Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2949-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2949-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
07 Apr 2022
Model evaluation paper |
| 07 Apr 2022
| 07 Apr 2022
Evaluation of a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments
Hengqi Wang
Department of Earth System Science, Ministry of Education Key
Laboratory for Earth System Modeling, Institute for Global Change Studies,
Tsinghua University, Beijing 100084, China
Yiran Peng
CORRESPONDING AUTHOR
Department of Earth System Science, Ministry of Education Key
Laboratory for Earth System Modeling, Institute for Global Change Studies,
Tsinghua University, Beijing 100084, China
Knut von Salzen
CORRESPONDING AUTHOR
Canadian Centre for Climate Modelling and Analysis, Environment and
Climate Change Canada, Victoria, British Columbia, Canada
Yan Yang
Beijing Weather Modification Office, Beijing, 100101, China
Wei Zhou
Beijing Weather Modification Office, Beijing, 100101, China
Delong Zhao
Beijing Weather Modification Office, Beijing, 100101, China
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Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Ruth A. R. Digby, Knut von Salzen, Adam H. Monahan, Nathan P. Gillett, and Jiangnan Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-1796, https://doi.org/10.5194/egusphere-2024-1796, 2024
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The refractive index of black carbon (BCRI), which determines how much energy black carbon absorbs and scatters, is difficult to measure and different climate models use different values. We show that varying the BCRI across commonly used values can increase absorbing aerosol optical depth by 42 % and the warming effect from interactions between black carbon and radiation by 47 %, an appreciable fraction of the overall spread between models reported in recent literature assessments.
Zizhan Hu, Yiran Peng, Mengke Zhu, and Jonathon S. Wright
EGUsphere, https://doi.org/10.5194/egusphere-2024-828, https://doi.org/10.5194/egusphere-2024-828, 2024
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Clouds and precipitation are among the most difficult features of the climate system to simulate. Water isotopes provide valuable information about how clouds and precipitation develop and evolve, but most models that simulate water isotopes cannot resolve individual clouds. Here we introduce a new isotope-enabled model, iPyCLES, that simulates liquid and ice clouds on scales of 10 to 100 meters. This model can help to translate isotopic observations into constraints for larger-scale models.
Yuanmou Du, Dantong Liu, Delong Zhao, Mengyu Huang, Ping Tian, Dian Wen, Wei Xiao, Wei Zhou, Baiwan Pan, Dongfei Zuo, Xiange Liu, Yingying Jing, Rong Zhang, Jiujiang Sheng, Fei Wang, Yu Huang, Yunbo Chen, and Deping Ding
EGUsphere, https://doi.org/10.5194/egusphere-2024-314, https://doi.org/10.5194/egusphere-2024-314, 2024
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By conducting in-situ measurements of the microphysical properties, we investigated the ice production and phase transformation of stratocumulus during an extratropical cyclone over the North China Plain. We find the key factors in controlling secondary ice production, and the microphysical properties of clouds with convective cells under different stages are elucidated, which will improve the understanding of the key processes in controlling the cloud glaciation and precipitation process.
Ruth A. R. Digby, Nathan P. Gillett, Adam H. Monahan, Knut von Salzen, Antonis Gkikas, Qianqian Song, and Zhibo Zhang
Atmos. Chem. Phys., 24, 2077–2097, https://doi.org/10.5194/acp-24-2077-2024, https://doi.org/10.5194/acp-24-2077-2024, 2024
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The COVID-19 lockdowns reduced aerosol emissions. We ask whether these reductions affected regional aerosol optical depth (AOD) and compare the observed changes to predictions from Earth system models. Only India has an observed AOD reduction outside of typical variability. Models overestimate the response in some regions, but when key biases have been addressed, the agreement is improved. Our results suggest that current models can realistically predict the effects of future emission changes.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, https://doi.org/10.5194/gmd-16-6553-2023, 2023
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We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
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The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
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This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
Siyuan Li, Dantong Liu, Shaofei Kong, Yangzhou Wu, Kang Hu, Huang Zheng, Yi Cheng, Shurui Zheng, Xiaotong Jiang, Shuo Ding, Dawei Hu, Quan Liu, Ping Tian, Delong Zhao, and Jiujiang Sheng
Atmos. Chem. Phys., 22, 6937–6951, https://doi.org/10.5194/acp-22-6937-2022, https://doi.org/10.5194/acp-22-6937-2022, 2022
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The understanding of secondary organic aerosols is hindered by the aerosol–gas evolution by different oxidation mechanisms. By concurrently measuring detailed mass spectra of aerosol and gas phases in a megacity online, we identified the primary and secondary source sectors and investigated the transformation between gas and aerosol phases influenced by photooxidation and moisture. The results will help us to understand the respective evolution of major sources in a typical urban environment.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
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To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Chenjie Yu, Dantong Liu, Kang Hu, Ping Tian, Yangzhou Wu, Delong Zhao, Huihui Wu, Dawei Hu, Wenbo Guo, Qiang Li, Mengyu Huang, Deping Ding, and James D. Allan
Atmos. Chem. Phys., 22, 4375–4391, https://doi.org/10.5194/acp-22-4375-2022, https://doi.org/10.5194/acp-22-4375-2022, 2022
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In this study, we applied a new technique to investigate the aerosol properties on both a mass and number basis and CCN abilities in Beijing suburban regions. The size-resolved aerosol chemical compositions and CCN activation measurement enable a detailed analysis of BC-containing particle hygroscopicity and its size-dependent contribution to the CCN activation. The results presented in this study will affect future models and human health studies.
