Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2671-2020
© Author(s) 2020. 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-13-2671-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
18 Jun 2020
Model evaluation paper |
| 18 Jun 2020
| 18 Jun 2020
Superparameterised cloud effects in the EMAC general circulation model (v2.50) – influences of model configuration
Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
German Weather Service, Offenbach am Main, Germany
Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
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Estimating the impact of convection on the upper-tropospheric water budget remains a problem for models employing resolutions of several kilometers or more. A sub-kilometer high-resolution model is used to study summertime convection. The results suggest mostly close agreement with ground- and satellite-based observational data while slightly overestimating total frozen water path and anvil lifetime. The simulations are well suited to supplying information for parameterization development.
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Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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Sarah Brüning, Stefan Niebler, and Holger Tost
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Ryan Vella, Andrea Pozzer, Matthew Forrest, Jos Lelieveld, Thomas Hickler, and Holger Tost
Biogeosciences, 20, 4391–4412, https://doi.org/10.5194/bg-20-4391-2023, https://doi.org/10.5194/bg-20-4391-2023, 2023
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We investigated the effect of the El Niño–Southern Oscillation (ENSO) on biogenic volatile organic compound (BVOC) emissions from plants. ENSO events can cause a significant increase in these emissions, which have a long-term impact on the Earth's atmosphere. Persistent ENSO conditions can cause long-term changes in vegetation, resulting in even higher BVOC emissions. We link ENSO-induced emission anomalies with driving atmospheric and vegetational variables.
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Geosci. Model Dev., 16, 885–906, https://doi.org/10.5194/gmd-16-885-2023, https://doi.org/10.5194/gmd-16-885-2023, 2023
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Edward Groot and Holger Tost
Atmos. Chem. Phys., 23, 565–585, https://doi.org/10.5194/acp-23-565-2023, https://doi.org/10.5194/acp-23-565-2023, 2023
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Thunderstorm systems play an important role in the dynamics of the Earth’s atmosphere, and some of them form a well-organised line: squall lines. Simulations of such squall lines with very small initial perturbations are compared to a reference simulation. The evolution of perturbations and processes amplifying them are analysed. It is shown that the formation of new secondary thunderstorm cells (after the initial primary cells) directly ahead of the line affects the spread strongly.
Mohamed Abdelkader, Georgiy Stenchikov, Andrea Pozzer, Holger Tost, and Jos Lelieveld
Atmos. Chem. Phys., 23, 471–500, https://doi.org/10.5194/acp-23-471-2023, https://doi.org/10.5194/acp-23-471-2023, 2023
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Vinod Kumar, Julia Remmers, Steffen Beirle, Joachim Fallmann, Astrid Kerkweg, Jos Lelieveld, Mariano Mertens, Andrea Pozzer, Benedikt Steil, Marc Barra, Holger Tost, and Thomas Wagner
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Harald Rybka, Ulrike Burkhardt, Martin Köhler, Ioanna Arka, Luca Bugliaro, Ulrich Görsdorf, Ákos Horváth, Catrin I. Meyer, Jens Reichardt, Axel Seifert, and Johan Strandgren
Atmos. Chem. Phys., 21, 4285–4318, https://doi.org/10.5194/acp-21-4285-2021, https://doi.org/10.5194/acp-21-4285-2021, 2021
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Sara Bacer, Sylvia C. Sullivan, Odran Sourdeval, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Atmos. Chem. Phys., 21, 1485–1505, https://doi.org/10.5194/acp-21-1485-2021, https://doi.org/10.5194/acp-21-1485-2021, 2021
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Edward Groot and Holger Tost
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Sensitivities and variability of upper tropospheric flow (~10 km height) resulting immediately and as a direct consequence of (thunder)storm activity have been modeled in detail down to resolutions of 100–200 m and explored for different (organisation/) storm types. It is shown that the amount of water condensation explains much of emerging variability in upper atmospheric flow. Part of the effects on the nearby upper atmospheric flow is suggested to be explained by (organisation/) storm type.
Matthew Forrest, Holger Tost, Jos Lelieveld, and Thomas Hickler
Geosci. Model Dev., 13, 1285–1309, https://doi.org/10.5194/gmd-13-1285-2020, https://doi.org/10.5194/gmd-13-1285-2020, 2020
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Julie M. Nicely, Bryan N. Duncan, Thomas F. Hanisco, Glenn M. Wolfe, Ross J. Salawitch, Makoto Deushi, Amund S. Haslerud, Patrick Jöckel, Béatrice Josse, Douglas E. Kinnison, Andrew Klekociuk, Michael E. Manyin, Virginie Marécal, Olaf Morgenstern, Lee T. Murray, Gunnar Myhre, Luke D. Oman, Giovanni Pitari, Andrea Pozzer, Ilaria Quaglia, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Kane Stone, Susan Strahan, Simone Tilmes, Holger Tost, Daniel M. Westervelt, and Guang Zeng
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Jianzhong Ma, Christoph Brühl, Qianshan He, Benedikt Steil, Vlassis A. Karydis, Klaus Klingmüller, Holger Tost, Bin Chen, Yufang Jin, Ningwei Liu, Xiangde Xu, Peng Yan, Xiuji Zhou, Kamal Abdelrahman, Andrea Pozzer, and Jos Lelieveld
Atmos. Chem. Phys., 19, 11587–11612, https://doi.org/10.5194/acp-19-11587-2019, https://doi.org/10.5194/acp-19-11587-2019, 2019
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We find a pronounced maximum in aerosol extinction in the upper troposphere and lower stratosphere over the Tibetan Plateau during the Asian summer monsoon, caused mainly by mineral dust emitted from the northern Tibetan Plateau and slope area, lofted to and accumulating within the anticyclonic circulation. Mineral dust, water-soluble compounds, such as nitrate and sulfate, and associated liquid water dominate aerosol extinction around the tropopause within the Asian summer monsoon anticyclone.
Mega Octaviani, Holger Tost, and Gerhard Lammel
Geosci. Model Dev., 12, 3585–3607, https://doi.org/10.5194/gmd-12-3585-2019, https://doi.org/10.5194/gmd-12-3585-2019, 2019
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This work presents a submodel description for the atmospheric cycling and air–surface exchange processes of semivolatile organic compounds. The submodel is meant to be applied within a global atmospheric chemistry–climate model. The simulation results for polycyclic aromatic hydrocarbons confirm progress in modelling semivolatile species, verified by comparison with surface monitoring data. The significance of new modelling features for tracer distributions was quantified in a sensitivity study.
