Wind and wave data are essential in climatological and engineering design applications.In this study,data from 15 buoys located throughout the South China Sea(SCS)were used to evaluate the ERA5 wind and wave data.Appl...Wind and wave data are essential in climatological and engineering design applications.In this study,data from 15 buoys located throughout the South China Sea(SCS)were used to evaluate the ERA5 wind and wave data.Applicability assessment are beneficial for gaining insight into the reliability of the ERA5 data in the SCS.The bias range between the ERA5 and observed wind-speed data was-0.78-0.99 m/s.The result indicates that,while the ERA5 wind-speed data underestimation was dominate,the overestimation of such data existed as well.Additionally,the ERA5 data underestimated annual maximum wind-speed by up to 38%,with a correlation coefficient>0.87.The bias between the ERA5 and observed significant wave height(SWH)data varied from-0.24 to 0.28 m.And the ERA5 data showed positive SWH bias,which implied a general underestimation at all locations,except those in the Beibu Gulf and centralwestern SCS,where overestimation was observed.Under extreme conditions,annual maximum SWH in the ERA5 data was underestimated by up to 30%.The correlation coefficients between the ERA5 and observed SWH data at all locations were greater than 0.92,except in the central-western SCS(0.84).The bias between the ERA5 and observed mean wave period(MWP)data varied from-0.74 to 0.57 s.The ERA5 data showed negative MWP biases implying a general overestimation at all locations,except for B1(the Beibu Gulf)and B7(the northeastern SCS),where underestimation was observed.The correlation coefficient between the ERA5 and observed MWP data in the Beibu Gulf was the smallest(0.56),and those of other locations fluctuated within a narrow range from 0.82 to 0.90.The intercomparison indicates that during the analyzed time-span,the ERA5 data generally underestimated wind-speed and SWH,but overestimated MWP.Under non-extreme conditions,the ERA5 wind-speed and SWH data can be used with confidence in most regions of the SCS,except in the central-western SCS.展开更多
背景使用行政管理数据时,确立清晰、适当的慢性病洗脱期时长是正确确定反复就医的慢性病患者发病时点、确定新发病例的基础。目的通过系统文献回顾,综述确定洗脱期时长的方法,以期为我国研究者后续使用行政管理数据识别慢性病新发病例...背景使用行政管理数据时,确立清晰、适当的慢性病洗脱期时长是正确确定反复就医的慢性病患者发病时点、确定新发病例的基础。目的通过系统文献回顾,综述确定洗脱期时长的方法,以期为我国研究者后续使用行政管理数据识别慢性病新发病例时确认洗脱期长短、正确识别新发病例提供思路。方法于2021年10月,系统检索PubMed、Web of Science、EmBase、中国知网、维普中文科技期刊全文数据库、万方知识服务平台,获取有关利用行政管理数据探究慢性病发病、患病情况的文献,检索时限均为建库至2022-10-01。由两名研究者独立筛选文献并提取相关信息,并采用定性研究报告评价标准(SRQR)评价文献方法学质量后,使用描述性分析法总结洗脱期时长的确定方法。结果共纳入26篇文献,纳入文献的SRQR评分均≥15分,方法学质量较好。文献所使用的数据主要来自加拿大、美国、澳大利亚等行政管理数据完整、丰富的国家(地区),聚焦的疾病包括糖尿病、肿瘤、精神分裂症等多种慢性病。研究指出,设定合适的洗脱期时长是准确识别发病病例的基础。目前,文献中确定洗脱期时长的方法主要包括直接限定法、一致性检验法和逆向生存函数法三大类,其中最常用的方法是直接限定法,逆向生存曲线法的使用率相对较低。结论直接限定法、一致性检验法和逆向生存函数法均有相应的优势和局限性,方法的选择标准、判断标准和稳定性有待进一步探究。展开更多
基金Supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2021SP102)the Key Laboratory of Marine Environmental Survey Technology and Application+2 种基金Ministry of Natural Resources(Nos.MESTA-2020-C003,MESTA-2020-C004)the Key Research and Development Project of Guangdong Province(No.2020B1111020003)the Science and Technology Research Project of Jiangxi Provincial Department of Education(No.GJJ200330)。
文摘Wind and wave data are essential in climatological and engineering design applications.In this study,data from 15 buoys located throughout the South China Sea(SCS)were used to evaluate the ERA5 wind and wave data.Applicability assessment are beneficial for gaining insight into the reliability of the ERA5 data in the SCS.The bias range between the ERA5 and observed wind-speed data was-0.78-0.99 m/s.The result indicates that,while the ERA5 wind-speed data underestimation was dominate,the overestimation of such data existed as well.Additionally,the ERA5 data underestimated annual maximum wind-speed by up to 38%,with a correlation coefficient>0.87.The bias between the ERA5 and observed significant wave height(SWH)data varied from-0.24 to 0.28 m.And the ERA5 data showed positive SWH bias,which implied a general underestimation at all locations,except those in the Beibu Gulf and centralwestern SCS,where overestimation was observed.Under extreme conditions,annual maximum SWH in the ERA5 data was underestimated by up to 30%.The correlation coefficients between the ERA5 and observed SWH data at all locations were greater than 0.92,except in the central-western SCS(0.84).The bias between the ERA5 and observed mean wave period(MWP)data varied from-0.74 to 0.57 s.The ERA5 data showed negative MWP biases implying a general overestimation at all locations,except for B1(the Beibu Gulf)and B7(the northeastern SCS),where underestimation was observed.The correlation coefficient between the ERA5 and observed MWP data in the Beibu Gulf was the smallest(0.56),and those of other locations fluctuated within a narrow range from 0.82 to 0.90.The intercomparison indicates that during the analyzed time-span,the ERA5 data generally underestimated wind-speed and SWH,but overestimated MWP.Under non-extreme conditions,the ERA5 wind-speed and SWH data can be used with confidence in most regions of the SCS,except in the central-western SCS.
文摘背景使用行政管理数据时,确立清晰、适当的慢性病洗脱期时长是正确确定反复就医的慢性病患者发病时点、确定新发病例的基础。目的通过系统文献回顾,综述确定洗脱期时长的方法,以期为我国研究者后续使用行政管理数据识别慢性病新发病例时确认洗脱期长短、正确识别新发病例提供思路。方法于2021年10月,系统检索PubMed、Web of Science、EmBase、中国知网、维普中文科技期刊全文数据库、万方知识服务平台,获取有关利用行政管理数据探究慢性病发病、患病情况的文献,检索时限均为建库至2022-10-01。由两名研究者独立筛选文献并提取相关信息,并采用定性研究报告评价标准(SRQR)评价文献方法学质量后,使用描述性分析法总结洗脱期时长的确定方法。结果共纳入26篇文献,纳入文献的SRQR评分均≥15分,方法学质量较好。文献所使用的数据主要来自加拿大、美国、澳大利亚等行政管理数据完整、丰富的国家(地区),聚焦的疾病包括糖尿病、肿瘤、精神分裂症等多种慢性病。研究指出,设定合适的洗脱期时长是准确识别发病病例的基础。目前,文献中确定洗脱期时长的方法主要包括直接限定法、一致性检验法和逆向生存函数法三大类,其中最常用的方法是直接限定法,逆向生存曲线法的使用率相对较低。结论直接限定法、一致性检验法和逆向生存函数法均有相应的优势和局限性,方法的选择标准、判断标准和稳定性有待进一步探究。