Julia Schmale, Sangeeta Sharma, Stefano Decesari, Jakob Pernov, Andreas Massling, Hans-Christen Hansson, Knut von Salzen, Henrik Skov, Elisabeth Andrews, Patricia K. Quinn, Lucia M. Upchurch, Konstantinos Eleftheriadis, Rita Traversi, Stefania Gilardoni, Mauro Mazzola, James Laing, and Philip Hopke
Atmos. Chem. Phys., 22, 3067–3096, https://doi.org/10.5194/acp-22-3067-2022, https://doi.org/10.5194/acp-22-3067-2022, 2022
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Long-term data sets of Arctic aerosol properties from 10 stations across the Arctic provide evidence that anthropogenic influence on the Arctic atmospheric chemical composition has declined in winter, a season which is typically dominated by mid-latitude emissions. The number of significant trends in summer is smaller than in winter, and overall the pattern is ambiguous with some significant positive and negative trends. This reflects the mixed influence of natural and anthropogenic emissions.
Donglin Chen, Hong Liao, Yang Yang, Lei Chen, Delong Zhao, and Deping Ding
Atmos. Chem. Phys., 22, 1825–1844, https://doi.org/10.5194/acp-22-1825-2022, https://doi.org/10.5194/acp-22-1825-2022, 2022
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The black carbon (BC) vertical profile plays a critical role in BC–meteorology interaction, which also influences PM2.5 concentrations. More BC mass was assigned into high altitudes (above 1000 m) in the model, which resulted in a stronger cooling effect near the surface, a larger temperature inversion below 421 m, more reductions in PBLH, and a larger increase in near-surface PM2.5 in the daytime caused by the direct radiative effect of BC.
Quan Liu, Dantong Liu, Yangzhou Wu, Kai Bi, Wenkang Gao, Ping Tian, Delong Zhao, Siyuan Li, Chenjie Yu, Guiqian Tang, Yunfei Wu, Kang Hu, Shuo Ding, Qian Gao, Fei Wang, Shaofei Kong, Hui He, Mengyu Huang, and Deping Ding
Atmos. Chem. Phys., 21, 14749–14760, https://doi.org/10.5194/acp-21-14749-2021, https://doi.org/10.5194/acp-21-14749-2021, 2021
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Through simultaneous online measurements of detailed aerosol compositions at both surface and surface-influenced mountain sites, the evolution of aerosol composition during daytime vertical transport was investigated. The results show that, from surface to the top of the planetary boundary layer, the oxidation state of organic aerosol had been significantly enhanced due to evaporation and further oxidation of these evaporated gases.
Dongfei Zuo, Deping Ding, Yichen Chen, Ling Yang, Delong Zhao, Mengyu Huang, Ping Tian, Wei Xiao, Wei Zhou, Yuanmou Du, and Dantong Liu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-221, https://doi.org/10.5194/amt-2021-221, 2021
Publication in AMT not foreseen
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According to the echo attenuation analysis of mixed precipitation, the melting layer is found to be the key factor affecting the attenuation correction. This study hereby proposes an adaptive echo attenuation correction method based on the melting layer, and uses the ground-based S-band radar to extract the echo on the aircraft trajectory to verify the correction results. The results show that the echo attenuation correction value above the melting layer is related to the flight position.
Shuo Ding, Dantong Liu, Kang Hu, Delong Zhao, Ping Tian, Fei Wang, Ruijie Li, Yichen Chen, Hui He, Mengyu Huang, and Deping Ding
Atmos. Chem. Phys., 21, 681–694, https://doi.org/10.5194/acp-21-681-2021, https://doi.org/10.5194/acp-21-681-2021, 2021
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In this study, we for the first time characterized the detailed black carbon (BC) microphysics at a mountain site located at the top of the planetary boundary layer (PBL) influenced by surface emission over the North China Plain. We investigated the optical and hygroscopic properties of BC at this level as influenced by microphysical properties. Such information will constrain the impacts of BC in influencing the PBL dynamics and low-level cloud formation over anthropogenically polluted regions.
Meixin Zhang, Chun Zhao, Zhiyuan Cong, Qiuyan Du, Mingyue Xu, Yu Chen, Ming Chen, Rui Li, Yunfei Fu, Lei Zhong, Shichang Kang, Delong Zhao, and Yan Yang
Atmos. Chem. Phys., 20, 5923–5943, https://doi.org/10.5194/acp-20-5923-2020, https://doi.org/10.5194/acp-20-5923-2020, 2020
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Analysis of multiple numerical experiments over the Himalayas and Tibetan Plateau (TP) shows that the complex topography results in 50 % stronger overall cross-Himalayan transport during the pre-monsoon season primarily due to the strengthened efficiency of near-surface meridional transport towards the TP, enhanced wind speed in some valleys and deeper valley channels associated with larger transported BC mass volume, which leads to 30–50 % stronger BC radiative heating over the TP.
