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.
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。
{"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":"https://doi.org/10.5194/gmd-16-6377-2023","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. 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.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"39 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135430669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. A single ozone (O3) tracer mode was developed in this work to build the capability of the Goddard Earth Observing System model with Chemistry (GEOS-Chem) for rapid O3 simulation. The single O3 tracer simulation demonstrates consistency with the GEOS-Chem full chemistry simulation, with dramatic reductions in computational costs of approximately 91 %–94 %. The single O3 tracer simulation was combined with surface and Ozone Monitoring Instrument (OMI) O3 observations to investigate the changes in tropospheric O3 over eastern China in 2015–2020. The assimilated O3 concentrations demonstrate good agreement with O3 observations because surface O3 concentrations are 43.2, 41.8, and 42.1 ppb and tropospheric O3 columns are 37.1, 37.9, and 38.0 DU in the simulations, assimilations, and observations, respectively. The assimilations indicate rapid rises in surface O3 concentrations by 1.60 (spring), 1.16 (summer), 1.47 (autumn), and 0.80 ppb yr−1 (winter) over eastern China in 2015–2020, and the increasing trends are underestimated by the a priori simulations. More attention is suggested to the rapid increases in the O3 pollution in spring and autumn. We find stronger rises in tropospheric O3 columns over highly polluted areas due to larger local contributions, for example, 0.12 DU yr−1 (North China Plain) in contrast to −0.29 (Sichuan Basin) and −0.25 DU yr−1 (southern China). Furthermore, our analysis demonstrated noticeable contributions of the interannual variability in background O3 to the trends in surface O3 (particularly in the summer) and tropospheric O3 columns over eastern China in 2015–2020. This work highlights the importance of rapid simulations and assimilations to extend and interpret atmospheric O3 observations.
摘要为了建立戈达德地球观测系统化学模型(GEOS-Chem)快速模拟臭氧的能力，建立了单一臭氧示踪模型。单一O3示踪剂模拟与GEOS-Chem全化学模拟结果一致，计算成本大幅降低约91% - 94%。利用单示踪剂模拟与地面臭氧监测仪器(OMI) O3观测相结合，研究了2015-2020年中国东部对流层O3的变化。在模拟、同化和观测中，地表O3浓度分别为43.2、41.8和42.1 ppb，对流层O3柱浓度分别为37.1、37.9和38.0 DU，与O3观测值吻合良好。同化结果表明，2015-2020年中国东部地区地表O3浓度快速上升1.60(春季)、1.16(夏季)、1.47(秋季)和0.80 ppb yr - 1(冬季)，先验模拟低估了上升趋势。春季和秋季臭氧污染的快速增加应引起重视。我们发现，在高污染地区，由于更大的局部贡献，对流层O3柱的上升更强，例如，华北平原为0.12 DU yr - 1，而四川盆地为- 0.29 DU yr - 1，华南地区为- 0.25 DU yr - 1。此外，我们的分析表明，背景O3的年际变化对2015-2020年中国东部地区地面O3(特别是夏季)和对流层O3柱的趋势有显著贡献。这项工作强调了快速模拟和同化对扩展和解释大气O3观测的重要性。
{"title":"Rapid O<sub>3</sub> assimilations – Part 1: Background and local contributions to tropospheric O<sub>3</sub> changes in China in 2015–2020","authors":"Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, Zhe Jiang","doi":"10.5194/gmd-16-6337-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6337-2023","url":null,"abstract":"Abstract. A single ozone (O3) tracer mode was developed in this work to build the capability of the Goddard Earth Observing System model with Chemistry (GEOS-Chem) for rapid O3 simulation. The single O3 tracer simulation demonstrates consistency with the GEOS-Chem full chemistry simulation, with dramatic reductions in computational costs of approximately 91 %–94 %. The single O3 tracer simulation was combined with surface and Ozone Monitoring Instrument (OMI) O3 observations to investigate the changes in tropospheric O3 over eastern China in 2015–2020. The assimilated O3 concentrations demonstrate good agreement with O3 observations because surface O3 concentrations are 43.2, 41.8, and 42.1 ppb and tropospheric O3 columns are 37.1, 37.9, and 38.0 DU in the simulations, assimilations, and observations, respectively. The assimilations indicate rapid rises in surface O3 concentrations by 1.60 (spring), 1.16 (summer), 1.47 (autumn), and 0.80 ppb yr−1 (winter) over eastern China in 2015–2020, and the increasing trends are underestimated by the a priori simulations. More attention is suggested to the rapid increases in the O3 pollution in spring and autumn. We find stronger rises in tropospheric O3 columns over highly polluted areas due to larger local contributions, for example, 0.12 DU yr−1 (North China Plain) in contrast to −0.29 (Sichuan Basin) and −0.25 DU yr−1 (southern China). Furthermore, our analysis demonstrated noticeable contributions of the interannual variability in background O3 to the trends in surface O3 (particularly in the summer) and tropospheric O3 columns over eastern China in 2015–2020. This work highlights the importance of rapid simulations and assimilations to extend and interpret atmospheric O3 observations.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"36 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135430389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.5194/gmd-16-6355-2023
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, Po-Lun Ma
Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.
