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近57年我国气温格点数据集的建立和质量评估
Establishment and Assessment of the Grid Air Temperature Data Sets in China for the Past 57 Years
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摘要: 在普通克里金插值方法的基础上, 引入高程因子并充分考虑插值的边界效应, 对1951:2007年我国气温站点资料进行空间结构分析和插值, 得到我国地面气温日、月、年平均值1°×1°格点数据集。数据集的质量评估结果表明:高程在我国区域气温空间结构分析和插值中起着重要作用, 高程资料的引入有效提高了大部分高山地区的插值效果; 相比站点资料, 所建立的格点数据集在描述我国年平均气温以及季节平均气温分布时更为合理, 突出了温度场的大尺度特征; 数据集反映出了我国年平均气温变化趋势主要的空间差异; 数据集较好地反映了我国年平均气温变化状况, 1951- 2007年气温变暖幅度约为1.6 ℃, 增温速率0.28 ℃/10 a, 比全球或半球同期平均增温速率明显偏高, 且气温增暖主要发生在最近的20余年之内。另外, 格点数据集显示, 1998—2007年是1951年以来最暖的10年, 其中2006年全国平均气温距平接近2000年之前的历史最高年份1998年, 而2007年全国平均气温距平值超过1998年, 达到1951年以来的历史最高值1.3 ℃, 为最暖的一年。Abstract: Temperature data from meteorological stations in China for the past 57 years are interpolated by introducing digital elevation model(DEM) and taking the edge effect of interpolations into consideration on the basis of the ordinary Kriging method. Using this method, the daily, monthly and annual mean data sets of the grid-based temperature in China with the resolution of 1°latitude by 1°longitude are obtained. The results of the grid data sets quality assessment show that DEM has an apparent effect on the spatial structure of temperatures and plays an important role on interpolations. Great improvements on the spatial interpolation in alpine spots are achieved after exploiting DEM. Compared with station data, grid data sets are more plausible to depict the annual and seasonal mean temperature distribution. The grid data sets can well simulate the spatial difference of the annual mean temperature trends in China. The grid data sets can also well demonstrate the change of annual mean temperature in China which as a whole rises by about 1.6 ℃ for 1951—2007, with a warming rate of about 0.28 ℃/10 a. The warming in the later half 20th century is more rapid than the average values of the world and the Northern Hemisphere. The most evident warming occurs in the past over 20 years. The grid data sets also indicate that: Period from 1998 to 2007 is a decade when the annual mean temperature is the highest since 1951, amongst which the annual mean temperature anomaly in 2006 is close to that in 1998 with the highest value before 2000, and the annual mean temperature anomaly in 2007 with a value of 1.3 ℃ beyond that in 1998, is the highest since 1951.
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图 1 1951年1月--2007年12月GHCN资料补充前后台站数量对比
Fig. 1 The station number variation after using GHCN in China from January 1951 to December 2007
图 2 高程订正前后1980年7月我国地面月平均气温空间结构及试验变异函数拟合效果对比
（a）原始站点温度，（b）高程订正后的温度
Fig. 2 Original and adjusted spatial structure of the monthly mean temperatures over China in July 1980
图 3 1961-2007年560个台站年平均气温观测资料序列与其临近格点序列的相关系数空间分布
Fig. 3 Correlation coefficients of the annual mean temperature in 560 stations with that in its adjacent grid point during 1961-2007
图 4 1971-2000年我国年平均气温空间分布 (单位:℃; 底图不同颜色代表数字高程)
(a) 站点资料二维插值, (b) 格点数据集
Fig. 4 Spatial distribution of the annual mean temperature over China during 1971-2000 (unit:℃; the different colors denote DEM)
(a) station data, (b) grid data sets
图 5 1961-2005年我国年平均气温变化趋势的空间分布 (单位:℃/ 10 a)
(a) 站点资料二维插值, (b) 格点数据集
Fig. 5 Trends in annual mean temperature over China during 1961-2005 (unit:℃/ 10 a)
(a) station data, (b) grid data sets
图 6 1961-2005年我国1月和7月平均气温趋势 (单位:℃/ 10 a)
(a)1月站点资料二维插值, (b)1月格点数据集, (c)7月站点资料二维插值, (d)7月格点数据集
Fig. 6 Trends in monthly mean temperature over China in January and July during 1961-2005 (unit:℃/ 10 a)
(a) station data in January, (b) grid data sets in January, (c) station data in July, (d) grid data sets in July
图 7 1951-2007年全国 (a) 及我国东部地区 (b) 年平均气温距平时间序列
Fig. 7 The time series of the annual mean temperature anomaly over China (a) and the east part of China (b) during 1951-2007
表 1 6种插值方法对近10年全国7月温度场的空间插值交叉验证结果
Table 1 The spatial interpolation effect of ordinary Kriging and five other methods over China in July during 1998-2007
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