三种再分析资料的高空温度与中国探空温度资料的对比分析
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摘要
本文利用1980-2008年中国105站探空资料和NCEP/NCAR、ERA和JRA三种再分析资料,采用多种统计分析方法,对再分析资料的年平均和季节平均的高空温度在中国区域的可信度进行了对比分析,同时根据REOF分区对中国区域的I区(东北)和V区(西北)挑选代表站进行了分析,得到了以下主要结论：
(1)在数值上,三种再分析资料温度场普遍小于探空资料温度场。就全年而言，NCEP资料在对流层上层更为接近,ERA和JRA资料在对流层中下层与探空资料更为接近。就季节而言,秋季的反映能力稍高于其它季节。
(2)在描述高空温度的年际变化和长期变化趋势方面,NCEP资料在我国南方的对流层上层描述较好,ERA资料在我国北方的对流层上层描述较好,而三种再分析资料在对流层中下层的再现能力相当。
(3)在时空变化特征方面,就全年而言,探空资料的年代际变化特征表现为对流层中下层和对流层上层温度反位相变化的特征,而年际变化特征则表现出南北反位相变化特征。NCEP和ERA资料能较好地表现我国高空温度的年代际变化特征,而ERA和JRA资料则能较好地表现我国高空温度的年际变化特征。就季节而言,三种再分析资料的第一模态分布在不同季节差异较大,而第二模态的分布在各个季节则较为一致。
(4)用REOF进行重新分区后,可以用哈尔滨站和库尔勒站作为工区(东北)和V区(西北)的代表站,来研究这两个区域的三种再分析资料和探空资料的变化特征。从气候平均的角度,对流层中低层三种再分析资料与探空资料的的均方根误差较小,高层较大；JRA资料相比于探空资料的均方根误差较小,NCEP资料较大；冬季的均方根误差较小,夏季较大,V区的均方根误差普遍大于I区。从年际变化的角度,对于I区,三种再分析资料在低层的反映程度明显好于高层,冬春季的反映程度明显好于夏季,JRA资料的反映程度明显好于其它资料。对于V区,相比于I区,三种再分析资料与探空资料的差值普遍较大。各层次再分析资料与探空资料的偏差并不特别明显的变化,其余特征和I区类似。从长期变化趋势的角度,三种再分析资料在对流层低层都反映得比较好,对于I区,在300hPa以上,NCEP资料能更好地反映探空资料的降温趋势。对于V区,在200hPa以上,JRA资料能更好地反映探空资料的降温趋势。
Based on radiosonde dataset from105stations in China, NCEP/NCAR reanalysis dataset, ERA reanalysis dataset, JRA reanalysis dataset in1980-2008, a study is performed of reliability of atmospheric temperature of reanalysis datasets based on the annual and monthly mean in China by means of many kinds of statistical analysis technique. At the same time, we select the representative station in area I (northeast) and V (northwest) in China to study based on the divided method of REOF. The main conclusions are as follows:
(1) In numerical aspects, three reanalysis datasets are lower than the radiosonde dataset, NCEP dataset is much closer to observed dataset in upper troposphere while ERA and JRA datasets are closer in middle and lower troposphere. So far as seasonal mean, the reliability in autumn is much more than other seasons.
(2) In terms of annual and interdecadal trend of atmospheric temperature, ERA dataset has higher ability to reproduce those trend in the north region of upper troposphere while NCEP dataset is better in the south region of upper troposphere. Three reanalysis datasets have comparable ability to show the trend in middle and lower troposphere.
(3) In the aspect of spatial and temporal variation characteristics, So far as annual mean, the interdecadal variation character of radiosonde dataset reveals the opposite phase change between middle and low troposphere and upper troposphere while the annual variation character displays the feature of the opposite phase change between north and south of the whole layer temperature. NCEP and ERA datasets can preferably perform the feature of interdecadal variance while ERA and JRA datasets can reveal the characteristic of annual variance well. So far as seasonal mean, there are quite differences of three reanalysis datasets in the distribution of the first mode while the second mode correlates quite the same with each other in four seasons.
