大气水汽氢氧同位素观测研究进展——理论基础、观测方法和模拟

doi:10.11820/dlkxjz.2015.03.009

Abstract

Abstract:

Stable isotopes of atmospheric water vapor have been used as informational tracer in understanding global earth surface processes and hydrological cycle. Based on the physical process of water transportation, this article introduces the theoretical basis of water vapor isotopic fractionation, including equilibrant and non-equilibrant fractionation such as evaporation process, transportation, and considerations, and reviews traditional measurement methods and new techniques such as laser spectrometer and satellite remote sensing infrared spectrometer. It shows that real-time and remote sensing observations have become useful methods for water vapor isotope research. The paper also summarizes the main progresses on water vapor isotopic theory and the general/regional climate models enabled with isotopic module. Iso-GCM/RCM has advantages in global and regional climate process research and environmental information reconstruction, and will be widely used in future research. Emerging focuses of atmospheric isotope research are high spatiotemporal resolution measurement and application of new indices such as 17O-excess and Iso-GCM/RCM.

Key words: atmospheric water vapor isotope, isotope fractionation, water vapor isotope observation, water cycle

Jingfeng LIU, Minghu DING, Cunde XIAO. Review on atmospheric water vapor isotopic observation and research: theory, method and modeling[J].PROGRESS IN GEOGRAPHY, 2015, 34(3): 340-353.

Figures/Tables 7

Tab.1

Kinetic fractionation effect of water isotopes during evaporation

动力分馏	引证
1 水汽分子扩散
$ε k = D D I - 1 × 103$	(Merlivat, 1978)
$D D I = 1.0251$ (²H); $D D I = 1.0285$ (¹⁸O)
$ε k$ =25.1(‰) (²H); $ε k$ =28.5(‰) (¹⁸O)
式中： $ε k$ 表示某反应系统中生成物的同位素组成相对于反应物中同位素组成的富集程度;D、D^I为空气中H₂O和¹H²HO(H₂¹⁸O)的分子扩散系数。
D(H₂¹⁶O)/D(HD¹⁶O)=1.0164; D(H₂¹⁶O)/D(H₂¹⁸O)=1.0319	(Cappa et al, 2003)
$ε k$ =16.4/‰(²H); $ε k$ =31.9/‰(¹⁸O)
式中： $ε k$ 表示某反应系统中生成物的同位素组成相对于反应物中同位素组成的富集程度;扩散系数D表示一种物质在另一种介质（或真空）内的运动过程中,同一元素的不同同位素分子的扩散速度的差异。
2 陆地环境风洞实验—分馏富集系数 $Δε$	(Vogt, 1976)
$Δε = 12.4 (1 - h d)$ (‰) (²H)
$Δε = 14.3 (1 - h d)$ (‰) (¹⁸O)
式中：h_d为蒸发表面以上10 m处相对湿度/%。
3 海洋环境	(Merlivat et al, 1979)
$ε k = k k - 1 1 - h 10$ , $ε k$ /‰
无风海表（1<u<7 m/s）: $k 18$ =6.2‰; $k D$ =5.5‰
风浪海表（u>7 m/s）: $k 18$ =3.5‰; $k D$ =3.1‰
式中： $k$ 为动力分馏常数; $h 10$ 为10 m高处大气相对湿度;u为10 m高处风速;k₁₈和 $k D$ 分别表示¹⁸O和²H原子的化学反应平衡常数。

Tab.1

Tab.2

Tab.3

Tab.4

Fig.1

Tab.5

Tab.6

Classification of simulation methods of water vapor isotopic modeling

模型方法	优点	缺陷
瑞利分馏模型或混合相分馏模型	能反映核心的微物理过程;能对水循环的各个传输环节的分馏(蒸发、过饱和)进行敏感性验证	是基于对初始条件的假设,如封闭方程模型或嵌入同位素模块的全球环流模型AGCM的水汽初始场,所以与实际有误差;不能很好的模拟对流过程
嵌入水体稳定同位素模拟的大气环流模型(AGCM)	环流模型本身与同位素分馏过程具有一致性和兼容性;能对气象条件和分馏过程进行耦合;基于不同的气候驱动条件可探究不同空间因子关系在时间上的稳定性	在某些特殊区域如极地可能造成气候学模拟的变差;由于模型分辨率和某些参数如下降风、边界层过程、平流层过程和云层微物理等的参数化误差可能造成缺陷;难以区分不同过程的相对重要性(如水汽源区、传输过程以及凝结等)
利用大气再分析资料辨识不同降水/降雪事件的的天气条件特征以及后向气团轨迹模型	基于实测气象数据,具有实际意义的天气学框架;利用同位素组分有可能将降水与相关的天气系统的气团联系起来	难以区分不同过程如水汽源区、传输轨迹、凝结等对最终降水同位素组分的相对重要性;利用后向轨迹也很难确定水汽源区
利用AGCM水汽分布根据后向轨迹进行简单的同位素模型计算	能够确定气团源区对最终水汽同位素组成的影响;基于再分析资料,因此避免了凝结温度的假设引起的误差	Iso-AGCM模型中水汽同位素组成分布和再分析资料后向轨迹之间可能存在不一致;另外对对流过程的描述有欠缺
再分析资料驱动的Iso-AGCM模型	可利用与实测资料一致的动力驱动模拟结果进行分析	不能区分水汽凝结和凝华过程;不能对浅薄逆温层进行有效处理;驱动场异常格点造成模拟误差;对云微物理结构的处理有欠缺
再分析资料驱动的区域气候模型	较好的模拟了降水相关的主要过程：云团微物理过程、边界层条件以及后沉降过程等	难以捕捉水气传输路径;难以区分不同过程如水汽源区、传输轨迹、凝结等对最终降水同位素组分的影响大小
详细模拟稳定同位素的区域大气模型	大气动力学与水体同位素分馏的一致性和兼容性	目前还不能用于极区