J. Christopher Kaiser, Johannes Hendricks, Mattia Righi, Patrick Jöckel, Holger Tost, Konrad Kandler, Bernadett Weinzierl, Daniel Sauer, Katharina Heimerl, Joshua P. Schwarz, Anne E. Perring, and Thomas Popp
Geosci. Model Dev., 12, 541–579, https://doi.org/10.5194/gmd-12-541-2019, https://doi.org/10.5194/gmd-12-541-2019, 2019
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The implementation of the aerosol microphysics submodel MADE3 into the global atmospheric chemistry model EMAC is described and evaluated against an extensive pool of observational data, focusing on aerosol mass and number concentrations, size distributions, composition, and optical properties. EMAC (MADE3) is able to reproduce main aerosol properties reasonably well, in line with the performance of other global aerosol models.
Sara Bacer, Sylvia C. Sullivan, Vlassis A. Karydis, Donifan Barahona, Martina Krämer, Athanasios Nenes, Holger Tost, Alexandra P. Tsimpidi, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 11, 4021–4041, https://doi.org/10.5194/gmd-11-4021-2018, https://doi.org/10.5194/gmd-11-4021-2018, 2018
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The complexity of ice nucleation mechanisms and aerosol--ice interactions makes their representation still challenging in atmospheric models. We have implemented a comprehensive ice crystal formation parameterization in the global chemistry-climate model EMAC to improve the representation of ice crystal number concentrations. The newly implemented parameterization takes into account processes which were previously neglected by the standard version of the model.
Mohamed Abdelkader, Swen Metzger, Benedikt Steil, Klaus Klingmüller, Holger Tost, Andrea Pozzer, Georgiy Stenchikov, Leonard Barrie, and Jos Lelieveld
Atmos. Chem. Phys., 17, 3799–3821, https://doi.org/10.5194/acp-17-3799-2017, https://doi.org/10.5194/acp-17-3799-2017, 2017
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We present a modeling study on the impacts of the key processes (dust emission flux, convection and dust aging parameterizations) that control the transatlantic dust transport using an advanced version of the EMAC atmospheric chemistry general circulation model. We define the
direct effect of dust agingas an increase in the AOD as a result of hygroscopic growth. We define the
indirect effectas a reduction in the dust AOD due to the higher removal of the aged dust particles.
Holger Tost
Atmos. Chem. Phys., 17, 1125–1142, https://doi.org/10.5194/acp-17-1125-2017, https://doi.org/10.5194/acp-17-1125-2017, 2017
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The paper describes the impact of lightning and the associated NOx emissions on upper-tropospheric aerosol nitrate. The consequences for both the chemical composition of the atmosphere as well as climatic impacts, which originate from lightning and modified aerosol particles, are analysed and discussed.
Mariano Mertens, Astrid Kerkweg, Patrick Jöckel, Holger Tost, and Christiane Hofmann
Geosci. Model Dev., 9, 3545–3567, https://doi.org/10.5194/gmd-9-3545-2016, https://doi.org/10.5194/gmd-9-3545-2016, 2016
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This fourth part in a series of publications describing the newly developed regional chemistry–climate system MECO(n) is dedicated to the evaluation of MECO(n) with respect to tropospheric gas-phase chemistry. For this, a simulation incorporating two regional instances, one over Europe with 50 km resolution and one over Germany with 12 km resolution, is conducted. The model results are compared with satellite, ground-based and aircraft in situ observations.
Simone Dietmüller, Patrick Jöckel, Holger Tost, Markus Kunze, Catrin Gellhorn, Sabine Brinkop, Christine Frömming, Michael Ponater, Benedikt Steil, Axel Lauer, and Johannes Hendricks
Geosci. Model Dev., 9, 2209–2222, https://doi.org/10.5194/gmd-9-2209-2016, https://doi.org/10.5194/gmd-9-2209-2016, 2016
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Four new radiation related submodels (RAD, AEROPT, CLOUDOPT, and ORBIT) are available within the MESSy framework now. They are largely based on the original radiation scheme of ECHAM5. RAD simulates radiative transfer, AEROPT calculates aerosol optical properties, CLOUDOPT calculates cloud optical properties, and ORBIT is responsible for Earth orbit calculations. Multiple diagnostic calls of the radiation routine are possible, so radiative forcing can be calculated during the model simulation.
Patrick Jöckel, Holger Tost, Andrea Pozzer, Markus Kunze, Oliver Kirner, Carl A. M. Brenninkmeijer, Sabine Brinkop, Duy S. Cai, Christoph Dyroff, Johannes Eckstein, Franziska Frank, Hella Garny, Klaus-Dirk Gottschaldt, Phoebe Graf, Volker Grewe, Astrid Kerkweg, Bastian Kern, Sigrun Matthes, Mariano Mertens, Stefanie Meul, Marco Neumaier, Matthias Nützel, Sophie Oberländer-Hayn, Roland Ruhnke, Theresa Runde, Rolf Sander, Dieter Scharffe, and Andreas Zahn
Geosci. Model Dev., 9, 1153–1200, https://doi.org/10.5194/gmd-9-1153-2016, https://doi.org/10.5194/gmd-9-1153-2016, 2016
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With an advanced numerical global chemistry climate model (CCM) we performed several detailed
combined hind-cast and projection simulations of the period 1950 to 2100 to assess the
past, present, and potential future dynamical and chemical state of the Earth atmosphere.
The manuscript documents the model and the various applied model set-ups and provides
a first evaluation of the simulation results from a global perspective as a quality check of the data.
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
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Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
A. J. G. Baumgaertner, P. Jöckel, A. Kerkweg, R. Sander, and H. Tost
Geosci. Model Dev., 9, 125–135, https://doi.org/10.5194/gmd-9-125-2016, https://doi.org/10.5194/gmd-9-125-2016, 2016
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The Community Earth System Model (CESM1) is connected to the the Modular Earth Submodel System (MESSy) as a new base model. This allows MESSy users the option to utilize either the state-of-the art spectral element atmosphere dynamical core or the finite volume core of CESM1. Additionally, this makes several other component models available to MESSy users.
