| 四套土壤湿度再分析数据在中国西北东部—华北—江淮地区的适用性研究 |
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| 引用本文： | 邹永成,宋耀明,王志福.四套土壤湿度再分析数据在中国西北东部—华北—江淮地区的适用性研究[J].气候与环境研究,2017,22(5):538-550. |
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| 作者姓名： | 邹永成 宋耀明 王志福 |
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| 作者单位： | 南京信息工程大学气象灾害教育部重点实验室, 南京 210044;南京信息工程大学气候与环境变化国际合作联合实验室, 南京 210044;南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044,南京信息工程大学气象灾害教育部重点实验室, 南京 210044;南京信息工程大学气候与环境变化国际合作联合实验室, 南京 210044;南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044,南京信息工程大学气象灾害教育部重点实验室, 南京 210044;南京信息工程大学气候与环境变化国际合作联合实验室, 南京 210044;南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044 |
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| 基金项目： | 国家自然科学基金项目41005047、41405066，江苏高校优势学科建设工程资助项目（PAPD），高等学校博士点学科专项科研基金项目20113228120002。 |
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| 摘 要： | 基于1992~2010年全国778个农业气象站土壤湿度观测资料、ERA-Interim、JRA55、NCEP-DOE R2和20CR土壤湿度再分析资料,通过平均差值、相关系数、差值标准差、标准差比四个参数,利用Brunke排名方法和EOF(Empirical Orthogonal Function)分析,对四套土壤湿度再分析资料在中国西北东部—华北—江淮区域的适用性进行了分析。主要结论如下:不同季节的平均偏差空间分布上,JRA55资料同观测数据的平均偏差在±0.08m~3 m~(-3)之间,春、夏季西北东部JRA55土壤湿度偏小,ERA-Interim、NCEP-DOE R2、20CR资料较观测数据偏湿,华北南部、江淮地区平均偏差小于西北东部、华北北部。在年际变化上,各个季节ERA-Interim资料同观测资料最为接近,能稳定地再现西北东部、华北、江淮地区土壤湿度干湿变化趋势,反映出重要的旱涝年。整体而言,四套再分析资料中ERA-Interim资料同观测资料接近,JRA55、NCEP-DOE R2资料次之,20CR资料最差。
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| 关 键 词： | 土壤湿度 观测资料 再分析资料 时空分布 |
| 收稿时间： | 2016/9/5 0:00:00 |
| 修稿时间： | 2017/3/8 0:00:00 |
Applicability of Four Soil Moisture Reanalysis Datasets over Eastern Northwest China, North China, and Jianghuai Region |
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| ZOU Yongcheng,SONG Yaoming and WANG Zhifu.Applicability of Four Soil Moisture Reanalysis Datasets over Eastern Northwest China, North China, and Jianghuai Region[J].Climatic and Environmental Research,2017,22(5):538-550. |
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| Authors: | ZOU Yongcheng SONG Yaoming and WANG Zhifu |
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| Institution: | Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044;Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044;Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044,Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044;Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044;Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 and Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044;Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044;Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 |
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| Abstract: | Based on the observational soil moisture data collected at 778 agrometeorological stations in China from 1992 to 2010, ERA-Interim reanalysis soil moisture data, JRA55 reanalysis soil moisture data, NCEP-DOE R2 soil moisture data, and Twentieth Century Reanalysis (20CR) data, four statistical quantities, i.e., mean bias, correlation coefficient, standard deviation of differences, and ratio of standard deviations were calculated first. The applicability of these four reanalysis soil moisture datasets over eastern Northwest China, North China, and Jianghuai region were then investigated based on the four quantities by using the Brunke ranking method and the empirical orthogonal function analysis (EOF). Major conclusions are as follows. In the spring and summer, the JRA55 data is drier in eastern Northwest China with the seasonal average deviations at most stations are between -0.08 m3 m-3 to 0.08 m3 m-3. The soil moisture content in ERA-Interim, NCEP-DOE R2, 20CR is larger than observations; the average deviations in southern North China and Jianghuai region are less than the average deviations in northern North China and eastern Northwest China. For the interannual variability, the ERA-Interim reanalysis data agrees best with the observational data; it also best reproduces the variation tendency of the observed soil moisture in eastern Northwest China, North China and Jianghuai region. Overall, the ERA-Interim reanalysis data shows the best relationship with the observed soil moisture data, followed by the JRA55, NCEP-DOE R2 data, and the 20CR data is the worst. |
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| Keywords: | Soil moisture Observational data Reanalysis data Spatial and temporal distribution |
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