190 Analyzing Weather-Regime-Dependence of GFS Extended Precipitation Forecast Skill Based on the Convective Adjustment Time Scale

Monday, 13 January 2020
Hall B (Boston Convention and Exhibition Center)
Malcolm T. Wilson, NCAR, Boulder, CO; The Pennsylvania State Univ., Univ. Park, PA; and M. Wong and C. Schwartz

Numerical weather prediction (NWP) models have been shown to have varying precipitation forecasting skill depending on the dominant weather regime. Specifically, NWP precipitation forecasts are generally more accurate under the equilibrium (synoptic) regime compared to the non-equilibrium (mesoscale) regime, where the former is typically better resolved by current NWP models. Limitations of NWP models, such as model resolution and model error due to physical parameterizations, lead to the discrepancy of forecast skill between the weather regimes. This research evaluated the skill of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) extended precipitation forecasts up to 10 days under different weather regimes. The forecast skill was analyzed over the conterminous United States during 2016. Spatial and temporal characteristics of the dominant weather regime were diagnosed based on the convective adjustment timescale. As expected, forecast skill generally degraded with increasing lead time under both regimes. Various skill scores based on a 2 x 2 contingency table indicated that warm-season precipitation forecasts had lower skill relative to the cold season, consistent with results from past studies. The warm season, using the convective adjustment timescale, can be characterized to be dominantly under the non-equilibrium regime, indicating that precipitation forecasting is more difficult under this regime as compared to the equilibrium regime.
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