Quan Liu, Dantong Liu, Qian Gao, Ping Tian, Fei Wang, Delong Zhao, Kai Bi, Yangzhou Wu, Shuo Ding, Kang Hu, Jiale Zhang, Deping Ding, and Chunsheng Zhao
Atmos. Chem. Phys., 20, 3931–3944, https://doi.org/10.5194/acp-20-3931-2020, https://doi.org/10.5194/acp-20-3931-2020, 2020
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We present a series of aircraft-based in situ measurements of aerosol chemical components and size distributions over the North China Plain, and the hygroscopicity is derived from aerosol chemical composition. These results reveal the vertical characteristics of aerosol hygroscopicity, and we investigated their impacts on optical properties and activation under different moisture and pollution conditions over this polluted region.
Jing Wei, Zhanqing Li, Maureen Cribb, Wei Huang, Wenhao Xue, Lin Sun, Jianping Guo, Yiran Peng, Jing Li, Alexei Lyapustin, Lei Liu, Hao Wu, and Yimeng Song
Atmos. Chem. Phys., 20, 3273–3289, https://doi.org/10.5194/acp-20-3273-2020, https://doi.org/10.5194/acp-20-3273-2020, 2020
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This study introduced an enhanced space–time extremely randomized trees (STET) approach to improve the 1 km resolution ground-level PM2.5 estimates across China using the remote sensing technology. The STET model shows high accuracy and strong predictive power and appears to outperform most models reported by previous studies. Thus, it is of great importance for future air pollution studies at medium- or small-scale areas and will be applied to generate the historical PM2.5 dataset across China.
Ping Tian, Dantong Liu, Delong Zhao, Chenjie Yu, Quan Liu, Mengyu Huang, Zhaoze Deng, Liang Ran, Yunfei Wu, Shuo Ding, Kang Hu, Gang Zhao, Chunsheng Zhao, and Deping Ding
Atmos. Chem. Phys., 20, 2603–2622, https://doi.org/10.5194/acp-20-2603-2020, https://doi.org/10.5194/acp-20-2603-2020, 2020
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This study paints a full picture of the evolution of vertical characteristics of aerosol optical properties and shortwave heating impacts of carbonaceous aerosols during different stages of pollution events over the Beijing region and highlights the increased contribution of brown carbon absorption, especially at higher levels, during pollution.
Xiaoyan Liu, Yan-Lin Zhang, Yiran Peng, Lulu Xu, Chunmao Zhu, Fang Cao, Xiaoyao Zhai, M. Mozammel Haque, Chi Yang, Yunhua Chang, Tong Huang, Zufei Xu, Mengying Bao, Wenqi Zhang, Meiyi Fan, and Xuhui Lee
Atmos. Chem. Phys., 19, 11213–11233, https://doi.org/10.5194/acp-19-11213-2019, https://doi.org/10.5194/acp-19-11213-2019, 2019
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Although a total ban on straw burning has been enforced in eastern China, the regionally transported biomass burning emissions remarkably impacted the chemical and optical properties of carbonaceous aerosols in Nanjing, which were quantified by a calculation based on measured data and a simulation based on a model. Results showed that regionally transported biomass burning emissions significantly contributed to the carbonaceous aerosols and impacted the solar radiation balance of the atmosphere.
Jing Wei, Yiran Peng, Rashed Mahmood, Lin Sun, and Jianping Guo
Atmos. Chem. Phys., 19, 7183–7207, https://doi.org/10.5194/acp-19-7183-2019, https://doi.org/10.5194/acp-19-7183-2019, 2019
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This study evaluates the suitability of 11 satellite-derived aerosol products in describing the spatio-temporal variations over the world. Our results show similar global patterns among these products but noticeable spatial heterogeneity and numerical differences over land regions. In general, MODIS products perform best at reflecting the spatial distributions and capturing the temporal trends of aerosol. This study help readers select a suitable aerosol dataset for their studies.
Delong Zhao, Mengyu Huang, Dantong Liu, Deping Ding, Ping Tian, Quan Liu, Wei Zhou, Jiujiang Sheng, Fei Wang, Kai Bi, Yan Yang, Xia Li, Yaqiong Hu, Xin Guo, Yang Gao, Hui He, Yunbo Chen, Shaofei Kong, and Jiayi Huang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1118, https://doi.org/10.5194/acp-2017-1118, 2018
Preprint withdrawn
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This study for the first time reports the 3D distributions of black carbon and detailed physical properties in the boundary layer over the North China Plain, using intensive aircraft measurements in both hot and cold seasons. The BC mass in the planetary boundary layer (PBL) was found to be largely influenced by meteorology which modulated the local emission and regional transport.
Xiaoning Xie, He Zhang, Xiaodong Liu, Yiran Peng, and Yangang Liu
Atmos. Chem. Phys., 17, 5877–5892, https://doi.org/10.5194/acp-17-5877-2017, https://doi.org/10.5194/acp-17-5877-2017, 2017
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New complete cloud parameterizations of cloud droplet effective radius and the two-moment cloud-to-rain autoconversion process explicitly accounting for dispersion are implemented into CAM5.1. The results show that the consideration of dispersion effect can significantly reduce the changes induced by anthropogenic aerosols in the cloud-top effective radius and the liquid water path, which reduces the AIF substantially at a global scale, especially in the Northern Hemisphere.