H. G. Ouwersloot, A. Pozzer, B. Steil, H. Tost, and J. Lelieveld
Geosci. Model Dev., 8, 2435–2445, https://doi.org/10.5194/gmd-8-2435-2015, https://doi.org/10.5194/gmd-8-2435-2015, 2015
A. Pozzer, A. de Meij, J. Yoon, H. Tost, A. K. Georgoulias, and M. Astitha
Atmos. Chem. Phys., 15, 5521–5535, https://doi.org/10.5194/acp-15-5521-2015, https://doi.org/10.5194/acp-15-5521-2015, 2015
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Thanks to numerical simulations and satellite observations, it is shown that aerosol optical depth (AOD) trends (2000--2010 period) over the US and Europe are due to emission decrease, while over the Sahara Desert and the Middle East they are due to meteorological changes. Over Southeast Asia, both meteorology and emission changes are important for the AOD trends.
It is shown that soluble components strongly influence AOD, as their contribution is enhanced by the aerosol water content.
K. Klingmüller, B. Steil, C. Brühl, H. Tost, and J. Lelieveld
Geosci. Model Dev., 7, 2503–2516, https://doi.org/10.5194/gmd-7-2503-2014, https://doi.org/10.5194/gmd-7-2503-2014, 2014
D. Y. Chang, H. Tost, B. Steil, and J. Lelieveld
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-21975-2014, https://doi.org/10.5194/acpd-14-21975-2014, 2014
Preprint withdrawn
H. Rybka and H. Tost
Atmos. Chem. Phys., 14, 5561–5576, https://doi.org/10.5194/acp-14-5561-2014, https://doi.org/10.5194/acp-14-5561-2014, 2014
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
C. Liu, S. Beirle, T. Butler, P. Hoor, C. Frankenberg, P. Jöckel, M. Penning de Vries, U. Platt, A. Pozzer, M. G. Lawrence, J. Lelieveld, H. Tost, and T. Wagner
Atmos. Chem. Phys., 14, 1717–1732, https://doi.org/10.5194/acp-14-1717-2014, https://doi.org/10.5194/acp-14-1717-2014, 2014
Y. F. Elshorbany, P. J. Crutzen, B. Steil, A. Pozzer, H. Tost, and J. Lelieveld
Atmos. Chem. Phys., 14, 1167–1184, https://doi.org/10.5194/acp-14-1167-2014, https://doi.org/10.5194/acp-14-1167-2014, 2014
C. Brühl, J. Lelieveld, M. Höpfner, and H. Tost
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-11395-2013, https://doi.org/10.5194/acpd-13-11395-2013, 2013
Revised manuscript not accepted
D. Kunkel, H. Tost, and M. G. Lawrence
Atmos. Chem. Phys., 13, 4203–4222, https://doi.org/10.5194/acp-13-4203-2013, https://doi.org/10.5194/acp-13-4203-2013, 2013
Related subject area
Climate and Earth system modeling
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Architectural Insights and Training Methodology Optimization of Pangu-Weather
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
Robust handling of extremes in quantile mapping – "Murder your darlings"
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)
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
Short-term effects of hurricanes on nitrate-nitrogen runoff loading: a case study of Hurricane Ida using E3SM land model (v2.1)
CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea
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
Evaluation of global fire simulations in CMIP6 Earth system models
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Design, evaluation and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Introducing the MESMER-M-TPv0.1.0 module: Spatially Explicit Earth System Model Emulation for Monthly Precipitation and Temperature
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
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20–30%. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases accessibility of training and working with the model.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 2000–2020 and improves significant errors in a low resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon river are well captured and the mean flows across the multiple passages in the Caribbean Sea agree with observations.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-85, https://doi.org/10.5194/gmd-2024-85, 2024
Revised manuscript accepted for GMD
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This study provides the first comprehensive assessment of historical fire simulations from 19 CMIP6 ESMs. Most models reproduce global total, spatial pattern, seasonality, and regional historical changes well, but fail to simulate the recent decline in global burned area and underestimate the fire sensitivity to wet-dry conditions. They addressed three critical issues in CMIP5. We present targeted guidance for fire scheme development and methodologies to generate reliable fire projections.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Giovanni Di Virgilio, Jason Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew Riley, and Jyothi Lingala
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-87, https://doi.org/10.5194/gmd-2024-87, 2024
Revised manuscript accepted for GMD
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models, and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows to generate monthly means of local precipitation and temperature at low computational costs.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Cited articles
Adler, R., Sapiano, M., Huffman, G., Wang, J., Gu, G., Bolvin, D., Chiu, L.,
Schneider, U., Becker, A., Nelkin, E., Xie, P., Ferraro, R., and Shin, D.:
The Global Precipitation Climatology Project (GPCP) monthly analysis (New
Version 2.3) and a review of 2017 global precipitation, Atmosphere, 9, 138,
https://doi.org/10.3390/atmos9040138, 2018. a
Arakawa, A., Jung, J.-H., and Wu, C.-M.: Toward unification of the multiscale modeling of the atmosphere, Atmos. Chem. Phys., 11, 3731–3742, https://doi.org/10.5194/acp-11-3731-2011, 2011. a, b
Baumgaertner, A. J. G., Jöckel, P., Kerkweg, A., Sander, R., and Tost, H.: Implementation of the Community Earth System Model (CESM) version 1.2.1 as a new base model into version 2.50 of the MESSy framework, Geosci. Model Dev., 9, 125–135, https://doi.org/10.5194/gmd-9-125-2016, 2016. a
Bechtold, P., Chaboureau, J. P., Beljaars, A., Betts, A. K., Kohler, M.,
Miller, M., and Redelsperger, J. L.: The simulation of the diurnal cycle of
convective precipitation over land in a global model, Q. J. Roy. Meteor. Soc., 130, 3119–3137, 2004. a
Beheng, K.: A parameterization of warm cloud microphysical conversion
processes, Atmos. Res., 33, 193–206,
https://doi.org/10.1016/0169-8095(94)90020-5, 11th International Conference on Clouds
and Precipitation, Part II, 1994. a
Blossey, P. N., Bretherton, C. S., and Wyant, M. C.: Subtropical Low Cloud
Response to a Warmer Climate in a Superparameterized Climate Model. Part II:
Column Modeling with a Cloud Resolving Model, J. Adv. Model.
Earth Syst., 1, 8, https://doi.org/10.3894/JAMES.2009.1.8, 2009. a
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein,
S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.:
COSP: Satellite simulation software for model assessment, B.