{"title":"Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations","authors":"Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, Po-Lun Ma","doi":"10.5194/gmd-16-6355-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6355-2023","url":null,"abstract":"Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"6 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.5194/gmd-16-6267-2023
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, Nate McDowell
Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.
{"title":"Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)","authors":"Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, Nate McDowell","doi":"10.5194/gmd-16-6267-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6267-2023","url":null,"abstract":"Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"104 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135540071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.5194/gmd-16-6309-2023
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Samantha Engwell
Abstract. We present developments to the physical model and the open-source numerical code IMEX_SfloW2D (de' Michieli Vitturi et al., 2019). These developments consist of a generalization of the depth-averaged (shallow-water) fluid equations to describe a polydisperse fluid–solid mixture, including terms for sedimentation and entrainment, transport equations for solid particles of different sizes, transport equations for different components of the carrier phase, and an equation for temperature/energy. Of relevance for the simulation of volcanic mass flows, vaporization and entrainment of water are implemented in the new model. The model can be easily adapted to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). The numerical algorithm and the code have been improved to allow for simulation of sub- to supercritical regimes and to simplify the setting of initial and boundary conditions. The code is open-source. The results of synthetic numerical benchmarks demonstrate the robustness of the numerical code in simulating transcritical flows interacting with the topography. Moreover, they highlight the importance of simulating transient in comparison to steady-state flows and flows in 2D versus 1D. Finally, we demonstrate the model capabilities to simulate a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles, through application to Krakatau volcano, showing the relevance, at a large scale, of non-linear fluid dynamic features, such as hydraulic jumps and von Kármán vortices, to flow conditions such as velocity and runout.
摘要我们介绍了物理模型的发展和开源数值代码IMEX_SfloW2D (de' Michieli Vitturi et al.， 2019)。这些发展包括对深度平均(浅水)流体方程的推广，以描述多分散的流固混合物，包括沉积和夹带的术语，不同大小的固体颗粒的输运方程，不同载体相组分的输运方程，以及温度/能量方程。与火山团块流的模拟相关的是，在新模型中实现了水的蒸发和夹带。该模型可以很容易地适应于模拟大范围的火山块流(火山碎屑雪崩、火山泥流、火山碎屑涌流)，这里我们介绍了它在瞬态稀释火山碎屑密度流(PDCs)中的应用。数值算法和代码已得到改进，以允许模拟亚至超临界状态，并简化了初始条件和边界条件的设置。代码是开源的。综合数值基准的结果表明，该数值程序在模拟与地形相互作用的跨临界流动方面具有鲁棒性。此外，他们还强调了与稳态流动和二维与一维流动相比，模拟瞬态流动的重要性。最后，通过应用于喀拉喀托火山，我们展示了模型的能力，以模拟一个复杂的自然情况，包括PDCs在海面和地形障碍上的传播，在大尺度上显示了非线性流体动力学特征(如水力跳跃和von Kármán漩涡)与流速和跳动等流动条件的相关性。
{"title":"IMEX_SfloW2D v2: a depth-averaged numerical flow model for volcanic gas–particle flows over complex topographies and water","authors":"Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Samantha Engwell","doi":"10.5194/gmd-16-6309-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6309-2023","url":null,"abstract":"Abstract. We present developments to the physical model and the open-source numerical code IMEX_SfloW2D (de' Michieli Vitturi et al., 2019). These developments consist of a generalization of the depth-averaged (shallow-water) fluid equations to describe a polydisperse fluid–solid mixture, including terms for sedimentation and entrainment, transport equations for solid particles of different sizes, transport equations for different components of the carrier phase, and an equation for temperature/energy. Of relevance for the simulation of volcanic mass flows, vaporization and entrainment of water are implemented in the new model. The model can be easily adapted to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). The numerical algorithm and the code have been improved to allow for simulation of sub- to supercritical regimes and to simplify the setting of initial and boundary conditions. The code is open-source. The results of synthetic numerical benchmarks demonstrate the robustness of the numerical code in simulating transcritical flows interacting with the topography. Moreover, they highlight the importance of simulating transient in comparison to steady-state flows and flows in 2D versus 1D. Finally, we demonstrate the model capabilities to simulate a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles, through application to Krakatau volcano, showing the relevance, at a large scale, of non-linear fluid dynamic features, such as hydraulic jumps and von Kármán vortices, to flow conditions such as velocity and runout.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"1 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135539366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.5194/gmd-16-6285-2023
Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, Bin Wang
Abstract. As earth system modeling develops ever finer grid resolutions, the inputting and outputting (I/O) of the increasingly large data fields becomes a processing bottleneck. Many models developed in China, as well as the community coupler (C-Coupler), do not fully benefit from existing parallel I/O supports. This paper reports the design and implementation of a common parallel input/output framework (CIOFC1.0) based on C-Coupler2.0. The CIOFC1.0 framework can accelerate the I/O of large data fields by parallelizing data read/write operations among processes. The framework also allows convenient specification by users of the I/O settings, e.g., the data fields for I/O, the time series of the data files for I/O, and the data grids in the files. The framework can also adaptively input data fields from a time series dataset during model integration, automatically interpolate data when necessary, and output fields either periodically or irregularly. CIOFC1.0 demonstrates the cooperative development of an I/O framework and coupler, and thus enables convenient and simultaneous use of a coupler and an I/O framework.
{"title":"CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0","authors":"Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, Bin Wang","doi":"10.5194/gmd-16-6285-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6285-2023","url":null,"abstract":"Abstract. As earth system modeling develops ever finer grid resolutions, the inputting and outputting (I/O) of the increasingly large data fields becomes a processing bottleneck. Many models developed in China, as well as the community coupler (C-Coupler), do not fully benefit from existing parallel I/O supports. This paper reports the design and implementation of a common parallel input/output framework (CIOFC1.0) based on C-Coupler2.0. The CIOFC1.0 framework can accelerate the I/O of large data fields by parallelizing data read/write operations among processes. The framework also allows convenient specification by users of the I/O settings, e.g., the data fields for I/O, the time series of the data files for I/O, and the data grids in the files. The framework can also adaptively input data fields from a time series dataset during model integration, automatically interpolate data when necessary, and output fields either periodically or irregularly. CIOFC1.0 demonstrates the cooperative development of an I/O framework and coupler, and thus enables convenient and simultaneous use of a coupler and an I/O framework.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"10 38","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135540468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.5194/gmd-16-6187-2023
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, Martyn P. Chipperfield
Abstract. The paper describes the development and performance of the Double Extended Stratospheric–Tropospheric (DEST vn1.0) chemistry scheme, which forms a part of the Met Office's Unified Model coupled to the United Kingdom Chemistry and Aerosol (UM–UKCA) chemistry–climate model, which is the atmospheric composition model of the United Kingdom Earth System Model (UKESM). The scheme extends the standard Stratospheric–Tropospheric chemistry scheme (StratTrop) by including a range of important updates to the halogen chemistry. These allow process-oriented studies of stratospheric ozone depletion and recovery, including the impacts from both controlled long-lived ozone-depleting substances (ODSs) and emerging issues around uncontrolled very short-lived substances (VSLS). The main updates in DEST are (i) an explicit treatment of 14 of the most important long-lived ODSs; (ii) an inclusion of brominated VSLS (Br-VSLS) emissions and chemistry; and (iii) an inclusion of chlorinated VSLS (Cl-VSLS) emissions/LBCs (lower boundary conditions) and chemistry. We evaluate the scheme's performance by comparing DEST simulations against analogous runs made with the standard StratTrop scheme and against observational and reanalysis datasets. Overall, our scheme addresses some significant shortcomings in the representation of atmospheric halogens in the standard StratTrop scheme and will thus be particularly relevant for studies of ozone layer recovery and processes affecting it, in support of future World Meteorological Organization (WMO) Ozone Assessment Reports.
