The LIS team hosted several summer interns in 2017 to work on adding new capabilities to the LIS software framework and to participate in studies using LIS-generated datasets. The interns were either part of NASA’s OSSI program or USRA interns.
Nishan Biswas and Shahryar Ahmad are graduate students from the University of Washington in the Department of Civil and Environmental Engineering. Shahryar and Nishan developed an interactive state-of-the-art LIS Atlas to visualize LIS-generated model output. The initial prototype was developed for the FEWS NET projects over the Central Asia and Africa to monitor the snow conditions and water availability, respectively. They implemented capabilities to visualize LIS model output from multiple model domains and multiple configurations at different timescales on Google Maps. Additionally, the LIS Atlas has flexible capabilities to generate display outputs at various spatial and temporal scales. The LIS Atlas has also been designed to display outputs from the Land surface Verification Toolkit (LVT), including quantitative evaluations of model outputs compared to observations. The LIS Atlas is expected to be operational on the NCCS data portal server this fall. Shahryar and Nishan worked with Jossy Jacob, Sujay Kumar, and Amy McNally.
Eli Dennis recently completed his M.S. in Meteorology at Penn State University and soon will begin his Ph.D. at University of Maryland, College Park. He used an array of LIS offline spin-up simulations with varying vegetation, soil layers, and atmospheric forcing to evaluate the respective impacts on coupled weather forecasts using the NASA Unified WRF (NU-WRF) system. Eli also inter-compared the soil moisture and surface fluxes generated from these LIS simulations against soil moisture from NASA’s SMAP mission, and fluxes from DOE’s ARM-SGP network over the U.S. Southern Great Plains. Eli worked with Joe Santanello and Patricia Lawston, and will continue his collaboration with them during his Ph.D. His poster title is: Initializing Numerical Weather Prediction Models with Model-Derived and Satellite-Based Soil Moisture Data.
Andrea Meado recently completed her M.S. in Geology at Southern Illinois University. She worked on improving soil parameters model inputs for soil moisture modeling. Andrea updated and evaluated low-resolution global soil data (FAO) with new, high-resolution soil data (ISRIC) as inputs for a land-surface model (Noah-MP model). Her results show significant differences between the two datasets with soil parameter inputs and modeled soil moisture. Her findings will aid the LIS Team in future soil moisture modeling when predicting regional droughts and weather forecasting. Andrea worked with Kristi Arsenault and Sujay Kumar. Her poster title is: Evaluating soil hydraulic parameter datasets and their impact on soil moisture simulations.
Victoria Hiten, a rising senior at the University of Georgia majoring in computer science and classics, used the LVT software to look at precipitation and temperature in the National Climate Assessment – Land Data Assimilation System (NCA-LDAS). She added capabilities to LVT to use multi-day analysis windows as well as a metric counting number of times (e.g., hours or days) a particular variable is above a threshold in a given period (e.g., in a month or in a year). Her poster title is: Precipitation and Temperature Intensity Indicators in NCA-LDAS using LVT.
Alex Robertson, a rising senior at Florida Institute of Technology majoring in meteorology, also used LVT on the NCA-LDAS data, to look at streamflow and irrigated water amounts. He added into the LVT code the ability to calculate the indicator of annual 7-day low streamflow totals. His poster title is: Trends in Irrigation and Streamflow in the National Climate Assessment – LDAS using the NASA Land Verification Toolkit software. Both Alex and Victoria worked with David Mocko.