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Furthermore, we developed new modules to support MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) meteorological data, which allows us to perform long-term analyses with consistent meteorological data for the period 1979–present. The performances of the developed capabilities were evaluated with the following steps: (1) diagnostic outputs of carbon monoxide (CO) sources and sinks to ensure the correct reading and use of emission inventories, (2) forward simulations to compare the modeled surface and column CO concentrations among various model versions, (3) backward simulations to compare adjoint gradients of global CO concentrations to CO emissions with finite-difference gradients, and (4) observing system simulation experiments (OSSEs) to evaluate the model performance in 4D variational (4D-Var) assimilations. Finally, an example application of 4D-Var assimilation was presented to constrain anthropogenic CO emissions in 2015 by assimilating Measurement of Pollution in the Troposphere (MOPITT) CO observations. The capabilities developed in this work are important for better applications of the adjoint of the GEOS-Chem model in the future. These capabilities will be submitted to the standard GEOS-Chem adjoint code base for better development of the community of the adjoint of the GEOS-Chem model.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"39 12","pages":"0"},"PeriodicalIF":4.0000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The capabilities of the adjoint of GEOS-Chem model to support HEMCO emission inventories and MERRA-2 meteorological data\",\"authors\":\"Zhaojun Tang, Zhe Jiang, Jiaqi Chen, Panpan Yang, Yanan Shen\",\"doi\":\"10.5194/gmd-16-6377-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. The adjoint of the GEOS-Chem (Goddard Earth Observing System with Chemistry) model has been widely used to constrain the sources of atmospheric compositions. 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引用次数: 0
摘要
摘要戈达德地球化学观测系统(Goddard Earth Observing System with Chemistry, GEOS-Chem)模式的伴随模式已被广泛用于大气成分来源的约束。在此,我们设计了一个新的框架,以促进GEOS-Chem模型伴随的排放清单更新。这个新框架的主要优点是良好的可读性和可扩展性,这使我们能够方便地支持协调排放组件(HEMCO)排放清单,并在GEOS-Chem正向模拟的未来更新后轻松添加更多的排放清单。此外,我们开发了新的模块来支持MERRA-2(现代研究与应用回顾性分析,第2版)气象数据,这使我们能够使用1979年至今的一致气象数据进行长期分析。已开发能力的性能按以下步骤进行评估:(1)一氧化碳(CO)源和汇的诊断输出,以确保正确读取和使用排放清单;(2)正演模拟,以比较不同模型版本中模拟的地表和柱状CO浓度;(3)反向模拟,以有限差分梯度比较全球CO浓度与CO排放的伴随梯度。(4)观测系统模拟实验(OSSEs),评估模型在4D变分同化(4D- var)中的性能。最后,通过同化对流层污染测量(MOPITT) CO观测数据,给出了利用4D-Var同化限制2015年人为CO排放的实例。在这项工作中开发的功能对于将来更好地应用GEOS-Chem模型的伴随体非常重要。这些功能将提交给标准的GEOS-Chem伴随代码库,以便更好地开发GEOS-Chem模型的伴随社区。
The capabilities of the adjoint of GEOS-Chem model to support HEMCO emission inventories and MERRA-2 meteorological data
Abstract. The adjoint of the GEOS-Chem (Goddard Earth Observing System with Chemistry) model has been widely used to constrain the sources of atmospheric compositions. Here, we designed a new framework to facilitate emission inventory updates in the adjoint of the GEOS-Chem model. The major advantage of this new framework is good readability and extensibility, which allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) meteorological data, which allows us to perform long-term analyses with consistent meteorological data for the period 1979–present. The performances of the developed capabilities were evaluated with the following steps: (1) diagnostic outputs of carbon monoxide (CO) sources and sinks to ensure the correct reading and use of emission inventories, (2) forward simulations to compare the modeled surface and column CO concentrations among various model versions, (3) backward simulations to compare adjoint gradients of global CO concentrations to CO emissions with finite-difference gradients, and (4) observing system simulation experiments (OSSEs) to evaluate the model performance in 4D variational (4D-Var) assimilations. Finally, an example application of 4D-Var assimilation was presented to constrain anthropogenic CO emissions in 2015 by assimilating Measurement of Pollution in the Troposphere (MOPITT) CO observations. The capabilities developed in this work are important for better applications of the adjoint of the GEOS-Chem model in the future. These capabilities will be submitted to the standard GEOS-Chem adjoint code base for better development of the community of the adjoint of the GEOS-Chem model.
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.