{"title":"Description and evaluation of the new UM–UKCA (vn11.0) Double Extended Stratospheric–Tropospheric (DEST vn1.0) scheme for comprehensive modelling of halogen chemistry in the stratosphere","authors":"Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, Martyn P. Chipperfield","doi":"10.5194/gmd-16-6187-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6187-2023","url":null,"abstract":"Abstract. The paper describes the development and performance of the Double Extended Stratospheric–Tropospheric (DEST vn1.0) chemistry scheme, which forms a part of the Met Office's Unified Model coupled to the United Kingdom Chemistry and Aerosol (UM–UKCA) chemistry–climate model, which is the atmospheric composition model of the United Kingdom Earth System Model (UKESM). The scheme extends the standard Stratospheric–Tropospheric chemistry scheme (StratTrop) by including a range of important updates to the halogen chemistry. These allow process-oriented studies of stratospheric ozone depletion and recovery, including the impacts from both controlled long-lived ozone-depleting substances (ODSs) and emerging issues around uncontrolled very short-lived substances (VSLS). The main updates in DEST are (i) an explicit treatment of 14 of the most important long-lived ODSs; (ii) an inclusion of brominated VSLS (Br-VSLS) emissions and chemistry; and (iii) an inclusion of chlorinated VSLS (Cl-VSLS) emissions/LBCs (lower boundary conditions) and chemistry. We evaluate the scheme's performance by comparing DEST simulations against analogous runs made with the standard StratTrop scheme and against observational and reanalysis datasets. Overall, our scheme addresses some significant shortcomings in the representation of atmospheric halogens in the standard StratTrop scheme and will thus be particularly relevant for studies of ozone layer recovery and processes affecting it, in support of future World Meteorological Organization (WMO) Ozone Assessment Reports.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135874943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. A particle-based cloud model was developed for meter- to submeter-scale-resolution simulations of warm clouds. Simplified cloud microphysics schemes have already made meter-scale-resolution simulations feasible; however, such schemes are based on empirical assumptions, and hence they contain huge uncertainties. The super-droplet method (SDM) is a promising candidate for cloud microphysical process modeling and is a particle-based approach, making fewer assumptions for the droplet size distributions. However, meter-scale-resolution simulations using the SDM are not feasible even on existing high-end supercomputers because of high computational cost. In the present study, we overcame challenges to realize such simulations. The contributions of our work are as follows: (1) the uniform sampling method is not suitable when dealing with a large number of super-droplets (SDs). Hence, we developed a new initialization method for sampling SDs from a real droplet population. These SDs can be used for simulating spatial resolutions between meter and submeter scales. (2) We optimized the SDM algorithm to achieve high performance by reducing data movement and simplifying loop bodies using the concept of effective resolution. The optimized algorithms can be applied to a Fujitsu A64FX processor, and most of them are also effective on other many-core CPUs and possibly graphics processing units (GPUs). Warm-bubble experiments revealed that the throughput of particle calculations per second for the improved algorithms is 61.3 times faster than those for the original SDM. In the case of shallow cumulous, the simulation time when using the new SDM with 32–64 SDs per cell is shorter than that of a bin method with 32 bins and comparable to that of a two-moment bulk method. (3) Using the supercomputer Fugaku, we demonstrated that a numerical experiment with 2 m resolution and 128 SDs per cell covering 13 8242×3072 m3 domain is possible. The number of grid points and SDs are 104 and 442 times, respectively, those of the highest-resolution simulation performed so far. Our numerical model exhibited 98 % weak scaling for 36 864 nodes, accounting for 23 % of the total system. The simulation achieves 7.97 PFLOPS, 7.04 % of the peak ratio for overall performance, and a simulation time for SDM of 2.86×1013 particle ⋅ steps per second. Several challenges, such as incorporating mixed-phase processes, inclusion of terrain, and long-time integrations, remain, and our study will also contribute to solving them. The developed model enables us to study turbulence and microphysics processes over a wide range of scales using combinations of direct numerical simulation (DNS), laboratory experiments, and field studies. We believe that our approach advances the scientific understanding of clouds and contributes to reducing the uncertainties of weather simulation and climate projection.
