Multi-predictor ensembles improving seasonal prediction of summer rainfall over the Bohai Sea Rim based on statistical downscaling of BCC_CSM1.1 m

Abstract

A model-circulation-based statistical downscaling (MCSD) method and its multi-predictor ensemble (MPE) schemes are proposed in this study to improve summer (June–July-August) rainfall prediction over the Bohai Sea Rim (BSR) area in the northern China where quite low prediction skills were found in Beijing Climate Center Climate System Model version 1.1 m (BCC_CSM1.1 m). This MCSD method, using both the empirical orthogonal function and singular value decomposition, can largely eliminate noise within variables and extract leading coupled patterns between the observed BSR summer rainfall and simultaneously predicted large-scale atmospheric circulation to significantly add prediction skill and spatial resolution. Three circulation anomaly predictors, the 500-hPa geopotential height (H500), 200-hPa zonal wind (U200) and 850-hPa meridional wind, are selected to implement statistical downscaling, and their MPE means are compared for verifications. Cross validations show considerable improvements of the MCSD with the MPE schemes, especially H500 and its ensemble mean with U200 (H5U2), where almost all temporal correlation coefficients between the predictions and observation are significantly positive over most BSR area, and particularly, spatial correlation coefficients reach 0.24 and 0.19 from −0.05 of the original model and the anomaly sign consistency rates reach 58.2% and 58.4% from 48.4%. In MCSD, to deal with the deficiency of underestimated rainfall anomaly, an intensity inflation for the downscaled rainfall prediction is carried out, which makes temporal correlation coefficients for the area-averaged H500 and H5U2 predictions improved from about 0.54 to 0.7. Overall, not only the tendency and spatial distribution but also magnitude accuracy of summer rainfall prediction over BSR can be significantly improved by the MCSD and its MPEs, providing a potentially effective tool for the mid-latitude seasonal prediction of summer rainfall usually showing low skills in dynamical models.