Satya Kalluri

Dr. Satya Kalluri

NOAA/ NESDIS, College Park, MD 20740, USA

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 January 2018 in Remote Sensing
Verified
Journal Article
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SKSatya Kalluri
Satya Kalluri
CAChristian Alcala
Christian Alcala
JCJames Carr
James Carr
PGPaul Griffith
Paul Griffith
WLWilliam Lebair
William Lebair
SZSpencer Zierk
Spencer Zierk
The Advanced Baseline Imager (ABI) is the primary Earth observing sensor on the new generation Geostationary Operational Environmental Satellites (GOES-R) series, and provides significant spectral, spatial and temporal observational enhancements compared to the legacy GOES satellites. ABI also provides enhanced capabilities for operational sensor calibration and image navigation and registration (INR) to enable observations of the Earth with high spectral fidelity as well as creating images that are accurately mapped and co-registered over time. Unlike earlier GOES Imagers, ABI has onboard calibration capability for all sixteen bands in the reflective and emissive bands. The calibration process includes periodic and routine views of the internal reflective and blackbody targets as well as views of space and the moon. Improvements in INR are made possible by having a Global Positioning System (GPS) on board the spacecraft and routine measurements of stars through the sensor’s boresight for orbit and attitude determination through a Kalman filter. This paper describes how the sensor data are processed into calibrated and geolocated radiances that enable the generation of imagery and higher level products for both meteorological and non-meteorological Earth science applications. Some examples of ABI images and calibration are presented to demonstrate the capabilities and applications of the sensor.

17 April 2020 in Remote Sensing
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WWWeile Wang
Weile Wang
SLShuang Li
Shuang Li
HHHirofumi Hashimoto
Hirofumi Hashimoto
HTHideaki Takenaka
Hideaki Takenaka
AHAtsushi Higuchi
Atsushi Higuchi
RNRamakrishna Nemani
Ramakrishna Nemani
GeoNEX is a collaborative project led by scientists from NASA, NOAA, and many other institutes around the world to generate Earth monitoring products using data streams from the latest Geostationary (GEO) sensors including the GOES-16/17 Advanced Baseline Imager (ABI), the Himawari-8/9 Advanced Himawari Imager (AHI), and more. An accurate and consistent product of the Top-Of-Atmosphere (TOA) reflectance and brightness temperature is the starting point in the scientific processing pipeline and has significant influences on the downstream products. This paper describes the main steps and the algorithms in generating the GeoNEX TOA products, starting from the conversion of digital numbers to physical quantities with the latest radiometric calibration information. We implement algorithms to detect and remove residual georegistration uncertainties automatically in both GOES and Himawari L1bdata, adjust the data for topographic relief, estimate the pixelwise data-acquisition time, and accurately calculate the solar illumination angles for each pixel in the domain at every time step. Finally, we reproject the TOA products to a globally tiled common grid in geographic coordinates in order to facilitate intercomparisons and/or synergies between the GeoNEX products and existing Earth observation datasets from polar-orbiting satellites.

1 February 2021 in Bulletin of the American Meteorological Society
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Journal Article
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SKSatya Kalluri
Satya Kalluri
CCC. Cao
C. Cao
AHA. Heidinger
A. Heidinger
AIA. Ignatov
A. Ignatov
JKJ. Key
J. Key
TST. Smith
T. Smith
The Advanced Very High Resolution Radiometers (AVHRR), which have been flying on National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting weather satellites since 1978, provide the longest global record of Earth observations from a visible–infrared imager. Experience gained through AVHRRs has been integral to the development of the new-generation sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and associated data processing algorithms in the United States, as well as a similar class of sensor by space agencies around the world. Over four decades of data have been vital for studying Earth and its change. TheMetOp-Csatellite that was successfully launched in 2018 carries the last AVHRR. This article reviews the contributions of AVHRR in building a continuous global data record over the last 40 years on the occasion of its last launch.

6 September 2020 in Remote Sensing
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Journal Article
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CZCheng-Zhi Zou
Cheng-Zhi Zou
Lihang ZhouLihang Zhou
Lihang Zhou
Lin LinLin Lin
Lin Lin
NSNinghai Sun
Ninghai Sun
Yong ChenYong Chen
Yong Chen
MGMitch Goldberg
Mitch Goldberg
The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.

