Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2975-2023
© Author(s) 2023. 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-16-2975-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
31 May 2023
Model evaluation paper |
| 31 May 2023
| 31 May 2023
Intercomparison of the weather and climate physics suites of a unified forecast–climate model system (GRIST-A22.7.28) based on single-column modeling
Xiaohan Li
2035 Future Laboratory, PIESAT Information Technology Co Ltd., Beijing, China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
2035 Future Laboratory, PIESAT Information Technology Co Ltd., Beijing, China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Beijing Research Institute, Nanjing University of Information Science
and Technology, Beijing, China
Xindong Peng
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Division of Numerical Model Techniques, CMA Earth System Modeling and Prediction Center, Beijing, China
Baiquan Zhou
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Jian Li
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Yiming Wang
2035 Future Laboratory, PIESAT Information Technology Co Ltd., Beijing, China
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Xiaohan Li, Yi Zhang, Xindong Peng, and Jian Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-254, https://doi.org/10.5194/gmd-2020-254, 2020
Revised manuscript not accepted
Short summary
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This study develops a single-column model (SGRIST1.0) to bridge the coupling of physical parameterizations and a new unstructured-mesh modeling system. The physical parameterization suite is first isolated and evaluated via SGRIST1.0 to reduce the uncertainty of physics during transfer, then the validated parameterization suite is coupled to the 3D dynamical framework. The transferred package shows reasonable behavior in the full physics-dynamics interaction.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Yihui Zhou, Yi Zhang, Jian Li, Rucong Yu, and Zhuang Liu
Geosci. Model Dev., 13, 6325–6348, https://doi.org/10.5194/gmd-13-6325-2020, https://doi.org/10.5194/gmd-13-6325-2020, 2020
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This paper explores the configuration of a global atmospheric model (global-to-regional integrated forecast system-atmosphere; GRIST-A) with various multiresolution grids. The model performance is evaluated from dry dynamics to simple physics and full physics. The model is able to resolve the fine-scale structures in the grid-refinement region, and the adverse impact due to the mesh transition and the coarse-resolution area can be controlled well.
Xiaohan Li, Yi Zhang, Xindong Peng, and Jian Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-254, https://doi.org/10.5194/gmd-2020-254, 2020
Revised manuscript not accepted
Short summary
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This study develops a single-column model (SGRIST1.0) to bridge the coupling of physical parameterizations and a new unstructured-mesh modeling system. The physical parameterization suite is first isolated and evaluated via SGRIST1.0 to reduce the uncertainty of physics during transfer, then the validated parameterization suite is coupled to the 3D dynamical framework. The transferred package shows reasonable behavior in the full physics-dynamics interaction.
Zhuang Liu, Yi Zhang, Xiaomeng Huang, Jian Li, Dong Wang, Mingqing Wang, and Xing Huang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-158, https://doi.org/10.5194/gmd-2020-158, 2020
Revised manuscript not accepted
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This paper describes several techniques for the parallelization and performance optimization of
an unstructured-mesh global atmospheric model. The purpose of this research is to facilitate the rapid iterative model development. These techniques are general and can be used for other parallel modeling on unstructured meshes.
Anlun Xu and Jian Li
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1131, https://doi.org/10.5194/acp-2019-1131, 2020
Revised manuscript not accepted
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Based on 12-year eddy covariance measurement over an agricultural field, we investigated the diurnal, seasonal and inter-annual changes in sensible heat flux, latent heat flux and carbon dioxide flux and their meteorological controls on multiple timescales. We found that each control has distinct effect on turbulent heat and dioxide flux over different temporal scales. Our results are useful for improving the numerical modelling of physical atmosphere-land processes over the complex terrain.
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Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Álvaro González-Cervera and Luis Durán
EGUsphere, https://doi.org/10.5194/egusphere-2024-958, https://doi.org/10.5194/egusphere-2024-958, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the Analog Method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities of broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-84, https://doi.org/10.5194/gmd-2024-84, 2024
Revised manuscript accepted for GMD
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We apply a comprehensive approach to select a subset of CMIP6 that is suitable for dynamical downscaling over Southeast Asia by considering model performance, model independence, data availability, and future climate change spread. The standardised benchmarking framework is applied to identify a subset of models through two stages of assessment: statistical-based and process-based metrics. We finalize a sub-set of two independent models for dynamical downscaling over Southeast Asia.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
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HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Cited articles
Bechtold, P., Semane, N., Lopez, P., Chaboureau, J. P., Beljaars, A., and
Bormann, N.: The role of shallow convection in ECMWF's Integrated
Forecasting System, ECMWF Technical Memoranda, 2014.
