Model Consistent Pseudo-Observations of Precipitation and Their Use for Bias Correcting Regional Climate Models

Climate

Peter Berg¹  Thomas Bosshard²  Wei Yang² 

[1] Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 601 76 Norrköping, Sweden;

关键词: bias correction;    regional climate model;    RCM;    spectral nudging;    high resolution;   

DOI  :  10.3390/cli3010118

来源: mdpi

【 摘 要 】

Lack of suitable observational data makes bias correction of high space and time resolution regional climate models (RCM) problematic. We present a method to construct pseudo-observational precipitation data by merging a large scale constrained RCM reanalysis downscaling simulation with coarse time and space resolution observations. The large scale constraint synchronizes the inner domain solution to the driving reanalysis model, such that the simulated weather is similar to observations on a monthly time scale. Monthly biases for each single month are corrected to the corresponding month of the observational data, and applied to the finer temporal resolution of the RCM. A low-pass filter is applied to the correction factors to retain the small spatial scale information of the RCM. The method is applied to a 12.5 km RCM simulation and proven successful in producing a reliable pseudo-observational data set. Furthermore, the constructed data set is applied as reference in a quantile mapping bias correction, and is proven skillful in retaining small scale information of the RCM, while still correcting the large scale spatial bias. The proposed method allows bias correction of high resolution model simulations without changing the fine scale spatial features, i.e., retaining the very information required by many impact models.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.