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降水中稳定同位素信息是研究局地和全球范围水分循环的重要载体,也是运用冰芯、石笋等沉积物来重建古气候的重要依据[1-3].降水过程作为水循环中的主要环节,在地表圈层间物质、能量和信息交换过程中最为活跃,降水中稳定同位素的组成在时空分布上呈现较大的变化,主要是受到水汽蒸发与凝结、降水形式(雨雪雾等)以及大气环流的影响[5-6].水汽相变过程中同位素的组成变化符合Rai-leigh分馏模式,降水较水汽富集重同位素,剩下的水汽中重同位素贫化,随着降水事件的发生,同一云团影响下的降水和水汽中的重同位素逐渐贫化. Graig曾大范围测定世界各区域的雨雪水和河湖水,计算了降水中δ18O-δD相关关系,将其定义为全球大气降水线(GMWL):δD=8δ18O+10[7].因水汽源地和气象条件的差异,局地大气降水线(LMWL):δD=aδ18O+b中,斜率a和截距b会出现不同程度的偏离,斜率表示相变过程的差异,包括云团再蒸发或降雪等;斜率变化受到海-气互相作用的影响[6],在输送过程中会保持平衡[8].随着同位素数据的逐渐丰富,我国众多学者对全国各区域尺度及流域尺度等的降水中稳定同位素陆续开展了完善而系统的研究[9-13],对氢氧同位素的分布特征其影响因素等均取得了一系列重要的认识[14-20].对降水中氢氧同位素的连续跟踪监测并研究其变化规律和机制,是定量恢复重建古气候和研究区域水循环的基础.
1961年起,国际原子能机构(IAEA)和世界气象组织(WMO)共同成立了全球降水稳定同位素监测网络(GNIP),对全球降水中稳定同位素及相关气象数据进行连续监测.目前,全球已建立1 000多个降水取样站点,为研究全球及局部地区大气环流及水循环机理提供了丰富的同位素资料.我国于1983年加入GNIP,黑龙江地区有2个监测站点:哈尔滨站(45.68°N,126.62°E,172 m)和齐齐哈尔站(47.38°N,123.92°E,147 m).基于科研需要,2004年我国以中国生态系统研究网络(CERN)各野外台站为依托,建立了中国大气降水同位素网络(CHNIP)对δ18O和δD进行连续系统的观测,黑龙江地区的站点有三江站(47.35°N,133.3°E,55 m)、海伦站(47.45°N,126.93°E,236 m)[15].本文着重分析黑龙江地区两站点中大气降水中氢氧同位素时空变化特征及与降水量、气温的相关关系,探讨大气降水中氢氧同位素与水汽输送的关系,为中高纬度季风区水汽输送和水汽来源提供理论依据,为古气候重建提供大气降水同位素监测的依据.
Stable Isotope Oxygen-18 (δ18O) in Rainfall and Snowfall in Heilongjiang and Their Relationship with Moisture Transport
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摘要: 根据全球降水中稳定同位素监测网络GNIP我国黑龙江地区监测站点(哈尔滨站和齐齐哈尔站)同位素及气象数据资料, 结合美国气象中心NCEP\NCAR逐月再分析数据, 讨论年际尺度和季节尺度下研究区降水中δ18O、气温、降水量的变化规律, 探讨两站点不同降水类型下δ18O-δD相关性以及同位素效应, 并利用水汽通量模型追踪季节上影响研究区的降水气团差异, 分析水汽输送过程中两站点间的关系.结果表明:①黑龙江地区大气降水中δ18O值总体较低, 并表现出冬季低值和夏季高值的变化; ②两站点不同降水类型δ18O-δD相关性如下:齐齐哈尔站点(δD=7.58δ18O-0.14, R=0.98, n=50), 哈尔滨站点(δD=5.52δ18O-19.42, R=0.83, n=30), 降雪样品较降雨样品具有高的斜率和截距值(7.54, -3.15), 这主要和水汽相变过程中的再蒸发有关.在年际尺度与年内尺度上, 大气降水中δ18O与温度均表现出明显的正相关(δ18O=0.35T-16.26, R=0.53, n=80; δ18O=0.17T-13.09, R=0.27, n=10; δ18O=0.08P-19.34, R=0.42, n=12), 与降水量相关性不显著; ③结合黑龙江地区水汽通量分析发现, 夏季降水受到来自太平洋的暖湿水汽影响, 冬季风期间降水形式以降雪为主, 受到蒙古-西伯利亚高压及西风带水汽和内陆水汽再蒸发的影响.Abstract: Based on the original data from two Chinese GNIP observation stations (in Harbin and Qiqihar) and the reanalysis data of National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP/NCAR) of NOAA, this study investigated the variations of stable isotopes, temperature and precipitation amount in interannual and seasonal patterns, and then explained the amount effect and temperature effect of δ18O in rainfall and snowfall. Using a vapor flux model and wind vector analysis to monitor the precipitation air masses in the two study areas, we analyzed the differences in water vapor transport between Harbin and Qiqihar. The results suggested that variations of δ18O in precipitation in Heilongjiang exhibited a significant seasonal variability and was generally lower than in other monsoon regions. The Local Meteoric Water Line (LMWL) of Qiqihar (δD=7.58δ18O-0.14, R=0.98, n=50) and Harbin (δD=5.52δ18O-19.42, R=0.83, n=30) were calculated. We found that the snowfall samples had a higher slope and intercept than rainfall samples, indicating an isotopic fractionation pattern induced by a non-equilibrium secondary evaporation during the process of falling, which occurred as a result of rayleigh distillation. In interannual and seasonal patterns, δ18O was in a significant positive correlation with temperature (δ18O=0.35T-16.26, R=0.53, n=80;δ18O=0.17T-13.09, R=0.27, n=10;δ18O=0.08P-19.34, R=0.42, n=12) and in an insignificant correlation with precipitation amount. According to the wind vector field and the moisture flux vector analysis, we found that the moisture sources during summer were mainly influenced by warm watervaper of the Pacific Ocean, while the form of precipitation was mainly snowfall during winter seasons, which moisture sources were closely related to the cold wapervaper from the Mongolia and Siberian High, westerly vapor transportation and local re-evaporation.
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Key words:
- precipitation /
- δ18O /
- δD /
- moisture transport /
- Heilongjiang .
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表 1 不同降水类型下δD-δ18O相关性分析
样品类型 样品数量 斜率 截距 R2 哈尔滨站降雨 28 5.38 -20.58 0.82 齐齐哈尔站降雨 32 7.18 -3.75 0.96 齐齐哈尔站降雪 16 7.54 -3.15 0.96 -
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