Bretherton, C. S. and Park, S.: The University of Washington Shallow
Convection and Moist Turbulence Schemes and Their Impact on Climate
Simulations with the Community Atmosphere Model, J. Climate, 22,
3449–3469, https://doi.org/10.1175/2008jcli2557.1, 2009.
Bogenschutz, P. A., Gettelman, A., Morrison, H., Larson, V. E., Schanen, D. P., Meyer, N. R., and Craig, C.: Unified parameterization of the planetary boundary layer and shallow convection with a higher-order turbulence closure in the Community Atmosphere Model: single-column experiments, Geosci. Model Dev., 5, 1407–1423, https://doi.org/10.5194/gmd-5-1407-2012, 2012.
Brown, A., Milton, S., Cullen, M., Golding, B., Mitchell, J., and Shelly,
A.: Unified Modeling and Prediction of Weather and Climate: A 25-Year
Journey, B. Am. Meteorol. Soc., 93, 1865–1877,
https://doi.org/10.1175/BAMS-D-12-00018.1, 2012.
Chepfer, H., Bony, S., Winker, D., Cesana, G., Dufresne, J. L., Minnis, P.,
Stubenrauch, C. J., and Zeng, S.: The GCM-oriented CALIPSO cloud product (CALIPSO-GOCCP), J.
Geophys. Res., 115, D00H16,
https://doi.org/10.1029/2009JD012251, 2010.
Davies, L., Jakob, C., Cheung, K., Genio, A. D., Hill, A., Hume, T., Keane,
R. J., Komori, T., Larson, V. E., Lin, Y., Liu, X., Nielsen, B. J., Petch,
J., Plant, R. S., Singh, M. S., Shi, X., Song, X., Wang, W., Whitall, M. A.,
Wolf, A., Xie, S., and Zhang, G.: A single-column model ensemble approach
applied to the TWP-ICE experiment, J. Geophys. Res.-Atmos., 118, 6544–6563, https://doi.org/10.1002/jgrd.50450, 2013.
Gettelman, A., Liu, X., Ghan, S. J., Morrison, H., Park, S., Conley, A. J.,
Klein, S. A., Boyle, J., Mitchell, D. L., and Li, J. L. F.: Global
simulations of ice nucleation and ice supersaturation with an improved cloud
scheme in the Community Atmosphere Model, J. Geophys. Res.,
115, D18216, https://doi.org/10.1029/2009jd013797, 2010.
Gettelman, A., Truesdale, J. E., Bacmeister, J. T., Caldwell, P. M., Neale,
R. B., Bogenschutz, P. A., and Simpson, I. R.: The Single Column Atmosphere
Model version 6 (SCAM6): Not a scam but a tool for model evaluation and
development, J. Adv. Model. Earth Sy., 11, 1381–1401,
https://doi.org/10.1029/2018MS001578, 2019.
Guo, Z., Wang, M., Qian, Y., Larson, V. E., Ghan, S., Ovchinnikov, M.,
Bogenschutz, P. A., Zhao, C., Lin, G., and Zhou, T.: A sensitivity analysis
of cloud properties to CLUBB parameters in the single-column Community
Atmosphere Model (SCAM5), J. Adv. Model. Earth Sy., 6,
829–858, https://doi.org/10.1002/2014MS000315, 2014.
Hong, S.-Y. and Lim, J.-O. J.: The WRF Single-Moment 6-Class Microphysics
Scheme (WSM6), J. Korean Meteor. Soc., 42, 129–151,
2006.
Hong, S. Y. and Pan, H. L.: Nonlocal boundary layer vertical diffusion in a
medium-range forecast model, Mon. Weather Rev., 124, 2322–2339, 1996.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S.
A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases
Calculations with the AER radiative transfer models, J. Geophys. Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008.
Kain, J. S. and Fritsch, J. M.: A one-dimensional entrainingdetraining plume
model and its application in convective parameterization, J.
Atmos. Sci., 47, 2784–2802, 1990.
Li, J. and Zhang, Y.: Enhancing the stability of a global model by using an
adaptively implicit vertical moist transport scheme, Meteorol.
