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| 1 | ERA-Interim气温数据在中国区域的适用性评估显示文摘运用中国756个观测站点的逐月平均气温数据,对比分析了ERA-Interim再分析资料的误差。结果发现:ERA—Interim再分析资料能够很好地反映观测值的年际变化,相关性达到0.955~0.995。ERA-Interim在580个站点的冷偏差或暖偏差小于1℃,占站点总数的76.7%,可信度较高。64个站点的冷偏差或暖偏差大于5℃,可信度较低。ERA—Interim在东部地区的暖偏差多于西部地区,冷偏差的高值主要集中在西部地区的高海拔站点。海拔低于200m的站点偏差最小,适用性好,多数海拔3000m以上的站点呈现较大冷偏差,适用性较差。通过回归分析发现,观测站点与ERA-Interim格点的高度差是导致误差的主要原因,因此通过高程校正能够有效降低误差,提高ERA—Interim适用性。 | 高路 郝璐 | 2014 | 亚热带资源与环境学报2014，9，2： | 38 |
| 2 | Evaluation of ERA-Interim Monthly Temperature Data over the Tibetan Plateau显示文摘In this study, surface air temperature from 75 meteorological stations above 3000 m on the Tibetan Plateau are applied for evaluation of the European Centre for Medium-Range Weather Forecasts(ECMWF) third-generation reanalysis product ERA-Interim in the period of 1979-2010. High correlations ranging from 0.973 to 0.999 indicate that ERA-Interim could capture the annual cycle very well. However, an average root-meansquare error(rmse) of 3.7°C for all stations reveals that ERA-Interim could not be applied directly for the individual sites. The biases can be mainly attributed to the altitude differences between ERA-Interim grid points and stations. An elevation correction method based on monthly lapse rates is limited to reduce the bias for all stations. Generally, ERA-Interim captured the Plateau-Wide annual and seasonal climatologies very well. The spatial variance is highly related to the topographic features of the TP. The temperature increases significantly(10°C- 15°C) from the western to the eastern Tibetan Plateau for all seasons, in particular during winter and summer. A significant warming trend(0.49°C/decade) is found over the entire Tibetan Plateau using station time series from 1979-2010. ERA-Interim captures the annual warming trend with an increase rate of 0.33°C /decade very well. The observation data and ERA-Interim data both showed the largest warming trends in winter with values of 0.67°C/decade and 0.41°C/decade, respectively. We conclude that in general ERA-Interim captures the temperature trends very well and ERA-Interim is reliable for climate change investigation over the Tibetan Plateau under the premise of cautious interpretation. | GAO Lu HAO Lu CHEN Xing-wei | 2014 | Journal of Mountain Science2014，11，5： | 13 |
| 3 | ERA-Interim和GHCN-CAM再分析气温数据在天山山区的适应性分析显示文摘天山山区是新疆主要河流的发源地,对该区域再分析气温数据进行适应性分析具有重要的研究意义,气温观测数据由于受到太阳辐射、海拔、大气环流和传感器角度等因素的影响,导致诸多误差;在其应用之前需要验证,尤其在海拔差异较大的天山山区。为验证ERA-Interim和GHCN-CAM两种再分析气温数据在天山山区的适应性,本文在数据预处理的基础上,利用45个气象站点日平均气温数据分别计算偏差(BIAS)、相关系数(R)、均方根误差(RMSE)等统计指标,并从不同海拔、偏差的空间分布上对天山山区1984-2016年ERA-Interim和GHCN-CAM逐月平均气温数据进行了适应性分析。结果表明:(1) GHCN-CAM(R=0. 94;BIAS=0. 55℃;RMSE=4. 08℃)气温值在天山山区的适应性强于ERA(R=0. 95;BIAS=2. 35℃;RMSE=4. 21℃)。(2)在气温的年内变化上,两种再分析数据值均低于观测值,表现为低估。(3)在季节尺度上,冬季(12月、1月和2月)表现为冷偏差,其他季节暖偏差。春秋两季模拟精度比夏冬两季高。(4)在1500~2000 m地区气温的模拟最好。从偏差的空间分布来看,天山中部、东部的再分析数据比天山南、北部能更好的反映气温的空间分布特征。山区地形复杂度和气象站点的不均匀是影响再分析数据精度的主要因素。 | 海日古丽·纳麦提 玉素甫江·如素力 玛地尼亚提·地里夏提 肉克亚木·艾克木 | 2019 | 山地学报2019，37，4： | 4 |
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