New satellite constellations to provide high-resolution atmospheric observations from microwave (MW) sounders operating in low-Earth orbit are now coming online and are providing operationally useful data. The first of these missions, the NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Earth Venture (EVI-3) mission, was successfully launched into orbit on May 7 and 25, 2023 (Eastern Daylight Time, two CubeSats in each of the two launches). TROPICS is now providing nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS is providing rapid-refresh MW measurements (median refresh rate of better than 60 min early in the mission with four functional CubeSats, and now approximately 70–90 min with three functional CubeSats) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. Hundreds of high-resolution images of TCs have been captured thus far by the TROPICS mission, revealing the detailed structure of the eyewall and surrounding rain bands. The new 205-GHz channel in particular (together with a traditional channel near 92 GHz) is providing new information on the inner storm structure, and, coupled with the relatively frequent revisit and low downlink latency, is already informing TC analysis at operational centers. Here, we present an overview of the TROPICS mission after two years of successful science operations with a focus on the suite of geophysical (Level 2) products (atmospheric vertical temperature and moisture profiles, instantaneous surface rain rate, and TC intensity) and the science investigations that have been enabled by these new measurements.

During the Asian summer monsoon rainy season, heavy and continuous rainfall usually causes widespread floods in many Asian countries, including the two most populated countries China and India. Flood mapping datasets from moderate-resolution satellites, such as the JPSS (Joint Polar Satellite System) series including Suomi-NPP (Suomi National Polar-orbiting Partnership) and NOAA-20, can be invaluable for monitoring floods and assessing the affected population. The flood maps derived from the VIIRS (Visible Infrared Imaging Radiometer Suite) imagery can provide a big picture of what’s on the ground over the entire Asia flooding region. The VIIRS 5-day composite flood maps, along with a population density dataset, can be combined to estimate the population potentially exposed (PPE) to flooding. The VIIRS flood maps demonstrate floods in China primarily occurred along the Yangtze River Basin and its tributaries. The VIIRS 5-day composite flood maps, along with a population density dataset, were combined to estimate the population potentially exposed to flooding. Here we use the summer of 2020 as an example, based on the flood extent along with the population density map, approximately over 50 million people in the entire China might have been affected by the floodwaters. In addition to China, several other countries including India, Bangladesh, and Myanmar were also affected. In India, the worst inundation and the affected population were located mainly in the northern states of Bihar, Assam, and West Bengal.

Long-term flood mapping datasets can be invaluable for historic flood investigation, flood potential or probability estimate, time series analysis and modelling, and climate change studies. With the developed flood detection algorithm and software for JPSS/VIIRS (Visible Infrared Imaging Radiometer Suite) (Li et al., 2017), in this study, VIIRS historic data since 2012 has been reprocessed from JPSS (Joint Polar Satellite System) series including Suomi-NPP (Suomi National Polar-orbiting Partnership) and NOAA-20. VIIRS global flood time series datasets have been generated and distributed by NOAA through Amazon Web Services (AWS). The derived dataset includes granule flood product, daily and 5-day composited flood products in netCDF4, geotiff and shapefile formats from 2012 to 2020. The dataset not only provides data records of historic flood events, but also shows potential in flood analysis and modelling. With the dataset, a simple application using annual composition is performed to analyze the annual change of flood extent globally and in each continent. The analysis has shown a slightly increasing trend in flood extent at a global scale, but varying in different regions.

Over ten-years, the Integrated Calibration and Validation System (ICVS) Long-Term Monitoring (LTM) System has provided near-real time (NRT) monitoring for Joint Polar Satellite System (JPSS) spacecraft and instruments including their on-orbit status and performance and science data product quality [1] - [4]. The ICVS also harnesses JPSS Sensor Data Record (SDR) data to rapidly (with little latency) visualize radiometric features of severe weather events such as hurricanes and volcanos [5] [6]. This study presents two case studies, one depicting the 3-dimensional (3D) atmospheric warm core structure inside Hurricane Ian from the 2022 North Atlantic Hurricane Season and another showing the 3D temperature structures present during the 2021 Heat Dome event by using JPSS ATMS (and VIIRS for hurricane events) SDR and TDR data. More details and images/animations for hurricane events can be found at https://www.star.nesdis.noaa.gov/smcd/sew/index.php.

The Suomi National Polar-orbiting Partnership (SNPP) satellite successfully completed 10 years of operations. SNPP enabled the success of JPSS mission and bridged the gap between legacy POES and JPSS satellites. This paper highlights the contributions of SNPP mission to the JPSS mission.

