Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Model Development Pub Date : 2024-03-13 DOI:10.5194/gmd-17-2117-2024
T. Extier, T. Caley, Didier Roche
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Abstract

Abstract. Stable water isotopes are used to infer changes in the hydrological cycle for different climate periods and various climatic archives. Following previous developments of δ18O in the coupled climate model of intermediate complexity, iLOVECLIM, we present here the implementation of the 1H2H16O and 1H217O water isotopes in the different components of this model and calculate the associated secondary markers deuterium excess (d-excess) and oxygen-17 excess (17O-excess) in the atmosphere and ocean. So far, the latter has only been modelled by the atmospheric model LMDZ4. Results of a 5000-year equilibrium simulation under preindustrial conditions are analysed and compared to observations and several isotope-enabled models for the atmosphere and ocean components. In the atmospheric component, the model correctly reproduces the first-order global distribution of the δ2H and d-excess as observed in the data (R=0.56 for δ2H and 0.36 for d-excess), even if local differences are observed. The model–data correlation is within the range of other water-isotope-enabled general circulation models. The main isotopic effects and the latitudinal gradient are properly modelled, similarly to previous water-isotope-enabled general circulation model simulations, despite a simplified atmospheric component in iLOVECLIM. One exception is observed in Antarctica where the model does not correctly estimate the water isotope composition, a consequence of the non-conservative behaviour of the advection scheme at a very low moisture content. The modelled 17O-excess presents a too-important dispersion of the values in comparison to the observations and is not correctly reproduced in the model, mainly because of the complex processes involved in the 17O-excess isotopic value. For the ocean, the model simulates an adequate isotopic ratio in comparison to the observations, except for local areas such as the surface of the Arabian Sea, a part of the Arctic and the western equatorial Indian Ocean. Data–model evaluation also presents a good match for the δ2H over the entire water column in the Atlantic Ocean, reflecting the influence of the different water masses.
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在耦合数值气候模式 iLOVECLIM(1.1.5 版)中建立水同位素(1H2H16O、1H217O)模型
摘要。稳定水同位素用于推断不同气候时期和各种气候档案中水文循环的变化。继之前在中等复杂程度的耦合气候模式 iLOVECLIM 中开发 δ18O 之后,我们在此介绍在该模式的不同组成部分中实施 1H2H16O 和 1H217O 水同位素的情况,并计算大气和海洋中相关的次要标记氘过量(d-excess)和氧-17 过量(17O-excess)。到目前为止,只有大气模型 LMDZ4 对后者进行了模拟。对工业化前条件下的 5000 年平衡模拟结果进行了分析,并将其与大气和海洋部分的观测结果和几个同位素模型进行了比较。在大气成分中,模式正确地再现了数据中观测到的δ2H 和 d-excess 的一阶全球分布(δ2H 的 R=0.56,d-excess 的 R=0.36),即使观测到的局部差异也是如此。模式与数据的相关性在其他支持水同位素的大气环流模式的范围之内。尽管在 iLOVECLIM 中简化了大气成分,但主要的同位素效应和纬度梯度都得到了正确模拟,与以前的水同位素支持的大气环流模式模拟相似。在南极洲观察到的一个例外情况是,该模式不能正确估计水同位素组成,这是由于在含水量非常低的情况下平流方案的非保守行为造成的。与观测值相比,模拟的 17O-excess 值的离散性太强,在模式中不能正确再现,这主要是由于 17O-excess 同位素值涉及到复杂的过程。在海洋方面,除了局部地区,如阿拉伯海海面、北冰洋部分海域和赤道印度洋西部,模型模拟的同位素比值与观测值相比是适当的。数据-模型评估还显示,大西洋整个水柱的 δ2H 匹配度很高,反映了不同水团的影响。
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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