12 March 2021 in Remote Sensing
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CCChangyong Cao
Changyong Cao
BZBin Zhang
Bin Zhang
XSXi Shao
Xi Shao
Wenhui WangWenhui Wang
Wenhui Wang
SUSirish Uprety
Sirish Uprety
SKSatya Kalluri
Satya Kalluri
Suomi NPP has been successfully operating since its launch on 28 October 2011. As one of the major payloads, along with microwave and infrared sounders (Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS)), and ozone mapping/profiling (OMPS) instruments, the Visible Infrared Imaging Radiometer Suite (VIIRS) has performed for well beyond its mission design life. Its data have been used for a variety of applications for nearly 30 environmental data products, including global imagery twice daily with 375 and 750 m resolutions, clouds, aerosol, cryosphere, ocean color and sea-surface temperature, a number of land products (vegetation, land-cover, fire and others), and geophysical and social economic studies with nightlights. During the early days of VIIRS operational calibration and data production, there were inconsistencies in both algorithms and calibration inputs, for several reasons. While these inconsistencies have less impact on nowcasting and near real-time applications, they introduce challenges for time series analysis due to calibration artifacts. To address this issue, we developed a comprehensive algorithm, and recalibrated and reprocessed the Suomi NPP VIIRS radiometric data that have been produced since the launch. In the recalibration, we resolved inconsistencies in the processing algorithms, terrain correction, straylight correction, and anomalies in the thermal bands. To improve the stability of the reflective solar bands, we developed a Kalman filtering model to incorporate onboard solar, lunar, desert site, inter-satellite calibration, and a deep convective cloud calibration methodology. We further developed and implemented the Solar Diffuser Surface Roughness Rayleigh Scattering model to account for the sensor responsivity degradation in the near infrared bands. The recalibrated dataset was validated using vicarious sites and alternative methods, and compared with independent processing from other organizations. The recalibrated radiometric dataset (namely, the level 1b or sensor data records) also incorporates a bias correction for the reflective solar bands, which not only addresses known calibration biases, but also allows alternative calibrations to be applied if so desired. The recalibrated data have been proven to be of high quality, with much improved stability (better than 0.3%) and accuracy (by up to 2%). The recalibrated radiance data are now available from 2012 to 2020 for users and will eventually be archived on the NOAA CLASS database.

6 October 2020 in Remote Sensing
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Nicholas R. NalliNicholas R. Nalli
Nicholas R. Nalli
CTChangyi Tan
Changyi Tan
JWJuying Warner
Juying Warner
MDMurty Divakarala
Murty Divakarala
AGAntonia Gambacorta
Antonia Gambacorta
MRMarkus Rettinger
Markus Rettinger
This paper provides an overview of the validation of National Oceanic and Atmospheric Administration (NOAA) operational retrievals of atmospheric carbon trace gas profiles, specifically carbon monoxide (CO), methane (CH4) and carbon dioxide (CO2), from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), a NOAA enterprise algorithm that retrieves atmospheric profile environmental data records (EDRs) under global non-precipitating (clear to partly cloudy) conditions. Vertical information about atmospheric trace gases is obtained from the Cross-track Infrared Sounder (CrIS), an infrared Fourier transform spectrometer that measures high resolution Earth radiance spectra from NOAA operational low earth orbit (LEO) satellites, including the Suomi National Polar-orbiting Partnership (SNPP) and follow-on Joint Polar Satellite System (JPSS) series beginning with NOAA-20. The NUCAPS CO, CH4, and CO2 profile EDRs are rigorously validated in this paper using well-established independent truth datasets, namely total column data from ground-based Total Carbon Column Observing Network (TCCON) sites, and in situ vertical profile data obtained from aircraft and balloon platforms via the NASA Atmospheric Tomography (ATom) mission and NOAA AirCore sampler, respectively. Statistical analyses using these datasets demonstrate that the NUCAPS carbon gas profile EDRs generally meet JPSS Level 1 global performance requirements, with the absolute accuracy and precision of CO 5% and 15%, respectively, in layers where CrIS has vertical sensitivity; CH4 and CO2 product accuracies are both found to be within ±1%, with precisions of ≈1.5% and ⪅0.5%, respectively, throughout the tropospheric column.