基于ECMWF(European Centre for Medium-Range Weather Forecasts)ERA5(Reanalysis version 5)、CFSR(Climate Forecast System Reanalysis)、MERRA2(Modern-Era Retrospective analysis for Research and Applications version 2)3种...基于ECMWF(European Centre for Medium-Range Weather Forecasts)ERA5(Reanalysis version 5)、CFSR(Climate Forecast System Reanalysis)、MERRA2(Modern-Era Retrospective analysis for Research and Applications version 2)3种再分析数据,13个海洋观测站和3个测风塔的观测数据,研究了中国近海风资源时空特征,并讨论了3种再分析数据在中国近海风资源评估中的适用性。结果表明,再分析数据在中国东海和南海的弱风频率比渤海、黄海高,且ERA5在所有海域小于6 m/s的弱风累积概率比CFSR(MERRA2)高39.0%(44.9%)、43.6%(47.5%)、60.7%(41.6%)和47.9%(38.2%)。ERA5、CFSR和MERRA2在中国近海的有效风时空间分布相似,量级都介于84%~95%;3种再分析平均风能密度自北向南呈“低高低”空间分布,其中台湾海峡是WPD大值中心(超过4000 W/m2)。风能稳定性方面,ERA5和CFSR的日变异呈“南弱北强”特征,而MERRA2日变异系数介于1.03~4。适用性分析表明,ERA5整体性能优于CFSR和MERRA2,但MERRA2在再现渤海、南海的风能日波动,CFSR在刻画黄海的有效风时、风能密度和东海、黄海的变异系数时具有一定优势。由此说明不同再分析数据对中国近海风资源不同指标的适用性各有优劣,应根据需要及数据条件,针对不同海域采用不同类的再分析数据开展风资源评估研究及工作。展开更多
基于中尺度气象数值模式WRF(Weather Research and Forecasting),分别对我国广东、浙江、山东这3个近海典型风能资源储备区域进行了45组物理参数化方案组合连续1 M的敏感性试验,对试验中多要素的模拟结果进行综合评估,分别确定了适用于...基于中尺度气象数值模式WRF(Weather Research and Forecasting),分别对我国广东、浙江、山东这3个近海典型风能资源储备区域进行了45组物理参数化方案组合连续1 M的敏感性试验,对试验中多要素的模拟结果进行综合评估,分别确定了适用于3个风能资源储备区各自排名前3的物理参数化方案组合,并对其模拟性能较优的原因进行分析。为了测试3个风能资源储备区筛选得到的物理参数化方案组合的适用性,利用不同于敏感性试验时段的模拟结果,结合海上测风塔和海洋气象站的实测数据开展进一步评估。结果表明,优选得到的物理参数化方案组合具有较好的适用性,其对近海的风速模拟性能较优,具有实际业务应用价值。展开更多
The seriousness of losses caused by disaster dependent on the hazard degree of environment,vulnerability of hazard-affected bodies,and emergency response capacity of the region is studied in this article.The study on ...The seriousness of losses caused by disaster dependent on the hazard degree of environment,vulnerability of hazard-affected bodies,and emergency response capacity of the region is studied in this article.The study on hazard-affected bodies is of importance to disaster risk management,regional hazard prevention,reduction,and investment in disaster insurance.With summarizing of various assessment methods of vulnerability of hazard-affected bodies,this paper presents a refined Spatial Quantification Model of regional vulnerability which combines refined spatial geographic data and land-use type data.A quantitative study on regional vulnerability was carried out by defining fine spatial grid as the basic evaluation unit based on GIS.展开更多
文摘基于ECMWF(European Centre for Medium-Range Weather Forecasts)ERA5(Reanalysis version 5)、CFSR(Climate Forecast System Reanalysis)、MERRA2(Modern-Era Retrospective analysis for Research and Applications version 2)3种再分析数据,13个海洋观测站和3个测风塔的观测数据,研究了中国近海风资源时空特征,并讨论了3种再分析数据在中国近海风资源评估中的适用性。结果表明,再分析数据在中国东海和南海的弱风频率比渤海、黄海高,且ERA5在所有海域小于6 m/s的弱风累积概率比CFSR(MERRA2)高39.0%(44.9%)、43.6%(47.5%)、60.7%(41.6%)和47.9%(38.2%)。ERA5、CFSR和MERRA2在中国近海的有效风时空间分布相似,量级都介于84%~95%;3种再分析平均风能密度自北向南呈“低高低”空间分布,其中台湾海峡是WPD大值中心(超过4000 W/m2)。风能稳定性方面,ERA5和CFSR的日变异呈“南弱北强”特征,而MERRA2日变异系数介于1.03~4。适用性分析表明,ERA5整体性能优于CFSR和MERRA2,但MERRA2在再现渤海、南海的风能日波动,CFSR在刻画黄海的有效风时、风能密度和东海、黄海的变异系数时具有一定优势。由此说明不同再分析数据对中国近海风资源不同指标的适用性各有优劣,应根据需要及数据条件,针对不同海域采用不同类的再分析数据开展风资源评估研究及工作。
文摘基于中尺度气象数值模式WRF(Weather Research and Forecasting),分别对我国广东、浙江、山东这3个近海典型风能资源储备区域进行了45组物理参数化方案组合连续1 M的敏感性试验,对试验中多要素的模拟结果进行综合评估,分别确定了适用于3个风能资源储备区各自排名前3的物理参数化方案组合,并对其模拟性能较优的原因进行分析。为了测试3个风能资源储备区筛选得到的物理参数化方案组合的适用性,利用不同于敏感性试验时段的模拟结果,结合海上测风塔和海洋气象站的实测数据开展进一步评估。结果表明,优选得到的物理参数化方案组合具有较好的适用性,其对近海的风速模拟性能较优,具有实际业务应用价值。
基金funded by the Science and Technology project of the Meteorological Bureau of Zhejiang Province in 2010(No.2010ZD05)Science and Technology projects in Zhejiang Province(No.2007C33062).
文摘The seriousness of losses caused by disaster dependent on the hazard degree of environment,vulnerability of hazard-affected bodies,and emergency response capacity of the region is studied in this article.The study on hazard-affected bodies is of importance to disaster risk management,regional hazard prevention,reduction,and investment in disaster insurance.With summarizing of various assessment methods of vulnerability of hazard-affected bodies,this paper presents a refined Spatial Quantification Model of regional vulnerability which combines refined spatial geographic data and land-use type data.A quantitative study on regional vulnerability was carried out by defining fine spatial grid as the basic evaluation unit based on GIS.