Near real-time satellite-derived flood maps are invaluable to river forecasters and decision-makers for disaster monitoring and relief efforts. Combining utilization of the LEO (low earth orbiting) and GEO (geostationary) satellite imagery shows great advantages in flood mapping. With the support from NOAA/NASA JPSS (Joint Polar Satellite System) Program and GOES-R program, the flood mapping system has been developed to derive flood maps from Suomi-NPP (Suomi National Polar-orbiting Partnership) & NOAA-20/VIIRS (Visible Infrared Imaging Radiometer Suite) imagery, GOES-16&17/ABI (Advanced Baseline Imager) imagery, and Himawari-8/AHI imagery. These flood maps are generated on a routine base at Space Science and Engineering Center at University of Wisconsin-Madison and have been applied in flood operations. Initial feedback from river forecasters on the product accuracy and performance has been largely positive. Evaluation efforts including visual inspection and quantitative validation using Landsat-8/OLI and Sentinel-2 imagery, and aerial photos have demonstrated steady performance of these products, which indicates a high feasibility of these flood maps to be produced at the product level.

Since early 2012, the cross-track infrared sounder (CrIS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has continually provided the hyperspectral infrared observations for profiling atmospheric temperature, moisture, and greenhouse gases. In this study, the CrIS sensor data record (SDR) data are improved for climate applications with its fine-tuning of calibration coefficients in an NOAA reprocessing project. A specific software system was developed to reprocess the CrIS SDR. This software system was updated with a new calibration algorithm, nonlinearity, and geolocation to improve the SDR data quality and long-term consistency. The calibration coefficients are refined with the latest updates, which were used to calibrate the latest operational SDR products and replace those in the engineering packet (EP) in the raw data record (RDR) data stream. The resampling wavelength was updated based on the metrology laser wavelength and resulted in zero sampling error in the spectral calibration. All the historical SDRs (from February 2012 to March 2017) were generated with the same calibration coefficients and same version of the processing software system, resulting in improved accuracy and stability in terms of spectral and radiometric calibration during the CrIS lifetime mission. The quality of the reprocessed CrIS SDR data at nominal spectral resolution (NSR) is assessed in terms of its radiometric and spectral calibration. Comparisons against the operational SDR data are carried out to demonstrate the improved long-term stability of the reprocessed CrIS SDR data. Overall radiometric biases are found to be small and highly stable over the instrument mission, the FOV-to-FOV differences are less than ~10 mK, and much better than that from the operational SDR data. It is shown that the CrIS metrology laser wavelength varies within 4 ppm as measured by the neon calibration system. The reprocessed SDR data have spectral errors less than 0.5 ppm, which is much better than the operational SDR data with about 4 ppm. This baseline version of the reprocessed SNPP CrIS SDR data is suitable for long-term climate monitoring and model assessments and can provide an infrared reference observation to assess other narrow- or broadband infrared instruments’ calibration accuracy.

The NOAA Unique Combined Atmospheric Processing System (NUCAPS) is the official operational hyperspectral enterprise sounding product system that produces vertical profiles of temperature, water vapor, ozone, and a variety of trace gas products (e.g. CO, CH4, and CO2). These products provide continued support of global environmental data from multiple polar-orbiting satellites to monitor atmospheric composition, trace gas concentrations, climate change and Earth system processes. This paper presents an overview of the NUCAPS atmospheric composition products, performance, and utilization for many regional and global applications. Future plans on collaborations, special data needs by user communities, and upgrades to the data products to support near real-time applications are discussed. In addition, continued efforts towards reprocessing to generate mission-long high-quality science products, adapting to enterprise algorithms, and providing calibrated radiances and geophysical data products via direct broadcast networks are discussed for user awareness and international collaborations.

An operational GOES ET and Drought (GET-D) product system has been developed at NESDIS of NOAA for numerical weather prediction (NWP), national water model validation, and drought monitoring. The GET-D system was generating ET and Evaporative Stress Index (ESI) maps at 8 km spatial resolution using thermal infrared (TIR) observations from the Imagers on GOES-13 and GOES-15 satellites. With the primary operational GOES satellites transitioned to GOES-16 and GOES-17 with the Advanced Baseline Imagers (ABI), the GET-D system is being upgraded to seamlessly generate ET products using ABI observations from GOES-16/17 at high special resolution of up to 2 km. The new ET product will be comprehensively validated using ground ET measurements. Moreover, AMSR2 Ka band observations will be coupled with the GOES TIR channel using machine learning technique to fill in cloudy pixels where current ET retrievals cannot be obtained because of cloud contamination. The all-weather ET product will also be validated against in-situ observations. Preliminary validation results will be presented in this paper.

