Based on the atmospheric self_memorization principle, a complex memory function was introduced and the spectral form of atmospheric self_memorial equation was derived. Setting up and solving the equation constitute a ...Based on the atmospheric self_memorization principle, a complex memory function was introduced and the spectral form of atmospheric self_memorial equation was derived. Setting up and solving the equation constitute a new approach of the numerical weather prediction. Using the spectral model T42L9 as a dynamic kernel, a global self_memorial T42 model (SMT42) was established, with which twelve cases of 30_d integration experiments were carried out. Compared with the T42L9, the SMT42 is much better in 500 hPa forecast not only for daily circulation but also for monthly mean circulation. The anomaly correlation coefficient (ACC) of forecast for monthly mean circulation has been improved to 0.42, increased by 0.05, and the root_mean_square error (RMSE) has been reduced from 6.09 to 4.03 dagpm.展开更多
This paper addresses a problem of flood forecasting with the self-memory function. Considering flood forecasting’s uncertainty and updating demand, a hybrid hydrological model, namely Differential Hy- drological Grey...This paper addresses a problem of flood forecasting with the self-memory function. Considering flood forecasting’s uncertainty and updating demand, a hybrid hydrological model, namely Differential Hy- drological Grey Model with self-memory function (DHGM-SM), is developed. The model has two fold features. One is to establish a self-memorization equation linked with DHGM, that could extract useful information from past data series and realize updating of hydrological dynamic process. The other is that this model has higher efficiency relative to original hydrological model without self-memory func- tion. This approach was applied to river flow forecasting of two representative basins in Tunxi of South China and Daqinggou of North China. It is shown that this hybrid method has satisfactory forecasting accuracy by examination of both calibration and validation.展开更多
文摘Based on the atmospheric self_memorization principle, a complex memory function was introduced and the spectral form of atmospheric self_memorial equation was derived. Setting up and solving the equation constitute a new approach of the numerical weather prediction. Using the spectral model T42L9 as a dynamic kernel, a global self_memorial T42 model (SMT42) was established, with which twelve cases of 30_d integration experiments were carried out. Compared with the T42L9, the SMT42 is much better in 500 hPa forecast not only for daily circulation but also for monthly mean circulation. The anomaly correlation coefficient (ACC) of forecast for monthly mean circulation has been improved to 0.42, increased by 0.05, and the root_mean_square error (RMSE) has been reduced from 6.09 to 4.03 dagpm.
基金Supported by the National Natural Science Foundation of China (Grant No. 40671035)the Special Fund of Ministry of Science & Technology of China (Grant No. 2006DFA21890)
文摘This paper addresses a problem of flood forecasting with the self-memory function. Considering flood forecasting’s uncertainty and updating demand, a hybrid hydrological model, namely Differential Hy- drological Grey Model with self-memory function (DHGM-SM), is developed. The model has two fold features. One is to establish a self-memorization equation linked with DHGM, that could extract useful information from past data series and realize updating of hydrological dynamic process. The other is that this model has higher efficiency relative to original hydrological model without self-memory func- tion. This approach was applied to river flow forecasting of two representative basins in Tunxi of South China and Daqinggou of North China. It is shown that this hybrid method has satisfactory forecasting accuracy by examination of both calibration and validation.
