This paper has two purposes. One is to evaluate the ability of an atmospheric general circulation model (IAP9L-AGCM) to predict summer rainfall over China one season in advance. The other is to propose a new approach to improve the predictions made by the model. First, a set of hindcast experiments for summer climate over China during 1982-2010 are performed from the perspective of real-time prediction with the IAP9L-AGCM model and the IAP ENSO prediction system. Then a new approach that effectively combines the hind-cast with its correction is proposed to further improve the model's predictive ability. A systematic evaluation reveals that the model's real-time predictions for 41 stations across China show significant improvement using this new approach, especially in the lower reaches between the Yellow River and Yangtze River valleys.
An effective statistical downscaling scheme was developed on the basis of singular value decomposition to predict boreal winter(December-January-February)precipitation over China.The variable geopotential height at 500 hPa(GH5)over East Asia,which was obtained from National Centers for Environmental Prediction’s Coupled Forecast System(NCEP CFS),was used as one predictor for the scheme.The preceding sea ice concentration(SIC)signal obtained from observed data over high latitudes of the Northern Hemisphere was chosen as an additional predictor.This downscaling scheme showed significantly improvement in predictability over the original CFS general circulation model(GCM)output in cross validation.The multi-year average spatial anomaly correlation coefficient increased from–0.03 to 0.31,and the downscaling temporal root-mean-square-error(RMSE)decreased significantly over that of the original CFS GCM for most China stations.Furthermore,large precipitation anomaly centers were reproduced with greater accuracy in the downscaling scheme than those in the original CFS GCM,and the anomaly correlation coefficient between the observation and downscaling results reached～0.6 in the winter of 2008.
The spring (March-April-May) rainfall over northern China (SPRNC) is predicted by using the interannual increment approach. DY denotes the difference between the current year and previous years. The seasonal forecast model for the DY of SPRNC is constructed based on the data that are taken from the 1965-2002 period (38 years), in which six predictors are available no later than the current month of February. This is favorable so that the seasonal forecasts can be made one month ahead. Then, SPRNC and the percentage anomaly of SPRNC are obtained by the predicted DY of SPRNC. The model performs well in the prediction of the inter-annual variation of the DY of SPRNC during 1965-2002, with a correlation coefficient between the predicted and observed DY of SPRNC of 0.87. This accounts for 76% of the total variance, with a low value for the average root mean square error (RMSE) of 20%. Both the results of the hindcast for the period of 2003-2010 (eight years) and the cross-validation test for the period of 1965-2009 (45 years) illustrate the good prediction capability of the model, with a small mean relative error of 10%, an RMSE of 17% and a high rate of coherence of 87.5% for the hindcasts of the percentage anomaly of SPRNC.
The relationship between winter sea surface temperature (SST) east of Australia and summer precipitation in the Yangtze River valley and a possibly related physical mechanism were investigated using observation data.It is found that winter SST east of Australia is correlated positively to summer precipitation in the Yangtze River valley.When the SST east of Australia becomes warmer in winter,the western Pacific subtropical high and the East Asian westerly jet tend to shift southward the following summer,concurrent with low-level southwesterly anomalies over eastern China.These conditions favor precipitation increase in the Yangtze River valley,whereas the opposite conditions favor precipitation decrease.The influence of winter SST east of Australia on East Asian summer atmospheric circulations may occur in two ways.First,by an anomalous SST signal east of Australia in winter that persists through the following summer,thus affecting East Asian atmospheric circulations via the inter-hemispheric teleconnection.Second,when the SST east of Australia is warmer in winter,higher SST appears simultaneously in the southwest Indian Ocean and subsequently develops eastward by local air-sea interaction.As a result,the SST in the Maritime Continent increases in summer,which may lead to an anomalous change in East Asian summer atmospheric circulations through its impact on convection.
Performances of 5 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the chloro-phyll concentration over the tropical Indian Ocean are evaluated. Results show that these models are able to capture the dominant spatial distribution of observed chlorophyll concentration and reproduce the maximum chlorophyll concentration over the western part of the Arabian Sea, around the tip of the Indian subcontinent, and in the southeast tropical Indian Ocean. The seasonal evolution of chlorophyll concentration over these regions is also reproduced with significant amplitude diversity among models. All of 5 mod-els is able to simulate the interannual variability of chlorophyll concentration. The maximum interannual variation occurs at the same regions where the maximum climatological chlorophyll concentration is located. Further analysis also reveals that the Indian Ocean Dipole events have great impact on chlorophyll concentration in the tropical Indian Ocean. In the general successful simulation of chlorophyll concentration, most of the CMIP5 models present higher than normal chlorophyll concentration in the eastern equatorial Indian Ocean.
LIU LinFENG LinYU WeidongWANG HuiwuLIU YanliangSUN Shuangwen
The purpose of this study was to design and test a statistical-dynamical scheme for the extraseasonal（one season in advance） prediction of summer rainfall at 160 observation stations across China.The scheme combined both valuable information from the preceding observations and dynamical information from synchronous numerical predictions of atmospheric circulation factors produced by an atmospheric general circulation model.First,the key preceding climatic signals and synchronous atmospheric circulation factors that were not only closely related to summer rainfall but also numerically predictable were identified as the potential predictors.Second,the extraseasonal prediction models of summer rainfall were constructed using a multivariate linear regression analysis for 15 subregions and then 160 stations across China.Cross-validation analyses performed for the period 1983-2008 revealed that the performance of the prediction models was not only high in terms of interannual variation,trend,and sign but also was stable during the whole period.Furthermore,the performance of the scheme was confirmed by the accuracy of the real-time prediction of summer rainfall during 2009 and 2010.
