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NASA NTRSDate not supplied

Status of the GSICS VIS/NIR DCC Calibration Efforts

This year's goals for the GSICS VIS/NIR group is to finalize the VIS/NIR demonstration product requirements and to process the product for public dissemination provided on the GSICS web page. The GSICS VIS/NIR group members have been working on a unified calibration approach among various agencies. Two calibration methods have been chosen for the visible bands, deep convective clouds (DCC) and lunar invariant targets. To come to consensus across the agencies, each step of the DCC process will be outlined. Brief discussions are to follow to determine any outstanding issues. The presentation will review the DCC calibration process implemented by the CERES calibration team. CERES has already implemented the DCC method across 18 geostationary satellites. The various agencies have taken the framework and optimized the method for their particular geostationary satellite. Several new improvements will be discussed, such as deseasonalization of the DCC reflectances, impact of the bidirectional model, and update frequency.

David Doelling↗
NASA NTRS2010

TPSAS-NF1676L-10863-DND

One important aspect of successful climate monitoring is satellite calibration. There is at least a 25-year of operational geostationary (GEO) record available for climate studies, if properly calibrated. The Global Space-based Inter-Calibration System (GSICS) project is another effort to provide the climate community consistent calibration across multiple platforms. Also, the Clouds and the Earth's Radiant Energy System (CERES) project, provides consistent GEO retrieved cloud properties and derived broadband fluxes across multiple platforms. This year GSICS is focusing on geostationary visible channel calibration. The GSICS strategy is to use multiple approaches, such as cross-calibrating the GEO radiances against MODIS as a reference, deep convective clouds as bright stable targets, deserts, sun-glint, stars, moon and other model based calibration methods. Each of these methods is independent of each other and can assess the stability of the GEO visible instrument with differing uncertainties. This study focuses on the inter-calibration of the GEO radiances against MODIS as a reference by using collocated, and coincident ray-matched radiances. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. This presentation will focus on the technique, some error analysis, comparisons with other methods, and an approach to inter-calibrate historical GEOs before MODIS.

D R Doelling↗
NASA NTRS2020

SEASONAL VARIATION IN THE MEASUREMENT OF GOES-16 ABI CHANNEL-TO-CHANNEL REGISTRATION

An Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) was developed to assess the US Geostationary Operational Environmental Satellite R-series (GOES-R) Advanced Baseline Imager (ABI) and Geostationary Lighting Mapper (GLM) INR performance.Channel-to-channel registration (CCR) is one of the five INR performance metricsproduced by IPATS. A seasonal variationis observed in the CCR assessment in north-south direction when one or both channels are reflective. However, indirect CCR, calculated as the difference of NAV measurements between two channels, does not presentthe similar seasonal variation. The phenomenon of the seasonal variationcoincides with the annual change of the subsolar point location. The amplitude of the seasonal variation is related tothe length and the direction of the shadow. DirectCCR, measured by IPATSdirectly,performs better than indirect CCR when both channels are visible wavelengthsor emissivechannels. For all other channel paircombinations, the assessment of indirect CCR is more accurate.

Bin Tan↗
NASA NTRSDate not supplied

Short Time Scale Stability Monitoring of GOES-16 Visible Channels by Utilizing Daily Inter-Calibration Events with both VIIRS and MODIS Sensors

The CERES project relies on MODIS, VIIRS and geostationary (GEO) imager retrieved cloud properties to compute surface fluxes and convert CERES and GEO radiances into TOA fluxes. The CERES TOA and surface fluxes need to be of climate quality and any anomaly or discontinuity in the calibration of the MODIS, VIIRS, GEO radiances need to be mitigated or avoided. Due to the nature of the CERES instrument calibration, there is a lag time of 3 months before the processing of the CERES product. This allows the CERES team to investigate any unforeseen problems in the input datasets or GEO calibration discontinuities or anomalies before processing. The CERES geostationary imager calibration team is developing a daily monitoring system of GEO, MODIS and VIIRS visible channel radiances in order to detect any day to day discontinuities as part of the CERES/GEO coincident ray-matching calibration efforts. a GEO discontinuity can be detected using two MODIS and 2 VIIRS sensors simultaneously, thus increasing the sampling greatly over a single GEO/LEO radiance pairs. This method is being automated and has already detected three erroneous radiometric calibration events, which were verified with the GOES-16 event log page. One advantage of daily monitoring is that the time period needed to verify calibration drifts is reduced and the confidence to detect even smaller magnitudes of the calibration drift is increased over monthly monitoring. By utilizing Terra and Aqua MODIS and NPP and NOAA20 VIIRS imagers to inter-calibrate GOES-16, the GOES-16 calibration can be referenced to anyone of these imagers. If the CERES project transitions between the Aqua-MODIS imager to the NOAA20 VIIRS imager, the NOAA-20 VIIRS imager can be radiometrically scale to Aqua-MODIS calibration, thus avoiding a GOES-16 calibration discontinuity.

