An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the an...An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.展开更多
The ten-year mean anomalies of seasonal and annual temperatures were reconstructed on the basis of historical documents of cold events such as severe snowing and freezing of lakes and rivers.The assorted events were c...The ten-year mean anomalies of seasonal and annual temperatures were reconstructed on the basis of historical documents of cold events such as severe snowing and freezing of lakes and rivers.The assorted events were calibrated with instrumental observations of temperature and transformed into ten-year mean anomalies. The reconstructed temperature series show predominance of cold climate in the first four hundred years of the period examined.The centenary seasonal temperature anomalies for the 16th to the 19th century vary between -0.1 and -0.7K.The coldest decades concentrated in the middle of 17th and 19th centuries.It provided the irrefutable evidence of the occurrence of the Little Ice Age in China.The minima of ten-year mean temperature anomalies ranged about -1.5 to 2.0K in spring and winter.Meanwhile,the variance of ten-year mean tempera- ture was increased by more than 20％ in comparison to the 20th century.展开更多
Climate change has a great influence on agricultural production,especially under extreme climatic conditions.In this study,Root Zone Water Quality Model(RZWQM)was used to predict grain yields of maize in the Siping re...Climate change has a great influence on agricultural production,especially under extreme climatic conditions.In this study,Root Zone Water Quality Model(RZWQM)was used to predict grain yields of maize in the Siping region,Jilin Province,Northeast China during the period from 1951 to 2015;and the response of grain yield to main climatic variables was qualitatively analyzed,especially in three special years of 1954,2000 and 2009.Results showed that 1℃ increase for minimum,maximum and mean air temperatures may produce 1224 kg/hm^(2),1860 kg/hm^(2) and 1540 kg/hm^(2) more grain yields,respectively,and seasonal rainfall amount of less than 450 mm,especially at the flowering and grain filling stages,greatly reduced grain yields.In the years of 1954,2000 and 2009,grain yields were reduced by 41%,47%and 40%compared to their mean value,respectively,correspondingly because of extra low temperature(lower by 2.1℃-2.3℃),less rainfall at the grain filling stage(36 mm)and extra high temperature(higher by 1.7℃-1.8℃),and less seasonal rainfall(252 mm).To reduce extreme climate’s effects on grain yield,it is suggested that supplementary irrigation at the flowering and grain filling stages should be provided when rainfall is much less at this stage and also appropriate maize species based on the longtime weather forecast should be selected.展开更多
基金National Natural Science Foundation of China(41405104)Specialized Project for Public Welfare Industries(Meteorological Sector)(GYHY201306004)+2 种基金Guangdong Science and Technology Planning Project(2012A061400012)Project of Guangdong Provincial Meteorological Bureau for Science and Technology(2013A04)Science and Technology Plan for the 12th Five-Year of Social and Economic Development(2012BAC22B00)
文摘An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.
文摘The ten-year mean anomalies of seasonal and annual temperatures were reconstructed on the basis of historical documents of cold events such as severe snowing and freezing of lakes and rivers.The assorted events were calibrated with instrumental observations of temperature and transformed into ten-year mean anomalies. The reconstructed temperature series show predominance of cold climate in the first four hundred years of the period examined.The centenary seasonal temperature anomalies for the 16th to the 19th century vary between -0.1 and -0.7K.The coldest decades concentrated in the middle of 17th and 19th centuries.It provided the irrefutable evidence of the occurrence of the Little Ice Age in China.The minima of ten-year mean temperature anomalies ranged about -1.5 to 2.0K in spring and winter.Meanwhile,the variance of ten-year mean tempera- ture was increased by more than 20％ in comparison to the 20th century.
基金This research was funded by The National Key Research and Development Program of China(2017YFD0201500)the 111 Project(B18006).
文摘Climate change has a great influence on agricultural production,especially under extreme climatic conditions.In this study,Root Zone Water Quality Model(RZWQM)was used to predict grain yields of maize in the Siping region,Jilin Province,Northeast China during the period from 1951 to 2015;and the response of grain yield to main climatic variables was qualitatively analyzed,especially in three special years of 1954,2000 and 2009.Results showed that 1℃ increase for minimum,maximum and mean air temperatures may produce 1224 kg/hm^(2),1860 kg/hm^(2) and 1540 kg/hm^(2) more grain yields,respectively,and seasonal rainfall amount of less than 450 mm,especially at the flowering and grain filling stages,greatly reduced grain yields.In the years of 1954,2000 and 2009,grain yields were reduced by 41%,47%and 40%compared to their mean value,respectively,correspondingly because of extra low temperature(lower by 2.1℃-2.3℃),less rainfall at the grain filling stage(36 mm)and extra high temperature(higher by 1.7℃-1.8℃),and less seasonal rainfall(252 mm).To reduce extreme climate’s effects on grain yield,it is suggested that supplementary irrigation at the flowering and grain filling stages should be provided when rainfall is much less at this stage and also appropriate maize species based on the longtime weather forecast should be selected.
