The South China Sea is a hotspot for regional climate research.Over the past 40 years,considerable improvement has been made in the development and utilization of the islands in the South China Sea,leading to a substa...The South China Sea is a hotspot for regional climate research.Over the past 40 years,considerable improvement has been made in the development and utilization of the islands in the South China Sea,leading to a substantial change in the land-use of the islands.However,research on the impact of human development on the local climate of these islands is lacking.This study analyzed the characteristics of local climate changes on the islands in the South China Sea based on data from the Yongxing Island Observation Station and ERA5 re-analysis.Furthermore,the influence of urbanization on the local climate of the South China Sea islands was explored in this study.The findings revealed that the 10-year average temperature in Yongxing Island increased by approximately 1.11℃from 1961 to 2020,and the contribution of island development and urbanization to the local warming rate over 60 years was approximately 36.2%.The linear increasing trend of the annual hot days from 1961–2020 was approximately 14.84 days per decade.The diurnal temperature range exhibited an increasing trend of 0.05℃per decade,whereas the number of cold days decreased by 1.06days per decade.The rapid increase in construction on Yongxing Island from 2005 to 2021 led to a decrease in observed surface wind speed by 0.32 m s^(-1)per decade.Consequently,the number of days with strong winds decreased,whereas the number of days with weak winds increased.Additionally,relative humidity exhibited a rapid decline from 2001 to 2016 and then rebounded.The study also found substantial differences between the ERA5 re-analysis and observation data,particularly in wind speed and relative humidity,indicating that the use of re-analysis data for climate resource assessment and climate change evaluation on island areas may not be feasible.展开更多
利用降水资料、地形资料与社会经济数据,建立楚雄彝族自治州(以下简称楚雄州)洪涝风险评估体系及评估模型.运用层次分析法计算出各个洪涝指标的权重值,再用加权综合评价法建立各影响因子模型,并用GIS(Geographic Information System)软...利用降水资料、地形资料与社会经济数据,建立楚雄彝族自治州(以下简称楚雄州)洪涝风险评估体系及评估模型.运用层次分析法计算出各个洪涝指标的权重值,再用加权综合评价法建立各影响因子模型,并用GIS(Geographic Information System)软件对数据结果制图,对致涝因子危险性、孕涝因子敏感性和承涝因子脆弱性3个指标进行分析,得到楚雄州洪涝风险的危险性、敏感性、脆弱性和综合风险评估指数.结果表明:楚雄州致涝因子危险性最高的是双柏县,危险性值是0.575,危险性最低的区域是元谋县,危险性值是0.067;楚雄州孕涝因子敏感性较高的是元谋县,敏感性值是0.392,敏感性最低的是双柏县,敏感性值是0.074;楚雄州承涝因子脆弱性最高的区域是双柏县,脆弱性值是0.194,脆弱性最低的区域是楚雄市,脆弱性值是0.011.洪涝风险综合评估的最高风险区域主要是双柏县,风险指数是0.437,最低风险的区域主要是元谋县,风险指数是0.137.展开更多
已有研究表明坝式水电站蓄水对局地气候有重要影响,但目前对梯级水电站蓄水的气候效应还不清楚,尤其是在干热河谷地区。为深入研究梯级水电站对区域气候的影响,以2005~2020年金沙江下游向家坝-溪洛渡梯级水电站所在流域及周边区域38个...已有研究表明坝式水电站蓄水对局地气候有重要影响,但目前对梯级水电站蓄水的气候效应还不清楚,尤其是在干热河谷地区。为深入研究梯级水电站对区域气候的影响,以2005~2020年金沙江下游向家坝-溪洛渡梯级水电站所在流域及周边区域38个气象站监测数据为基础,采用ANUSPLIN(Australian National University Spline)模型模拟流域内的气温、降水参数,进而采用PELT(Pruned Exact Linear Time)算法、CV(Coefficient of Variation)和Trend方法探究梯级水库蓄水前后气候的时空变化特征。结果表明:(1)ANUSPLIN模型能较好地模拟气温和降水,气温、降水模拟的相对误差分别介于2.26%~10.62%和9.74%~38.14%之间,且该模型对高温、旱季的模拟效果分别优于低温、雨季。(2)蓄水后流域年均气温的降温幅度较蓄水前有所增大,其中冬、夏季表现为气温增加,春、秋季表现为气温降低;年降水量降低的趋势也较蓄水前极大减缓,并且夏、秋、冬三季的降水量均表现为增加。(3)从突变检验结果来看,蓄水后冬、夏季气温均有突变现象;春、夏、秋季以及年降水量也都发生了突变。(4)蓄水后,流域气温、降水均呈现变异减弱、稳定性增强的特征,且距离库区越近,稳定性越强。研究成果有助于加深理解大型梯级水电开发所引起的气候变化效应。展开更多
