内循环降水率是本地蒸发产生的降水与总降水量的比值,可以表征陆气相互作用的强度。本研究使用准等熵拉格朗日后向轨迹追踪模型(Quasi-isentropic backward trajectory,QIBT),基于全球陆面数据同化产品(Global Land Data Assimilation S...内循环降水率是本地蒸发产生的降水与总降水量的比值,可以表征陆气相互作用的强度。本研究使用准等熵拉格朗日后向轨迹追踪模型(Quasi-isentropic backward trajectory,QIBT),基于全球陆面数据同化产品(Global Land Data Assimilation Systems,GLDAS)的降水和蒸发数据,以及ERA-Interim再分析资料(ERAI),选取降水量与气候平均态相当的2001年,研究了青藏高原内循环降水率。其次,使用2001年ERAI降水和蒸发数据替换GLDAS数据,分析地表数据不确定性对内循环降水率的影响,最后,选取30年降水和蒸发量的极端情况,探讨了极端干湿年对内循环降水率的影响。结果表明,青藏高原内循环降水率东南部小于西北部,年平均内循环降水率为0.42。极端干年大于2001年,极端湿年小于2001年。使用再分析资料的降水和蒸发数据后,内循环降水率减小为0.28,与再分析资料对青藏高原降水量的高估有关。展开更多
In this paper, the applicability of soil-moisture(SM) datasets of GLDAS(Global Land Data Assimilation System) in an alpine region(Tibet Plateau, TP) is investigated. The relations and discrepancies between the GLDAS-N...In this paper, the applicability of soil-moisture(SM) datasets of GLDAS(Global Land Data Assimilation System) in an alpine region(Tibet Plateau, TP) is investigated. The relations and discrepancies between the GLDAS-NOAH SM(0~10cm) and the observations are compared; the possible reasons for errors over the TP are explored. The results show that GLDAS SM biases mainly show up in errors of values in the nonfrozen period(April to October) and changes of SM along with the temperature, especially during the freezing-thawing process in the frozen period(November to March). The biases of GLDAS SM in the nonfrozen period are mainly caused by the GLDAS precipitation-forcing data. The errors of GLDAS SM in the frozen period are speculated to be induced by the freeze-thaw parameterization scheme in the land-surface model.展开更多
文摘内循环降水率是本地蒸发产生的降水与总降水量的比值,可以表征陆气相互作用的强度。本研究使用准等熵拉格朗日后向轨迹追踪模型(Quasi-isentropic backward trajectory,QIBT),基于全球陆面数据同化产品(Global Land Data Assimilation Systems,GLDAS)的降水和蒸发数据,以及ERA-Interim再分析资料(ERAI),选取降水量与气候平均态相当的2001年,研究了青藏高原内循环降水率。其次,使用2001年ERAI降水和蒸发数据替换GLDAS数据,分析地表数据不确定性对内循环降水率的影响,最后,选取30年降水和蒸发量的极端情况,探讨了极端干湿年对内循环降水率的影响。结果表明,青藏高原内循环降水率东南部小于西北部,年平均内循环降水率为0.42。极端干年大于2001年,极端湿年小于2001年。使用再分析资料的降水和蒸发数据后,内循环降水率减小为0.28,与再分析资料对青藏高原降水量的高估有关。
基金supported by the National Science Foundation of China (Nos. 91437217, 41275061, 41471034, and 41661144017)the China National Basic Research Program (2013CBA01800)
文摘In this paper, the applicability of soil-moisture(SM) datasets of GLDAS(Global Land Data Assimilation System) in an alpine region(Tibet Plateau, TP) is investigated. The relations and discrepancies between the GLDAS-NOAH SM(0~10cm) and the observations are compared; the possible reasons for errors over the TP are explored. The results show that GLDAS SM biases mainly show up in errors of values in the nonfrozen period(April to October) and changes of SM along with the temperature, especially during the freezing-thawing process in the frozen period(November to March). The biases of GLDAS SM in the nonfrozen period are mainly caused by the GLDAS precipitation-forcing data. The errors of GLDAS SM in the frozen period are speculated to be induced by the freeze-thaw parameterization scheme in the land-surface model.
