Based on the simulations of cloud features in February 2001 by the regional numerical weather prediction model-Advanced Regional Eta-coordinate Model (AREM), the dynamic and thermodynamic conditions for middle cloud f...Based on the simulations of cloud features in February 2001 by the regional numerical weather prediction model-Advanced Regional Eta-coordinate Model (AREM), the dynamic and thermodynamic conditions for middle cloud formation over eastern China are studied. Diagnostic analysis partly confirms the previous suggestion that the middle stratiform clouds downstream of the Tibetaan Plateau are maintained by the frictional and blocking effects of the plateau. In addition, it is found that the temperature inversion at plateau height over eastern China generated by the warm air advected from the plateau provides a favorable thermodynamic condition for middle clouds. Both diurnal variations of the mid-level divergence and the inversion over eastern China, which are determined by the atmospheric boundary activity over the Tibetan Plateau, dominate the cloud diurnal cycle. The middle cloud amount decreases and the cloud top falls in the daytime, but reverses at night. The comparison of cloud features between the simulations and the observations also proves that the AREM can well capture the distinctive continental stratiform cloud features downstream of the Tibetan Plateau.展开更多
By using the Advanced Regional Eta-coordinate Model （AREM）, the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations. Five sets of experiments are designed to investi...By using the Advanced Regional Eta-coordinate Model （AREM）, the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations. Five sets of experiments are designed to investigate the effects of the cloud microphysical processes on the model cloud structure and precipitation features. The importance of the ice-phase microphysics, the cooling effect related to microphysical characteristics change, and the influence of terminal velocity of graupel are examined. The results indicate that the cloud microphysical processes impact more on the cloud development and precipitation features of the typhoon than on its intensity and track. Big differences in the distribution pattern and content of hydro-meteors, and types and amount of rainfall occur in the five experiments, resulting in different heating and cooling effects. The largest difference of 24-h rain rate reaches 52.5 mm h-1 . The results are summarized as follows： 1） when the cooling effect due to the evaporation of rain water is excluded, updrafts in the typhoon＇s inner core are the strongest with the maximum vertical velocity of -19 Pa s-1 and rain water and graupel grow most dominantly with their mixing ratios increased by 1.8 and 2.5 g kg-1, respectively, compared with the control experiment; 2） the melting of snow and graupel affects the growth of rain water mainly in the spiral rainbands, but much less significantly in the eyewall area; 3） the warm cloud microphysical process produces the smallest rainfall area and the largest percentage of convective precipitation （63.19%）, while the largest rainfall area and the smallest percentage of convective precipitation （48.85%） are generated when the terminal velocity of graupel is weakened by half.展开更多
A heavy storm rainfall caused by Typhoon Aere (No.0418) when landing at Fujian has been successfully simulated by using AREM model. The simulation result is scale-separated by spatial band-pass filtering, which reveal...A heavy storm rainfall caused by Typhoon Aere (No.0418) when landing at Fujian has been successfully simulated by using AREM model. The simulation result is scale-separated by spatial band-pass filtering, which reveals the mesoscale low pressure and convergence line that has direct impact on this rainfall process. The physical characteristics of the two mesoscale systems and their relation with rainfall are also analyzed. Study shows that there exists a well corresponding relationship between the storm rainfall and mesoscale divergence and strong updraft arising from the convergence, which is caused by the interactions between the mesoscale systems and topographic features, and is directly responsible for the rainfall.展开更多
The Advanced Regional Eta-coordinate Model （AREM） is used to explore the predictability of a heavy rainfall event along the Meiyu front in China during 3-4 July 2003. Based on the sensitivity of precipitation predic...The Advanced Regional Eta-coordinate Model （AREM） is used to explore the predictability of a heavy rainfall event along the Meiyu front in China during 3-4 July 2003. Based on the sensitivity of precipitation prediction to initial data sources and initial uncertainties in different variables, the evolution of error growth and the associated mechanism are described and discussed in detail in this paper. The results indicate that the smaller-amplitude initial error presents a faster growth rate and its growth is characterized by a transition from localized growth to widespread expansion error. Such modality of the error growth is closely related to the evolvement of the precipitation