The overall goal of this project is to study surface flux, snow/ICE storage, and water balance changes in HMA and investigate the causality of these changes at the regional to local scale. To this…

This federal contract award to George Mason University, doing business as Mason, consists of a $638,241.38 grant for a research project titled "HMA-LDAS: Hyper-Resolution High Mountain Asia - Land Data Assimilation System". The overall goal is to study surface flux, snow/ice storage, and water balance changes in the High Mountain Asia (HMA) region and investigate the causes of these changes at regional and local scales.

The project will develop a high-resolution (1 km) land data assimilation system for the 4.3 million km2 HMA region, utilizing NASA satellite data, land surface modeling, and weather boundary conditions dating back to 1980. This HMA-LDAS will be a critical component of the Glacial Melt Toolbox (GMELT) and support Earth science research on the drivers of change in the HMA region's glaciers, snow, permafrost, and precipitation. The contract does not include a set-aside designation.

The overall goal of this project is to study surface flux, snow/ICE storage, and water balance changes in HMA and investigate the causality of these changes at the regional to local scale. To this end, we propose to develop a hyper-resolution 1KM high mountain area (HMA)-land data assimilation system (LDAS) 1980-current terrestrial reanalysis using the community land model and the community ICE system model, forced by physically downscaled surface meteorology, parameterized by remotely sensed topography and vegetation, and constrained by remotely sensed snow, temperature, and snow/ICE observations. The 4.3 million KM2 hmaldas will be a critical component of the glacial melt toolbox (GMELT) and will help to address earth science questions concerning causality of HMA water balance change across scales. Specific objectives to achieve this broader goal are: (1) develop a hourly, 1KM hyper-resolution forcing land surface weather boundary condition dataset (near-surface air temperature and humidity, wind speed and direction, incident longwave and shortwave radiation, pressure and precipitation) over 4.3 million KM2 HMA for 1980-current; (2) to study the spatial (both horizontally and vertically) and temporal variability of hyper-resolution key land surface states and fluxes, such as temperature, soil moisture, snow, ICE, evaporation and runoff, over the HMA domain, produced by assimilating NASA satellite-based products into a land data assimilation system, forced with a hyper-resolution land surface weather boundary condition dataset; (3) to assess the utility of assimilating remote sensing data, such as snow, freeze/thaw condition, and temperature; (4) to investigate the causality of changes in land states and fluxes and snow and ICE storage at the regional to local scale by analyzing the hyper-resolution system output; (5) to calibrate and validate the hyper-resolution output using ground-based, airborne, and satellite observations (mostly in cooperation with the himat team). This project directly addresses the priority of the program element NASA roses 2015 a.48 understanding changes in high mountain asia, of improving our understanding of regional changes, water resources, and induced impacts, while furthering nasas strategic goals in earth system science and societal applications. As called for in the a.48 solicitation, this is an earth science investigation addressing: 1) satellite remote sensing studies aimed at better characterizing and understanding the processes controlling change of snow, glaciers, permafrost, precipitation, and ecosystems; 2) modeling of these processes to support earth science research and regional forecasts; and 3) optimizing high-resolution meteorological models for HMA, preferably spanning the time period from 1980 to the present, aimed at understanding the drivers of change in the glaciers, snow, permafrost, and precipitation of the region. To this end, this proposal will 1) include NASA satellite products as forcing and observations in a land data assimilation system; 2) develop a hyper-resolution modeling technique that will greatly enhance forecast models in the region and that will be integrated in the GMELT; and 3) build a hyper-resolution forcing database and produce surface states and fluxes since 1980 to present to enable a better understanding of climate and surface changes in the HMA region. As has been demonstrated by other LDAS systems (global-LDAS, north american-LDAS, mena-LDAS, etc.) the resulting HMA-LDAS data layers will be analyzed to study surface flux, snow/ICE storage, and water balance changes in HMA and investigate the causality of these changes at the regional to local scale, and will support a wide range of subsequent applications from atmospheric forecast initialization and climate change assessment to water resource management and hazard mitigation.