Dynamical Downscaling in Seasonal Climate Forecasts: Comparison between RegCM- and WRF-Based Approaches

The purpose of the present study is to assess large-scale signal modulation produced by two dynamically downscaled Seasonal Forecasting Systems (SFSs) and investigate if additional predictive skill can be achieved, compared driving global-scale Climate Forecast System (CFS). SFSs are evaluated in terms physical values anomaly interannual variability. Downscaled consist two-step dynamical ensembles NCEP-CFSv2 re-forecasts. In first step, CFS field from 100 km 60 over Southern Europe (D01). second downscaling, driven corresponding D01, performed at 12 Central Italy (D02). Downscaling using different Regional Models (RCMs): RegCM v.4 WRF 3.9.1.1. SFS skills assessed a period 21 winter seasons (1982–2002), means deterministic probabilistic approach with metric specifically designed isolate downscaling percentiles distribution. Considering temperature fields both metrics, regional-scale consistently improve original Anomaly Signal (SAS). For precipitation, added value mainly limited topography refinement precipitation field, whereas SAS “inherited” CFS. do not seem benefit (D01 D02) improvement. Finally, show substantial differences climatologically averaged fields, highlighting impact common SST field.