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Detecting and Attributing Evapotranspiration Deviations Using Dynamical Downscaling and Convection-Permitting Modeling over the Tibetan Plateau
Water ( IF 3.4 ) Pub Date : 2021-07-30 , DOI: 10.3390/w13152096
Jingyu Dan , Yanhong Gao , Meng Zhang

Terrestrial evapotranspiration (ET) over the Tibetan Plateau (TP) exerts considerable impacts on the local climate and the water cycle. However, the high-altitude, mountainous areas over the TP pose a challenge for field observations. To finely capture its ET characteristics, we employed dynamical downscaling modeling (DDM) with a 28 km resolution and convection-permitting modeling (CPM) with a 4 km resolution in a normal climatology year, 2014. The benchmark data were the surface energy balance–based global land ET dataset (EB). Other compared data included the Global Land-Surface Data Assimilation System (GLDAS) and two reanalysis datasets: ERA-Interim and ERA5. Results showed that EB exhibits a gradient from the southeastern to northwestern TP, which is in line with the precipitation pattern. GLDAS generally reproduces the annual mean magnitude and pattern but poorly represents the seasonal variations. DDM and CPM perform well in the monsoon season but underestimate ET in the non-monsoon season. The two reanalysis datasets greatly overestimate the ET in the monsoon season, but ERA-Interim performs well in the non-monsoon season. All five datasets underestimate the ET over tundra and snow/ice areas, both in the annual and seasonal means. ET deviations are dominated by precipitation deviations in the monsoon season and by surface net radiation deviations in the non-monsoon season.

中文翻译:

使用动态降尺度和允许对流模型检测和归因青藏高原的蒸散偏差

青藏高原(TP)的陆地蒸散量(ET)对当地气候和水循环产生了相当大的影响。然而,高原上的高海拔山区对野外观测提出了挑战。为了精细地捕捉其 ET 特征,我们采用了 28 公里分辨率的动态降尺度建模 (DDM) 和 2014 年正常气候年分辨率为 4 公里的对流允许建模 (CPM)。基准数据是地表能量平衡——基于全球陆地ET数据集(EB)。其他比较数据包括全球地表数据同化系统 (GLDAS) 和两个再分析数据集:ERA-Interim 和 ERA5。结果表明,EB呈现出从青藏高原东南部到西北部的梯度,与降水模式一致。GLDAS 通常再现年平均量级和模式,但不能很好地代表季节性变化。DDM 和 CPM 在季风季节表现良好,但低估了非季风季节的 ET。这两个再分析数据集大大高估了季风季节的 ET,但 ERA-Interim 在非季风季节表现良好。所有五个数据集都低估了苔原和雪/冰区的 ET,无论是年度平均值还是季节性平均值。ET偏差主要由季风季节的降水偏差和非季风季节的地表净辐射偏差主导。但 ERA-Interim 在非季风季节表现良好。所有五个数据集都低估了苔原和雪/冰区的 ET,无论是年度平均值还是季节性平均值。ET偏差主要由季风季节的降水偏差和非季风季节的地表净辐射偏差主导。但 ERA-Interim 在非季风季节表现良好。所有五个数据集都低估了苔原和雪/冰区的 ET,无论是年度平均值还是季节性平均值。ET偏差主要由季风季节的降水偏差和非季风季节的地表净辐射偏差主导。
更新日期:2021-07-30
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