Earth Science Branch

The Earth Science Branch conducts research of the Earth as a system with a focus on lightning and precipitation processes, weather and climate variability, monitoring fluxes of heat and water from the surface, and associated data management and mining activities for scientific discovery and applications for societal benefit.

"Subtropical South American Hailstorm Characteristics and Environments" Article Published in Monthly Weather Review

An article titled "Subtropical South American Hailstorm Characteristics and Environments" has been published in Monthly Weather Review, with authors Zachary Bruick (Colorado State University), Kristen Rasmussen (Colorado State University), and Daniel Cecil (MSFC/ST11).  The article uses methods developed by Cecil to identify potential hailstorms based on NASA Satellite data and to assess the likelihood of large hail from each storm. Those methods were applied to parts of Argentina, Paraguay, Brazil, and Uruguay, where intense thunderstorms are common, but ground-based observational data are limited.  A broad diurnal cycle was found, with hailstorms extending later into the night than in other regions.  Environmental atmospheric conditions accompanying the hailstorms were documented, with anomalously warm and moist low levels contributing to thermodynamic instability, together with strong upper- and lower-level jets providing dynamic support for the storms.

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Anomaly fields for the atmospheric environments on days likely to have severe hailstorms in subtropical South America, compared to other days with significant convection, but not likely to include severe hailstorms. The image shows: (a) Surface pressure, with lower pressure in blue; 500-hPa geopotential height contoured. (b) Surface temperature, with warmer temperature in red; surface dew point contoured. (c) 850-hPa wind vectors and specific humidity, with moisture in green; meridional wind speed contoured (dashed contours are wind from the north). (d) 250-hPa wind speed, with orange for winds from the east and purple for winds from west; 250-hPa geopotential height contoured. All fields plotted are anomalies, for hail-days minus non-hail days.

These findings are significant because the Northern Argentina-Southern Brazil-Paraguay-Uruguay region has some of the most intense thunderstorms on Earth, as indicated by multiple NASA satellite datasets.  Ground-based observational networks are more limited there than in the United States, where intense thunderstorms also occur.  Understanding both similarities and differences between severe thunderstorm behavior and environments in different parts of the world can lead to a better understanding (and ultimately, better prediction) of severe thunderstorms and associated weather hazards (hail, damaging wind, tornadoes).

To read the article, go to:

Science Coordination Office (SCO) Team Members Meet with King of Bhutan

On November 1, 2018, Mr. Tony Kim (SERVIR Project Manager) and Dr. Ashutosh Limaye (SERVIR Chief Scientist) participated in a meeting with the King of Bhutan and Dr. Eugene Tu, NASA Ames Research Center (ARC) Director, when His Majesty, Jigme Khesar Namgyel Wangchuck visited ARC.

Mr. Kim and Dr. Limaye were given the opportunity to share an overview of NASA's SERVIR, Develop, and Global Learning and Observation to Benefit the Environment (GLOBE) projects, and how the funding from the new Inter-Agency Agreement with the DoS can help capacity building in the Kingdom of Bhutan.

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Southern Africa Development Community's (SADC) Climate Service Center Using SERVIR Products for Improved Meteorological Analysis

The Southern Africa Development Community's (SADC's) Climate Service Center (CSC) is now using Early Warning Explorer (EWX) and Climate Hazard InfraRed Precipitation with Stations - Global Ensemble Forecast System (CHIRPS-GEFS) to help produce their meteorological, environmental, hydro-met, and historical analysis products for risk management and mitigating climate extremes for end users, including national meteorological services in the regions and for partners such as the United Nations World Food Programme (WFP), the Food and Agriculture Organization (FAO), and the International Red Cross.

A series of workshops held in 2018 and 2019 focused on training potential users to access, validate, and apply EWX data. After the September 2018 training in Lusaka, Zambia, the country's Meteorological Department now uses EWS to produce official weather bulletins for farmers and other regional users.

EWX Training in Lukasa, Zambia
EWX Training in Lukasa, Zambia

EWX, developed by Dr. Shraddhan Shukla's Applied Sciences Team Project, has been fully transitioned to SERVIR - Eastern and Southern Africa at the Regional Centre for Mapping of Resources for Development (RCMRD) and CHIRPS-GEFS forecasts were integrated into EWX. Through the EWX portal, the CSC is able to access the CHIRPS data to generate monthly and seasonal rainfall assessments and historical climate extreme indices.

