The spatial and temporal distributions of the stable isotopes such as HD16O (or 1H2H16O, or HDO) and H218O in atmospheric water vapor are related to evaporation in source places, vapor condensation during transport, and vapor convergence and divergence, and thus provide useful information for investigation and understanding of the global water cycle. This paper analyzes spatiotemporal variations of the content of isotope HDO (i.e., δD), in atmospheric water vapor, namely, δDv , and the relationship of δDv with atmospheric humidity and temperature at different levels in the troposphere, using the HDO and H2O data retrieved from the Tropospheric Emission Spectrometer (TES) at seven pressure levels from 825 to 100 hPa. The results indicate that δDv has a clear zonal distribution in the troposphere and a good correspondence with atmospheric precipitable water. The results also show that δDv decreases logarithmically with atmospheric pressure and presents a decreasing trend from the equator to high latitudes and from lands to oceans. Seasonal changes of δDv exhibit regional differences. The spatial distribution and seasonal variation of δDv in the low troposphere are consistent with those in the middle troposphere, but opposite situations occur from the upper troposphere to the lower stratosphere. The correlation between δDv and temperature has a similar distribution pattern to the correlation between δDv and precipitable water in the troposphere. The stable isotope HDO in water vapor (δDv ), compared with that in precipitation (δDp ), is of some differences in spatial distribution and seasonal variation, and in its relationship with temperature and humidity, indicating that the impacts of stable isotopic fractionation and atmospheric circulation on the two types of stable isotopes are different.
In this paper, we examine the performance of four isotope incorporated GCMs, i.e., ECHAM4 (University 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 Precipitation) observations. The spatial distributions of mean annual δD and mean annual deuterium excess d in precipitation, and the relationship between δ18 o 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 observations, 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 fractionation) 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.