(4) After redivided by the method of REOF, we can use the station of Haerbin and Korla as the representative station in area I (northeast) and V (northwest), to find out the variation character of three reanalysis datasets and radiosonde dataset in these areas. In the aspect of climate mean, the root-mean-square error is much lower in middle and low troposphere then in upper troposphere; Compared to radiosonde dataset, the root-mean-square error of JRA datasets is low while NCEP datasets is high; The root-mean-square error in winter is low while it is high in summer; The root-mean-square error in area V is higher than area I. From the perspective of annual variance, as for area I, the quality of three reanalysis dataset in low levels is obviously better then in high levels, and more reliable in winter and spring than in summer. The reliability of JRA dataset is much better than other datasets. As for area V, when compared to area I, the difference between three reanalysis dataset and radiosonde dataset is much bigger. There are not apparent variation in the difference between three reanalysis dataset and radiosonde dataset, and the other character is quite the same as area I. In the aspect of long-term trend, three reanalysis dataset both show the better conditions in the low troposphere. As for area I, NCEP dataset can reveals the cooling trend of radiosonde dataset better when above300hPa. As for area V, JRA dataset can reveals the cooling trend of radiosonde dataset better when above200hPa.
(1)在数值上,三种再分析资料温度场普遍小于探空资料温度场。就全年而言，NCEP资料在对流层上层更为接近,ERA和JRA资料在对流层中下层与探空资料更为接近。就季节而言,秋季的反映能力稍高于其它季节。
(2)在描述高空温度的年际变化和长期变化趋势方面,NCEP资料在我国南方的对流层上层描述较好,ERA资料在我国北方的对流层上层描述较好,而三种再分析资料在对流层中下层的再现能力相当。
(3)在时空变化特征方面,就全年而言,探空资料的年代际变化特征表现为对流层中下层和对流层上层温度反位相变化的特征,而年际变化特征则表现出南北反位相变化特征。NCEP和ERA资料能较好地表现我国高空温度的年代际变化特征,而ERA和JRA资料则能较好地表现我国高空温度的年际变化特征。就季节而言,三种再分析资料的第一模态分布在不同季节差异较大,而第二模态的分布在各个季节则较为一致。
(4)用REOF进行重新分区后,可以用哈尔滨站和库尔勒站作为工区(东北)和V区(西北)的代表站,来研究这两个区域的三种再分析资料和探空资料的变化特征。从气候平均的角度,对流层中低层三种再分析资料与探空资料的的均方根误差较小,高层较大；JRA资料相比于探空资料的均方根误差较小,NCEP资料较大；冬季的均方根误差较小,夏季较大,V区的均方根误差普遍大于I区。从年际变化的角度,对于I区,三种再分析资料在低层的反映程度明显好于高层,冬春季的反映程度明显好于夏季,JRA资料的反映程度明显好于其它资料。对于V区,相比于I区,三种再分析资料与探空资料的差值普遍较大。各层次再分析资料与探空资料的偏差并不特别明显的变化,其余特征和I区类似。从长期变化趋势的角度,三种再分析资料在对流层低层都反映得比较好,对于I区,在300hPa以上,NCEP资料能更好地反映探空资料的降温趋势。对于V区,在200hPa以上,JRA资料能更好地反映探空资料的降温趋势。
Based on radiosonde dataset from105stations in China, NCEP/NCAR reanalysis dataset, ERA reanalysis dataset, JRA reanalysis dataset in1980-2008, a study is performed of reliability of atmospheric temperature of reanalysis datasets based on the annual and monthly mean in China by means of many kinds of statistical analysis technique. At the same time, we select the representative station in area I (northeast) and V (northwest) in China to study based on the divided method of REOF. The main conclusions are as follows:
(1) In numerical aspects, three reanalysis datasets are lower than the radiosonde dataset, NCEP dataset is much closer to observed dataset in upper troposphere while ERA and JRA datasets are closer in middle and lower troposphere. So far as seasonal mean, the reliability in autumn is much more than other seasons.