Atmos. Phys., 134, 55, https://doi.org/10.1007/s00703-022-00895-5, 2022.
Li, X.: Code and data availability, Zenodo [code], https://doi.org/10.5281/zenodo.7350131, 2022.
Li, X., Peng, X., and Zhang, Y.: Investigation of the effect of the time
step on the physics–dynamics interaction in CAM5 using an idealized
tropical cyclone experiment, Clim. Dynam., 55, 665–680,
https://doi.org/10.1007/s00382-020-05284-5, 2020.
Li, X., Zhang, Y., Peng, X., Chu, W., Lin, Y., and Li, J.: Improved Climate
Simulation by Using a Double-Plume Convection Scheme in a Global Model,
J. Geophys. Res.-Atmos., 127, e2021JD036069, https://doi.org/10.1029/2021jd036069,
2022a.
Li, X., Zhang, Y., Lin, Y. L., Peng, X. D., Zhou, B. Q., Zhai, P. M., and
Li, J.: Impact of a revised trigger-closure of the double-plume convective
parameterization on precipitation simulation over East Asia, Adv.
Atmos. Sci., 40, 1225–1243, https://doi.org/10.1007/s00376-022-2225-9, 2023.
Lin, Y., Zhao, M., Ming, Y., Golaz, J. C., Donner, L. J., Klein, S. A.,
Ramaswamy, V., and Xie, S.: Precipitation Partitioning, Tropical Clouds, and
Intraseasonal Variability in GFDL AM2, J. Climate, 26, 5453–5466,
https://doi.org/10.1175/jcli-d-12-00442.1, 2013.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Smith, N. M., and Wong, T.: Toward optimal closure of the Earth's top-of-at- mosphere
radiation budget, J. Climate, 22, 748–766,
https://doi.org/10.1175/2008JCLI2637.1, 2009.
Morrison, H. and Gettelman, A.: A New Two-Moment Bulk Stratiform Cloud
Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3).
Part I: Description and Numerical Tests, J. Climate, 21, 3642–3659,
https://doi.org/10.1175/2008jcli2105.1, 2008.
Neale, R. B., Richter, J. H., and Jochum, M.: The Impact of Convection on
ENSO: From a Delayed Oscillator to a Series of Events, J. Climate,
21, 5904–5924, https://doi.org/10.1175/2008jcli2244.1, 2008.
Park, S. and Bretherton, C. S.: A New Moist Turbulence Parameterization in
the Community Atmosphere Model, J. Climate, 22, 3422–3448,
https://doi.org/10.1175/2008jcli2556.1, 2009.
Park, S., Bretherton, C. S., and Rasch, P. J.: Integrating Cloud Processes
in the Community Atmosphere Model, Version 5, J. Climate, 27,
6821–6856, https://doi.org/10.1175/jcli-d-14-00087.1, 2014.
Randall, D. A., Bitz, C. M., Danabasoglu, G., Denning, A. S., Gent, P. R.,
Gettelman, A., Griffies, S. M., Lynch, P., Morrison, H., Pincus, R., and
Thuburn, J.: 100 Years of Earth System Model Development, Meteorol.
Monogr., 59, 12.11–12.66, https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0018.1, 2018.
Rasch, P. J. and Kristjansson, J. E.: A Comparison of the CCM3 Model Climate
Using Diagnosed and Predicted Condensate Parameterizations, J.
Climate, 11, 1587–1614, https://doi.org/10.1175/1520-0442(1998)011<1587:acotcm>2.0.co;2, 1998.
Richter, J. H. and Rasch, P. J.: Effects of Convective Momentum Transport on
the Atmospheric Circulation in the Community Atmosphere Model, Version 3,
J. Climate, 21, 1487–1499, https://doi.org/10.1175/2007jcli1789.1, 2008.
Santos, S. P., Caldwell, P. M., and Bretherton, C. S.: Cloud Process
Coupling and Time Integration in the E3SM Atmosphere Model, J.
Adv. Model. Earth Sy., 13, e2020MS002359, https://doi.org/10.1029/2020ms002359, 2021.