Tab.6

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水汽收集方法	原理	优点	缺陷
液氮冷阱冷凝	液氮等冷凝剂约-70℃环境下将水汽分子完全冷却凝结	足够低的温度使水分子完全凝结	需要持续供给液氮;冷阱极高的气流(>1 L·m^-1)造成额外的分馏或冰晶流失;极端制冷剂造成CO₂和O₂凝结
Peltier制冷法	半导体制冷产生约-50℃的冷凝温度	避免其他气体的过冷凝结	冷凝温度不够低造成凝结水量少,不能满足质谱仪分析的精度要求;有可能造成重同位素的富集,而富集校正又需要精确测量采样时的气流量、凝结温度、气温及相对湿度等,造成误差累积放大
干燥剂脱水法	分子筛选吸附	精度高	吸湿性干燥剂含O₂,会引起同位素交换;需要做非饱和-饱和状态的校正恢复;需要集成以适应野外作业
Flask真空采样瓶	真空直接采样	直接取样,没有冷凝等造成的信息失真	采集量少,可用于HDO ,但不能满足¹⁸O测量剂量

激光光谱分析类型	原理	代表性仪器	应用研究
Off-Axis ICOS离轴积分振腔输出光谱技术	将激光谐振腔与气体测量室合为一体,激光在谐振腔两端的反射镜中反复震荡,其中少部分透过反射镜到达检测器。进入检测室的激光必先在待测气体中反复通过上万次才能到达检测器,相当于增加了测量室的厚度,使水汽吸收信号明显增强,来检测含量极低的水汽中²H和¹⁸O。	LGRinc. 908-00040003	Steen-Larsen et al, 2011; Steen-Larsen et al, 2013
CRDS振腔衰荡光谱技术	激光进入谐振腔后透过待测水汽在镜片间反射震荡,强度不断增加,其中少部分光透过镜片到达检测器。当检测器中的光信号达到一定的稳定值后,停止照射激光,体系在检测器方向的漏光将使检测器监测到的光强度随时间按指数规律衰减。由于待测水汽重的同位素吸收特定频率的光,所以光衰减到某一确定程度所需要的时间将变短,根据这一变短的时间推算水汽同位素含量。	PICARRO inc. L1102-i	Steen-Larsen et al, 2013; Steen-Larsen et al, 2014
TDL-可调谐二极管激光吸收光谱技术	利用激光器波长调谐通过被测气体的特征吸收区,水汽同位素的直接吸收光谱就是以波长为函数记录对入射光吸收的原型吸收线。由测量获得的线性、线宽和强度可以计算出同位素分子的吸收截面,进而计算出被测水汽同位素的浓度,可用于同时观测水汽( 1. 37 L m 波长)和 CO₂ 同位素含量。	Campbell Inc. TDL-TGA1001	Wen et al, 2010

星载同位素监测传感器类型	观测简介
温室气体观测干涉仪(Interferometric Monitor for Greenhouse-gasses, IMG);	属于日本EOS观测系统的一部分,在1996-997年运行了9个月;基于该观测数据估算的HDO表明其可以重现纬向递变规律;
迈克尔森大气无源探测干涉仪(Michelson Interferometer for Passive Atmospheric Sounding, MIPAS);	搭载于Envisat卫星上,运行于2002-2004年,可用来反演6 km以上至平流层顶部HDO,其中平流层结果相对可靠;
对流层发射光谱仪(Tropospheric Emission Spectrometer, TES);	搭载NASA Arua航天器上,发射于2004年。连续扫描,可提供全球5°×5°分辨率的HDO分布;
红外大气探测干涉仪(Infrared Atmospheric Sounding Interferometer, IASI)	类似于TES,但不是对地观测

Iso-GCMs/Iso-RCMs	模型类别	开发机构	参考文献
Iso-GCMs	CAM3	U.Colorado	Noone et al, 2010
	CAM2	UC Berkeley	Lee et al, 2007
	ECHAM5	AWI-Bremerhaven	Werner et al, 2011
	ECHAM4	MPI-Hamburg	Hoffmann et al, 1998
	LMDZ4	LMD-Paris	Risi et al, 2010
	GSM	Scripps-San Diego	Yoshimura et al, 2011
	GISS-E	GISS-New York	Schmidt et al, 2007
	GENESIS	Penn U	Mathieu et al, 2002
	HadCM3	U.Bristol	Tindall et al, 2009
	HadAM3	BAS-Cambridge	Sime et al, 2008
Iso-RCMs	REMOiso	MPIM-Hamburg	Sturm et al, 2005
	Iso-RCM	-	Yoshimura et al, 2008

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Review on atmospheric water vapor isotopic observation and research: theory, method and modeling

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