The European Center for Medium-Range Weather Forecasts (ECMWF) released its latest reanalysis dataset named ERA5 in 2017. To assess the performance of ERA5 in Antarctica, we compare the near-surface temperature data from ERA5 and ERA-Interim with the measured data from 41 weather stations. ERA5 has a strong linear relationship with monthly observations, and the statistical significant correlation coefficients (p < 0.05) are higher than 0.95 at all stations selected. The performance of ERA5 shows regional differences, and the correlations are high in West Antarctica and low in East Antarctica. Compared with ERA5, ERA-Interim has a slightly higher linear relationship with observations in the Antarctic Peninsula. ERA5 agrees well with the temperature observations in austral spring, with significant correlation coefficients higher than 0.90 and bias lower than 0.70 degrees C. The temperature trend from ERA5 is consistent with that from observations, in which a cooling trend dominates East Antarctica and West Antarctica, while a warming trend exists in the Antarctic Peninsula except during austral summer. Generally, ERA5 can effectively represent the temperature changes in Antarctica and its three subregions. Although ERA5 has bias, ERA5 can play an important role as a powerful tool to explore the climate change in Antarctica with sparse in situ observations.

地表温度综合反映了大气、植被和土壤等因素的能量交换状况,是冻土分布模型和一些寒区陆面过程模式的上边界条件,对多年冻土分布制图和活动层厚度估算有重要意义.为了评估ERAInterim地表温度产品在青藏高原地区的适用性,综合比较了青藏高原69个海拔2 000 m以上气象站1981-2013年地面实际观测值与ERA-Interim之间的差异及其分布状况.结果表明,两种资料的变化趋势一致,但是ERA-Interim地表温度在数值上与实际观测值差别显著,平均偏低7.4℃.原因之一可能是由ERA-Interim再分析资料格点的海拔高度与气象站实际海拔高度差异引起的.根据两种温度产品之间海拔的差异,对ERA-Interim地表温度重新进行模拟,经过模拟后的ERA-Interim地表温度与实际观测值的差值在大部分气象站变小,平均偏高0.4℃.因此,经过重新模拟的ERA-Interim地表温度基本能够反映青藏高原地表温度的真实情况.以模拟后的ERA-Interim地表温度作为地面冻结数模型的输入参数模拟了青藏高原冻土分布,结果表明青藏高原多年冻土区面积为1.14×106km2,季节冻土区面积为1.43×...

It is important to assess the freezing and thawing condition of ground surface for understanding the impacts of frozen ground on surface and subsurface hydrology, the surface energy and moisture balance, ecosystem conservation, and engineering construction on the Qinghai-Tibet Plateau (QTP). However, assessing the changes of ground surface freezing and thawing condition on the QTP still remains a challenge owing to data sparseness and discontinuous observations. The annual ground surface freezing index (GFI) and ground surface thawing index (GTI) could be used to predict changes of the thermal regime of permafrost and can be good indicators of climate change on the QTP, which has important engineering applications. In this study, we first calibrated the reanalysis ground surface temperature (GST) data using the methods of elevation correction on the QTP. After calibration, the quality of reanalysis data has been improved significantly. For the annual time series, the root mean square error decreased from 7.7 to 1.6 degrees C, the absolute value of mean bias error decreased from 7.5 to 0.0 degrees C, and the correlation coefficient increased from 0.62 to 0.86. Second, we estimated the annual and seasonal spatial distributions of GST. The spatial distribution of spring and autumn GST closely resembled the annual mean pattern. The long-term mean GFI and GTI from the calibrated reanalysis dataset were 1322.3 and 2027.9 degrees C/day, respectively. The GFI and GTI were presented as latitude and elevation zonation; it can also be seen that permafrost mostly occurred in the high GFI and low GTI regions. Estimating the GFI and GTI precisely will be utilized to model the permafrost distribution and estimate active layer thickness in the future.