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Improving Flash Flood Prediction through a Synthesis of NASA Products, NWP Models, and Flash Flood Decision Support Systems
Investigators: PI Brian Cosgrove (NASA/GSFC/SAIC), Co-I Charles Alonge.
(NASA/GSFC/SAIC).
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Abstract
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The purpose of this project is to assess the potential for NASA satellite
products and the NASA LIS modeling infrastructure to improve the performance
of NOAA flash flood predictions, thereby improving public safety.
In particular, given that the land surface greatly impacts precipitation
events, better initialization of land surface states such as soil moisture,
snow pack, and soil temperature from NASA products will lead to better NWP
precipitation forecasts. By taking advantage of this link between
precipitation events and land surface conditions, and initializing
high-resolution Weather Research and Forecasting (WRF) model simulations
with offline land surface conditions derived from a high-resolution NASA
Land Information System (LIS), more accurate precipitation forecasts with
longer lead times will be produced than are conventionally available. By
supplying the resulting ensemble precipitation forecasts to the USGS MMS
flash flood DSS, the utility of these forecasts for flash flood applications
can be assessed, and greater understanding of the effect of hydrologic, land
surface, and meteorological input uncertainty on flash flood forecasts will
be gained; something which is now only poorly understood.
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