(2) In terms of annual and interdecadal trend of atmospheric temperature, ERA dataset has higher ability to reproduce those trend in the north region of upper troposphere while NCEP dataset is better in the south region of upper troposphere. Three reanalysis datasets have comparable ability to show the trend in middle and lower troposphere.
(3) In the aspect of spatial and temporal variation characteristics, So far as annual mean, the interdecadal variation character of radiosonde dataset reveals the opposite phase change between middle and low troposphere and upper troposphere while the annual variation character displays the feature of the opposite phase change between north and south of the whole layer temperature. NCEP and ERA datasets can preferably perform the feature of interdecadal variance while ERA and JRA datasets can reveal the characteristic of annual variance well. So far as seasonal mean, there are quite differences of three reanalysis datasets in the distribution of the first mode while the second mode correlates quite the same with each other in four seasons.
(4) After redivided by the method of REOF, we can use the station of Haerbin and Korla as the representative station in area I (northeast) and V (northwest), to find out the variation character of three reanalysis datasets and radiosonde dataset in these areas. In the aspect of climate mean, the root-mean-square error is much lower in middle and low troposphere then in upper troposphere; Compared to radiosonde dataset, the root-mean-square error of JRA datasets is low while NCEP datasets is high; The root-mean-square error in winter is low while it is high in summer; The root-mean-square error in area V is higher than area I. From the perspective of annual variance, as for area I, the quality of three reanalysis dataset in low levels is obviously better then in high levels, and more reliable in winter and spring than in summer. The reliability of JRA dataset is much better than other datasets. As for area V, when compared to area I, the difference between three reanalysis dataset and radiosonde dataset is much bigger. There are not apparent variation in the difference between three reanalysis dataset and radiosonde dataset, and the other character is quite the same as area I. In the aspect of long-term trend, three reanalysis dataset both show the better conditions in the low troposphere. As for area I, NCEP dataset can reveals the cooling trend of radiosonde dataset better when above300hPa. As for area V, JRA dataset can reveals the cooling trend of radiosonde dataset better when above200hPa.
引文
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[3]Kistler R, Kalnay E, CollinsW, et al. The NCEP-NCAR 50-year reanalysis:Monthly means CD-ROM and documentation. Bulletin of the American Meteorological Society,2001,82: 247-267.
[4]Kanamitsu M, Ebisuzaki W, Woollen J, et al. NCEP/DOE AMIP-II Reanalysis(R-2). Bulletin of the American Meteorological Society,2002,83:1631-1643.
[5]Takacs L L, Molod A, Wang T. Documentation of the Goddard Earth OBServing System (GEOS) GenERA1 CirculationModel-Version 1. NASA Technical Memorandum,104606, Vol.1, Goddard Space Flight Center Greenbelt, MD,1994.
[6]Schubert S D, Park C K, Wu C Y, et al. A multi-year assimilation with the GEOS-1 system: Overview and results. Suarea M J, ed. NASA Technical Report Series on Global Modelling and Data Assimilation,1995:6.
[7]Gibs on J K, Kallberg P, Uppala S, et al. ERA Description. ECMWF ReAnalysis Project Report Series No.1. European Centre for Medium-range Weather Forecasts, Reading, UK, 1997.
[8]SimmonsA J, Gibson J K. The ERA Project Plan. ECMWF ReAnalysis Project Report Series No.1,2000.
[9]Uppala SM, Kallberg PW, Simmons A J, et al. The ERA re-analysis. Quarterly Journal of the RoyalMeteorological Society,2005,131:2961-3012.
[10]Onogi K, Tsutsui J, Koide H, et al. The JRA reanalysis Journal of the Meteorological Society of Japan,2007,85(3):369-432.
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