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
Related authors
No articles found.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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. Discuss., https://doi.org/10.5194/gmd-2024-24, https://doi.org/10.5194/gmd-2024-24, 2024
Revised manuscript under review for GMD
Short summary
Short summary
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 changing climate.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Related subject area
Climate and Earth system modeling
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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”.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
Short summary
Short summary
We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
Short summary
Short summary
For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
Short summary
Short summary
Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
Short summary
Short summary
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
Short summary
Short summary
Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
Short summary
Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
Short summary
Short summary
Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
Short summary
Short summary
We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
Short summary
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
Short summary
This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
Short summary
Short summary
This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Short summary
Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
Short summary
Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
Short summary
Short summary
Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. 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 testbed for climate attribution studies.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
Short summary
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
Short summary
Short summary
A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
Short summary
Short summary
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
Short summary
Short summary
The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
Short summary
Short summary
We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
Short summary
Short summary
This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
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...