SERVIR-West Africa Hosts Cloud Computing and Big Data Forum in Accra, Ghana


SERVIR-Hindu Kush Himalaya Hosts Regional Knowledge Forum on Early Warning Systems


On October 21-25, SERVIR-West Africa hosted a Cloud-Computing and Big Data Forum as a part of the Africa Geospatial Data and internet Conference in Accra, Ghana. The week was book-ended with opening remarks from Ambassador Stephanie Sullivan, the US Ambassador to Ghana, and a keynote address from Marshall Space Flight Center's Dan Irwin, Program Manager of SERVIR.  The event consisted of presentations from a wide range of representatives from academia to the private sector all focused around how cloud-computing can be beneficial to Africa, as well as the challenges and how to overcome them.  The event ended with clearly identified takeaways and next steps for cloud computing and big data in West Africa.

A press release on the event can be found at


SERVIR-Hindu Kush Himalaya (SERVIR-HKH) hosted the Regional knowledge Forum on Early Warning for Floods and High-Impact Weather Events on October 22 and 23, at the International Centre for Integrated Mountain Development (ICIMOD), the hub host consultation workshop, as well as a day of internal SERVIR conversations.  The Department of Hydrology and Meteorology (DHM, Nepal), the Flood Forecasting and Warning Center (FFWC, Bangladesh), North Eastern Space Applications Centre (NESAC, India), and the National Center for Hydrology and Meteorology (NHCM, Bhutan) discussed challenges to Early Warning Systems (EWS) in the region, including specific recommendations for improving the utility of SERVIR's High Impact Weather Assessment Toolkit (HIWAT) system, co-developed by SERVIR-HKH and an applied Sciences Team led by Dr. Patrick Gatlin (MSFC). In his presentation during the stakeholder workshop, the representative from NCHM (Bhutan) expressed high interest in being more involved with SERVIR, specifically extending HIWAT coverage and other existing services to include Bhutan.  During the forum, it was suggested that the way forward for implementing SERVIR EWS includes collaboration between all countries on validation of the products, and the use of the SERVIR-provided Hydrostat tool.


Global Hydrology Resource Center (GHRC) Successfully Migrates its Operations to the Commercial Cloud

To address the challenge of managing data from several upcoming large missions, NASA's Earth Observing System Data and Information System (EOSDIS) is seeking to utilize the commercial cloud.  Toward that end, GHRC was selected as the first Distributed Active Archive Center (DAAC) to fully migrate to the commercial cloud.  One of the reasons GHRC was selected as the first DAAC to fully migrate to the cloud was due to its history of managing data from a wide variety of sources including satellite missions, field campaigns, and science investigators.

In 2017, GHRC provided requirements and DAAC expertise for Cumulus, an EOSDIS developed re-usable, open source, cloud native framework for data ingest, archive, and processing.  After a yearlong successful prototype of Cumulus, GHRC was selected to fully migrate to cloud and serve as a pathfinder DAAC.  GHRC was involved in providing requirements, planning new features, deploying features, and collaboratively solving issues with the EOSDIS team using the scaled agile framework (SAF3) methodology.

A simplified GHRC data publication architecture in the NASA-compliant cloud platform.
A simplified GHRC data publication architecture in the NASA-compliant cloud platform.

At the end of 2019, GHRC successfully completed migration of its operations to the cloud on time and on budget without disrupting its existing day-to-day operations.  As a result, all of GHRC's data is now being distributed from cloud.  GHRC deployed its data publication workflows for backup restoration, on-going datasets, and new datasets to the NASA-compliant General Application Platform (NGAP), a NASA security compliant platform used for hosting EOSDIS applications. Several members of the GHRC team are now trained to operate Cumulus hosted in NGAP. Lessons learned, as part of the migration, have been documented for future migration of other DAACs to the commercial cloud.

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MSFC Disasters Team led response efforts to wet spring and summer across Midwest.

The MSFC Disasters Team led response efforts for the broader NASA Earth Science Disasters Program throughout the spring and summer as floodwaters impacted portions of the Midwest multiple times.

MSFC Disasters coordinators worked with multiple federal agencies such as the Federal Emergency Management Agency (FEMA), the National Guard Bureau (NGB), and the United States Department of Agriculture (USDA) to understand their needs as the floods evolved and worked with them to provide derived products that could help them with situational awareness. In addition to coordinating with these agencies and other NASA Disaster coordinators across various centers, the MSFC team was able to produce satellite derived water extents from multiple sensors.