Stevens, B., Moeng, C-H, Ackerman, A. S., Bretherton, C. S., Chlond, A., Roode, S., Edwards, J., Golaz, J.-C., Jiang, H. L., Khairoutdinov, M., Kirkpatrick, M. P., Lewellen, D. C., Lock, A., Muller, F., Stevens, D. E., Whelan, E., and Zhu, P.: Evaluation of Large-Eddy
Simulations via Observations of Nocturnal Marine Stratocumulus, Mon.
Weather Rev., 133, 1443–1462, 2005 (data available at: https://gcss-dime.giss.nasa.gov/pub/DYCOMS-II/GCSS7-RF01/gcss7.nc, last access: 30 May 2023).
Sundqvist, H.: A parameterization scheme for non-convective condensation
including prediction of cloud water content, Q. J. Roy.
Meteor. Soc., 104, 677–690, https://doi.org/10.1002/qj.49710444110, 1978.
Tang, S. Q., Xie, S. C., Guo, Z., Hong, S. Y., Khouider, B., Klocke, D., Köhler, M., Koo, M. S., Krishna, P. M., Larson, V. E., Park, S., Vaillancourt, P. A., Wang, Y. C., Yang, J., Daleu, C. L., Homeyer, C. R., Jones, T. R., Malap, N., Neggers, R., Prabhakaran, T., Ramirez, E., Schumacher, C., Tao, C., Bechtold, P., Ma, H. Y., Neelin, J. D., and Zeng, X. B.: Long-term single-column model intercomparison
ofdiurnal cycle ofprecipitation over midlatitude and tropical land,
Q. J. Roy.
Meteor. Soc., 148, 641–669, https://doi.org/10.1002/qj.4222, 2022.
Wan, H., Rasch, P. J., Zhang, K., Kazil, J., and Leung, L. R.: Numerical issues associated with compensating and competing processes in climate models: an example from ECHAM-HAM, Geosci. Model Dev., 6, 861–874, https://doi.org/10.5194/gmd-6-861-2013, 2013.
Wan, H., Rasch, P. J., Zhang, K., Qian, Y., Yan, H., and Zhao, C.: Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models, Geosci. Model Dev., 7, 1961–1977, https://doi.org/10.5194/gmd-7-1961-2014, 2014.
Wan, H., Rasch, P. J., Taylor, M. A., and Jablonowski, C.: Short-term time
step convergence in a climate model, J. Adv. Model. Earth
Sy., 7, 215–225, https://doi.org/10.1002/2014MS000368, 2015.
Wan, H., Zhang, S., Rasch, P. J., Larson, V. E., Zeng, X., and Yan, H.: Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1, Geosci. Model Dev., 14, 1921–1948, https://doi.org/10.5194/gmd-14-1921-2021, 2021.
Wang, L., Zhang, Y., Li, J., Liu, Z., and Zhou, Y.: Understanding the
Performance of an Unstructured-Mesh Global Shallow Water Model on Kinetic
Energy Spectra and Nonlinear Vorticity Dynamics,
J. Meteorol. Res., 33, 1075–1097, https://doi.org/10.1007/s13351-019-9004-2, 2019.
Wicker, L. J. and Skamarock, W. C.: Time-splitting methods for elastic models using forward time schemes, Mon. Weather Rev., 130, 2088–2097
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002.
Williamson, D. L.: The effect of time steps and time-scales on
parametrization suites, Q. J. Roy. Meteor.
Soc., 139, 548–560, https://doi.org/10.1002/qj.1992, 2013.
Xu, K. and Randall, D. A.: A semiempirical cloudiness parameterization for
use in climate models, J. Atmos. Sci., 53,
3084–3102, 1996.
Yanai, M., Esbensen, S., and Chu, J.-H.: Determination of bulk properties of
tropical cloud clusters from large-scale heat and moisture budgets, J. Atmos. Sci., 30, 611–627, 1973.
Yao, M. and Austin, P. M.: A model for hydrometeor growth and evolution of
raindrop size spectra in cumulus cells, J. Atmos. Sci.,
36, 655–668, 1979.
Yu, R., Zhang, Y., Wang, J., Li, J., Chen, H., Gong, J., and Chen, J.:
Recent Progress in Numerical Atmospheric Modeling in China, Adv.
Atmos. Sci., 36, 938–960, https://doi.org/10.1007/s00376-019-8203-1, 2019.
Zhang, C. and Wang, Y.: Projected Future Changes of Tropical Cyclone
Activity over the Western North and South Pacific in a 20-km-Mesh Regional
Climate Model, J. Climate, 30, 5923–5941,
https://doi.org/10.1175/jcli-d-16-0597.1, 2017.
Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to the
parameterization of cumulus convection in the Canadian climate centre
general circulation model, Atmos. Ocean, 33, 407–446,
https://doi.org/10.1080/07055900.1995.9649539, 1995.
Zhang, M., Lin, W., Bretherton, C. S., Hack, J. J., and Rasch, P. J.: A
modified formulation of fractional stratiform condensation rate in the NCAR
Community Atmospheric Model (CAM2), J. Geophys. Res., 108, 4035,
https://doi.org/10.1029/2002jd002523, 2003.
Zhang, M., Bretherton, C. S., Blossey, P. N., Austin, P. H., Bacmeister, J.
T., Bony, S., Brient, F., Cheedela, S. K., Cheng, A., Del Genio, A. D., De
Roode, S. R., Endo, S., Franklin, C. N., Golaz, J.-C., Hannay, C., Heus, T.,
Isotta, F. A., Dufresne, J.-L., Kang, I.-S., Kawai, H., Köhler, M.,
Larson, V. E., Liu, Y., Lock, A. P., Lohmann, U., Khairoutdinov, M. F.,
Molod, A. M., Neggers, R. A. J., Rasch, P., Sandu, I., Senkbeil, R.,
Siebesma, A. P., Siegenthaler-Le Drian, C., Stevens, B., Suarez, M. J., Xu,
K.-M., von Salzen, K., Webb, M. J., Wolf, A., and Zhao, M.: CGILS: Results
from the first phase of an international project to understand the physical
mechanisms of low cloud feedbacks in single column models, J.
Adv. Model. Earth Sy., 5, 826–842, https://doi.org/10.1002/2013ms000246,
2013.
Zhang, M., Somerville, R. C. J., and Xie, S.: The SCM Concept and Creation
of ARM Forcing Datasets, Meteorol. Monogr., 57, 24.21–24.12,
https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0040.1, 2016.
Zhang, Y., Li, J., Yu, R., Zhang, S., Liu, Z., Huang, J., and Zhou, Y.: A
Layer-Averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh
for Global and Regional Atmospheric Modeling: Model Description, Baseline
Evaluation, and Sensitivity Exploration, J. Adv. Model.
Earth Sy., 11, 1685–1714, https://doi.org/10.1029/2018MS001539, 2019.
Zhang, Y., Yu, R., Li, J., Liu, Z., Zhou, Y., Li, X., and Huang, X.: A
Multiscale Dynamical Model in a Dry-Mass Coordinate for Weather and Climate
Modeling: Moist Dynamics and Its Coupling to Physics, Mon. Weather
Rev., 148, 2671–2699, https://doi.org/10.1175/mwr-d-19-0305.1, 2020.
Zhang, Y., Yu, R., Li, J., Li, X., Rong, X., Peng, X., and Zhou, Y.: AMIP
Simulations of a Global Model for Unified Weather-Climate Forecast:
Understanding Precipitation Characteristics and Sensitivity Over East Asia,
J. Adv. Model. Earth Sy., 13, e2021MS002592, https://doi.org/10.1029/2021ms002592,
2021.
Zhang, Y., Li, X., Liu, Z., Rong, X., Li, J., Zhou, Y., and Chen, S.:
Resolution Sensitivity of the GRIST Nonhydrostatic Model From 120 to 5 km
(3.75 km) During the DYAMOND Winter, Earth Space Sci., 9, e2022EA002401,
https://doi.org/10.1029/2022ea002401, 2022.
Zhou, Y., Zhang, Y., Li, J., Yu, R., and Liu, Z.: Configuration and evaluation of a global unstructured mesh atmospheric model (GRIST-A20.9) based on the variable-resolution approach, Geosci. Model Dev., 13, 6325–6348, https://doi.org/10.5194/gmd-13-6325-2020, 2020.
Short summary
The weather and climate physics suites used in GRIST-A22.7.28 are compared using single-column modeling. The source of their discrepancies in terms of modeling cloud and precipitation is explored. Convective parameterization is found to be a key factor responsible for the differences. The two suites also have intrinsic differences in the interaction between microphysics and other processes, resulting in different cloud features and time step sensitivities.
The weather and climate physics suites used in GRIST-A22.7.28 are compared using single-column...
