| Experimental Seasonal Forecast
Real time observational data are needed for the development and validation of downscaling techniques. Thirty years, 1983 – 2012, real time observational seasonal precipitation data of thirty one stations is used in this study. The time series of precipitation data are then needed to be correlated with the large scale variables.The large scale meteorological fields were taken from Global Atmosphere-Ocean Coupled Model (CGCM), which is developed by Beijing Climate Center, China Meteorological Administration, China.
The global coupled ocean-atmosphere model currently used in the NCC is composed of an AGCM (Version 1.0) named T63L16 AGCM_1.0) which was developed on the basis of the operational medium-range prediction model of the National Meteorological Center of China Meteorological Administration (NMC/CMA), and an OGCM Version 1.0, named GT63L30 OGCM_1.0 which was developed by the State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics (LASG) of the IAP/CAS on the basis of the original LASG OGCM (20 levels in vertical direction and 4°×5° horizontal resolution). These are coupled through the coupling scheme of the Daily Flux Anomaly on the open sea surface. The brief of the whole CGCM model system is shown in Table 1. This model contains large scale variables like SLP, SST, Precipitation and Temperatures at 2M at the resolution 1.875°×1.875°, and H500, H200, T850, U200, V200, U850, V850 at the resolution 2.5°×2.5°.
- It is important for a large scale predictor that it should be reproduced by the global or regional climate model, which is in use, realistically.
- They should represent most part of the variability in the predictands.
- The links between predictors and predictands should be strong and stable in time.