Optimization of precipitation and streamflow forecasts in the southwest Contiguous US for warm season convection

Abstract:

Warm season convection associated with the North American Monsoon (NAM) provides an important source of precipitation for much of the Southwest Contiguous US (CONUS) and Northwest Mexico. Convection associated with the NAM can also result in flash flooding, a hazard to metropolitan areas such as Tucson and Phoenix, as well as rural areas where washouts of main roads can sever critical transportation infrastructure. In order to mitigate the effects of this problem, the National Oceanic and Atmospheric Administration (NOAA) National Water Center (NWC) is developing a national distributed hydrologic model using the WRF-Hydro framework with forcing from the High Resolution Rapid Refresh (HRRR) mesoscale atmospheric model. We aim to improve this National hydrologic and atmospheric modeling framework through the calibration of the WRF-Hydro model for the southwest CONUS and the optimization of planetary boundary layer and cloud microphysics schemes for the Weather Research and Forecasting (WRF) model in the same region. The WRF-Hydro model, with a similar structure as the national configuration used by the NWC, has been set up for the Gila River basin in southern Arizona. We demonstrate the utility of the model for forecasting high impact precipitation events in catchments with limited human modification. The WRF-Hydro model is spun up using past precipitation from the NCEP Stage-IV records and TRMM estimates. Atmospheric forcing for WRF-Hydro comes from the NASA Phase 2 North American Land Data Assimilation (NLDAS-2) dataset. WRF-Hydro is forced for selected high-impact events using a 3-km grid resolution Advanced Research WRF (WRF-ARW) atmospheric simulation. WRF-ARW is forced with the operational National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) operational model. This methodology demonstrates the modeling framework that will be used for future parameter calibration of WRF-Hydro and optimization of WRF-ARW.