Dr. Ruby Leung
(Pacific Northwest National Laboratory)
Atmospheric Rivers From a Hierarchy of Climate Simulations and the CalWater 2015 Field Campaign.
|What||HusseyLecture Meteo Colloquium Homepage GR|
Apr 13, 2016 03:30 PM
Apr 13, 2016 04:30 PM
Apr 13, 2016
from 03:30 pm to 04:30 pm
|Contact Name||Dave Stensrud|
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The western U.S. receives precipitation predominantly during the cold season when storms approach from the Pacific Ocean. The snowpack that accumulates during winter storms provides about 70-90% of water supply for the region. Associated with the warm sector of extratropical cyclones over the Pacific Ocean, atmospheric rivers (ARs) provide enhanced water vapor transport from the tropics. Because of the large lower-tropospheric water vapor content, strong atmospheric winds and neutral moist static stability, ARs can produce heavy precipitation by orographic enhancement during landfall on the U.S. West Coast. Using a suite of idealized aqua-planet simulations and AMIP simulations with the Model for Prediction Across Scales (MPAS) at resolutions ranging from 30km to 240km, we investigate the sensitivity of simulated AR frequency to model resolution. The impacts of global warming on ARs and heavy precipitation are investigated using model outputs from the Community Earth System Model Large Ensemble Project (CESM-LE) and the multi-model ensemble of the Coupled Model Intercomparison Project Phase 5 (CMIP5). This hierarchy of climate simulations reveals important linkages between the jet stream and uncertainty in simulating AR frequency and projecting AR changes in a warmer climate, with important implications to projecting changes in extreme precipitation in western U.S. and Europe. Lastly, multi-platform measurements of aerosols, cloud microphysics and the atmospheric environment in the multi-agency CalWater 2015 field campaign reveal an important role for long-range transported aerosols on clouds and precipitation associated with AR. Both modeling and measurements point to important research areas for advancing understanding and modeling AR and associated heavy precipitation.