ERA5再分析数据适用性初步评估
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摘要
利用山东省及周边地区10个站点的地面和高空观测资料对ERA5再分析资料的适用性进行了初步评估。结果表明:再分析的海平面气压和2 m温度与实况资料的相关性明显优于2 m相对湿度和10 m风场;高空温度和相对湿度在对流层中低层的适用性要好于高层,而位势高度和风场在中高层适用性较好;海平面气压再分析与实况的相关有着最明显的季节变化,2 m温度、2 m相对湿度和10 m风速则在部分站点有较明显的季节变化,而10 m风向的相关系数更多地表现出站点之间的差异,高空要素的适用性,季节和区域差异不明显。另外,对比发现,ERA5的适用性总体上要优于ERA-Interim再分析资料,地面和对流层低层的相对湿度、风场提高更为明显。
The ERA5 reanalysis data is introduced firstly,then the conventional observation data from 10 meteorological stations in Shandong province and its surrounding areas are compared with ERA5 reanalysis for the verification preliminarily. The results are as follows. Mean sea level pressure and 2 m temperature have higher correlation coefficients than 2 m relative humidity and 10 m wind between ERA5 reanalysis and observation. Temperature and relative humidity have better evaluation applicability in the middle and lower level than the upper level troposphere,meanwhile geopotential height and wind agree well with the observed data in the middle and upper level of troposphere. The correlation of mean sea level pressure has the most significant seasonal variation,while 2 m temperature,2 m relative humidity and 10 m wind speed have more significant seasonal variation at partial stations. The correlation of 10 m wind direction has obvious regional differences. The evaluation applicability of upper level elements from ERA5 doesn't have significant seasonal variation and regional differences. ERA5 reanalysis has better evaluation applicability than ERA-Interim reanalysis based on comparisons,especially relative humidity and wind have more improvement in surface and low level of troposphere.
The ERA5 reanalysis data is introduced firstly,then the conventional observation data from 10 meteorological stations in Shandong province and its surrounding areas are compared with ERA5 reanalysis for the verification preliminarily. The results are as follows. Mean sea level pressure and 2 m temperature have higher correlation coefficients than 2 m relative humidity and 10 m wind between ERA5 reanalysis and observation. Temperature and relative humidity have better evaluation applicability in the middle and lower level than the upper level troposphere,meanwhile geopotential height and wind agree well with the observed data in the middle and upper level of troposphere. The correlation of mean sea level pressure has the most significant seasonal variation,while 2 m temperature,2 m relative humidity and 10 m wind speed have more significant seasonal variation at partial stations. The correlation of 10 m wind direction has obvious regional differences. The evaluation applicability of upper level elements from ERA5 doesn't have significant seasonal variation and regional differences. ERA5 reanalysis has better evaluation applicability than ERA-Interim reanalysis based on comparisons,especially relative humidity and wind have more improvement in surface and low level of troposphere.
引文
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[15]朱彦良,凌超,陈洪滨,等.两种再分析资料与RS92探空资料的比较分析[J].气候与环境研究,2012,17(3):381-391.
[16]余君,李庆祥,廖捷,等.中国区域高空三种气温、湿度资料交叉对比[J].气象,2016,42(6):743-755.
[17]滕华超,陈艳春,汤子东.ERA-Interim风速再分析数据在山东省的适用性评估[J].山东气象,2016,36(1):27-31.
[18]陈艳春,王娜,顾伟宗,等.环渤海区域再分析资料地面风速场的适用性对比分析[J].海洋气象学报,2017,37(1):67-72.
[19]范苏丹,盛春岩,曲巧娜,等.利用春季黄渤海沿海大风观测资料评估CFSR风场再分析数据[J].气象科技,2017,45(5):917-924.
[20]Taylor K E.Summarizing multiple aspects of model performance in a single diagram[J].J Geophys Res:Atmospheres,2001,106(D7):7183-7192.
[2]Kanamitsu M,Ebisuzaki W,Woollen J,et al.NCEP-DOE AMIP-II reanalysis(R-2)[J].Bull Amer Meteor Soc,2002,83(11):1631-1643.
[3]Saha S,Moorthi S,Pan H L,et al.The NCEP climate forecast system reanalysis[J].Bull Amer Meteor Soc,2010,91(8):1015-1057.
[4]Rienecker M M,Suarez M J,Gelaro R,et al.MERRA:NASA's modern-era retrospective analysis for research and applications[J].J Climate,2011,24(14):3624-3648.
[5]Onogi K,Tsutsui J,Koide H,et al.The JRA-25 reanalysis[J].J Meteor Soc Japan,2007,85(3):369-432.
[6]Kobayashi S,Ota Y,Harada Y,et al.The JRA-55reanalysis:General specifications and basic characteristics[J].J Meteor Soc Japan Ser i,2015,93(1):5-48.
[7]Uppala S M,Kllberg P W,Simmons A J,et al.The ERA-40 re-analysis[J].Quart J Roy Meteor Soc,2005,131(612):2961-3012.
[8]Uppala S M,Dee D,Kobayashi S,et al.Towards a climate data assimilation system:Status update of ERA-Interim[J].ECMWF Newslett,2008(115):12-18.
[9]Dee D P,Uppala S M,Simmons A J,et al.The ERAInterim reanalysis:configuration and performance of the data assimilation system[J].Quart J Roy Meteor Soc,2011,137(656):553-597.
[10]支星,徐海明.三种再分析资料的高空温度与中国探空温度资料的对比:年平均特征[J].大气科学学报,2013,36(1):77-87.
[11]支星,徐海明.三种再分析资料的高空温度与中国探空温度资料的季节平均特征对比分析[J].高原气象,2013,32(1):97-109.
[12]韦芬芬,汤剑平,王淑瑜.中国区域夏季再分析资料高空变量可信度的检验[J].地球物理学报,2015,58(2):383-397.
[13]袁松,程华,王东勇,等.模式再分析与实际探空资料的对比分析[J].气象科学,2012,32(1):62-67.
[14]王秀明,俞小鼎,朱禾.NCEP再分析资料在强对流环境分析中的应用[J].应用气象学报,2012,23(2):139-146.
[15]朱彦良,凌超,陈洪滨,等.两种再分析资料与RS92探空资料的比较分析[J].气候与环境研究,2012,17(3):381-391.
[16]余君,李庆祥,廖捷,等.中国区域高空三种气温、湿度资料交叉对比[J].气象,2016,42(6):743-755.
[17]滕华超,陈艳春,汤子东.ERA-Interim风速再分析数据在山东省的适用性评估[J].山东气象,2016,36(1):27-31.
[18]陈艳春,王娜,顾伟宗,等.环渤海区域再分析资料地面风速场的适用性对比分析[J].海洋气象学报,2017,37(1):67-72.
[19]范苏丹,盛春岩,曲巧娜,等.利用春季黄渤海沿海大风观测资料评估CFSR风场再分析数据[J].气象科技,2017,45(5):917-924.
[20]Taylor K E.Summarizing multiple aspects of model performance in a single diagram[J].J Geophys Res:Atmospheres,2001,106(D7):7183-7192.