3A.4 SAR-FV3 Storm-Scale Ensemble Forecasts (CAPS SSEF) and Ensemble Consensus Products for the 2019 HMT FFaIR Experiment

Monday, 13 January 2020: 2:45 PM
252A (Boston Convention and Exhibition Center)
Keith A. Brewster, Univ. of Oklahoma, Norman, OK; and N. Snook, F. Kong, M. Xue, T. A. Supinie, C. Zhang, and K. W. Thomas

The Center for Analysis and Prediction of Storms (CAPS) runs a set of real-time CONUS-scale convection-allowing ensemble forecasts to support operations in the NOAA Hazardous Weather Testbed (HWT) Spring Forecast Experiment and Hydrometeorology Testbed (HMT) Flash Flood and Intense Rainfall (FFaIR) Experiment. For the 2019 FFaIR, CAPS produced an ensemble comprised of 14 members of the StandAlone Regional FV3 model (SAR FV3) at 3-km grid spacing over the contiguous United States. Diversity within the ensemble was provided through the use of three different microphysics schemes, three boundary layer schemes, two surface layer schemes and two land-surface parameterizations. Most of the members were initialized using the operational NAM model, with six having perturbations applied to the initial and lateral boundary conditions based on the SREF ensemble. One was initialized from the operational GFS model.

CAPS has led the development of two novel consensus finding algorithms, the Local Probability Matched Mean (LPM mean) and the Spatially-Aligned Mean (SAM).

The LPM mean algorithm is designed to confer many of the benefits of the traditional domain-wide Probability Matched mean (PM) while better retaining smaller-scale local convective structures within the forecast ensemble. Rather than performing the PM calculations over the entire CONUS domain, the LPM divides the domain into overlapping patches on which the PM algorithm is applied; the patches are then stitched together to generate the final LPM product.

Common differences noted among various ensemble forecast members are differences in storm initiation timing, location and propagation phase speed. Together these differences lead to offsets in location of convective features among the ensemble members. Averaging members with such offsets creates blurring and smoothing in the resultant ensemble mean products. The Spatially-Aligned Mean (SAM) is designed to reduce these affects by first spatially aligning the 2D products to a common location. SAM can also provide information on spatial spread among the ensemble members.

Statistical results of the SAR-FV3 ensemble for the 2019 HMT FFaIR, including the consensus from the LPM Mean and SAM will be presented, as well as plans for the upcoming 2020 HMT Winter Experiment and 2020 FFaIR.

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