Modeling studies of landfalling atmospheric rivers and orographic precipitation over northern California
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This study investigated a slow-moving long-wave trough that brought four Atmospheric Rivers (AR) “episodes” within a week to the U.S. West Coast from 28 November to 3 December 2012, bringing over 500 mm to some coastal locations. The highest 6- and 12-hourly rainfall rates (131 and 195 mm, respectively) over northern California occurred during Episode 2 along the windward slopes of the coastal Santa Lucia Mountains. Surface observations from NOAA’s Hydrometeorological Testbed sites in California, available GPS Radio Occultation (RO) vertical profiles from the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) satellite mission were both assimilated into WRF-ARW via eight combinations of observation nudging, grid nudging, and 3DVAR to improve the upstream moisture characteristics and quantitative precipitation forecast (QPF) during this event. Results during the 6-hourly rainfall maximum period in Episode 2 revealed that the models underestimated the observed 6-hourly rainfall rate maximum on the windward slopes of the Santa Lucia mountain range. The grid-nudging experiments smoothed out finer mesoscale details in the inner domain that may affect the final QPFs. Overall, the experiments that did not use grid nudging were more accurate in terms of less mean absolute error. In the time evolution of the accumulated rainfall forecast, the observation nudging experiment that included RAOB and COSMIC GPS RO data demonstrated results with the least error for the north central Coastal Range and the 3DVAR cold-start experiment demonstrated the least error for the windward Sierra Nevada. The experiment that combined 3DVAR cold start, observation nudging, and grid nudging showed the most error in the rainfall forecasts. Results from this study further suggest that including surface observations at frequencies less than 3 h for observation nudging and having cycling intervals less than 3 h for 3DVAR cycling would be more beneficial for short-to-medium range mesoscale QPFs during high-impact AR events over northern California.
KeywordsData Assimilation Radio Occultation Windward Slope Integrate Water Vapor Data Assimilation Method
The critical reviews of anonymous reviewers were very helpful. We thank Timothy Coleman from NOAA/ESRL for assistance with the HMT dataset, Cindy Bruyere from UCAR in assistance with the WRF data assimilation methods, and the other suppliers of the data used. The research was supported by the Grant W911NF-09-1-0441 from the US Army Research Office.
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