episode, and consequently remarkable forecast divergence is found near the rainband, indicating that the rainfall area is a sensitive region for error growth. The initial error in the rainband contributes significantly to the forecast divergence, and its amplification and propagation are largely determined by the initial moisture distribution. The moisture condition also affects the error growth on smaller scales and the subsequent upscale error cascade. In addition, the error growth defined by an energy norm reveals that large error energy collocates well with the strong latent heating, implying that the occurrence of precipitation and error growth share the same energy source-the latent heat. This may impose an intrinsic predictability limit on the prediction of heavy precipitation.展开更多
Shuibuya control basin in upper reaches of Qingjiang River,Hubei Province was taken as the case. By combining grouping Z-I relation with ground meteorological rainfall station,rainfall estimation by radar was calibrat...Shuibuya control basin in upper reaches of Qingjiang River,Hubei Province was taken as the case. By combining grouping Z-I relation with ground meteorological rainfall station,rainfall estimation by radar was calibrated,and actual average surface rainfall in the basin was calculated.By combining genetic algorithm with neural network,the corrected AREM rainfall forecast model was established,to improve rainfall forecast accuracy by AREM. Finally,AREM rainfall forecast models before and after correction were input in Xin＇an River hydrologic model for flood forecast test. The results showed that the corrected AREM rainfall forecast model could significantly improve forecast accuracy of accumulative rainfall,and decrease range of average relative error was more than 60%. Hourly rainfall forecast accuracy was improved somewhat,but there was certain difference from actual situation. Average deterministic coefficient of AREM flood forest test before and after correction was improved from -32. 60% to 64. 38%,and relative error of flood peak decreased from 39. 00% to 25. 04%. The improved effect of deterministic coefficient was better than relative error of flood peak,and whole flood forecast accuracy was improved somewhat.展开更多
This paper preliminarily evaluates the speedup,scalability,and prediction skill of the highperformance advanced regional eta coordinate model（H-AREM）,which is based on several parallel processing methods and decompo...This paper preliminarily evaluates the speedup,scalability,and prediction skill of the highperformance advanced regional eta coordinate model（H-AREM）,which is based on several parallel processing methods and decomposition strategies.Results show that the parallel version of the model that is based on a modular parallel framework and a multidimensional domain decomposition strategy performs better overall,e.g.it is faster and more scalable than the version based on a message passing interface and a one-dimensional decomposition strategy.In particular,the scalability of the H-AREM with a resolution of 8 km approaches 8099 cores.Moreover,in the H-AREM,higher resolutions result in more realistic precipitation predictions without remarkable increases in simulation time.展开更多
基金This work was jointly supported by the National Key Basic Research and Development project of China under Grant No.2004CB418304the National Natural Science Foundation of China under Grant Nos.40233031 and 40221503.
文摘Based on the simulations of cloud features in February 2001 by the regional numerical weather prediction model-Advanced Regional Eta-coordinate Model (AREM), the dynamic and thermodynamic conditions for middle cloud formation over eastern China are studied. Diagnostic analysis partly confirms the previous suggestion that the middle stratiform clouds downstream of the Tibetaan Plateau are maintained by the frictional and blocking effects of the plateau. In addition, it is found that the temperature inversion at plateau height over eastern China generated by the warm air advected from the plateau provides a favorable thermodynamic condition for middle clouds. Both diurnal variations of the mid-level divergence and the inversion over eastern China, which are determined by the atmospheric boundary activity over the Tibetan Plateau, dominate the cloud diurnal cycle. The middle cloud amount decreases and the cloud top falls in the daytime, but reverses at night. The comparison of cloud features between the simulations and the observations also proves that the AREM can well capture the distinctive continental stratiform cloud features downstream of the Tibetan Plateau.
基金Supported by the National Basic Research and Development （973） Program of China （2004CB418304） Acknowledgments. The authors are grateful to Prof. Zhou Xiaoping at IAP/CAS, Prof. Yuqing Wang at Hawaii University, Prof. Xu Huaubin at Beijing Institute of Applied Meteorology, Prof. Zhou Tianjun at LASG/IAP/CAS, and Prof. Guosheng Liu at FSU for their helpful suggestions and comments in the typhoon simulation and manuscript writing. We thank Mrs. Sun Jiao at Beijing Institute of Applied Meteorology for English polishing.