Am. Meteor. Soc., 92, 1023–1043,
https://doi.org/10.1175/2011BAMS2856.1, 2011. a
Bodas-Salcedo, A., Hill, P., Furtado, K., Williams, K., Field, P., Manners, J.,
Hyder, P., and Kato, S.: Large Contribution of Supercooled Liquid Clouds to
the Solar Radiation Budget of the Southern Ocean, J. Climate, 29, 4213–4228,
https://doi.org/10.1175/JCLI-D-15-0564.1, 2016. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster,
P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh,
S., Sherwood, S., Stevens, B., and Zhang, X.: Clouds and Aerosols, book
section 7, 571–658, Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA, https://doi.org/10.1017/CBO9781107415324.016, 2013. a
Calisto, M., Folini, D., Wild, M., and Bengtsson, L.: Cloud radiative forcing intercomparison between fully coupled CMIP5 models and CERES satellite data, Ann. Geophys., 32, 793–807, https://doi.org/10.5194/angeo-32-793-2014, 2014. a
Cheng, A. and Xu, K.-M.: An explicit representation of vertical momentum
transport in a multiscale modeling framework through its 2-D cloud-resolving
model component, J. Geophys. Res.-Atmos., 119,
2356–2374, https://doi.org/10.1002/2013JD021078, 2014. a
Cheng, A. N. and Xu, K. M.: Diurnal variability of low clouds in the Southeast
Pacific simulated by a multiscale modeling framework model, J.
Geophys. Res.-Atmos., 118, 9191–9208, https://doi.org/10.1002/jgrd.50683,
2013. a
Cole, J. N. S., Barker, H. W., Randall, D. A., Khairoutdinov, M. F., and
Clothiaux, E. E.: Global consequences of interactions between clouds and
radiation at scales unresolved by global climate models, Geophys. Res.
Lett., 32, L06703, https://doi.org/10.1029/2004GL020945, 2005. a, b, c
Collier, J. C. and Bowman, K. P.: Diurnal cycle of tropical precipitation in a
general circulation model, J. Geophys. Res.-Atmos., 109, d17105,
https://doi.org/10.1029/2004JD004818, 2004. a
Cui, X. and Li, X.: Diurnal responses of tropical convective and stratiform
rainfall to diurnally varying sea surface temperature, Meteorol.
Atmos. Phys., 104, 53–61, https://doi.org/10.1007/s00703-008-0016-1, 2009. a
Dai, A.: Precipitation Characteristics in Eighteen Coupled Climate Models,
J. Climate, 19, 4605–4630, https://doi.org/10.1175/JCLI3884.1, 2006. a
Demory, M.-E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J.,
Schiemann, R., and Mizielinski, M. S.: The role of horizontal resolution in
simulating drivers of the global hydrological cycle, Clim. Dynam., 42,
2201–2225, https://doi.org/10.1007/s00382-013-1924-4, 2014. a
Dietmüller, S., Jöckel, P., Tost, H., Kunze, M., Gellhorn, C., Brinkop, S., Frömming, C., Ponater, M., Steil, B., Lauer, A., and Hendricks, J.: A new radiation infrastructure for the Modular Earth Submodel System (MESSy, based on version 2.51), Geosci. Model Dev., 9, 2209–2222, https://doi.org/10.5194/gmd-9-2209-2016, 2016. a, b
Elliott, E. J., Yu, S., Kooperman, G. J., Morrison, H., Wang, M., and
Pritchard, M. S.: Sensitivity of summer ensembles of fledgling
superparameterized U.S. mesoscale convective systems to cloud resolving model
microphysics and grid configuration, J. Adv. Model. Earth
Syst., 8, 634–649, https://doi.org/10.1002/2015MS000567, 2016. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S., Collins, W.,
Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P.,
Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.:
Evaluation of Climate Models, book section 9, 741–866, Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA,
https://doi.org/10.1017/CBO9781107415324.020, 2013. a
Grabowski, W. W.: Coupling cloud processes with the large-scale dynamics using
the Cloud-Resolving Convection Parameterization (CRCP), J.
Atmos. Sci., 58, 978–997,
https://doi.org/10.1175/1520-0469(2001)058<0978:CCPWTL>2.0.CO;2, 2001. a
Grabowski, W. W.: An improved framework for superparameterization, J.
Atmos. Sci., 61, 1940–1952,
https://doi.org/10.1175/1520-0469(2004)061<1940:AIFFS>2.0.CO;2, 2004a. a
Grabowski, W. W.: An Improved Framework for Superparameterization, J.
Atmos. Sci., 61, 1940–1952,
https://doi.org/10.1175/1520-0469(2004)061<1940:AIFFS>2.0.CO;2, 2004b. a
Grabowski, W. W.: Towards Global Large Eddy Simulation: Super-Parameterization
Revisited, J. Meteor. Soc. Japan. Ser. II, 94,
327–344, https://doi.org/10.2151/jmsj.2016-017, 2016. a
Grabowski, W. W. and Smolarkiewicz, P. K.: CRCP: a Cloud Resolving Convection
Parameterization for modeling the tropical convecting atmosphere, Physica D,
133, 171–178, https://doi.org/10.1016/S0167-2789(99)00104-9, 1999. a
Guichard, F., Petch, J. C., Redelsperger, J.-L., Bechtold, P., Chaboureau,
J.-P., Cheinet, S., Grabowski, W., Grenier, H., Jones, C. G., Köhler, M.,
Piriou, J.-M., Tailleux, R., and Tomasini, M.: Modelling the diurnal cycle of
deep precipitating convection over land with cloud-resolving models and
single-column models, Q. J. Roy. Meteor. Soc., 130, 3139–3172,
https://doi.org/10.1256/qj.03.145, 2004. a
Gustafson, W. I., Berg, L. K., Easter, R. C., and Ghan, S. J.: The
Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud
interactions in multiscale modeling framework models: tracer transport
results, Environ. Res. Lett., 3, 025005, https://doi.org/10.1088/1748-9326/3/2/025005, 2008. a
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016. a
Haynes, J. M., Jakob, C., Rossow, W. B., Tselioudis, G., and Brown, J.: Major
Characteristics of Southern Ocean Cloud Regimes and Their Effects on the
Energy Budget, J. Climate, 24, 5061–5080,
https://doi.org/10.1175/2011JCLI4052.1, 2011. a
Heinze, R., Dipankar, A., Henken, C. C., Moseley, C., Sourdeval, O., Trömel,
S., Xie, X., Adamidis, P., Ament, F., Baars, H., Barthlott, C., Behrendt, A.,
Blahak, U., Bley, S., Brdar, S., Brueck, M., Crewell, S., Deneke, H.,
Di Girolamo, P., Evaristo, R., Fischer, J., Frank, C., Friederichs, P.,
Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A., Hege, H.-C., Hoose,
C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S., Knippertz, P., Kuhn,
A., van Laar, T., Macke, A., Maurer, V., Mayer, B., Meyer, C. I., Muppa,
S. K., Neggers, R. A. J., Orlandi, E., Pantillon, F., Pospichal, B., Röber,
N., Scheck, L., Seifert, A., Seifert, P., Senf, F., Siligam, P., Simmer, C.,
Steinke, S., Stevens, B., Wapler, K., Weniger, M., Wulfmeyer, V., Zängl, G.,
Zhang, D., and Quaas, J.: Large-eddy simulations over Germany using ICON: a
comprehensive evaluation, Q. J. Roy. Meteor.
