900 Using Convection-Allowing Ensembles to Understand the Predictability of Extreme Rainfall

Thursday, 14 January 2016
Hall D/E ( New Orleans Ernest N. Morial Convention Center)
Erik R. Nielsen, Colorado State University, Fort Collins, CO; and R. S. Schumacher

The meteorological community has well established the usefulness of ensemble based numerical weather predication for precipitation guidance, which has led to an increasing need to determine the most effective use of these systems in high impact, extreme precipitation events. This research will focus on using a recently developed, operationally based ensemble dataset, specifically NOAA's Second Generation Global Medium-Range Ensemble Reforecast Dataset (Reforecast-2), to create downscaled ensemble reforecasts of the extreme precipitation events. Some events examined during the course of this research are the inland propagation tropical storm Erin in 2007, the MCV associated flooding that occurred in Arkansas in 2010, and San Antonio, TX in 2013.

The global reforecasts are used to force an ensemble of convection-allowing WRF-ARW numerical simulations for the purpose of evaluating ensemble based precipitation forecasts associated with specific extreme rainfall events. Using these ensemble forecasts, we also address several questions related to the predictability of extreme rainfall. Experiments that vary the magnitude of the perturbations to the initial and lateral boundary conditions (ICs and LBCs) reveal a seemingly linear scaling of ensemble spread across all times associated with the magnitude of the perturbation. Additionally, a diurnal cycle in ensemble spread growth is observed with large growth associated with afternoon convection, but the growth rate then reduced after convection dissipates the next morning rather than continuing to grow. Lastly, the ensemble spread was found to be influenced by the size of the IC perturbations out to at least 48 hours. These spread evolution characteristics speak to the viability of running convection allowing ensembles for prediction on multi-day timescales, since no saturation of the ensemble spread is seen despite extreme precipitation within the modeled time period.

In addition to the overall ensemble characteristics, sub-atmospheric scale precipitation variability associated with the terrain feature known as the Balcones Escarpment, located in central Texas, is analyzed in multiple instances of heavy rainfall in San Antonio and the surrounding area. Terrain altering simulations reveal that when the synoptic to mesoscale forcing for heavy rainfall are in place over the Balcones Escarpment, the terrain does not directly affect the occurrence or magnitude of precipitation. It does affect the spatial distribution of the precipitation in a small but consistent way. This shift in precipitation associated with removing the Balcones Escarpment, when compared to a WRF-ARW ensemble for the event, is smaller than shifts associated with typical atmospheric variability.

The combined results of these experiments demonstrate that downscaled ensemble NWP systems can faithfully represent previously unresolved mesoscale features, precipitation totals, and depict ensemble-spread characteristics associated with moist convection.

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