文摘By using the Advanced Regional Eta-coordinate Model （AREM）, the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations. Five sets of experiments are designed to investigate the effects of the cloud microphysical processes on the model cloud structure and precipitation features. The importance of the ice-phase microphysics, the cooling effect related to microphysical characteristics change, and the influence of terminal velocity of graupel are examined. The results indicate that the cloud microphysical processes impact more on the cloud development and precipitation features of the typhoon than on its intensity and track. Big differences in the distribution pattern and content of hydro-meteors, and types and amount of rainfall occur in the five experiments, resulting in different heating and cooling effects. The largest difference of 24-h rain rate reaches 52.5 mm h-1 . The results are summarized as follows： 1） when the cooling effect due to the evaporation of rain water is excluded, updrafts in the typhoon＇s inner core are the strongest with the maximum vertical velocity of -19 Pa s-1 and rain water and graupel grow most dominantly with their mixing ratios increased by 1.8 and 2.5 g kg-1, respectively, compared with the control experiment; 2） the melting of snow and graupel affects the growth of rain water mainly in the spiral rainbands, but much less significantly in the eyewall area; 3） the warm cloud microphysical process produces the smallest rainfall area and the largest percentage of convective precipitation （63.19%）, while the largest rainfall area and the smallest percentage of convective precipitation （48.85%） are generated when the terminal velocity of graupel is weakened by half.
文摘A heavy storm rainfall caused by Typhoon Aere (No.0418) when landing at Fujian has been successfully simulated by using AREM model. The simulation result is scale-separated by spatial band-pass filtering, which reveals the mesoscale low pressure and convergence line that has direct impact on this rainfall process. The physical characteristics of the two mesoscale systems and their relation with rainfall are also analyzed. Study shows that there exists a well corresponding relationship between the storm rainfall and mesoscale divergence and strong updraft arising from the convergence, which is caused by the interactions between the mesoscale systems and topographic features, and is directly responsible for the rainfall.
基金Supported by the National Natural Science Foundation of China (40975031)
文摘The Advanced Regional Eta-coordinate Model （AREM） is used to explore the predictability of a heavy rainfall event along the Meiyu front in China during 3-4 July 2003. Based on the sensitivity of precipitation prediction to initial data sources and initial uncertainties in different variables, the evolution of error growth and the associated mechanism are described and discussed in detail in this paper. The results indicate that the smaller-amplitude initial error presents a faster growth rate and its growth is characterized by a transition from localized growth to widespread expansion error. Such modality of the error growth is closely related to the evolvement of the precipitation episode, and consequently remarkable forecast divergence is found near the rainband, indicating that the rainfall area is a sensitive region for error growth. The initial error in the rainband contributes significantly to the forecast divergence, and its amplification and propagation are largely determined by the initial moisture distribution. The moisture condition also affects the error growth on smaller scales and the subsequent upscale error cascade. In addition, the error growth defined by an energy norm reveals that large error energy collocates well with the strong latent heating, implying that the occurrence of precipitation and error growth share the same energy source-the latent heat. This may impose an intrinsic predictability limit on the prediction of heavy precipitation.
基金Supported by the Science and Technology Development Key Fund of Hubei Provincial Meteorological Bureau(2015Z02)
文摘Shuibuya control basin in upper reaches of Qingjiang River,Hubei Province was taken as the case. By combining grouping Z-I relation with ground meteorological rainfall station,rainfall estimation by radar was calibrated,and actual average surface rainfall in the basin was calculated.By combining genetic algorithm with neural network,the corrected AREM rainfall forecast model was established,to improve rainfall forecast accuracy by AREM. Finally,AREM rainfall forecast models before and after correction were input in Xin＇an River hydrologic model for flood forecast test. The results showed that the corrected AREM rainfall forecast model could significantly improve forecast accuracy of accumulative rainfall,and decrease range of average relative error was more than 60%. Hourly rainfall forecast accuracy was improved somewhat,but there was certain difference from actual situation. Average deterministic coefficient of AREM flood forest test before and after correction was improved from -32. 60% to 64. 38%,and relative error of flood peak decreased from 39. 00% to 25. 04%. The improved effect of deterministic coefficient was better than relative error of flood peak,and whole flood forecast accuracy was improved somewhat.
基金jointly supported by the National Basic Research Program of China(973 Program)[grant number 6131270305]the Ministry of Water Resources'special research grant for non-profit public service[grant number 201301062-02]+1 种基金the National Natural Science Foundation of China[grant number61572058]the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA05110304]
文摘This paper preliminarily evaluates the speedup,scalability,and prediction skill of the highperformance advanced regional eta coordinate model（H-AREM）,which is based on several parallel processing methods and decomposition strategies.Results show that the parallel version of the model that is based on a modular parallel framework and a multidimensional domain decomposition strategy performs better overall,e.g.it is faster and more scalable than the version based on a message passing interface and a one-dimensional decomposition strategy.In particular,the scalability of the H-AREM with a resolution of 8 km approaches 8099 cores.Moreover,in the H-AREM,higher resolutions result in more realistic precipitation predictions without remarkable increases in simulation time.