Soc., 143, 69–100, https://doi.org/10.1002/qj.2947, 2017a. a
Heinze, R., Moseley, C., Böske, L. N., Muppa, S. K., Maurer, V., Raasch, S., and Stevens, B.: Evaluation of large-eddy simulations forced with mesoscale model output for a multi-week period during a measurement campaign, Atmos. Chem. Phys., 17, 7083–7109, https://doi.org/10.5194/acp-17-7083-2017, 2017b. a
Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan, Q.,
Folini, D., Ji, D., Klocke, D., Qian, Y., Rauser, F., Rio, C., Tomassini, L.,
Watanabe, M., and Williamson, D.: The Art and Science of Climate Model
Tuning, B. Am. Meteor. Soc., 98, 589–602,
https://doi.org/10.1175/BAMS-D-15-00135.1, 2017. a
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu,
G., Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM Multisatellite
Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor
Precipitation Estimates at Fine Scales, J. Hydrometeorol., 8,
38–55, https://doi.org/10.1175/JHM560.1, 2007. a
Jansson, F., van den Oord, G., Pelupessy, I., Grönqvist, J. H., Siebesma,
A. P., and Crommelin, D.: Regional Superparameterization in a Global
Circulation Model Using Large Eddy Simulations, J. Adv.
Model. Earth Syst., 11, 2958–2979, https://doi.org/10.1029/2018MS001600, 2019. a
Jiang, J. H., Su, H., Zhai, C. X., Perun, V. S., Del Genio, A., Nazarenko,
L. S., Donner, L. J., Horowitz, L., Seman, C., Cole, J., Gettelman, A.,
Ringer, M. A., Rotstayn, L., Jeffrey, S., Wu, T. W., Brient, F., Dufresne,
J. L., Kawai, H., Koshiro, T., Watanabe, M., LEcuyer, T. S., Volodin, E. M.,
Iversen, T., Drange, H., Mesquita, M. D. S., Read, W. G., Waters, J. W.,
Tian, B. J., Teixeira, J., and Stephens, G. L.: Evaluation of cloud and water
vapor simulations in CMIP5 climate models using NASA “A-Train” satellite
observations, J. Geophys. Res.-Atmos., 117, D14105,
https://doi.org/10.1029/2011JD017237, 2012. a
Jöckel, P., Sander, R., Kerkweg, A., Tost, H., and Lelieveld, J.: Technical Note: The Modular Earth Submodel System (MESSy) – a new approach towards Earth System Modeling, Atmos. Chem. Phys., 5, 433–444, https://doi.org/10.5194/acp-5-433-2005, 2005. a
Jöckel, P., Kerkweg, A., Pozzer, A., Sander, R., Tost, H., Riede, H., Baumgaertner, A., Gromov, S., and Kern, B.: Development cycle 2 of the Modular Earth Submodel System (MESSy2), Geosci. Model Dev., 3, 717–752, https://doi.org/10.5194/gmd-3-717-2010, 2010. a, b
Johnson, D.: Parametrization of the cloud topped boundary layer: aircraft
measurements, in: Workshop on Parametrization of the Cloud Topped Boundary
layer, 8–11 June 1993, 77–118, ECMWF, ECMWF, Shinfield Park, Reading,
1993. a
Jung, J. H. and Arakawa, A.: Development of a Quasi-3D Multiscale Modeling
Framework: Motivation, Basic Algorithm and Preliminary results, J.
Adv. Model. Earth Syst., 2, 11, https://doi.org/10.3894/JAMES.2010.2.11,
2010. a
Jung, J. H. and Arakawa, A.: Simulation of subgrid orographic precipitation
with an embedded 2-D cloud-resolving model, J. Adv. Model.
Earth Syst., 8, 31–40, https://doi.org/10.1002/2015MS000539, 2016. a
Kajikawa, Y., Yamaura, T., Tomita, H., and Satoh, M.: Impact of Tropical
Disturbance on the Indian Summer Monsoon Onset Simulated by a Global
Cloud-System-Resolving Model, SOLA, 11, 80–84,
https://doi.org/10.2151/sola.2015-020, 2015. a
Kajikawa, Y., Miyamoto, Y., Yoshida, R., Yamaura, T., Yashiro, H., and Tomita,
H.: Resolution dependence of deep convections in a global simulation from
over 10-kilometer to sub-kilometer grid spacing, Prog. Earth
Planet. Sci., 3, 16, https://doi.org/10.1186/s40645-016-0094-5, 2016. a
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.-K., Hnilo, J. J., Fiorino,
M., and Potter, G. L.: NCEP–DOE AMIP-II Reanalysis (R-2), B.
Am. Meteorol. Soc., 83, 1631–1643,
https://doi.org/10.1175/BAMS-83-11-1631, 2002. a
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Fokke Meirink, J., Devasthale, A., Hanschmann, T., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Schlundt, C., Stein, D., Finkensieper, S., Håkansson, N., and Hollmann, R.: CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data, Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, 2017. a
Kerkweg, A. and Jöckel, P.: The 1-way on-line coupled atmospheric chemistry model system MECO(n) – Part 1: Description of the limited-area atmospheric chemistry model COSMO/MESSy, Geosci. Model Dev., 5, 87–110, https://doi.org/10.5194/gmd-5-87-2012, 2012. a
Khairoutdinov, M., Randall, D., and DeMott, C.: Simulations of the atmospheric
general circulation using a cloud-resolving model as a superparameterization
of physical processes, J. Atmos. Sci., 62, 2136–2154,
https://doi.org/10.1175/JAS3453.1, 2005. a, b, c
Khairoutdinov, M., DeMott, C., and Randall, D.: Evaluation of the simulated
interannual and subseasonal variability in an AMIP-Style simulation using the
CSU multiscale modeling framework, J. Climate, 21, 413–431,
https://doi.org/10.1175/2007JCLI1630.1, 2008. a, b, c, d
Khairoutdinov, M. F. and Randall, D. A.: A cloud resolving model as a cloud
parameterization in the NCAR Community Climate System Model: Preliminary
results, Geophys. Res. Lett., 28, 3617–3620,
https://doi.org/10.1029/2001GL013552, 2001. a, b
Khairoutdinov, M. F. and Randall, D. A.: Cloud resolving modeling of the ARM
summer 1997 IOP: Model formulation, results, uncertainties, and
sensitivities, J. Atmos. Sci., 60, 607–625,
https://doi.org/10.1175/1520-0469(2003)060<0607:CRMOTA>2.0.CO;2, 2003. a, b, c
Khairoutdinov, M. F. and Randall, D.: High-Resolution Simulation of
Shallow-to-Deep Convection Transition over Land, J. Atmos.
