S107 Evaluating the Predictability of Summertime Precipitation in the Southeastern United States

Sunday, 7 January 2018
Exhibit Hall 5 (ACC) (Austin, Texas)
Daniel James Lloveras, GFDL, Princeton, NJ; and X. Yang

This study investigates the influence of oceanic and atmospheric processes on the predictability of summertime precipitation in the southeastern United States. Two sets of retrospective forecasts from GFDL’s Forecast-Oriented Low Ocean Resolution - Flux Adjusted (FLOR-FA) model are compared. The two sets of 12-member ensemble forecasts are initialized on the first day of each June from 1982 through 2015, with a lead time of three months. The two sets of forecasts are initialized identically in the ocean, but differently in the atmosphere. While one set uses model output for atmosphere initialization, the other set’s atmosphere initial conditions are nudged toward reanalysis and thus are expected to be more realistic. Analysis of the two sets of forecasts indicates that nudging atmosphere initial conditions toward reanalysis drastically improves prediction skill for summertime precipitation in the Southeast. The nudging process also improves the model’s ability to capture the geopotential height and sea surface temperature patterns associated with rainfall in the region. In particular, prediction skill for sea surface temperature in the northeast Atlantic improves substantially. This shows that using reanalysis for atmosphere initialization improves the predictability of air-sea interactions, resulting in an enhanced coupled system for predicting summertime precipitation in the Southeast.
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