Radiances and Environmental Data Records (EDR) from the Joint Polar Satellite System (JPSS) are critical for weather prediction. A variety of EDRs such as fire detection, retrievals of aerosols and water vapor are used by forecasters to provide warnings and alerts during disasters. Several JPSS products also provide continuity of essential climate variables such as upper atmospheric temperature and ozone concentration for climate change monitoring.

In this presentation, we present details on ways that the Joint Polar Satellite System (JPSS) Program uses its investments in environmental satellites to benefit not only the NOAA mission but other countries as well. The United States component of polar satellite, the NOAA-20 and the Suomi National Polar-orbiting Partnership (Suomi NPP) satellites continue to provide critical data and products to support user missions worldwide. New sensors are being built and integrated onto the next satellites in the JPSS Program. The JPSS Program is also starting to consider what its polar satellite program may look like after the last JPSS Satellite is launched.

The NOAA Unique Combined Atmospheric Processing System (NUCAPS) is currently the National Oceanic and Atmospheric Administration (NOAA) operational hyper-spectral infrared sounding product system for deriving vertical profiles of temperature, water vapor, ozone, and trace gas products (CO, CH4, and CO2). In pursuance on the use of European Organisation for the Exploitation of Meteorological Satellite Second Generation (EUMETSAT-SG, expected launch in 2022) IASI Next Generation (IASI-NG) hyperspectral observations, NOAA Center for Satellite Applications and Research (STAR) has initiated refinements to the NUCAPS algorithm to produce NOAA unique products from the IASI-NG and accompanying Microwave Sounder (MWS). This paper presents an overview of the NUCAPS Suomi-NPP/NOAA-20 products performance and on-going efforts in setting up a NUCAPS-NG product development system using proxy/synthetic data sets provided by the EUMETSAT and generated at STAR for the IASI-NG instrument.

The latest generation of geostationary satellites (Himawari 8/9, GOES-16/17, FY-4, GK-2A) carries sensors that closely mimic the spatial and spectral characteristics of widely used polar-orbiting, global monitoring sensors such as MODIS and VIIRS. When combined, data from various currently operating/planned geostationary platforms provide a geo-ring of hyper-temporal (5-10 minutes), multispectral observations at spatial resolutions as high as 500 m. These high frequency observations offer exciting new possibilities for monitoring our planet, including better retrievals of geophysical variables by overcoming cloud cover, enabling studies of diurnally varying phenomena in the atmosphere, land, and the oceans, and support operational decision-making in agriculture, hydrology and disaster management. The NASA Earth Exchange (NEX) team, in collaboration with scientists from JAXA, KARI, NOAA and other international institutions, created the GeoNEX (www.nasa.gov/geonex) pipeline to integrate data from all available geostationary platforms and produce and distribute spatially, temporally, and radiometrically consistent data for the earth science community. We envision various institutions adapting the Geo component (e.g., GeoNOAA, GeoKARI, GeoChiba, GeoJAXA, GeoCMA) and customizing the pipeline and downstream products to serve the local/regional research and applied science communities.

In this work, the current performance of the calibrated Joint Polar Satellite System (JPSS) Cross-track Infrared Sensor (CrIS) observations is reported. The CrIS instrument is currently on-board the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 spacecraft, and planned for the JPSS-2, -3 and -4 satellites. Presently, calibrated and validated CrIS observations, in the form of sensor data record (SDR) products, are being assimilated by operational NWP models and atmospheric retrieval systems. CrIS measurements from SNPP and NOAA-20 are expected to improve our understanding of the dynamics of the atmosphere due to the higher temporal and spatial coverage resulting from optimally blending the hyperspectral Earth observations. This work also reports recent improvements performed on the CrIS SDR products, including: 1) the implementation of the polarization correction, 2) the optimization of the spike detection and correction algorithm, and 3) the optimization of the lunar intrusion algorithm.

National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometers (AVHRR) which has been flying on polar orbiting weather satellites since 1978 provide the longest global daily record of Earth observations. Data from AVHRRs have been vital for studying global change through their remote sensing observations of land, oceans, atmosphere and the cryosphere. MetOp-C satellites that was launched successful this year carries the last AVHRR. This paper reviews the glorious contributions of AVHRR during the past 40 years.