Y. Peng, V. K. Arora, W. A. Kurz, R. A. Hember, B. J. Hawkins, J. C. Fyfe, and A. T. Werner
Biogeosciences, 11, 635–649, https://doi.org/10.5194/bg-11-635-2014, https://doi.org/10.5194/bg-11-635-2014, 2014
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Software sustainability of global impact models
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Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20–30%. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases accessibility of training and working with the model.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-85, https://doi.org/10.5194/gmd-2024-85, 2024
Revised manuscript accepted for GMD
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This study provides the first comprehensive assessment of historical fire simulations from 19 CMIP6 ESMs. Most models reproduce global total, spatial pattern, seasonality, and regional historical changes well, but fail to simulate the recent decline in global burned area and underestimate the fire sensitivity to wet-dry conditions. They addressed three critical issues in CMIP5. We present targeted guidance for fire scheme development and methodologies to generate reliable fire projections.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Giovanni Di Virgilio, Jason Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew Riley, and Jyothi Lingala
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-87, https://doi.org/10.5194/gmd-2024-87, 2024
Revised manuscript accepted for GMD
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models, and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows to generate monthly means of local precipitation and temperature at low computational costs.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Emily Black, John Ellis, and Ross Maidment
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-75, https://doi.org/10.5194/gmd-2024-75, 2024
Revised manuscript accepted for GMD
Short summary
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We present General TAMSAT-ALERT: a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and forecasting data into probabilistic hazard assessments. As such, it complements existing systems and enhances their utility for actionable hazard assessment.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation
2. Multiple aerosol types, J. Geophys. Res.-Atmos., 105, 6837–6844,
https://doi.org/10.1029/1999JD901161, 2000.
Abdul-Razzak, H., Ghan, S. J., and Rivera-Carpio, C.: A parameterization of
aerosol activation 1. Single aerosol type, J. Geophys. Res.-Atmos., 103,
6123–6131, https://doi.org/10.1029/97JD03735, 1998.
Albanese, D., Riccadonna, S., Donati, C., and Franceschi, P.: A practical
tool for maximal information coefficient analysis, Gigascience, 7, 1–8,
https://doi.org/10.1093/gigascience/giy032, 2018.
Albrecht, B.: 2011 CIRPAS Twin Otter Navigation and State Parameters. Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.26023/36PD-HZKW-RJ03, 2008.
ARM (Atmospheric Radiation Measurement) user facility: Ambient Winds – AIMMS, updated hourly, 2014-02-15 to 2014-10-15, ARM Mobile Facility (MAO) Manacapuru, Amazonas, Brazil, compiled by: Hobbe, J., ARM Data Center [data set], https://adc.arm.gov/discovery/#/results/site_code::mao (last access: 26 October 2020), 2014a.
ARM (Atmospheric Radiation Measurement) user facility: Fast Cloud Droplet Probe (FCDP), updated hourly, 2014-02-15 to 2014-10-15, ARM Mobile Facility (MAO) Manacapuru, Amazonas, Brazil, compiled by: Mei, F., ARM Data Center [data set], https://adc.arm.gov/discovery/#/results/site_code::mao (last access: 26 October 2020), 2014b.
ARM (Atmospheric Radiation Measurement) user facility: Passive Cavity Aerosol Spectrometer, updated hourly, 2014-02-22 to 2014-3-23, ARM Mobile Facility (MAO) Manacapuru, Amazonas, Brazil, compiled by: Tomlinson, J., ARM Data Center [data set], https://adc.arm.gov/discovery/#/results/site_code::mao (last access: 26 October 2020), 2014c.
ARM (Atmospheric Radiation Measurement) user facility: Time of Flight Aerosol Mass Spectrometer, updated hourly, 2014-02-22 to 2014-03-23, ARM Mobile Facility (MAO) Manacapuru, Amazonas, Brazil, compiled by: Shilling, J., ARM Data Center [data set], https://adc.arm.gov/discovery/#/results/site_code::mao (last access: 26 October 2020), 2014d.
Barahona, D. and Nenes, A.: Parameterization of cloud droplet formation in
large-scale models: Including effects of entrainment, J. Geophys. Res.-Atmos., 112, D16206, https://doi.org/10.1029/2007JD008473, 2007.
Boucher, O. and Lohmann, U.: The sulfate-CCN-cloud albedo effect, Tellus B,
47, 281–300, https://doi.org/10.1034/j.1600-0889.47.issue3.1.x, 1995.
Brenguier, J. L.: Parameterization of the condensation process: a
theoretical approach, J. Atmos. Sci., 48, 264–282,
https://doi.org/10.1175/1520-0469(1991)048<0264:POTCPA>2.0.CO;2,
1991.
Chen, J., Liu, Y., Zhang, M., and Peng, Y.: New understanding and
quantification of the regime dependence of aerosol-cloud interaction for
studying aerosol indirect effects, Geophys. Res. Lett., 43, 1780–1787,
https://doi.org/10.1002/2016GL067683, 2016.
Cohard, J. M., Pinty, J. P., and Suhre, K.: On the parameterization of
activation spectra from cloud condensation nuclei microphysical properties,
J. Geophys. Res.-Atmos., 105, 11753–11766, https://doi.org/10.1029/1999JD901195,
2000.
Emanuel, K. A.: Atmospheric convection, Oxford University Press, ISBN 0195066308, 1994.
Ferek, R. J., Hegg, D. A., Hobbs, P. V., Durkee, P., and Nielsen, K.: Measurements of ship-induced tracks in clouds off the Washington coast, J. Geophys. Res.-Atmos., 103, 23199–23206, https://doi.org/10.1029/98JD02121, 1998.