Sci., 63, 3421–3436, https://doi.org/10.1175/JAS3810.1, 2006. a
Kikuchi, K. and Wang, B.: Diurnal Precipitation Regimes in the Global Tropics,
J. Climate, 21, 2680–2696, https://doi.org/10.1175/2007JCLI2051.1, 2008. a
Knutti, R., Stocker, T. F., Joos, F., and Plattner, G. K.: Constraints on
radiative forcing and future climate change from observations and climate
model ensembles, Nature, 416, 719–723, https://doi.org/10.1038/416719a, 2002. a
Kodama, C., Yamada, Y., Noda, A. T., Kikuchi, K., Kajikawa, Y., Nasuno, T.,
Tomita, T., Yamaura, T., Takahashi, H. G., Hara, M., Kawatani, Y., Satoh, M.,
and Sugi, M.: A 20-Year Climatology of a NICAM AMIP-Type Simulation, J. Meteor. Soc. Japan Ser. II, 93, 393–424,
https://doi.org/10.2151/jmsj.2015-024, 2015. a
Kooperman, G. J., Pritchard, M. S., and Somerville, R. C. J.: Robustness and
sensitivities of central U.S. summer convection in the super-parameterized
CAM: Multi-model intercomparison with a new regional EOF index, Geophys.
Res. Lett., 40, 3287–3291, https://doi.org/10.1002/grl.50597, 2013. a
Kooperman, G. J., Pritchard, M. S., and Somerville, R. C. J.: The response of
US summer rainfall to quadrupled CO2 climate change in conventional and
superparameterized versions of the NCAR community atmosphere model, J. Adv. Model. Earth Syst., 6, 859–882,
https://doi.org/10.1002/2014MS000306, 2014. a
Kooperman, G. J., Pritchard, M. S., Burt, M. A., Branson, M. D., and Randall,
D. A.: Robust effects of cloud superparameterization on simulated daily
rainfall intensity statistics across multiple versions of the Community Earth
System Model, J. Adv. Model. Earth Syst., 8, 140–165,
https://doi.org/10.1002/2015MS000574, 2016. a, b
Lauer, A. and Hamilton, K.: Simulating Clouds with Global Climate Models: A
Comparison of CMIP5 Results with CMIP3 and Satellite Data, J.
Climate, 26, 3823–3845, https://doi.org/10.1175/JCLI-D-12-00451.1, 2013. a
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the
Earth's top-of-atmosphere radiation budget, J. Climate, 22, 748–766,
2009. a
Lohmann, U. and Roeckner, E.: Design and performance of a new cloud
microphysics scheme developed for the ECHAM general circulation model,
Clim. Dynam., 12, 557–572, https://doi.org/10.1007/s003820050128, 1996. a
Luo, Z. and Stephens, G. L.: An enhanced convection-wind-evaporation feedback
in a superparameterization GCM (SP-GCM) depiction of the Asian summer
monsoon, Geophys. Res. Lett., 33, L06707, https://doi.org/10.1029/2005GL025060, 2006. a
Mace, G. G.: Cloud properties and radiative forcing over the maritime storm
tracks of the Southern Ocean and North Atlantic derived from A-Train, J. Geophys. Res.-Atmos., 115, D10201, https://doi.org/10.1029/2009JD012517, 2010. a
Maher, P., Vallis, G. K., Sherwood, S. C., Webb, M. J., and Sansom, P. G.: The
Impact of Parameterized Convection on Climatological Precipitation in
Atmospheric Global Climate Models, Geophys. Res. Lett., 45,
3728–3736, https://doi.org/10.1002/2017GL076826, 2018. a
Marchand, R. and Ackerman, T.: An analysis of cloud cover in multiscale
modeling framework global climate model simulations using 4 and 1 km
horizontal grids, J. Geophys. Res.-Atmos., 115, D16207,
https://doi.org/10.1029/2009JD013423, 2010. a, b, c, d
Marchand, R., Haynes, J., Mace, G. G., Ackerman, T., and Stephens, G.: A
comparison of simulated cloud radar output from the multiscale modeling
framework global climate model with CloudSat cloud radar observations,
J. Geophys. Res.-Atmos., 114, D00A20,
https://doi.org/10.1029/2008JD009790, 2009. a
Matsui, T., Chern, J.-D., Tao, W.-K., Lang, S., Satoh, M., Hashino, T., and
Kubota, T.: On the Land–Ocean Contrast of Tropical Convection and
Microphysics Statistics Derived from TRMM Satellite Signals and Global
Storm-Resolving Models, J. Hydrometeorol., 17, 1425–1445,
https://doi.org/10.1175/JHM-D-15-0111.1, 2016. a
Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta, M.,
Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz, D.,
Pincus, R., Schmidt, H., and Tomassini, L.: Tuning the climate of a global
model, J. Adv. Model. Earth Syst., 4, M00A01,
https://doi.org/10.1029/2012MS000154, 2012. a, b
Minghuai, W., E., L. V., Steven, G., Mikhail, O., P., S. D., Heng, X.,
Xiaohong, L., Philip, R., and Zhun, G.: A multiscale modeling framework model
(superparameterized CAM5) with a higher-order turbulence closure: Model
description and low-cloud simulations, J. Adv. Model. Earth
Syst., 7, 484–509, https://doi.org/10.1002/2014MS000375, 2015. a
Miura, H., Satoh, M., Nasuno, T., Noda, A. T., and Oouchi, K.: A Madden-Julian
Oscillation Event Realistically Simulated by a Global Cloud-Resolving Model,
Science, 318, 1763–1765, https://doi.org/10.1126/science.1148443, 2007. a
Miyakawa, T., Satoh, M., Miura, H., Tomita, H., Yashiro, H., Noda, A. T.,
Yamada, Y., Kodama, C., Kimoto, M., and Yoneyama, K.: Madden-Julian
Oscillation prediction skill of a new-generation global model demonstrated
using a supercomputer, Nat. Commun., 5, 3769,
https://doi.org/10.1038/ncomms4769, 2014. a
Miyamoto, Y., Kajikawa, Y., Yoshida, R., Yamaura, T., Yashiro, H., and Tomita,
H.: Deep moist atmospheric convection in a subkilometer global simulation,
Geophys. Res. Lett., 40, 4922–4926, https://doi.org/10.1002/grl.50944, 2013. a
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of Cloud Microphysics on
the Development of Trailing Stratiform Precipitation in a Simulated Squall
Line: Comparison of One- and Two-Moment Schemes, Mon. Weather Rev., 137,
991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009. a
Moss, S., Francis, P., and Johnson, D.: Calculation and parameterization of the
effective radius of ice particles using aircraft data, in: Proc. 12th Int.