MSFC derived water extents across Midwest from Sentinel Satellites
MSFC derived water extents across Midwest from Sentinel Satellites

The water extents are derived from satellite imagery and an ancillary dataset, such as land-classification.  MSFC's methodology calculates statistics on known water in the images and then uses those statistics to classify all water in the image.  The land classification is then used again to identify which areas should be water and which areas are now anomalous water (i.e. flooded).  The picture above shows an aggregate of multiple days of acquisitions of the MSFC derived water extents across parts of the Midwest from Sentinel-1 and Sentinel-2 satellites in late March 2019.  The USDA provided feedback to the program stating that the "water extents helped them with their creation of quantitative and qualitative products for a near real-time response at the request of the NASS Nebraska Regional Field Office as well as the NASS Agricultural Statistics Board in preparation for the March Prospective Plantings Report." These areas experienced several more flooding events and severely impacted the 2019 growing season.  The MSFC Disasters team continues to follow up with USDA to understand the limitations of the water extents to improve the product for the next time flooding occurs.

More about the NASA Disasters Program can be found here:

Artificial Intelligence developed to detect smoke plumes in geostationary satellite imagery.

The Interagency Implementation and Advanced Concepts Team (IMPACT) housed within Marshall's Earth Science Branch is applying artificial intelligence (AI) to devise new satellite data analysis techniques.  A recent example is the use of deep learning to enhance the detection of smoke plumes from geostationary satellite measurements.

Traditional satellite-based smoke detection relies upon multispectral techniques that can be clouded by features with similar spectral characteristics (e.g., in the visible range, clouds, dust, pollution and smoke). Additionally, this spectral analysis requires large data volumes and often subjective and time-consuming manual evaluation, which is not readily scalable. To address these weaknesses, an automated, deep learning based detection model capable of identifying smoke plumes using shortwave reflectance from the Geostationary Operational Environmental Satellite (GOES) Series R Advanced Baseline Imager (ABI).

In a recent study, IMPACT data scientists used a large number of satellite images with known smoke plumes obtained from a subset of GOES-16 observations between 2017-2019 to train a convolutional neural network (i.e., machine learning algorithm) to predict the probability that GOES-R ABI shortwave reflectance pixel contains smoke. The image on the right gives two examples of GOES-16 satellite pseudo true color images (top: 2345 UTC 19 May 2018: bottom: 2230 UTC 2 March 2018) and regions where the algorithm identified smoke plumes (yellow shaded regions). The model is able to detect smoke over open ocean and most land surfaces, including snow and urban areas, as well as distinguish the smoke plumes from most types of clouds. Compared with the non-training sample of GOES-16 images, accuracy of the smoke detection model is 92%. This GOES-based smoke detection is being integrated by IMPACT into an online web portal for operational detection and analysis of smoke, among other Earth Science phenomena.

Click on the link below to find out more about the IMPACT Project Office at Marshall Space Flight Center.


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Smoke Plumes

Marshall Earth Science Research & Analysis tapped for innovative extreme weather capacity building solutions.

A SERVIR Applied Science Team project led by Dr. Patrick Gatlin at Marshall Space Flight Center (MSFC) has brought together numerical weather prediction from the Short-Term Prediction Research and Transition Center (SPoRT), satellite-based storm assessment from the Global Precipitation Measurement (GPM) mission, and sattelite-based storm damage mapping from MSFC's Disasters Team into one toolkit being used in extreme weather services in Nepal and Bangladesh.

A demonstration of this service took place during the pre-monsoon and monsoon seasons of 2018 and 2019. A significantly damaging hailstorm that occurred on 30 March 2018 over Bangladesh was captured by the High Impact Weather Assessment Toolkit (HIWAT).

The top image on the right shows an example of the brightness temperature measured at 37 GHz with GPM's microwave imager (GMI) used by HIWAT to determine the probability of damaging hail. The two highlighted storms in the next picture have a >95% chance of damaging hail and the final picture shows the giant hailstones observed with these Bangladesh storms. This satellite-based hail probability is a result of recent Passive Microwave (PMW) research at MSFC by Dr. Daniel Cecil.

Find out more about SERVIR's Extreme Weather Service in the Hindu Kush-Himalyan (HKH) region at

Observing severe storms with NASA's GPM constellation of satellites for capacity building in South Asia.
GPM Hail Probability in Bangladesh Storms
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