fusion of data of different sounders.

Wan Wu↗
NASA NTRSDate not supplied

Two Decades of Atmospheric and Surface Temperature, Water Vapor, and Cloud Trends Derived from Satellite Remote Sensors

Satellite remote sensor such as Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) 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. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our 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. 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. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

remote sensing↗
NASA NTRSDate not supplied

The National Airborne Sounder Testbed-Interferometer (NAST-I): Pathfinder for Satellite Capabilities and Airborne Science

The National Airborne Sounder Testbed-Interferometer (NAST-I) is an existing ultraspectral infrared sounder flown on high-altitude aircraft that provides high spectral and spatial resolution measurements which continue to advance understanding of science critical for weather, climate, chemistry, and radiation applications. NAST-I provides high-spatial linear resolution equal to 13% of the aircraft altitude at nadir (i.e., 2.6 km IFOV on the ground from an aircraft altitude of 20 km), and high-spectral resolution (0.25 cm -1 ) measurements within the spectral region of 645–2700 cm -1 . The NAST-I suborbital system serves as a spaceborne instrument simulator and pathfinder for future satellite capabilities and airborne science experiments. 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 air quality, wildfire, and other science applications.

NAST-I↗