基金National Natural Science Foundation of China(U21A6001,42075059)Specific Research Fund of The Innovation Platform for Academicians of Hainan Province(YSPTZX202143)+1 种基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)Science and Technology Project of Guangdong Meteorological Service(GRMC2020M29)。
文摘The South China Sea is a hotspot for regional climate research.Over the past 40 years,considerable improvement has been made in the development and utilization of the islands in the South China Sea,leading to a substantial change in the land-use of the islands.However,research on the impact of human development on the local climate of these islands is lacking.This study analyzed the characteristics of local climate changes on the islands in the South China Sea based on data from the Yongxing Island Observation Station and ERA5 re-analysis.Furthermore,the influence of urbanization on the local climate of the South China Sea islands was explored in this study.The findings revealed that the 10-year average temperature in Yongxing Island increased by approximately 1.11℃from 1961 to 2020,and the contribution of island development and urbanization to the local warming rate over 60 years was approximately 36.2%.The linear increasing trend of the annual hot days from 1961–2020 was approximately 14.84 days per decade.The diurnal temperature range exhibited an increasing trend of 0.05℃per decade,whereas the number of cold days decreased by 1.06days per decade.The rapid increase in construction on Yongxing Island from 2005 to 2021 led to a decrease in observed surface wind speed by 0.32 m s^(-1)per decade.Consequently,the number of days with strong winds decreased,whereas the number of days with weak winds increased.Additionally,relative humidity exhibited a rapid decline from 2001 to 2016 and then rebounded.The study also found substantial differences between the ERA5 re-analysis and observation data,particularly in wind speed and relative humidity,indicating that the use of re-analysis data for climate resource assessment and climate change evaluation on island areas may not be feasible.
文摘利用降水资料、地形资料与社会经济数据,建立楚雄彝族自治州(以下简称楚雄州)洪涝风险评估体系及评估模型.运用层次分析法计算出各个洪涝指标的权重值,再用加权综合评价法建立各影响因子模型,并用GIS(Geographic Information System)软件对数据结果制图,对致涝因子危险性、孕涝因子敏感性和承涝因子脆弱性3个指标进行分析,得到楚雄州洪涝风险的危险性、敏感性、脆弱性和综合风险评估指数.结果表明:楚雄州致涝因子危险性最高的是双柏县,危险性值是0.575,危险性最低的区域是元谋县,危险性值是0.067;楚雄州孕涝因子敏感性较高的是元谋县,敏感性值是0.392,敏感性最低的是双柏县,敏感性值是0.074;楚雄州承涝因子脆弱性最高的区域是双柏县,脆弱性值是0.194,脆弱性最低的区域是楚雄市,脆弱性值是0.011.洪涝风险综合评估的最高风险区域主要是双柏县,风险指数是0.437,最低风险的区域主要是元谋县,风险指数是0.137.
文摘已有研究表明坝式水电站蓄水对局地气候有重要影响,但目前对梯级水电站蓄水的气候效应还不清楚,尤其是在干热河谷地区。为深入研究梯级水电站对区域气候的影响,以2005~2020年金沙江下游向家坝-溪洛渡梯级水电站所在流域及周边区域38个气象站监测数据为基础,采用ANUSPLIN(Australian National University Spline)模型模拟流域内的气温、降水参数,进而采用PELT(Pruned Exact Linear Time)算法、CV(Coefficient of Variation)和Trend方法探究梯级水库蓄水前后气候的时空变化特征。结果表明:(1)ANUSPLIN模型能较好地模拟气温和降水,气温、降水模拟的相对误差分别介于2.26%~10.62%和9.74%~38.14%之间,且该模型对高温、旱季的模拟效果分别优于低温、雨季。(2)蓄水后流域年均气温的降温幅度较蓄水前有所增大,其中冬、夏季表现为气温增加,春、秋季表现为气温降低;年降水量降低的趋势也较蓄水前极大减缓,并且夏、秋、冬三季的降水量均表现为增加。(3)从突变检验结果来看,蓄水后冬、夏季气温均有突变现象;春、夏、秋季以及年降水量也都发生了突变。(4)蓄水后,流域气温、降水均呈现变异减弱、稳定性增强的特征,且距离库区越近,稳定性越强。研究成果有助于加深理解大型梯级水电开发所引起的气候变化效应。