{"title":"Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method","authors":"Toshiki Matsushima, Seiya Nishizawa, Shin-ichiro Shima","doi":"10.5194/gmd-16-6211-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6211-2023","url":null,"abstract":"Abstract. A particle-based cloud model was developed for meter- to submeter-scale-resolution simulations of warm clouds. Simplified cloud microphysics schemes have already made meter-scale-resolution simulations feasible; however, such schemes are based on empirical assumptions, and hence they contain huge uncertainties. The super-droplet method (SDM) is a promising candidate for cloud microphysical process modeling and is a particle-based approach, making fewer assumptions for the droplet size distributions. However, meter-scale-resolution simulations using the SDM are not feasible even on existing high-end supercomputers because of high computational cost. In the present study, we overcame challenges to realize such simulations. The contributions of our work are as follows: (1) the uniform sampling method is not suitable when dealing with a large number of super-droplets (SDs). Hence, we developed a new initialization method for sampling SDs from a real droplet population. These SDs can be used for simulating spatial resolutions between meter and submeter scales. (2) We optimized the SDM algorithm to achieve high performance by reducing data movement and simplifying loop bodies using the concept of effective resolution. The optimized algorithms can be applied to a Fujitsu A64FX processor, and most of them are also effective on other many-core CPUs and possibly graphics processing units (GPUs). Warm-bubble experiments revealed that the throughput of particle calculations per second for the improved algorithms is 61.3 times faster than those for the original SDM. In the case of shallow cumulous, the simulation time when using the new SDM with 32–64 SDs per cell is shorter than that of a bin method with 32 bins and comparable to that of a two-moment bulk method. (3) Using the supercomputer Fugaku, we demonstrated that a numerical experiment with 2 m resolution and 128 SDs per cell covering 13 8242×3072 m3 domain is possible. The number of grid points and SDs are 104 and 442 times, respectively, those of the highest-resolution simulation performed so far. Our numerical model exhibited 98 % weak scaling for 36 864 nodes, accounting for 23 % of the total system. The simulation achieves 7.97 PFLOPS, 7.04 % of the peak ratio for overall performance, and a simulation time for SDM of 2.86×1013 particle ⋅ steps per second. Several challenges, such as incorporating mixed-phase processes, inclusion of terrain, and long-time integrations, remain, and our study will also contribute to solving them. The developed model enables us to study turbulence and microphysics processes over a wide range of scales using combinations of direct numerical simulation (DNS), laboratory experiments, and field studies. We believe that our approach advances the scientific understanding of clouds and contributes to reducing the uncertainties of weather simulation and climate projection.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"15 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Accurate wind speed prediction is crucial for the safe and efficient utilization of wind resources. However, current single-value deterministic numerical weather prediction methods employed by wind farms do not adequately meet the actual needs of power grid dispatching. In this study, we propose a new hybrid forecasting method for correcting 10 m wind speed predictions made by the Weather Research and Forecasting (WRF) model. Our approach incorporates variational mode decomposition (VMD), principal component analysis (PCA), and five artificial intelligence algorithms: deep belief network (DBN), multilayer perceptron (MLP), random forest (RF), eXtreme gradient boosting (XGBoost), light gradient boosting machine (lightGBM), and the Bayesian optimization algorithm (BOA). We first predict wind speeds using the WRF model, with initial and lateral boundary conditions from the Global Forecast System (GFS). We then perform two sets of experiments with different input factors and apply BOA optimization to tune the four artificial intelligence models, ultimately building the final models. Furthermore, we compare the aforementioned five optimal artificial intelligence models suitable for five provinces in southern China in the wintertime: VMD-PCA-RF in December 2021 and VMD-PCA-lightGBM in January 2022. We find that the VMD-PCA-RF evaluation indices exhibit relative stability over nearly a year: the correlation coefficient (R) is above 0.6, forecasting accuracy (FA) is above 85 %, mean absolute error (MAE) is below 0.6 m s−1, root mean square error (RMSE) is below 0.8 m s−1, relative mean absolute error (rMAE) is below 60 %, and relative root mean square error (rRMSE) is below 75 %. Thus, for its promising performance and excellent year-round robustness, we recommend adopting the proposed VMD-PCA-RF method for improved wind speed prediction in models.
