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.