Conf. on Clouds and Precipitation, 1255–1258, 1996. a
Nordeng, T. E.: Extended versions of the convective parametrization scheme at
ECMWF and their impact on the mean and transient activity of the model in the
tropics, Technical Momorandum 206, ECMWF Research Department, European
Centre for Medium Range Weather Forecasts, Reading, UK, 1994. a
O’Dell, C. W., Wentz, F. J., and Bennartz, R.: Cloud Liquid Water Path from
Satellite-Based Passive Microwave Observations: A New Climatology over the
Global Oceans, J. Climate, 21, 1721–1739,
https://doi.org/10.1175/2007JCLI1958.1, 2008. a
Parishani, H., Pritchard, M. S., Bretherton, C. S., Terai, C. R., Wyant, M. C.,
Khairoutdinov, M., and Singh, B.: Insensitivity of the Cloud Response to
Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud
Microphysics: Results From the Ultraparameterized CAM, J. Adv.
Model. Earth Syst., 10, 3139–3158, https://doi.org/10.1029/2018MS001409, 2018. a, b, c
Pritchard, M. S. and Somerville, R. C. J.: Assessing the Diurnal Cycle of
Precipitation in a Multi-Scale Climate Model, J. Adv. Model.
Earth Syst., 1, 12, 2009a. a
Pritchard, M. S. and Somerville, R. C. J.: Empirical orthogonal function
analysis of the diurnal cycle of precipitation in a multi-scale climate
model, Geophys. Res. Lett., 36, L05812, https://doi.org/10.1029/2008GL036964, l05812,
2009b. a, b
Pritchard, M. S., Bretherton, C. S., and DeMott, C. A.: Restricting 32–128 km
horizontal scales hardly affects the MJO in the Superparameterized Community
Atmosphere Model v.3.0 but the number of cloud-resolving grid columns
constrains vertical mixing, J. Adv. Model. Earth Syst., 6,
723–739, https://doi.org/10.1002/2014MS000340, 2014. a, b, c
Probst, P., Rizzi, R., Tosi, E., Lucarini, V., and Maestri, T.: Total cloud
cover from satellite observations and climate models, Atmos.
Res., 107, 161–170, https://doi.org/10.1016/j.atmosres.2012.01.005, 2012. a
Qin, H., Pritchard, M. S., Kooperman, G. J., and Parishani, H.: Global Effects
of Superparameterization on Hydrothermal Land-Atmosphere Coupling on Multiple
Timescales, J. Adv. Model. Earth Syst., 10, 530–549,
https://doi.org/10.1002/2017MS001185, 2018. a, b, c
Randall, D., Khairoutdinov, M. F., Arakawa, A., and Grabowski, W.: Breaking the
cloud parameterization deadlock, B. Am. Meteor.
Soc., 84, 1547–1564, https://doi.org/10.1175/BAMS-84-11-1547, 2003. a
Randall, D. A.: Beyond deadlock, Geophys. Res. Lett., 40, 5970–5976,
https://doi.org/10.1002/2013GL057998, 2013. a
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta,
M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A.,
Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general
circulation model ECHAM 5. Part I: Model description., Tech. Rep. 349,
Max-Planck-Institute for Meteorology, Hamburg,
available at: https://www.mpimet.mpg.de/fileadmin/publikationen/Reports/max_scirep_349.pdf (last access: 27 May 2020),
2003. a, b, c
Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh,
L., Manzini, E., Schlese, U., and Schulzweida, U.: Sensitivity of simulated
climate to horizontal and vertical resolution in the ECHAM5 atmosphere model,
J. Climate, 19, 3771–3791, https://doi.org/10.1175/JCLI3824.1, 2006. a, b
Rybka, H. and Tost, H.: SP-EMAC – analysis and plotting scripts, Zenodo,
https://doi.org/10.5281/zenodo.3387004, 2019a. a
Rybka, H. and Tost, H.: SP-EMAC – model source code and input files, Zenodo,
https://doi.org/10.5281/zenodo.3386969, 2019b. a
Sato, T., Miura, H., Satoh, M., Takayabu, Y. N., and Wang, Y.: Diurnal Cycle of
Precipitation in the Tropics Simulated in a Global Cloud-Resolving Model,
J. Climate, 22, 4809–4826, https://doi.org/10.1175/2009JCLI2890.1, 2009. a, b, c
Song, H., Zhang, Z., Ma, P.-L., Ghan, S., and Wang, M.: The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models, Geosci. Model Dev., 11, 3147–3158, https://doi.org/10.5194/gmd-11-3147-2018, 2018. a
Stephens, G. L., L'Ecuyer, T., Forbes, R., Gettelmen, A., Golaz, J.-C.,
Bodas-Salcedo, A., Suzuki, K., Gabriel, P., and Haynes, J.: Dreary state of
precipitation in global models, J. Geophys. Res.-Atmos.,
115, D24211, https://doi.org/10.1029/2010JD014532, 2010. a
Stevens, B., Satoh, M., Auger, L., Biercamp, J., Bretherton, C. S., Chen, X.,
Düben, P., Judt, F., Khairoutdinov, M., Klocke, D., Kodama, C.,
Kornblueh, L., Lin, S.-J., Neumann, P., Putman, W. M., Röber, N.,
Shibuya, R., Vanniere, B., Vidale, P. L., Wedi, N., and Zhou, L.: DYAMOND:
the DYnamics of the Atmospheric general circulation Modeled On
Non-hydrostatic Domains, Progr. Earth Planet. Sci., 6, 61,
https://doi.org/10.1186/s40645-019-0304-z, 2019. a
Stevens, B., Acquistapace, C., Hansen, A., Heinze, R., Klinger, C., Klocke, D.,
Rybka, H., Schubotz, W., Windmiller, J., Adamidis, P., Arka, I., Barlakas,
V., Biercamp, J., Brueck, M., Brune, S., Buehler, S., Burkhardt, U., Cioni,
G., Costa-Surós, M., Crewell, S., Crueger, T., Deneke, H., Friederichs, P.,
Carbajal Henken, C., Hohenegger, C., Jacob, M., Jakub, F., Kalthoff, N.,
Kohler, M., Li, P., Lohnert, U., Macke, A., Madenach, N., Mayer, B., Nam, C.,
Naumann, A., Peters, K., Poll, S., Quaas, J., Rober, N., Rochetin, N.,
Scheck, L., Schemann, V., Schnitt, S., Seifert, A., Senf, F., Shapkalijevski,
M., Simmer, C., Singh, S., Sourdeval, O., Spickermann, D., Strandgren, J.,
Tessiot, O., Laar, T. v., Vercauteren, N., Vial, J., Voigt, A., and Zangl,
G.: The Added Value of Large-eddy and Storm-resolving Models for Simulating
Clouds and Precipitation, J. Meteor. Soc. Japan, 98, 395–435,
https://doi.org/10.2151/jmsj.2020-021, 2020. a
Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G.,
Chepfer, H., Di Girolamo, L., Getzewich, B., Guignard, A., Heidinger, A.,
Maddux, B. C., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen,
C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.:
Assessment of Global Cloud Datasets from Satellites: Project and Database
Initiated by the GEWEX Radiation Panel, B. Am.