David Robert Doelling↗
NASA NTRS2020

Reflective Solar Band Striping Mitigation Method for the GOES-R Series Advanced Baseline Imager Using Special Scans

The large focal plane arrays used in the new generation of the Geostationary Operational Environmental Satellites (GOES) advanced baseline imager (ABI) introduce new calibration challenges compared with the heritage GOES imagers. The increased number of detectors allows for increased spatial, spectral, and temporal performance, but as a trade-off, it has an increased risk of image striping. We detail the development of a new postlaunch relative calibration capability for ABI reflective solar bands that utilizes ABI special scans to generate a set of relative gains that can be applied to improve image quality and reduce image striping. Results demonstrate that the method reduces image striping in the ABI solar reflective bands over varying scene content and time, both diurnally and over an extended period. This methodology ensures a calibration strategy that is consistent with heritage approaches yet adapts to the new postlaunch validation challenges presented by the new class of operational imagers in the GOES-R series. The developed approach is ready for operational use, as needed, and can be easily implemented into operations to support the operational production of geostationary imagery of the Earth.

Monica Cook↗
NASA NTRSDate not supplied

Mapping Ocean-Reflected Radio Frequency Interference for the GPM Microwave Imager Using Normalized Retrieval Cost Function

By adapting an approach originally developed for WindSat, we identify regions where GMI is affected by radio frequency interference from ocean-reflected geostationary satellite emissions. Around North America, K-band emissions from geostationary satellites affect the GMI 18.7-GHz brightness temperatures, resulting in increases in the retrieval cost function. The method does not detect any 10.7-GHz RFI reflected of the ocean surrounding Europe. This study, which depends on the physically-based forward model for non-raining ocean retrievals, confirms results from a previous study that employed an empirical methodology.

Ian S. Adams↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with a high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of the atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRSDate not supplied

How Well Satellite Remote Sensing Can Inform Surface Level Ozone Production Sensitivity to Precursor Trace Gas Emissions?

Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.

Satellite↗
NASA NTRS2021

Second Time-Resolved Observations of Precipitation Structure and Storm Intensity With a Constellation of Smallsats (TROPICS) Mission Applications Workshop

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of state-of-the-science observing platforms that will measure temperature and humidity soundings and precipitation with spatial resolution comparable to current operational passive microwave (PMW) sounders but with unprecedented temporal resolution (Mission Website).1 TROPICS is a cost-capped ($30.2 million), Venture-class mission funded by the NASA Earth Science Division (ESD) and led by Principal Investigator Dr. William Blackwell from the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). The mission consists of a constellation of six, three-unit (3U) CubeSats (approximately 10×10×34 cm), each hosting a 12-channel PMW spectrometer based on the Micro-sized Microwave Atmospheric Satellite-2 (MicroMAS-2) developed at MIT LL, but with a substantially improved design. TROPICS will provide imagery near 91 and 205 GHz, temperature sounding near 118 GHz, and moisture sounding near 183 GHz. Spatial resolution at nadir will be around 27 km for temperature and 17 km for moisture and precipitation with a swath width of approximately 2,000 km from a 550-km orbit altitude. Both the spatial resolution and swath width are similar to the Advanced Technology Microwave Sounder (ATMS) that is being flown as part of the Suomi National Polar-orbiting Partnership (SNPP) and National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS). In addition, TROPICS meets many of the requirements outlined in the 2007 Decadal Survey for the Precision and All-Weather Tempera-ture and Humidity (PATH) mission, which was originally envisioned as a microwave instrument in geostationary orbit. TROPICS enables temporal resolution approaching that of geostationary orbit but at a much lower cost, demonstrating a technology that could impact the design of future Earth-observing missions. The satellites for the TROPICS mission were delivered to NASA in 2019 for launches planned in the 2021–2022 timeframe. The primary mission objective of TROPICS is to relate temperature, humidity, and precipitation structure to the evolution of tropical cyclone (TC) intensity.

