37 Seasonal to Sub-Seasonal Skill in NMME Forecasts of Extreme Precipitation and Heat Waves in California and Nevada

Monday, 23 January 2017
4E (Washington State Convention Center )
Shraddhanand Shukla, Univ. of California, Santa Barbara, CA; and A. M. Sheffield, D. Cayan, J. Kalansky, and K. Redmond

This presentation reports on our work to evaluate forecasts of extreme precipitation and heat wave events on the sub-seasonal (2 weeks to 1 month) and seasonal (<1 month).  These “S2S” forecasts, if they can be demonstrated to be skillful,  are needed by stakeholders for making water resource decisions, emergency preparations and public health planning. The study focuses on California and Nevada because in both states a significant fraction of the precipitation in this region tends to come from a few large precipitation events (e.g. atmospheric rivers).  These large events  make the precipitation more variable in this region than nearly any other in the U.S. Consequently, water resources management is a challenging task. Heat waves are a different form of extreme events, but may be linked, in part to the hydrological cycle in that they exacerbate the effects of drought through increased water demand and, human and livestock health impacts. The North American Multi-Model Ensemble, NMME, is a state-of-the-art dynamical forecast system that could help to meet S2S forecasting needs. However, the ability of NMME in forecasting extreme precipitation and heat waves at S2S time scales in this region is largely underexplored. Here the skill of the individual NMME models is examined over the hindcast period (1982-2010) and during specific anomalous climate events such as ENSO events that are known to have some influence on the precipitation and temperature in this region. By examining identifying models that best capture the extremes in the hindcasts, we hope to improve the S2S forecasts for California and Nevada. Finally, based on direct stakeholder interaction through the California-Nevada Climate Applications Program (CNAP), the study will highlight challenges in  communicating the complexity of S2S forecasts and uncertainty to regional stakeholder.
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