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Ellenburg, W. Lee

Publications and source records attributed to Ellenburg, W. Lee.

6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Developing a Customized Composite Drought Index for Pakistan

Pakistan experiences frequent and intense agricultural drought, varying spatially and temporally. Prolonged dry conditions often result in failed crop production. Using multiple variables, different components of drought can be captured across a multitude of climatic zones and throughout different seasons. Developing a composite drought index (CDI), specific for each district, will provide a more complete view of agricultural drought and enhance early warning systems.

Schwartz, Caily↗
NASA NTRS2019

Monitoring Extreme Weather in the Hindu Kush Himalaya Region

Why is monitoring extreme weather events important? The HKH (Hindu Kush Himalaya region experiences many extreme weather events, such as thunderstorms, especially during monsoon season. These events can cause economic hardship and loss of life. Monitoring Extreme Weather in the HKH Region is a service in development through SERVIR-Hindu Kush Himalaya that aims to develop a customized numerical weather prediction toolkit to assess these high impact events in this relatively data-sparse region. The High Impact Weather Assessment Toolkit (HIWAT) consists of an ensemble Weather Research and Forecasting (WRF)model, threat assessments based on the Global Precipitation Measurement (GPM) missions, and impact assessments based on Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. In spring 2019, we began validation of forecasted precipitation using station data in Bangladesh and Climate Hazards Group InfraRed with Station data (CHIRPS).

Remote Sensing↗
NASA NTRS2018

Assimilation of Satellite Derived Soil Moisture Profiles into a Crop Modeling System for Robust Yield Estimates

Soil Moisture Measurement - Remote Sensing. - Microwave (MW) Remote Sensing: Physically based and quantitative in nature; Based on difference in dielectric constant; Coarse spatial resolution 25-40 km; Shallow SM estimation depth 0-5 cm (approx.); All weather capabilities (e.g. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) etc.) - Thermal Infrared (TIR) Remote Sensing: Indirect SM retrieval through energy flux estimations; Relatively better spatial resolution 1-10 km; Root-zone moisture retrieval capability; Can not penetrate through clouds, hence data gaps (e.g. Surface Energy Balance Algorithm for Land (SEBAL), Atmospheric Land Exchange Inverse (ALEXI) etc.)

SERVIR↗