The spatial and temporal distributions of the stable isotopes such as HD16O （or 1H2H16O, or HDO） and H2 18O 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 iso- tope HDO （i.e., 5D）, 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. Sea- sonal 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, in- dicating that the impacts of stable isotopic fractionation and atmospheric circulation on the two types of stable isotopes are different.
将稳定同位素作为诊断工具引入CLM(Community Land Model),并对巴西马瑙斯站在平衡年的不同水体中稳定同位素的季节变化进行了模拟和分析,旨在通过对陆面过程中稳定水同位素的模拟试验,了解陆面过程中稳定水同位素的循环过程,以补充观测资料之缺乏,并最终利用稳定同位素的变化特性进行水文气象过程的预测.模拟的结果表明,降水、水汽和地表径流中的δ18O均存在显著的季节性变化,并与相应的水量存在反比关系.与IAEA/WMO监测数据相比,CLM的模拟基本上揭示了降水中δ18O的实际分布特征.另外,模拟的月降水量与月δ18O之间的降水量效应以及大气水线(MWL)均接近实际状况.这在一定程度上说明,引入稳定同位素效应的CLM的模拟是合理的.但也看到,模拟的降水中δ18O的季节差异明显小于实际值,降水中δ18O的季节变化展示了赤道地区理想的双峰型特点,但实际的分布却是单峰型.这些差异的产生可能与CLM本身的模拟能力有关,也可能与强迫资料的准确性有关.
Using the isotope enabled ECHAM4, GISS E and HadCM3 GCMs, the spatial distribution of mean 6180 in precipitation, mean seasonality and the correlations of 6180 in precipitation with temperature and precipitation amount are analyzed. The simulated results are in agreement with stable isotopic features by GNIP observations. Over East Asia. the distribution of ~180 in precipita- tion is of marked latitude effect and altitude effect. The latitude effect is covered by the continent effect in some regions. The larg- est seasonality of^lSo in precipitation appears in eastern Siberia controlled by cold high pressure, and the smallest seasonality is in the western Pacific controlled by the subtropical high. Relatively weak seasonality appears in middle latitudes where oceanic and continental air masses frequently interact. However, three GCMs show significant systematic lower ~180 for inland mid-high lati- tudes than GNIP data, which is related to the used isotopic scheme in GCMs. Temperature effect occurs mainly in inland mid-high latitudes. The higher the latitude and the closer the distance to inland is, then the stronger the temperature effect. Amount effect occurs mainly in low-mid latitudes and monsoon areas, with the strongest effect in low-latitude coasts or islands. However, three GCMs provide virtually non-existent amount effect in arid regions over Central Asia. The enrichment action of stable isotopes in falling raindrops under a cloud base, which is enlarged by these modes, is responsible for such a result. A significant difference between spatial distributions of δ^18O statistics by GCMs simulations and by GNIP observations is that the standard deviation of GCMs statistics is greater than that of GNIP statistics. In contrast, by comparing parallel time series at a single station, the standard deviations of GCMs simulations are smaller than that of GNIP observations.
根据2010年1月～2011年2月长沙地区日降水中δD、δ18 O资料,分析了该地区天气尺度下降水中δD、δ18 O变化特征。结果表明:在天气尺度下长沙地区大气降水中δ18 O与降水量、水汽压、温度及相对湿度之间存在显著的负相关关系,表明该地区降水中δ18 O的变化具有显著的降水量效应、湿度效应及反温度效应。长沙地区的大气降水线为:δD=8.38δ18 O+17.3,该方程与GNIP(Globe Network of Isotopes in Precipitation)提供的长沙在月尺度下所得到的大气水线方程的斜率和截距相近,但斜率和截距都比GMWL(Globe Meteoric Water Line)偏大,说明该地区具有湿润多雨的气候特点。研究结果对揭示东亚季风区稳定同位素变化特征以及古气候的解释具有重要意义。
