Convective Meteorology (Mesoscale Dynamics)

Ensemble Prediction of Splitting Supercells and Hail on 10 May 2010

Jonathan Labriola
OU School of Meteorology

27 March 2015, 2:00 PM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

Severe hail is a major weather hazard, causing injuries and billions of dollars in damage each year. Though modern convective-scale NWP forecast ensembles have shown skill in predicting supercell thunderstorms, relatively little study has been performed on explicit short-term prediction of hail. The Severe Hail Analysis Representation and Prediction Project (SHARP), a 3-year NSF funded study within CAPS, seeks to investigate and improve the capability of NWP ensemble analyses/forecasts to represent and predict hail within 0-2 hour NWP forecasts through the use of optimally-configured EnKF data assimilation and forecast ensembles using sub-kilometer grid spacing.

On 10 May 2010, a left-splitting supercell occurred over southwestern Oklahoma, producing a swath of severe hail, as well as two anticyclonic tornadoes. Long-lived left-split supercells are relatively uncommon; accurate numerical prediction of such storms requires capturing the sheared environment in which they develop, making prediction difficult. Furthermore, left-moving supercells have been found to cause a disproportionate number of hail reports—predicting hail produced by splitting storms is thus an important area of study in improving hail forecasts. To predict the splitting storms of 10 May 2010 and their environment, multiple data sources, including NEXRAD and CASA radar data, Mesonet surface observations, as well as radiosonde and wind profiler data, were assimilated into a set of 40-member ensemble forecast experiments with 500 m horizontal grid spacing run using the ARPS EnKF system. Experiments examined the capability of forecasts with differing lead-times and data assimilation configurations to predict the splitting behavior of the observed storms, as well as size and geographic distribution of hail produced by the storms.

Most members of the experiments with shorter lead times (approximately 15 minutes) were able to predict the left-splitting supercell while experiments with a lead time longer than 30 minutes failed to produce the storm. It was found that proper representation of the near-storm environment, especially the low- and mid-level shear, was vital for predicting the observed storm split. The Lin (single moment) and the double-moment Milbrandt and Yau (MY2) microphysics schemes were also compared for the left splitting thunderstorm. Using gridded NEXRAD maximum estimated size of hail (MESH) data as a proxy for observed hail, both schemes produced 0-60 minute hail forecasts that were representative of the hail produced by the 10 May 2010 storms though the double moment MY2 scheme outperformed the single moment Lin scheme in terms of predicted hail intensity and spatial extent. The Lin scheme overestimated both hail size and coverage, while the MY2 scheme, which is able to capture microphysical processes including size sorting and drop evaporation, more accurately predicted the size and extent of hail.

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