Verification and Evaluation of Total Cloud Cover Prediction Performance of CMA-BJ
Cloud is one of the most important and active factors in weather and climate,and plays an impor-tant role in modulating the radiation-energy balance and water cycle of atmospheric system.The effective forecast of total cloud cover can lay a basis for better grasp of weather phenomena and prediction of new energy output such as photovoltaic power generation.The model CMA-BJ(Beijing Rapid Update Cycle System)can provide hourly high-resolution total cloud cover prediction products.In this paper,the prediction performance of CMA-BJ is systematically examined and evaluated by the time scale separation method,and the error sources are analyzed,so as to provide a reference for product interpretation and model improve-ment.The results show that the spatial distribution characteristics and diurnal variation intensity of total cloud cover can be well predicted by CMA-BJ.The pattern correlation coefficients between the CMA-BJ forecasted and observed total cloud cover with 1-24 h lead time are all greater than 0.6 in each month.However,the total cloud cover and diurnal variation intensity are significantly underestimated in winter(January),with the deviation of CMA-BJ reaching-0.133.As the forecasting time increases,the predic-tion ability of CMA-BJ decreases,with the averaged TCC skills being 0.470,0.409,0.355 and 0.315 for the 1-4 d forecast,which means the skillful prediction can be maintained up to 48-72 hours.The diag-nostic analysis shows that the low relative humidity in the model may largely contribute to the negative de-viation in total cloud cover prediction.Besides,the bias of vertical velocity prediction is also an important reason for the cloud cover prediction error.
万方数据
维普
