Solving Forward and Inverse Problems for Hyperspectral Satellite Remote Sensors using Principal Component Analysis
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PCA↗
Engineering topics
Liqiao Lei
Publications and source records attributed to Liqiao Lei.
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↗
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↗
Fusion of Hyperspectral Sounder Products Via Spectral Fingerprinting Methodology
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Wan Wu↗
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↗
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↗
Development of An Improved BRDF Hotspot Model and its Use in VLIDORT to Study the Impact of Atmospheric Scattering on Hotspot Directional Signatures in the Atmosphere
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, in this paper 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. Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), we found that reasonable TOA hotspot accuracy can be obtained with just 23 Fourier terms for clear atmospheres, and 63 Fourier terms for atmospheres with aerosol scattering. One advantage of this modified model is that the new hotspot model agrees very well with the original RossThick model away the hotspot region, making it is very convenient to use in the condition with and without hotspot in applications. This model can calculate the amplitude of hot spot accurately, and has been added in the most recent version of VLIDORT. However, there are some difference of this modified model with the original model for scattering angle close the hot spot, and it may not be appropriate for those who need an exact representation of the hot spot angular signature close to hot spot.
Xiaozhen (Shawn) Xiong↗
A Principal-Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Shortwave and Longwave Satellite Sensors and Its Applications
The radiative transfer model (RTM) or forward model is an essential component in satellite remote sensing. For modern hyperspectral remote sensors, fast and accurate RTMs are needed due to a large number of spectral dimensions and high spatial resolutions. We will describe a Principal Component-based radiative transfer model (PCRTM) which can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra 250 nm to 2000 micrometers quickly and accurately. The PCRTM has been demonstrated to be extremely accurate, compared to the line-by-line RTM benchmarks, and the former is several orders more computationally efficient than the latter. We will demonstrate how the PCRTM and the associated inversion algorithms are used to infer atmospheric temperature, moisture, and trace gas profiles, as well as cloud and surface properties from hyperspectral IR sounders such as Atomspheric Infrared Souder (AIRS) and Cross-track Infrared Sounder (CrIS). High-quality climate records for a 20-year duration have been derived from these IR hyperspectral data. Finally, we will show some examples of using PCRTM to retrieve cloud properties from Earth Surface Mineral Dust Source Investigation (EMIT) and its applicability of PCRTM to future missions such as the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) CPF and the Surface Biology and Geology (SBG).
Xu Liu↗
Climate Fingerprinting Sounder Product (ClimFiSP) Skin Temperature Trends Analysis
Climate fingerprinting Sounder Product (ClimFiSP) has been developed at NASA Langley Research Center which includes daily skin temperature, surface emissivity, air temperature, H2O, trace gases, and cloud properties on 0.5x0.5 grid. Those properties are derived from IR hyper-spectral radiance measured by AIRS on Aqua and CrIS on SNPP and JPSS series. Global skin temperature trends have been derived using more than 20 years of monthly mean skin temperature data from ClimFiSP. The ClimFiSP algorithm use the spectral fingerprinting methodology that allows a low latency procession of more than two decades long satellite data record. The computational cost can be reduced by more than two orders of magnitude as compared with traditional Level-Level2-Level3 retrieval algorithms. In this presentation the global skin temperature trend from ClimFiSP will be compared with skin temperature trend derived from CLIMCAPS, ERA5, GISTEMP, HadCRUT5, and IASI data products, and the results show that pattern of ClimFiSP global skin temperature trends overall matches well with other datasets. The zonally averaged skin temperature anomaly will also be validated using those datasets. It is expected that ClimFiSP surface temperature data can serve as an important complement for surface-based estimates, especially in the regions where the spatial coverage of the surface-based observations is scarce.
