About This Project
The Global Energy and Water Cycle Experiment (GEWEX) is designed in part to improve the ability to predict the hydrologic cycle and energy fluxes at the land surface. Progress in the area of water resources applications has been slow, in part because of the mismatch in construct and spatial scales between land hydrology models and the Soil-Vegetation-Atmosphere Transfer Schemes (SVATS) used by weather prediction and climate models to represent the land surface. The GCIP-funded Land Data Assimilation System (LDAS) has facilitated implementation of several land surface schemes and has produced over the same domain long-term retrospective data sets that can be used for model testing and bias correction. The GCIP/GAPP investment in LDAS facilitates the development of hydrologic nowcast and forecast products over the continental U.S.
This collaborative project, with the University of Washington (Dennis Lettenmaier, Co-Investigator) , has four main objectives:
- The first will identify target areas for LDAS-derived nowcast and forecast products. Nowcast products for state variables like soil moisture and snow water equivalent will be produced over the continental U.S. portion of the LDAS domain, with a subset of specific sites identified for purposes of point evaluations using NRCS SCAN soil moisture stations, and SNOTEL snow water equivalent observations (the latter mostly over the western U.S.). The work at Princeton University will focus primarily on the development of these products in the eastern portion of the U.S., while the University of Washington is focusing on producing forecast products for the western U.S.;
- The second task will develop and test methods for production of hydrologic forecast products (primarily streamflow). The experimental forecast products will have a range of lead times including 72 hours, 15 days, and 6 months. All forecasts will be initialized with LDAS fields at the time of forecasts, and will be for a selected set (about 100) of gaged streams with drainage areas greater than about 1500 km2 (equivalent to about 10 LDAS grid cells). Synthetic ensemble forcings will be created for the 72 hours forecasts, which will be based on real-time Eta model output, with a 6-hour update cycle. The 15-day forecasts will be based on ensembles produced operationally by NCEP from the MRF model, and the 6-month forecasts will be based on Global Spectral Model ensembles, also produced by NCEP. Unbiasing of the coupled model forcings will be accomplished through use and/or adaptation of methods previously developed by the PIs for experimental long-range streamflow forecasting (6 month lead) in the Eastern U.S. and the Columbia River basin;
- The third task will evaluate the nowcast and forecast products, which will be accomplished through use of point observations of soil moisture and snow, station and remote sensing-based estimates of snow extent, and streamflow (the latter over a range of temporal aggregations, and with focus on forecast error characteristics over both the rising and falling limbs of hydrographs);
- The final task will be coordination and cooperation with the NWS River Forecast Centers and Office of Hydrologic Development.
Our current focus is to develop a method for making ensembles that will have enough spread and accuracy. We are testing our method over the Ohio river basin and South Atlantic Gulf region at this time, but we expect to expend the forecast domain to the entire east-side U.S. as illustrated in the following map.
This research is supported by NOAA grant NAI7RJ2612 through GAPP .