Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin

摘要

Satellite rainfall estimates (SREs) are prone to bias as they are indirect derivatives of the visible, infrared, and/or microwave cloud properties, and hence SREs need correction. We evaluate the influence of elevation and distance from large-scale open water bodies on bias for Climate Prediction Center-MORPHing (CMORPH) rainfall estimates in the Zambezi basin. The effectiveness of five linear/non-linear and time-space-variant/-invariant bias-correction schemes was evaluated for daily rainfall estimates and climatic seasonality. The schemes used are spatio-temporal bias (STB), elevation zone bias (EZ), power transform (PT), distribution transformation (DT), and quantile mapping based on an empirical distribution (QME). We used daily time series (1998-2013) from 60 gauge stations and CMORPH SREs for the Zambezi basin. To evaluate the effectiveness of the bias-correction schemes spatial and temporal cross-validation was applied based on eight stations and on the 1998-1999 CMORPH time series, respectively. For correction, STB and EZ schemes proved to be more effective in removing bias. STB improved the correlation coefficient and Nash-Sutcliffe efficiency by 50 % and 53 %, respectively, and reduced the root mean squared difference and relative bias by 25 % and 33 %, respectively. Paired t tests showed that there is no significant difference (p < 0.05) in the daily means of CMORPH against gauge rainfall after bias correction. ANOVA post hoc tests revealed that the STB and EZ bias-correction schemes are preferable. Bias is highest for very light rainfall (<2 5 mm d(-1)), for which most effective bias reduction is shown, in particular for the wet season. Similar findings are shown through quantile-quantile (q-q) plots. The spatial cross-validation approach revealed that most bias-correction schemes removed bias by > 28 %. The temporal cross-validation approach showed effectiveness of the bias-correction schemes. Taylor diagrams show that station elevation has an influence