remote sensing↗
NASA NTRS2019

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗
NASA NTRS2020

An Algorithm for Hyperspectral Remote Sensing of Aerosols: 3. Application to the GEO-TASO Data in KORUS-AQ Field Campaign

This paper describes the third part of a series of investigations to develop algorithms for simultaneous retrieval of aerosol parameters and surface spectral reflectance from the data measured by GEOstationary Trace gas and Aerosol Sensor Optimization (GEO-TASO) instrument. Since the algorithm is designed for future hyperspectral and geostationary satellite sensors, such as Tropospheric Emissions: Monitoring of Pollution (TEMPO), it is applied to GEO-TASO data measured over the same area by different flights as part of the Korea-United Stated Air Quality Study (KORUS-AQ) field campaign in 2016. While GEO-TAOS has a spectral sampling interval of ~0.28 nm in the visible, its data is thinned through a band selection approach with consideration of atmospheric transmittance and different surface types, which yields 20 common spectral bands to be used by the algorithm. The algorithm starts with 4 common principal components (PCs) for surface spectral reflectance extracted from various spectral libraries, and the constraints of surface reflectance parameters and aerosol scattering models respectively from k- means clustering analysis of the Rayleigh-corrected GEO-TASO spectra and AERONET data. The algorithm then proceeds iteratively with an optimal estimation approach to update PCs and retrieve aerosol optical depth (AOD) until the best match between simulated and GEOS-TASO measured spectra is achieved. The spectral AODs are compared between those retrieved from GEO-TASO (x) and 7 AERONETS (y) in 440, 550, 550, 675 nm, respectively. The comparison reveals that iterative updates of surface spectral PCs (and so surface reflectance) yield significant enhancement in AOD retrievals, improving the mean linear fitting equations from y = 0.735x + 0.088 (without update of PCs) to y = 1.055x+ 0.01, and the Pearson correlation coefficient (𝑅𝑅2) from 0.54 to 0.76, respectively. Move case studies are need to further evaluate the algorithm for its application to TEMPO that carries a enhanced version of GEO-TASO instrument.

Tropospheric Emissions: Monitoring of Pollution (T↗
NASA NTRS2019

Field Calibration Techniques used to Characterize the Radiometric Stability of the GEO-CAPE Airborne Simulator (GCAS)

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed at NASA’s Goddard Space Flight Center (GSFC) and has flown in multiple field campaigns to perform mapping of the regional-scale EPA criteria pollutants nitrogen dioxide, ozone, and formaldehyde. GCAS will also participate invalidation campaigns for NASA’s Tropospheric Emissions: Monitoring POllution (TEMPO) mission and the Korean Geostationary Environment Monitoring Spectrometer (GEMS) mission, both scheduled to launch in the early 2020s. GCAS houses two commercial Offner-type grating spectrometers that measure backscattered solar spectral radiance from the near-ultraviolet to near-infrared at high spatial resolution (typically 250 meters at 8.5 kilometer altitude). These radiances are used to retrieve spatial and temporal distributions of trace gases relevant to the boundary layer and free tropospheric atmospheric chemistry cycles. In this paper, we describe the field calibration techniques employed to characterize the spectral and temporal radiometric stability of the system during its most recent deployment in the 2018 Long Island Sound Trace Ozone Study (LISTOS) field campaign. Overall measurement uncertainty, retrieval impacts, and lessons learned for future deployments will also be described.

