东篱科研大数据发现系统（DRDS）

位置：成果数据库 > 期刊 > 期刊详情页

东亚降水中δ^18O的GCM模拟及其与GNIP实测值的比较

ISSN号：1001-7410
期刊名称：《第四纪研究》
时间：0
分类：P426.612[天文地球—大气科学及气象学]
作者机构：[1]湖南师范大学资源与环境科学学院,长沙410081, [2]Centre for Australian Weather and Climate Research, Melbourne 3001 ,AU
相关基金：国家自然科学基金项目（批准号：41171035和40871094）、湖南省重点学科建设项目（批准号：2011001）和中国科学院青藏高原环境变化与地表过程重点实验室开放课题（批准号：2011004）联合资助

关键词： GCM, GNIP稳定同位素, 模拟, 温度效应, 降水量效应, GCM, GNIP, stable isotope, simulation, temperature effect, amount effect

中文摘要：

本文利用引入稳定同位素循环的ECHAM4，GISSE，HadCM3和MUGCM模式的模拟对东亚降水中平均分δ^18O的空间分布、季节差异以及δ^18O与温度、降水量的关系进行了分析。模拟结果很好地再现了由GNIP实测资料得到δ^18O的的变化特征。在东亚，降水中δ^18O的分布具有明显的纬度效应和高度效应。降水中分的季节差的最大值出现在受冷高压控制的东西伯利亚，最小值出现在受副热带高压控制的西太平洋。在海洋性气团与大陆性气团频繁交绥的中纬度地区，δ^18O季节差相对较弱，但经向变化梯度较大。然而，4个GCM的模拟均显示在中高纬度内陆降水中δ^18O明显偏低。温度效应主要出现在中高纬度和内陆区，纬度越高、越接近内陆，温度效应越强。降水量效应主要出现在中低纬度和季风区，最强的降水量效应出现在低纬度沿海或海岛。然而，4个GCM均给出实际上并不存在的发生在中亚干旱区的降水量效应。这个结果与雨滴在降落过程中重同位素的富集作用有关，但模式对该机制起到了放大作用。GCM和GNIP降水中δ^18O统计量空间分布差异的一个显著特点是，GCM统计量的标准差大于GNIP统计量的标准差。然而，当对单站降水δ^18O时间序列作对比时，GCM模拟值的标准差反而小于GNIP实测值的标准差。

英文摘要：

Using the isotope enabled ECHAM4, GISS E, HadCM3 and MUGCM GCMs, the spatial distribution of mean δ^18O in precipitation,the mean seasonality（JJA-DJF）and correlations of δ^18O in precipitation with temperature and precipitation amount were analyzed,in order to assess modeling abilities of different isotope GCMs and enhance the understanding of how energy and water cycle processes function and quantify their contribution to climate feedbacks. The simulations well reproduced the stable isotopic features by the GNIP observations. Over East Asia, the distribution of δ^18O in precipitation is of marked latitude effect and altitude effect. The largest seasonality of δ^18O in precipitation appears in the eastern Siberia controlled by cold High Pressure, and the lowest one in the western Pacific controlled by the Subtropical High. The comparatively weak seasonality appears in mid-latitudes there oceanic and continental air masses frequently interact. However,four GCMs show all the significantly systematically lower δ^18O in mid-high latitude inlands than the GNIP data. Temperature effect occurs mainly in mid-high latitudes and inlands. The higher the latitude, the closer to inland, and then the stronger the temperature effect. Precipitation effect occurs mainly in mid-low latitudes and monsoon areas with the strongest effect in low-latitude coasts or islands. However,four GCMs give all the virtually non-existent amount effect in the arid zone over Central Asia. The enrichment action of stable isotopes in falling raindrops under cloud base, which is enlarged by these modes, is responsible to such a result. A significant feature of differences between spatial distributions of δ^18O statistics by GCMs simulations and GNIP observations is that the standard deviation of GCMs statistics is greater than that of GNIP statistics. On the contrary, as comparing parallelly time series in each station, the standard deviations of GCMs simulations is smaller than that of GNIP observations.