Flossmann, A. I., Hall, W. D., and Pruppacher, H. R.: A Theoretical Study of the Wet Removal of Atmospheric Pollutants. Part I: The Redistribution of Aerosol Particles Captured through Nucleation and Impaction Scavenging by Growing Cloud Drops, J. Atmos. Sci., 42, 583–606, https://doi.org/10.1175/1520-0469(1985)042<0583:ATSOTW>2.0.CO;2, 1985.
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J. L., Frame, D., Lunt, D. J., Mauritsen, T., Palmer, M. D., Watanabe, M., Wild, M., and Zhang, H.: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu R., and Zhou B., Cambridge University Press, in press, 2022.
Forster, P. M., Richardson, T., Maycock, A. C., Smith, C. J., Samset, B. H.,
Myhre, G., Andrews, T., Pincus, R., and Schulz, M.: Recommendations for
diagnosing effective radiative forcing from climate models for CMIP6, J.
Geophys. Res., 121, 12460–12475, https://doi.org/10.1002/2016JD025320, 2016.
Fountoukis, C. and Nenes, A.: Continued development of a cloud droplet
formation parameterization for global climate models, J. Geophys. Res. D
Atmos., 110, 1–10, https://doi.org/10.1029/2004JD005591, 2005.
Fountoukis, C., Nenes, A., Meskhidze, N., Bahreini, R., Conant, W. C.,
Jonsson, H., Murphy, S., Sorooshian, A., Varutbangkul, V., Brechtel, F.,
Flagan, R. C., and Seinfeld, J. H.: Aerosol-cloud drop concentration closure
for clouds sampled during the International Consortium for Atmospheric
Research on Transport and Transformation 2004 campaign, J. Geophys. Res.-Atmos., 112, D10, https://doi.org/10.1029/2006JD007272, 2007.
Gerber, H. E., Frick, G. M., Jensen, J. B., and Hudson, J. G.: Entrainment,
mixing, and microphysics in trade-wind cumulus, J. Meteorol. Soc. Japan,
86A, 87–106, https://doi.org/10.2151/jmsj.86a.87, 2008.
Ghan, S. J.: Technical Note: Estimating aerosol effects on cloud radiative forcing, Atmos. Chem. Phys., 13, 9971–9974, https://doi.org/10.5194/acp-13-9971-2013, 2013.
Ghan, S. J., Abdul-Razzak, H., Nenes, A., Ming, Y., Liu, X., Ovchinnikov, M., Shipway, B., Meskhidze, N., Xu, J., and Shi, X.: Droplet nucleation: Physically-based parameterizations and comparative evaluation, J. Adv. Model. Earth Sys., 3, M10001, https://doi.org/10.1029/2011MS000074, 2011.
Guibert, S., Snider, J. R., and Brenguier, J. L.: Aerosol activation in
marine stratocumulus clouds: 1. Measurement validation for a closure study,
J. Geophys. Res.-Atmos., 108, 8628, https://doi.org/10.1029/2002jd002678, 2003.
Hallberg, A., Wobrock, W., Flossmann, A. I., Bower, K. N., Noone, K. J.,
Wiedensohler, A., Hansson, H. C., Wendisch, M., Berner, A., Kruisz, C., Laj,
P., Facchini, M. C., Fuzzi, S., and Arends, B. G.: Microphysics of clouds:
Model vs measurements, Atmos. Environ., 31, 2453–2462,
https://doi.org/10.1016/S1352-2310(97)00041-1, 1997.
Herrington, A. R. and Reed, K. A.: On resolution sensitivity in the
Community Atmosphere Model, Q. J. R. Meteorol. Soc., 146, 3789–3807,
https://doi.org/10.1002/qj.3873, 2020.
Jarecka, D., Pawlowska, H., Grabowski, W. W., and Wyszogrodzki, A. A.: Modeling microphysical effects of entrainment in clouds observed during EUCAARI-IMPACT field campaign, Atmos. Chem. Phys., 13, 8489–8503, https://doi.org/10.5194/acp-13-8489-2013, 2013.
Jones, A. and Slingo, A.: Predicting cloud-droplet effective radius and
indirect sulphate aerosol forcing using a general circulation model, Q. J.
R. Meteorol. Soc., 122, 1573–1595, https://doi.org/10.1002/qj.49712253506, 1996.
Jones, A., Roberts, D. L., and Slingo, A.: A climate model study of indirect
radiative forcing by anthropogenic sulphate aerosols, Nature, 370,
450–453, https://doi.org/10.1038/370450a0, 1994.
Kang, I. S., Yang, Y. M., and Tao, W. K.: GCMs with implicit and explicit
representation of cloud microphysics for simulation of extreme precipitation
frequency, Clim. Dyn., 45, 325–335, https://doi.org/10.1007/s00382-014-2376-1,
2015.
Khain, A. P., Beheng, K. D., Heymsfield, A., Korolev, A., Krichak, S. O.,
Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., Van Den
Heever, S. C., and Yano, J. I.: Representation of microphysical processes in
cloud-resolving models: Spectral (bin) microphysics versus bulk
parameterization, Rev. Geophys., 53, 247–322, https://doi.org/10.1002/2014RG000468,
2015.
Khvorostyanov, V. I. and Curry, J. A.: Parameterization of cloud drop
activation based on analytical asymptotic solutions to the supersaturation
equation, J. Atmos. Sci., 66, 1905–1925, https://doi.org/10.1175/2009JAS2811.1,
2009.