摘要准确的风速预测对风资源的安全高效利用至关重要。然而，目前风电场采用的单值确定性数值天气预报方法不能很好地满足电网调度的实际需要。在这项研究中，我们提出了一种新的混合预报方法，用于校正由天气研究与预报(WRF)模式预测的10 m风速。我们的方法结合了变分模态分解(VMD)、主成分分析(PCA)和五种人工智能算法:深度信念网络(DBN)、多层感知器(MLP)、随机森林(RF)、极限梯度增强(XGBoost)、轻梯度增强机(lightGBM)和贝叶斯优化算法(BOA)。我们首先利用全球预报系统(GFS)的初始和横向边界条件，利用WRF模式预测风速。然后，我们使用不同的输入因素进行两组实验，并应用BOA优化来调整四个人工智能模型，最终构建最终模型。此外，我们还比较了上述适用于中国南方五省冬季的五种最优人工智能模型:2021年12月的VMD-PCA-RF和2022年1月的VMD-PCA-lightGBM。研究发现，近一年来，VMD-PCA-RF评价指标表现出相对稳定性:相关系数(R)在0.6以上，预测精度(FA)在85%以上，平均绝对误差(MAE)在0.6 m s−1以下，均方根误差(RMSE)在0.8 m s−1以下，相对平均绝对误差(rMAE)在60%以下，相对均方根误差(rRMSE)在75%以下。因此，由于其良好的性能和出色的全年鲁棒性，我们建议采用所提出的VMD-PCA-RF方法来改进模型中的风速预测。
{"title":"A robust error correction method for numerical weather prediction wind speed based on Bayesian optimization, variational mode decomposition, principal component analysis, and random forest: VMD-PCA-RF (version 1.0.0)","authors":"Shaohui Zhou, Chloe Yuchao Gao, Zexia Duan, Xingya Xi, Yubin Li","doi":"10.5194/gmd-16-6247-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6247-2023","url":null,"abstract":"Abstract. Accurate wind speed prediction is crucial for the safe and efficient utilization of wind resources. However, current single-value deterministic numerical weather prediction methods employed by wind farms do not adequately meet the actual needs of power grid dispatching. In this study, we propose a new hybrid forecasting method for correcting 10 m wind speed predictions made by the Weather Research and Forecasting (WRF) model. Our approach incorporates variational mode decomposition (VMD), principal component analysis (PCA), and five artificial intelligence algorithms: deep belief network (DBN), multilayer perceptron (MLP), random forest (RF), eXtreme gradient boosting (XGBoost), light gradient boosting machine (lightGBM), and the Bayesian optimization algorithm (BOA). We first predict wind speeds using the WRF model, with initial and lateral boundary conditions from the Global Forecast System (GFS). We then perform two sets of experiments with different input factors and apply BOA optimization to tune the four artificial intelligence models, ultimately building the final models. Furthermore, we compare the aforementioned five optimal artificial intelligence models suitable for five provinces in southern China in the wintertime: VMD-PCA-RF in December 2021 and VMD-PCA-lightGBM in January 2022. We find that the VMD-PCA-RF evaluation indices exhibit relative stability over nearly a year: the correlation coefficient (R) is above 0.6, forecasting accuracy (FA) is above 85 %, mean absolute error (MAE) is below 0.6 m s−1, root mean square error (RMSE) is below 0.8 m s−1, relative mean absolute error (rMAE) is below 60 %, and relative root mean square error (rRMSE) is below 75 %. Thus, for its promising performance and excellent year-round robustness, we recommend adopting the proposed VMD-PCA-RF method for improved wind speed prediction in models.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"16 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.5194/gmd-16-6087-2023
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, Terry Deshler
Abstract. We implemented the Community Aerosol and Radiation Model for Atmospheres (CARMA) in both the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2). CARMA is a sectional microphysical model, which we use for aerosol in both the troposphere and stratosphere. CARMA is fully coupled to chemistry, clouds, radiation, and transport routines in CESM2. This development enables the comparison of simulations with a sectional (CARMA) and a modal (MAM4) aerosol microphysical model in the same modeling framework. The new implementation of CARMA has been adopted from previous work, with some additions that align with the current CESM2 Modal Aerosol Model (MAM4) implementation. The main updates include an interactive secondary organic aerosol description in CARMA, using the volatility basis set (VBS) approach, updated wet removal, and the use of transient emissions of aerosols and trace gases. In addition, we implemented an alternative aerosol nucleation scheme in CARMA, which is also used in MAM4. Detailed comparisons of stratospheric aerosol properties after the Mount Pinatubo eruption reveal the importance of prescribing sulfur injections in a larger region rather than in a single column to better represent the observed