本文提供了另外一个六维抽象空间数学模型——矩阵 T。t_(ij)是一个项目网状均衡预测系数,表示国有商业银行集团(银团)一亿元第 j 项资产总量能够耗散该银团若干亿元的第 i 项负债总量。设 X 为工具(输入)变量——银团各项资产总量心理...本文提供了另外一个六维抽象空间数学模型——矩阵 T。t_(ij)是一个项目网状均衡预测系数,表示国有商业银行集团(银团)一亿元第 j 项资产总量能够耗散该银团若干亿元的第 i 项负债总量。设 X 为工具(输入)变量——银团各项资产总量心理预期值,则项目网状均衡预测式 TX=Y 表示银团各项负债总量的预测值,Y 揭示了央行调控力度如果渗透到银团资产、负债各项目的总量上,就能够从源头上优化资源配置。展开更多
A debris flow forecast model based on a water-soil coupling mechanism that takes the debrisflow watershed as a basic forecast unit was established here for the prediction of disasters at the watershed scale.This was a...A debris flow forecast model based on a water-soil coupling mechanism that takes the debrisflow watershed as a basic forecast unit was established here for the prediction of disasters at the watershed scale.This was achieved through advances in our understanding of the formation mechanism of debris flow.To expand the applicable spatial scale of this forecasting model,a method of identifying potential debris flow watersheds was used to locate areas vulnerable to debris flow within a forecast region.Using these watersheds as forecasting units and a prediction method based on the water-soil coupling mechanism,a new forecasting method of debris flow at the regional scale was established.In order to test the prediction ability of this new forecasting method,the Sichuan province,China was selected as a study zone and the large-scale debris flow disasters attributable to heavy rainfall in this region on July 9,2013 were taken as the study case.According to debris flow disaster data on July 9,2013 which were provided by the geo-environmental monitoring station of Sichuan province,there were 252 watersheds in which debris flow events actually occurred.The current model predicted that 265 watersheds were likely to experience a debris flow event.Among these,43 towns including 204 debrisflow watersheds were successfully forecasted and 24 towns including 48 watersheds failed.The false prediction rate and failure prediction rate of thisforecast model were 23% and 19%,respectively.The results show that this method is more accurate and more applicable than traditional methods.展开更多
This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studi...This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.展开更多
Climate change projections over the Mediterranean region have been elaborated by using the outputs of ten ENSEMBLES regional climate simulations with an horizontal resolution of 25 km under the SRES A1B emission scena...Climate change projections over the Mediterranean region have been elaborated by using the outputs of ten ENSEMBLES regional climate simulations with an horizontal resolution of 25 km under the SRES A1B emission scenario. The analysis concerns some surface atmospheric variables： mean sea level pressure, temperature, precipitation and wind speed. At first, model validations have been performed by comparing model results with E-OBS and ERA-Interim data in reproducing the last decades over some Italian sub-areas and the Alpine region. In spite of the considerable spread in the models＇ performances to represent the reference climate, a multi-model reconstruction has been computed and some seasonal climate change projections have been elaborated. About the mean climate changes, the more significant signals expected by 2050 are a maximum warming （about 2 ~C） and maximum drying （about 20%） in the southern Europe in summer. Moreover, the results indicate an increasing risk for some severe weather conditions： more days of extremely high temperature in summer over the whole area, a greater occurrence of flooding and storms over coasts during spring and autumn seasons and a more serious wet-snow event over Alpine region in winter. No significant signals of wind changes have been detected.展开更多
基金supported by the foundation of the Research Fund for Commonweal Trades (Meteorology) (Grant No. GYHY201006039)the International Cooperation Project of the Department of Science and Technology of Sichuan Province (Grant No. 2009HH0005)
文摘A debris flow forecast model based on a water-soil coupling mechanism that takes the debrisflow watershed as a basic forecast unit was established here for the prediction of disasters at the watershed scale.This was achieved through advances in our understanding of the formation mechanism of debris flow.To expand the applicable spatial scale of this forecasting model,a method of identifying potential debris flow watersheds was used to locate areas vulnerable to debris flow within a forecast region.Using these watersheds as forecasting units and a prediction method based on the water-soil coupling mechanism,a new forecasting method of debris flow at the regional scale was established.In order to test the prediction ability of this new forecasting method,the Sichuan province,China was selected as a study zone and the large-scale debris flow disasters attributable to heavy rainfall in this region on July 9,2013 were taken as the study case.According to debris flow disaster data on July 9,2013 which were provided by the geo-environmental monitoring station of Sichuan province,there were 252 watersheds in which debris flow events actually occurred.The current model predicted that 265 watersheds were likely to experience a debris flow event.Among these,43 towns including 204 debrisflow watersheds were successfully forecasted and 24 towns including 48 watersheds failed.The false prediction rate and failure prediction rate of thisforecast model were 23% and 19%,respectively.The results show that this method is more accurate and more applicable than traditional methods.
基金Under the jointly auspices of the Special Public Research for Meteorological Industry (No. GYHY200806009)Wind Energy Resources Detailed Survey and Assessment WorkEU-China Energy and Environment Program (No. Europe Aid/ 123310/D/Ser/CN)
文摘This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.
文摘Climate change projections over the Mediterranean region have been elaborated by using the outputs of ten ENSEMBLES regional climate simulations with an horizontal resolution of 25 km under the SRES A1B emission scenario. The analysis concerns some surface atmospheric variables： mean sea level pressure, temperature, precipitation and wind speed. At first, model validations have been performed by comparing model results with E-OBS and ERA-Interim data in reproducing the last decades over some Italian sub-areas and the Alpine region. In spite of the considerable spread in the models＇ performances to represent the reference climate, a multi-model reconstruction has been computed and some seasonal climate change projections have been elaborated. About the mean climate changes, the more significant signals expected by 2050 are a maximum warming （about 2 ~C） and maximum drying （about 20%） in the southern Europe in summer. Moreover, the results indicate an increasing risk for some severe weather conditions： more days of extremely high temperature in summer over the whole area, a greater occurrence of flooding and storms over coasts during spring and autumn seasons and a more serious wet-snow event over Alpine region in winter. No significant signals of wind changes have been detected.