Kiehl, J. T., Schneider, T. L., Rasch, P. J., Barth, M. C., and Wong, J.:
Radiative forcing due to sulfate aerosols from simulations with the National
Center for Atmospheric Research Community Climate Model, Version 3, J.
Geophys. Res.-Atmos., 105, 1441–1457, https://doi.org/10.1029/1999JD900495, 2000.
Kivekäs, N., Kerminen, V. M., Anttila, T., Korhonen, H., Lihavainen, H.,
Komppula, M., and Kulmala, M.: Parameterization of cloud droplet activation
using a simplified treatment of the aerosol number size distribution, J.
Geophys. Res.-Atmos., 113, D15207, https://doi.org/10.1029/2007JD009485, 2008.
Kleinman, L. I., Daum, P. H., Lee, Y.-N., Lewis, E. R., Sedlacek III, A. J., Senum, G. I., Springston, S. R., Wang, J., Hubbe, J., Jayne, J., Min, Q., Yum, S. S., and Allen, G.: Aerosol concentration and size distribution measured below, in, and above cloud from the DOE G-1 during VOCALS-REx, Atmos. Chem. Phys., 12, 207–223, https://doi.org/10.5194/acp-12-207-2012, 2012.
Kreidenweis, S. M., Petters, M. D., and DeMott, P. J.: Single-parameter estimates of aerosol water content, Environ. Res. Lett., 3, 035002, https://doi.org/10.1088/1748-9326/3/3/035002, 2008.
Li, S., Zhang, F., Jin, X., Sun, Y., Wu, H., Xie, C., Chen, L., Liu, J., Wu,
T., Jiang, S., Cribb, M., and Li, Z.: Characterizing the ratio of nitrate to
sulfate in ambient fine particles of urban Beijing during 2018–2019, Atmos.
Environ., 237, 117662, https://doi.org/10.1016/j.atmosenv.2020.117662, 2020.
Li, S. M., Strawbridge, K. B., Leaitch, W. R., and Macdonald, A. M.: Aerosol
backscattering determined from chemical and physical properties and lidar
observations over the east coast of Canada, Geophys. Res. Lett., 25,
1653–1656, https://doi.org/10.1029/98GL00910, 1998.
Liu, Q., Liu, D., Gao, Q., Tian, P., Wang, F., Zhao, D., Bi, K., Wu, Y., Ding, S., Hu, K., Zhang, J., Ding, D., and Zhao, C.: Vertical characteristics of aerosol hygroscopicity and impacts on optical properties over the North China Plain during winter, Atmos. Chem. Phys., 20, 3931–3944, https://doi.org/10.5194/acp-20-3931-2020, 2020.
Lohmann, U.: Impact of sulfate aerosols on albedo and lifetime of clouds: A
sensitivity study with the ECHAM4 GCM, J. Geophys. Res.-Atmos., 102,
13685–13700, https://doi.org/10.1029/97JD00631, 1997.
Martin, S. T., Artaxo, P., Machado, L. A. T., Manzi, A. O., Souza, R. A. F., Schumacher, C., Wang, J., Andreae, M. O., Barbosa, H. M. J., Fan, J., Fisch, G., Goldstein, A. H., Guenther, A., Jimenez, J. L., Pöschl, U., Silva Dias, M. A., Smith, J. N., and Wendisch, M.: Introduction: Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5), Atmos. Chem. Phys., 16, 4785–4797, https://doi.org/10.5194/acp-16-4785-2016, 2016.
Martin, S. T., Artaxo, P., Machado, L., Manzi, A. O., Souza, R. A. F.,
Schumacher, C., Wang, J., Biscaro, T., Brito, J., Calheiros, A., Jardine,
K., Medeiros, A., Portela, B., De Sá, S. S., Adachi, K., Aiken, A. C.,
Alblbrecht, R., Alexander, L., Andreae, M. O., Barbosa, H. M. J., Buseck,
P., Chand, D., Comstmstmstock, J. M., Day, D. A., Dubey, M., Fan, J.,
Fastst, J., Fisch, G., Fortner, E., Giangrande, S., Gilllles, M.,
Goldststein, A. H., Guenther, A., Hubbbbe, J., Jensen, M., Jimenez, J. L.,
Keutstsch, F. N., Kim, S., Kuang, C., Laskskin, A., McKinney, K., Mei, F.,
Millller, M., Nascimento, R., Pauliquevis, T., Pekour, M., Peres, J.,
Petäjä, T., Pöhlklker, C., Pöschl, U., Rizzo, L., Schmid,
B., Shilllling, J. E., Silva Dias, M. A., Smith, J. N., Tomlmlinson, J. M.,
Tóta, J., and Wendisch, M.: The green ocean amazon experiment
(GOAMAZON2014/5) observes pollution affecting gases, aerosols, clouds, and
rainfall over the rain forest, B. Am. Meteorol. Soc., 98, 981–997,
https://doi.org/10.1175/BAMS-D-15-00221.1, 2017.
Menon, S., Del Genio, A. D., Koch, D., and Tselioudis, G.: GCM simulations of
the aerosol indirect effect: Sensitivity to cloud parameterization and
aerosol Burden, J. Atmos. Sci., 59, 692–713,
https://doi.org/10.1175/1520-0469(2002)059<0692:gsotai>2.0.co;2,
2002.