evolution of aerosols. Both CARMA and MAM4 in CESM2 are able to represent stratospheric and tropospheric aerosol properties reasonably well when compared to observations. Several differences in the performance of the two aerosol models show, in general, an improved representation of aerosols when using the sectional aerosol model in CESM2. These include a better representation of the aerosol size distribution after the Mount Pinatubo volcanic eruption in CARMA compared to MAM4. MAM4 produces on average smaller aerosols and less removal than CARMA, which results in a larger total mass. Both CARMA and MAM4 reproduce the stratospheric aerosol optical depth (AOD) within the error bar of the observations between 2001 and 2020, except for recent larger volcanic eruptions that are overestimated by both model configurations. The CARMA background surface area density and aerosol size distribution in the stratosphere and troposphere compare well to observations, with some underestimation of the Aitken-mode size range. MAM4 shows shortcomings in reproducing coarse-mode aerosol distributions in the stratosphere and troposphere. This work outlines additional development needs for CESM2 CARMA to improve the model compared to observations in both the troposphere and stratosphere.
{"title":"Description and performance of a sectional aerosol microphysical model in the Community Earth System Model (CESM2)","authors":"Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, Terry Deshler","doi":"10.5194/gmd-16-6087-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-6087-2023","url":null,"abstract":"Abstract. We implemented the Community Aerosol and Radiation Model for Atmospheres (CARMA) in both the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2). CARMA is a sectional microphysical model, which we use for aerosol in both the troposphere and stratosphere. CARMA is fully coupled to chemistry, clouds, radiation, and transport routines in CESM2. This development enables the comparison of simulations with a sectional (CARMA) and a modal (MAM4) aerosol microphysical model in the same modeling framework. The new implementation of CARMA has been adopted from previous work, with some additions that align with the current CESM2 Modal Aerosol Model (MAM4) implementation. The main updates include an interactive secondary organic aerosol description in CARMA, using the volatility basis set (VBS) approach, updated wet removal, and the use of transient emissions of aerosols and trace gases. In addition, we implemented an alternative aerosol nucleation scheme in CARMA, which is also used in MAM4. Detailed comparisons of stratospheric aerosol properties after the Mount Pinatubo eruption reveal the importance of prescribing sulfur injections in a larger region rather than in a single column to better represent the observed evolution of aerosols. Both CARMA and MAM4 in CESM2 are able to represent stratospheric and tropospheric aerosol properties reasonably well when compared to observations. Several differences in the performance of the two aerosol models show, in general, an improved representation of aerosols when using the sectional aerosol model in CESM2. These include a better representation of the aerosol size distribution after the Mount Pinatubo volcanic eruption in CARMA compared to MAM4. MAM4 produces on average smaller aerosols and less removal than CARMA, which results in a larger total mass. Both CARMA and MAM4 reproduce the stratospheric aerosol optical depth (AOD) within the error bar of the observations between 2001 and 2020, except for recent larger volcanic eruptions that are overestimated by both model configurations. The CARMA background surface area density and aerosol size distribution in the stratosphere and troposphere compare well to observations, with some underestimation of the Aitken-mode size range. MAM4 shows shortcomings in reproducing coarse-mode aerosol distributions in the stratosphere and troposphere. This work outlines additional development needs for CESM2 CARMA to improve the model compared to observations in both the troposphere and stratosphere.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"59 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135327900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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