Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
1558 The University of Texas at Arlington (143446)
Principal Investigator: Yu Zhang,yu.zhang@uta.edu,(817) 272-5055
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 246,223
Exceeds $250,000 (Is it flagged?): No
Start and End Dates: 2/9/23 - 2/8/26
Restricted Research: YES
Academic Discipline: Department of Civil Engineering
Department, Center, School, or Institute: none
Title of Contract, Award, or Gift: Improving S2S Hydrometeorological Predictions for the state of Texas through Synergistic Infusion of Remotely Sensed SST and Land Surface Variables to a Coupled Modeling System
Name of Granting or Contracting Agency/Entity:
National Aeronautics & Space Administration (NASA)
CFDA Link: NASA
43.001
Program Title:
none
CFDA Linked: Aerospace Education Services Program
Note:
(SAM Category 1.1.1.) Proposed herein is an effort to establish a regional S2S prediction system for the State of Texas that is capable of producing forecasts of precipitation and streamflow anomalies for weeks 3-6. The system will be based on a coupling of a regional implementation of WRF-ARW with the National Water Model (NWM). In the proposed undertaking, the WRF-ARW will be set up for a domain that extends from the Gulf of Mexico to the Oklahoma/Arkansas, and from the eastern portion of Mexico to Alabama; it will be nested within the NWS Global Ensemble Forecast System (GEFS)-V12 grid. The coupled system will be reinitialized using remotely sensed soil moisture from SMAP, MODIS skin temperature, dynamic vegetation, and MODIS sea surface temperature. Two sets of forecasts will be produced running the coupled modeling system using GEFS-v12 control run as lateral boundary conditions. The first/second control run will be done without/with any infusion of remotely sensed land conditions to identify the impacts of data assimilation. The hindcast experiment will focus on windows surrounding the flood of 2015, Hurricane Harvey of 2017, and the flash drought of 2019. Forecasts of precipitation and other variables from the coupled model will be validated against surface observations and analyses. These forecasts will also be gauged relative to NWS S2S streamflow and soil moisture products to determine skills gained through improved representations of processes and data infusions.
Discussion: No discussion notes