Meskhidze, N., Nenes, A., Conant, W. C., and Seinfeld, J. H.: Evaluation of a
new cloud droplet activation parameterization with in situ data from
CRYSTAL-FACE and CSTRIPE, J. Geophys. Res. D Atmos., 110, 1–10,
https://doi.org/10.1029/2004JD005703, 2005.
Ming, Y., Ramaswamy, V., Donner, L. J., and Phillips, V. T. J.: A new
parameterization of cloud droplet activation applicable to general
circulation models, J. Atmos. Sci., 63, 1348–1356,
https://doi.org/10.1175/JAS3686.1, 2006.
Morrison, H. and Pinto, J. O.: Mesoscale modeling of springtime arctic
mixed-phase stratiform clouds using a new two-moment bulk microphysics
scheme, J. Atmos. Sci., 62, 3683–3704, https://doi.org/10.1175/JAS3564.1, 2005.
Murray, F. W.: On the Computation of Saturation Vapor Pressure, J. Appl.
Meteorol., 6, 203–204, https://doi.org/10.1175/1520-0450(1967)006<0203:otcosv>2.0.co;2, 1967.
Nakao, S., Tang, P., Tang, X., Clark, C. H., Qi, L., Seo, E., Asa-Awuku, A.,
and Cocker, D.: Density and elemental ratios of secondary organic aerosol:
Application of a density prediction method, Atmos. Environ., 68, 273–277,
https://doi.org/10.1016/j.atmosenv.2012.11.006, 2013.
Nenes, A. and Seinfeld, J. H.: Parameterization of cloud droplet formation
in global climate models, J. Geophys. Res.-Atmos., 108, 4415,
https://doi.org/10.1029/2002jd002911, 2003.
Nenes, A., Ghan, S., Abdul-Razzak, H., Chuang, P. Y., and Seinfeld, J. H.: Kinetic limitations on cloud droplet formation and impact on cloud albedo, Tellus B, 53, 133–149, https://doi.org/10.3402/tellusb.v53i2.16569, 2001.
Pandis, S. N., Seinfeld, J. H., and Pilinis, C.: Chemical composition
differences in fog and cloud droplets of different sizes, Atmos. Environ.
Part A, Gen. Top., 24, 1957–1969, https://doi.org/10.1016/0960-1686(90)90529-V,
1990.
Peng, Y., Lohmann, U., Leaitch, R., Banic, C., and Couture, M.: The cloud
albedo-cloud droplet effective radius relationship for clean and polluted
clouds from RACE and FIRE.ACE, J. Geophys. Res.-Atmos., 107, AAC
1-1–AAC 1-6, https://doi.org/10.1029/2000JD000281, 2002.
Peng, Y., Lohmann, U., and Leaitch, W. R.: Importance of vertical velocity
variations in the cloud droplet nucleation process of marine stratus clouds,
J. Geophys. Res.-Atmos., 110, 1–13, https://doi.org/10.1029/2004JD004922, 2005.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007.
Pruppacher, H. R., Klett, J. D., and Wang, P. K.: Microphysics of Clouds and
Precipitation, Aerosol Sci. Technol., 28, 381–382,
https://doi.org/10.1080/02786829808965531, 1998.
Ramaswamy, V., Collins, W., Haywood, J., Lean, J., Mahowald, N., Myhre, G., Naik, V., Shine, K. P., Soden, B., Stenchikov, G., and Storelvmo, T.: Radiative Forcing of Climate: The Historical Evolution of the Radiative Forcing Concept, the Forcing Agents and their Quantification, and Applications, Meteorol. Monogr., 59, 14.1–14.101, https://doi.org/10.1175/amsmonographs-d-19-0001.1, 2019.
Reshef, D. N., Reshef, Y. A., Finucane, H. K., Grossman, S. R., McVean, G.,
Turnbaugh, P. J., Lander, E. S., Mitzenmacher, M., and Sabeti, P. C.:
Detecting novel associations in large data sets, Science,
334, 1518–1524, https://doi.org/10.1126/science.1205438, 2011.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From
Air Pollution to Climate Change, 3rd edn., John Wiley and Sons Inc., New York, USA, ISBN 978-1-118-94740-1, 2016.
Shilling, J. E., Pekour, M. S., Fortner, E. C., Artaxo, P., de Sá, S., Hubbe, J. M., Longo, K. M., Machado, L. A. T., Martin, S. T., Springston, S. R., Tomlinson, J., and Wang, J.: Aircraft observations of the chemical composition and aging of aerosol in the Manaus urban plume during GoAmazon 2014/5, Atmos. Chem. Phys., 18, 10773–10797, https://doi.org/10.5194/acp-18-10773-2018, 2018.
Shipway, B. J. and Abel, S. J.: Analytical estimation of cloud droplet
nucleation based on an underlying aerosol population, Atmos. Res., 96,
344–355, https://doi.org/10.1016/j.atmosres.2009.10.005, 2010.
Slawinska, J., Grabowski, W. W., Pawlowska, H., and Morrison, H.: Droplet
activation and mixing in large-eddy simulation of a shallow cumulus field,
J. Atmos. Sci., 69, 444–462, https://doi.org/10.1175/JAS-D-11-054.1, 2012.
Snider, J. R. and Brenguier, J. L.: Cloud condensation nuclei and cloud
droplet measurements during ACE-2, Tellus B,
52, 828–842, https://doi.org/10.1034/j.1600-0889.2000.00044.x, 2000.
