Hydrometeorological Processes Research
Research on hydrometeorological processes is intended to link research and applications between the traditional meteorological and hydrological research disciplines. Hydrological impacts of significant weather and climate events often translate into staggering human, economic and environmental costs. Despite decades of research, significant gaps remain in how weather and climate information are used for reliable hydrological prediction. Additionally, it is now well-recognized that terrestrial hydrologic processes are not only influenced by weather and climate but also exert a significant feedback to the coupled Earth system. The nature of the relationship between terrestrial hydrologic processes and the atmospheric processes that simultaneously drive and respond to them are the focus of RAL’s Hydrometeorological Processes efforts. This work is funded by the NSF, NOAA, the World Bank, and the Tellus Institute.
FY06 Accomplishments:
Figure 1. Detail of inflow (m3/sec) to stream reaches on the Arges River basin in Romania using the Noah-distributed hydrological model embedded within the NASA Land Information System (LIS). The stream inflow values calculated by Noah-distributed determine how much runoff is moving from the landscape into a stream channel network. This new functionality within Noah-distributed enables runoff and streamflow simulation and prediction in both coupled and uncoupled applications of the community Noah land surface model. (Image provided courtesy Baron Advanced Met. Systems).
Scientists from RAL are developing a real-time water resources assessment and forecasting tool for the country of Romania. The approach used employs physically-based, dynamical routing techniques of surface and subsurface water across the landscape and through both natural and managed river systems. Figure 1 below shows results from the first implementation of the new hydrological monitoring and prediction system into the Arges River Basin in Romania.
D. Gochis continues to participate in the NOAA-NSF-NASA sponsored North American Monsoon Experiment (NAME), operating a network of 87 tipping bucket rain gauges in the remote regions of the Sierra Madre Occidental Mountains in northwest Mexico. An article on this work has been accepted for publication in a forthcoming special issue of the "Journal of Climate" on NAME. Additionally, Gochis and D.Yates are advising a graduate student from the U. of Arizona, K. Maitaria, on the development of a statistical downscaling model. Once completed, the suite of forecasting tools generated will provide a robust, community-model based platform from which seasonal forecasts of precipitation and streamflow will be made. Yates is also participating in an effort to develop an integrated water resource modeling framework for use in investigating medium- to long- term water resource planning and management issues throughout the Sacramento Basin. This framework makes use of climate data derived from a new Bayesian analysis technique that yields statistical distributions of regional climate change based on regional projections from multiple Atmosphere-Ocean.