NASA’s Tropospheric Emissions: Monitoring POllutio↗
NASA NTRSDate not supplied

Design and Optimization of Steering Laws for Geocentric Solar Sailing

Solar sail technology has the potential to be a practical method of propulsion for future deep space Cubesats and small satellites. Although in general, deep space, heliocentric flight is the optimal regime for solar sailing, many near-term solar sail flight demonstrations have, or will occur in Earth-centered orbits. This is particularly true for low-cost, smallsat-based solar sail technology demonstration flights, such as the Planetary Society LightSail 1 and 2, and the upcoming NASA Advanced Composite Solar Sail System (ACS3). ACS3 will be the first spaceflight application of NASA’s newest smallsat deployable composite boom technology, and NASA’s first practical solar sail. Launch of ACS3 is currently anticipated for late 2021 or early 2022. In this paper, we will describe the challenges of operating solar sailing spacecraft in low Earth orbits, where, depending on initial orbital altitude and inclination, disturbances due to aerodynamic drag, eclipsing can be of the same order or greater than forces caused by solar radiation pressure. A notional smallsat-class solar sailing vehicle based on the ACS3 solar sail will be used as a reference for trajectory design and optimization studies. As a starting point we will assume initially circular orbits, and a locally optimal steering law designed to maximize the rate of change in semi major axis, similar to that described by McInnes. This will be generalized to orbits with arbitrary initial inclinations and non-zero eccentricities, and to account for atmospheric drag and eclipsing effects. Optimal steering laws for maximizing rate-of-change in orbit inclination and eccentricity will also be explored. Finally, we will examine potential for Earth-centered solar sailing mission applications beyond technology demonstrations, including: continuous observations from inside the Earth’s magnetotail; augmented geostationary capabilities from displaced geostationary orbits; and continuous polar observation for climate science investigations from pole-sitter orbits.

W. Keats Wilkie↗
NASA NTRSDate not supplied

Development of the GeoNEX Level 2G Products: Exploiting the Diurnal Variability of TOA Reflectance in Atmospheric Correction

This study develops a new atmospheric correction algorithm to generate the Level 2G products, in particular the gap-filled Surface Reflectance at 10-minute time steps, for the Geostationary-NASA Earth Exchange (GeoNEX) project. The algorithm is based on the MODIS MAIAC (Multi-Angle Implementation of Atmospheric Correction) framework but with significant modifications to exploit angular/temporal information from the diurnal variability of the GeoNEX L1G TOA (Top-of-Atmosphere) reflectance. The algorithm starts by evaluating the roughness/smoothness of the diurnal time series of the TOA reflectance. Because rapid changes in TOA reflectance are generally caused by passing clouds or shadows, rough segments of the time series are automatically filtered out while the smooth segments are further tested for brightness and temperature to identify clear-sky and snow-free observations. Next the algorithm runs the MAIAC RTM (Radiative Transfer Model) to retrieve the Ross-Thick-Li-Sparse (RTLS) BRDF model parameters and the daily-mean atmospheric optical depth (AOD) that allow the RTM to optimally simulate the observed diurnal variability of clear-sky TOA reflectance. Once the initial RTLS parameters are retrieved after the algorithm’s burn-in period, they are used as the prior information to predict the AOD level for the next days, while the subsequent clear-sky observations are used to make necessary adjustments to the RTLS parameters in an continuous fashion. This “prediction-analysis” cycle is then iterated to process the full time series of the L1G data, skipping only total-cloudy days or when surface snow is detected. We tested the algorithm over a list of selected AERONET sites. The retrieved results (the daily mean AOD and the RTLS parameters) reasonably agree with the ground-based measurements. Importantly, the results indicate that the diurnal cycles of surface reflectance are continuous functions of the illumination-view geometry. Thus we can use the retrieved RTLS model to accurately fill in data gaps on partial cloudy days. Also, our algorithm is totally independent from the traditional approaches based on the use of spectral band ratios between the shortwave infrared (e.g., 2.2µm) and the visible (e.g., 0.47µm and 0.64µm) bands. Our results thus demonstrate that the high-frequent diurnal geostationary observations contain unique information that helps us improve atmospheric correction of remote sensing data.

