在这份报纸,我们检验四同位素的性能合并 GCM ,即, ECHAM4 (汉堡包的大学), HadCM3 (哈德利中心), GISS E (空格科学的戈达德研究所),和 MUGCM (墨尔本大学),由比较,模型与 GNIP (在 降水的同位素的全球网络)结果观察。在降水的吝啬的年度 D 和吝啬的年度重氢过量 d 的空间分布,和在在降水的 18O 和 D 之间的关系,在东亚上在 GCM 和 GNIP 数据之间被比较。总的来说,四 GCM 在由 GNIP 观察了的降水复制 D 的主要特征。在四个模型之中, ECHAM4 和 GISS E 的结果与 GNIP 更一致观察降水 D 分发。模仿的 d 分布与 GNIP 结果不太一致。这可以显示运动分别过程适当地没在 GCM 的同位素的计划被代表。GCM 为斜坡接近的 MWL (大气的水线) 建模 GNIP 导出 MWL,而是模仿的 MWL 拦截显著地被过高估计。这支持四同位素合并了 GCM,这不能代表运动分别过程很好。以 LMWL (本地大气的水线) ,模仿的 LMWL 斜坡类似于从 GNIP 观察的那些,但是稍微为大多数地点过高估计。总的来说, ECHAM4 在模仿 MWL 和 LMWL 有更好的能力,由 GISS E 列在后面。一些同位素的功能(特别那些与运动分别有关) 并且他们在 GCM 的 parameterizations 可能引起了差异在之间模仿了, GNIP 观察了结果。未来工作被建议根据高分辨率的同位素观察改进同位素的功能 parameterization。
In this paper, we examine the performance of four isotope incorporated GCMs, i.e., ECHAM4 (Univer- sity of Hamburg), HadCM3 (Hadley Centre), GISS E (Goddard Institute of Space Sciences), and MUGCM (Melbourne University), by comparing the model results with GNIP (Global Network of Isotopes in Precip- itation) observations. The spatial distributions of mean annual δD and mean annual deuterium excess d in precipitation, and the relationship between δ18O and δD in precipitation, are compared between GCMs and GNIP data over East Asia. Overall, the four GCMs reproduce major characteristics of δD in precipitation as observed by GNIP. Among the four models, the results of ECHAM4 and GISS E are more consistent with GNIP observed precipitation δD distribution. The simulated d distributions are less consistent with the GNIP results. This may indicate that kinetic fractionation processes are not appropriately represented in the isotopic schemes of GCMs. The GCM modeled MWL (meteoric water line) slopes are close to the GNIP derived MWL, but the simulated MWL intercepts are significantly overestimated. This supports that the four isotope incorporated GCMs may not represent the kinetic fractionation processes well. In term of LMWLs (local meteoric water lines), the simulated LMWL slopes are similar to those from GNIP observa- tions, but slightly overestimated for most locations. Overall, ECHAM4 has better capability in simulating MWL and LMWLs, followed by GISS E. Some isotopic functions (especially those related to kinetic frac- tionation) and their parameterizations in GCMs may have caused the discrepancy between the simulated and GNIP observed results. Future work is recommended to improve isotopic function parameterization on the basis of the high-resolution isotope observations.