Imaging radiometers such as the advanced baseline imager and the advanced Himawari imager on the new generation geostationary environmental satellites provide new opportunities for several non-meteorological applications. Examples of three such applications in fire detection, monitoring atmospheric aerosols for air quality and modelling downwelling solar radiation for power plants are presented here.

The NOAA-20 Ozone Mapping and Profiler Suite (OMPS) is one of the five instruments in the US Joint Polar Satellite System (JPSS) program. Like the first OMPS instrument [1],[2], the N20 OMPS contains two advanced nadir viewing hyper-spectral instruments, the Nadir Profiler and the Nadir Mapper, to track the health of the ozone layer via measurements the concentration of ozone in the Earth's atmosphere. This paper presents the NOAA-20 OMPS in-flight spectral calibration through solar observations and Earth views. Using a working solar diffuser and a reference solar diffuser, changes in the instruments' wavelength registration are determined through the OMPS solar calibrations. The observed sensor degradation at the shortest wavelengths is less than 0.5% for the sensor optics, but in excess of 1.0% for the OMPS working solar diffuser. The absolute irradiance calibration uncertainties meet system requirement of 7% for most of the channels. The in-flight sensor wavelength variation due to thermal-optical influence is less than 0.02 nm, which could cause about 1.6% error, not compliant with a 2% allocation, so a routine wavelength calibration will take place to accommodate the exceedance.

The Suomi National Polar-orbiting Partnership NPP satellite, which was launched in October 2011 as the predecessor to the recently launched Joint Polar Satellite System (JPSS-1, November 11, 2017) satellite has been extremely successful in operations for the last six years. In order to realize mission-long products of consistent high quality, the JPSS program at the Center for Satellite Applications and Research (STAR) has initiated reprocessing of S-NPP geophysical data products (termed as Environmental Data Records or EDRs) using the most matured enterprise algorithms. The Sensors Data Records (SDRs) needed as inputs to generate the reprocessed EDRs have already been reprocessed for the S-NPP suite of instruments and the EDR science teams are currently assessing improvements in using reprocessed SDRs and EDR enterprise algorithms operating at S-NPP Data exploitation (NDE) at the Office of Satellite Product Operations (OSPO). This paper discusses the implementation of enterprise EDR algorithms and their impact on product performance, and outlines the reprocessing efforts, plans, and preparations to generate missing-long S-NPP EDR products.

The Advanced Baseline Imager (ABI) on GOES-16 meteorological satellite successfully completed one year in orbit and scientists at NOAA and NASA have been conducting extensive calibration and validation activities since data collection began in January 2017. The results look impressive and the sensor is performing as expected. ABI imagery has been extensively used to detect monitor and track numerous significant meteorological and environmental events such as Atlantic hurricanes in 2017. This presentation will highlights analysis of sensor data during the first year and showcase the impact of ABI on operational decision making in the United States during the first year.

A planned life cycle development improves the transition of remote sensing research to operations. The application lifecycle can be broadly divided into three stages: user needs and technical feasibility analysis, prototype development, and production and deployment. There are several checks within each phase to ensure that the final operational system adequately meets users' needs. The authors' experience in NASA's Synergy program shows that the life cycle process should be user centric for the application to be successful

NASA's Earth Observation System (EOS) satellite data are contributing to the development of a variety of policy relevant remote sensing applications within State/Regional governments in the United States. The Synergy program is a NASA-funded activity designed to promote the use of EOS data and related remote sensing technologies for a variety of applications. Examples from the Synergy program indicate that EOS data are suitable for developing policy relevant applications in precision agriculture, management of natural resources, management of water resources, public health, urban planning and disaster management. There are however several barriers that need to be overcome before users outside the research community fully adopt these technologies. Some of the barriers include lack of awareness, experience and training by end users in these technologies, unproven cost benefits, and issues related to data formats, consistence and continuity.

Using seventeen years of annual maximum value Normalized Difference Vegetation Index (NDVI) data, interannual variations in global vegetation dynamics are assessed. Comparisons are made between NDVI variability, rainfall, land cover classes and climate classes. Semi-arid regions covered by open shrublands exhibit the highest inter-annual variability among different land cover classes. These areas received a mean monthly rainfall of 10-30mm with a coefficient of variation in rainfall greater than 20% between years.

Under the aegis of the EOSDIS program, NASA's Synergy program has been exploring the development of applications for users at the state, local and tribal level in the US using remote sensing data in six application sectors. Eleven information centers or InfoMarts have been established during the past two years, and the data sets and products from these InfoMarts are having a significant impact on decision making abilities within their user communities. Selected impacts of the Synergy project and lessons learned are presented.