GeoNEX↗
NASA NTRSDate not supplied

The Radiometric Scaling of the MODIS and VIIRS Imagers to a Common Reference and Stability Analysis for the Next Edition of CERES Products

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert Terra, Aqua, NPP, and NOAA-20 CERES footprint radiance observations into fluxes. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The CERES imager and GEO calibration team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to the Aqua-MODIS calibration reference. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The team will rely primarily on deep convective clouds to monitor the imager channel calibration stability and to correct for short term calibration drifts. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. The excellent radiometric stability of EPIC allows the use of EPIC observations as a stable reference to validate both the short term drift corrections of the imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗
NASA NTRSDate not supplied

High Latitude Considerations in the Latest GPCP monthly and daily products (V3.1)

The Global Precipitation Climatology Project (GPCP) product is a popular combined satellite-gauge precipitation data set in which the long-term standards of consistency and homogeneity is underlined. Here we discuss various high latitude analysis considered in the recently released GPCP V3.1 monthly and daily products. Satellite data are used over land and ocean and obtained from the Special Sensor Microwave Imager (SSMI), Special Sensor Microwave Imager/Sounder (SSMIS), geostationary imagers and polar orbiting infrared sounders. GPCP uses the Global Precipitation Climatology Centre (GPCC) over land, as its in situ component, but prior to combination with satellite data GPCC estimates are adjusted for gauge undercatch. Advanced sensors aboard the Tropical Rainfall Measuring Mission (TRMM), CloudSat, and Global Precipitation Measurement (GPM) mission have enabled more accurate estimation of rain and snowfall rates in recent years. Started with GPCP V3.1 these observations are integrated into GPCP through the development of the Tropical Combined Climatology (TCC) used at lower latitudes and the Merged CloudSat, TRMM, and GPM (MCTG) climatology used over the extra tropics and higher latitudes. Improved calibrations of Television-Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) and Advanced Infrared Sounder (AIRS) precipitation are used outside 60ºN-S, where inside this zone the Goddard Profiling (GPROF) algorithm retrievals from SSMI/SSMIS is used to calibrate geostationary IR based precipitation estimate at monthly scale. The Gravity Recovery and Climate Experiment (GRACE) mass change observations are used to determine snowfall accumulations over frozen land and arctic basins and to assess gauge undercatch corrections. Observations of snow on sea ice from NASA’s Operation IceBridge (OIB) flights are utilized as an additional tool for snowfall assessment over sea ice. GPCP V3.1 has higher spatial resolution (0.5ox0.5o) than earlier versions (2.5ox2.5o) over both land and ocean, going back to 1983. Version 3 Daily product uses the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) Final Run V06 estimates, where available (initially restricted to 60°N-S), as well as rescaled TOVS/AIRS data in high-latitude areas, all calibrated to the GPCP V3.1 Monthly estimate. GPCP V3.1 shows about 6% increase in global oceanic precipitation and about 4.5% increase over global land and ocean compared to the previous version (V2.3), some major changes occur over the ocean and around 40oS and 60 oS. We will discuss other important changes of GPCP V3.1, compared to the earlier versions, and our future plans. Through this presentation we will also discuss that while ACCP will provide key information about precipitation, synergistic use of other Earth observing systems (e.g., mass change; recognized as a designated mission in 2017 decadal survey) can also help refine precipitation analysis, especially in high latitude and cold regions.

Ali Behrangi↗
NASA NTRSDate not supplied

Investigating Lightning Behavior in Rapidly Intensifying Atlantic Tropical Cyclones

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). The Geostationary Lightning Mapper (GLM) aboard the GOES-16 geostationary satellite measures a multitude of lightning parameters, such as flash extent density (FED), average flash area (AFA) and optical energy for most of North America, South America, and the Pacific Ocean. GLM has brought about an era of spaceborne measurements to track storms many miles off the coasts and has allowed for the study of lightning throughout a TCs entire lifespan. FED has been found to be indicative of strength and intensification in TCs, but optical energy is a relatively new parameter that has not been studied intensively. This presentation analyzes the relationship between rapid intensification (RI) and GLM optical energy, AFA, and FED in Hurricanes Florence (2018) and Laura (2020). Using a 24-hour time interval in which each storm underwent RI, optical energy was analyzed from the innermost 100 kilometers of the eye and then was averaged for each minute to determine if there was a relationship between optical energy, AFA, FED, and intensification. Optical energy, FED, and AFA spiked just before RI began and then fell as the storms intensified more rapidly. These parameters increased again as intensification slowed slightly, while the optical energy peaks much lower in Hurricane Laura and much higher in Hurricane Florence. While these results show a pattern in lightning in these two TCs, further investigation of parameters like updraft strength and charge separation from microwave imagery during these secondary peaks in which optical energy behaves differently than the first peak may provide further insight as to the behavior of these TCs during RI.

Kiahna Mollette↗