Snider, J. R., Guibert, S., Brenguier, J. L., and Putaud, J. P.: Aerosol
activation in marine stratocumulus clouds: 2. Köhler and parcel theory
closure studies, J. Geophys. Res.-Atmos., 108, 8629, https://doi.org/10.1029/2002jd002692,
2003.
Twomey, S.: Pollution and the planetary albedo, Atmos. Environ., 8, 1251–1256, https://doi.org/10.1016/0004-6981(74)90004-3, 1974.
Twomey, S.: The Influence of Pollution on the Shortwave Albedo of Clouds, J. Atmos. Sci., 34, 1149–1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977.
UCAR/NCAR – Earth Observing Laboratory: 1970. DOE Gulf Stream 1 (G-1) CAS Data, Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://data.eol.ucar.edu/dataset/89.262 (last access: 30 January 2018), 2008a.
UCAR/NCAR – Earth Observing Laboratory: 1970. DOE Gulf Stream 1 (G-1) LWC (Gerber Probe) Data, Version 1.0. UCAR/NCAR – Earth Observing Laboratory [data set], https://data.eol.ucar.edu/dataset/89.288 (last access: 30 January 2018), 2008b.
UCAR/NCAR – Earth Observing Laboratory: 1970. DOE Gulf Stream 1 (G-1) Navigation and State Parameters, Version 1.0. UCAR/NCAR – Earth Observing Laboratory [data set], https://data.eol.ucar.edu/dataset/89.217 (last access: 30 January 2018), 2008c.
UCAR/NCAR – Earth Observing Laboratory: 1970. DOE Gulf Stream 1 (G-1) PCASP Data, Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://data.eol.ucar.edu/dataset/89.289 (last access: 30 January 2018), 2008d.
Wang, H., Peng, Y., Salzen, K. von, Yang, Y., Zhou, W., and Zhao, D.:
Evaluation of a numerically efficient aerosol activation scheme by using
cloud data from multiple aircraft campaigns in continental and marine
regions, Zenodo [data set and code], https://doi.org/10.5281/ZENODO.4841035, 2021.
Wang, M., Peng, Y., Liu, Y., Liu, Y., Xie, X., and Guo, Z.: Understanding
Cloud Droplet Spectral Dispersion Effect Using Empirical and Semi-Analytical
Parameterizations in NCAR CAM5.3, Earth Sp. Sci., 7, e2020EA001276,
https://doi.org/10.1029/2020EA001276, 2020.
Wexler, A. S. and Clegg, S. L.: Atmospheric aerosol models for systems
including the ions H+, NH4+, Na+, so42−, NO3−, Cl−, Br−, and H2O, J.
Geophys. Res.-Atmos., 107, 4207, https://doi.org/10.1029/2001JD000451, 2002.
Whitby, K. T.: The physical characteristics of sulfur aerosols, Atmos.
Environ., 12, 135–159, https://doi.org/10.1016/0004-6981(78)90196-8, 1978.
Wood, R., Mechoso, C. R., Bretherton, C. S., Weller, R. A., Huebert, B., Straneo, F., Albrecht, B. A., Coe, H., Allen, G., Vaughan, G., Daum, P., Fairall, C., Chand, D., Gallardo Klenner, L., Garreaud, R., Grados, C., Covert, D. S., Bates, T. S., Krejci, R., Russell, L. M., de Szoeke, S., Brewer, A., Yuter, S. E., Springston, S. R., Chaigneau, A., Toniazzo, T., Minnis, P., Palikonda, R., Abel, S. J., Brown, W. O. J., Williams, S., Fochesatto, J., Brioude, J., and Bower, K. N.: The VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx): goals, platforms, and field operations, Atmos. Chem. Phys., 11, 627–654, https://doi.org/10.5194/acp-11-627-2011, 2011.
Zamora, M. L., Peng, J., Hu, M., Guo, S., Marrero-Ortiz, W., Shang, D., Zheng, J., Du, Z., Wu, Z., and Zhang, R.: Wintertime aerosol properties in Beijing, Atmos. Chem. Phys., 19, 14329–14338, https://doi.org/10.5194/acp-19-14329-2019, 2019.
Zhang, Y., Zhang, X., Wang, K., He, J., Leung, L. R., Fan, J., and Nenes, A.:
Incorporating an advanced aerosol activation parameterization into WRF-CAM5:
Model evaluation and parameterization intercomparison, J. Geophys. Res.,
120, 6952–6979, https://doi.org/10.1002/2014JD023051, 2015.
Zhou, W., Gao, M., He, Y., Wang, Q., Xie, C., Xu, W., Zhao, J., Du, W., Qiu, Y., Lei, L., Fu, P., Wang, Z., Worsnop, D. R., Zhang, Q., and Sun, Y.: Response of aerosol chemistry to clean air action in Beijing, China: Insights from two-year ACSM measurements and model simulations, Environ. Pollut., 255, 113345, https://doi.org/10.1016/j.envpol.2019.113345, 2019.
Short summary
The aerosol activation scheme is an important part of the general circulation model, but evaluations using observed data are mostly regional. This research introduced a numerically efficient aerosol activation scheme and evaluated it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The decent performance indicates that the scheme is suitable for simulations of cloud droplet number concentrations over wide conditions.
The aerosol activation scheme is an important part of the general circulation model, but...
