Recent Developments and Applications of the WRF-Hydro Modeling System for Continental Scale Water Cycle Predictions

Thursday, 18 December 2014: 11:05 AM
David J Gochis1, Wei Yu1, Aubrey L Dugger1, James L McCreight2, David N Yates3, Martyn P Clark4, Andrew W Wood1, Kevin Michael Sampson4 and Roy Rasmussen5, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)Univ of Colorado, Boulder, CO, United States, (3)University Corporation for Atmospheric Research, Denver, CO, United States, (4)NCAR, Boulder, CO, United States, (5)NCAR/RAL, Boulder, CO, United States
The translation of weather and climate forcing through complex landscapes to drive terrestrial hydrologic processes is a true multi-scale problem. Model architectures that attempt to capture these processes and feedbacks in a physically realistic way must be able to bridge spatial scales from meters to kilometers. To represent these processes across continental domains modeling systems must fully embrace high performance computing. Also, because there are both scientific and computational trade-offs in modeling many terrestrial hydrologic and land-atmosphere exchange processes, it is often highly advantageous to support multiple physics options in order to test competing hypotheses and apply scale-appropriate parameterizations for different prediction problems. In this talk we provide an update of new developments to the WRF-Hydro system in meeting these needs from both a process representation and high performance computing perspective. A key feature of these developments centers on new multi-scale modeling capabilities recently added to WRF-Hydro. We will discuss prediction and computational performance metrics for several recent large river basin and continental scale applications of the WRF-Hydro system over the coterminous U.S. and over Mexico in modes both coupled and uncoupled to the Weather Research and Forecasting (WRF) model. We will also provide updates on new developments to the WRF-Hydro system in the areas of water management applications and hydrologic data assimilation.