Liqiao Lei↗
Observtion of Hunga Tonga Volcanic Eruption Using Hyperspectral Infrared Satellite Sensors
The Hunga Tonga-Hunga Ha'apai volcanic eruption, with the largest eruption occurred on 15 January 2022, injected unprecedented amounts of water vapor (H 2 O) and SO 2 to the stratosphere. Using the hyperspectral infrared sounder CrIS we present some unique features of the spectral near 9.6 µm and its great potential value for detecting plume or clouds with the tops above tropopause. It is found the existence of two umbrella clouds and the propagation of the upper plume even in 8-9 hour after the eruption. Using a new Single Field-of-view Sounder Atmospheric Products (SiFSAP) from CrIS and ATMS on JPSS-1 that has a high spatial resolution of about 14 km, this study analyzes the impact of Hunga Tonga eruption on the distribution of H 2 O and ozone, particularly the unprecedented ejection of water vapor in the stratosphere. These results demonstrate the value of hyperspectral infrared sounder and single-field-view products for monitoring the volcanic eruption and studying its impact to climate.
Xiaozhen Xiong↗
Pushing the Application Limit of Hyperspectral IR Sounder Remote Sensing for Frontiers of Weather and Climate Studies
Since the launch of AQUA Atmospheric Infrared Sounder (AIRS) in 2002, space-borne hyperspectral infrared (IR) sounders have provided information-rich, climate quality, and time-continuous spectral radiance measurements at the top of the atmosphere for more than two decades. Satellite based hyperspectral IR sensors, including AIRS, Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI), have demonstrated their critical roles for various weather applications and climate related studies. New use of hyperspectral IR sounder data will focus on underexplored areas. Current use of those data is generally limited by the capability of fully exploring and exploiting high spectral resolution information content, achieving radiometric accuracy and stability defined by the instruments, and merging data from different sensors to build a consistent, long-term climate data record. We will present the on-going research efforts at NASA Langley Research Center (LaRC) to develop novel hyperspectral IR sounder data products to address those potentials yet to be fully realized. Some applications of these products, including the study of Planetary Boundary Layer (PBL), the construction of climate data record over polar region, and the fusion of AIRS and CrIS data via the radiometric consistent climate fingerprinting method will be discussed.
Wan Wu↗
Deriving High-quality Climate Data Records from Two Decades of Satellite Hyperspectral Remote Sensors
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Xu Liu↗
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↗
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↗
Development of Radiative Transfer Models and Retrieval Algorithms for Satellite Remote Sensors
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.
Xu Liu↗
Observation of Hunga Tonga Volcanic Eruption Using Hyperspectral Infrared Satellite Sensors
The Hunga Tonga-Hunga Ha'apai volcanic eruption, with the largest eruption occurred on 15 January 2022, injected unprecedented amounts of water vapor (H 2 O) and SO 2 to the stratosphere. Using the hyperspectral infrared sounder CrIS we present some unique features of the spectral near 9.6 µm and its great potential value for detecting plume or clouds with the tops above tropopause. It is found the existence of two umbrella clouds and the propagation of the upper plume even in 8-9 hour after the eruption. Using a new Single Field-of-view Sounder Atmospheric Products (SiFSAP) from CrIS and ATMS on JPSS-1 that has a high spatial resolution of about 14 km, this study analyzes the impact of Hunga Tonga eruption on the distribution of H 2 O and ozone, particularly the unprecedented ejection of water vapor in the stratosphere. These results demonstrate the value of hyperspectral infrared sounder and single-field-view products for monitoring the volcanic eruption and studying its impact to climate.
Xiaozhen (Shawn) Xiong↗
Hyperspectral Sounder Spectral Fingerprinting: Using Machine Learning Techniques to Enhance Model-Based Physical Inversion
Different retrieval algorithms have been developed to process top-of-atmosphere (TOA) spectral radiance data provided by hyperspectral infrared sounder missions. Those algorithms are either optimal estimation method (OEM) based schemes with radiative transfer calculation involved in the retrieval process, or machine learning based methods that allow ultra-efficient data procession but lack of radiometric consistency validation based on the directly measured information. Combining both approaches leverages their respective technical advantages, leading to more accurate results. This study introduces a hyperspectral sounder fingerprinting algorithm to explore this hybrid approach. This approach involves the use of a spectral information-based classification method to identify an reference geophysical state and the corresponding radiative kernel. This enables the efficient retrieval of geophysical variables of interest through a radiative kernel-based linear inversion procedure. The fingerprinting method has been applied to analyze a decade-long hyperspectral sounder data record.
Wan Wu↗
Principal Component-based Radiatiative Transfer Model (PCRTM) for Hyperspectral Remote Sensor
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PCRTM↗