By using the Betts-Miller-Janji'c,Grell-Devenyi,and Kain-Fritsch cumulus convective parameterization schemes in the Weather Research and Forecasting(WRF) model,long time simulations from 2000 to 2009 are conducted to investigate the impacts of different cumulus convective parameterization schemes on summermonsoon precipitation simulation over China.The results show that all the schemes have the capability to reasonably reproduce the spatial and temporal distributions of summer monsoon precipitation and the corresponding background circulation.The observed north-south shift of monsoon rain belt is also well simulated by the three schemes.Detailed comparison indicates that the Grell-Devenyi scheme gives a better performance than the others.Deficiency in simulated water vapor transport is one possible reason for the precipitation simulation bias.
A new empirical approach for the seasonal prediction of annual Atlantic tropical storm number (ATSN) was developed using precipitation and 500 hPa geopotential height data from the preceding January February and April May.The 2.5°×2.5° resolution reanalysis data from both the US National Center for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) and the European Center for Medium-Range Weather Forecasting (ECMWF) were applied.The model was cross-validated using data from 1979 2002.The ATSN predictions from the two reanalysis models were correlated with the observations with the anomaly correlation coefficients (ACC) of 0.79 (NCEP/NCAR) and 0.78 (ECMWF) and the multi-year mean absolute prediction errors (MAE) of 1.85 and 1.76,respectively.When the predictions of the two models were averaged,the ACC increased to 0.90 and the MAE decreased to 1.18,an exceptionally high score.Therefore,this new empirical approach has the potential to improve the operational prediction of the annual tropical Atlantic storm frequency.
A new seasonal prediction model for annual tropical storm numbers(ATSNs)over the western North Pacific was developed using the preceding January-February(JF)and April-May(AM)grid-point data at a resolution of 2.5°×2.5°.The JF and AM mean precipitation and the AM mean 500-hPa geopotential height in the Northern Hemisphere,together with the JF mean 500-hPa geopotential height in the Southern Hemisphere,were employed to compose the ATSN forecast model via the stepwise multiple linear regression technique.All JF and AM mean data were confined to the Eastern Hemisphere.We established two empirical prediction models for ATSN using the ERA40 reanalysis and NCEP reanalysis datasets,respectively,together with the observed precipitation.The performance of the models was verified by cross-validation.Anomaly correlation coefficients(ACC)at 0.78 and 0.74 were obtained via comparison of the retrospective predictions of the two models and the observed ATSNs from 1979 to 2002.The multi-year mean absolute prediction errors were 3.0 and 3.2 for the two models respectively,or roughly 10% of the average ATSN.In practice,the final prediction was made by averaging the ATSN predictions of the two models.This resulted in a higher score,with ACC being further increased to 0.88,and the mean absolute error reduced to 1.92,or 6.13% of the average ATSN.
Correlation analysis revealed that winter precipitation in six regions of eastern China is closely related not only to preceding climate signals but also to synchronous atmospheric general circulation fields.It is therefore necessary to use a method that combines both dynamical and statistical predictions of winter precipitation over eastern China(herein after called the hybrid approach).In this connection,seasonal real-time prediction models for winter precipitation were established for the six regions.The models use both the preceding observations and synchronous numerical predictions through a multivariate linear regression analysis.To improve the prediction accuracy,the systematic error between the original regression model result and the corresponding observation was corrected.Cross-validation analysis and real-time prediction experiments indicate that the prediction models using the hybrid approach can reliably predict the trend,sign,and interannual variation of regionally averaged winter precipitation in the six regions of concern.Averaged over the six target regions,the anomaly correlation coefficient and the rate with the same sign of anomaly between the cross-validation analysis and observation during 1982-2008 are 0.69 and 78%,respectively.This indicates that the hybrid prediction approach adopted in this study is applicable in operational practice.
This study evaluates the ability of the global coupled climate models in hind casting the Arctic Oscillation(AO)and Antarctic Oscillation(AAO).The results show that the models can well simulate the spatial distribution of AO with better results in winter than in spring.In the troposphere in spring,the simulation of AO on the whole is still relatively good with a comparatively high correlation with the NCEP/NCARre analysis.The models can also well reproduce the spatial distribution of AAO throughout the year at all levels of the troposphere,and the spatial simulation is better at 850 hPa than at the surface.Although the simulation is better in winter than in other seasons,the seasonal variation is not so significant andthe differences among different models are relatively small.In addition,the capability of the models for "predicting" the AO and the AAO index time series is limited,because only a few models can capture their observed interannual variability at the 95% significance level.
This study evaluates the ability of the Abdus Salam International Center for Theoretical Physics(ICTP)version 3 Regional Climate Model(RegCM3) in simulating the summer rainfall amount and distribution and large-scale circulation over the Huaihe River basin of China.We conducted the simulation for the period of 1982-2001 and the wet year of 2003 to test the ensemble simulation capacity of RegCM3.First,by comparing the simulated rainfall amount and distribution against the observations,it is found that RegCM3 can reproduce the rainfall pattern and its annual variations.In addition,the simulated spatial patterns of 850-hPa wind and specific humidity fields are close to the observations,although the wind speed and humidity values are larger.Finally,the ensemble simulation of RegCM3 for summer 2003 failed to capture the spatial distribution and underestimated the magnitude of the precipitation anomalies,and the reasons are analyzed.