Meteorol. Soc., 94, 1031–1049, https://doi.org/10.1175/BAMS-D-12-00117.1,
2013. a
Subramanian, A., Weisheimer, A., Palmer, T., Vitart, F., and Bechtold, P.:
Impact of stochastic physics on tropical precipitation in the coupled ECMWF
model, Q. J. Roy. Meteorol. Soc., 143, 852–865,
https://doi.org/10.1002/qj.2970, 2017. a
Sui, C.-H., Lau, K.-M., Takayabu, Y. N., and Short, D. A.: Diurnal Variations
in Tropical Oceanic Cumulus Convection during TOGA COARE, J.
Atmos. Sci., 54, 639–655,
https://doi.org/10.1175/1520-0469(1997)054<0639:DVITOC>2.0.CO;2, 1997. a
Sui, C.-H., Li, X., and Lau, K.-M.: Radiative–Convective Processes in
Simulated Diurnal Variations of Tropical Oceanic Convection, J.
Atmos. Sci., 55, 2345–2357,
https://doi.org/10.1175/1520-0469(1998)055<2345:RCPISD>2.0.CO;2, 1998. a
Sun, J. and Pritchard, M. S.: Effects of Explicit Convection on Land Surface
Air Temperature and Land-Atmosphere Coupling in the Thermal Feedback Pathway,
J. Adv. Model. Earth Syst., 10, 2376–2392,
https://doi.org/10.1029/2018MS001301, 2018. a, b, c
Suzuki, K., Stephens, G., Bodas-Salcedo, A., Wang, M., Golaz, J.-C., Yokohata,
T., and Koshiro, T.: Evaluation of the Warm Rain Formation Process in Global
Models with Satellite Observations, J. Atmos. Sci., 72,
3996–4014, https://doi.org/10.1175/JAS-D-14-0265.1, 2015. a
Swales, D. J., Pincus, R., and Bodas-Salcedo, A.: The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2, Geosci. Model Dev., 11, 77–81, https://doi.org/10.5194/gmd-11-77-2018, 2018. a
Tao, W. K., Chern, J. D., Atlas, R., Randall, D., Khairoutdinov, M., Li, J. L.,
Waliser, D. E., Hou, A., Lin, X., Peters-Lidard, C., Lau, W., Jiang, J., and
Simpson, J.: A Multiscale Modeling System: Developments, Applications, and
Critical Issues, B. Am. Meteorol. Soc., 90,
515–534, https://doi.org/10.1175/2008BAMS2542.1, 2009. a, b, c, d
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192,
https://doi.org/10.1029/2000JD900719, 2001. a
Tiedtke, M.: A Comprehensive Mass Flux Scheme For Cumulus Parameterization In
Large-scale Models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a
Tompkins, A. M.: Organization of Tropical Convection in Low Vertical Wind
Shears: The Role of Cold Pools, J. Atmos. Sci., 58,
1650–1672, https://doi.org/10.1175/1520-0469(2001)058<1650:OOTCIL>2.0.CO;2, 2001. a
Tost, H., Jöckel, P., and Lelieveld, J.: Influence of different convection parameterisations in a GCM, Atmos. Chem. Phys., 6, 5475–5493, https://doi.org/10.5194/acp-6-5475-2006, 2006. a
Tulich, S. N.: A strategy for representing the effects of convective momentum
transport in multiscale models: Evaluation using a new superparameterized
version of the Weather Research and Forecast model (SP-WRF), J.
Adv. Model. Earth Syst., 7, 938–962, https://doi.org/10.1002/2014MS000417,
2015. a, b, c
Wang, M., Ghan, S., Easter, R., Ovchinnikov, M., Liu, X., Kassianov, E., Qian, Y., Gustafson Jr., W. I., Larson, V. E., Schanen, D. P., Khairoutdinov, M., and Morrison, H.: The multi-scale aerosol-climate model PNNL-MMF: model description and evaluation, Geosci. Model Dev., 4, 137–168, https://doi.org/10.5194/gmd-4-137-2011, 2011a. a, b, c
Wang, M., Ghan, S., Ovchinnikov, M., Liu, X., Easter, R., Kassianov, E., Qian, Y., and Morrison, H.: Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF, Atmos. Chem. Phys., 11, 5431–5455, https://doi.org/10.5194/acp-11-5431-2011, 2011b. a
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., III, R. B. L., Smith,
G. L., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System
(CERES): An Earth Observing System Experiment, B. Am.
Meteor
. Soc., 77, 853–868,
https://doi.org/10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2, 1996. a
Wyant, M. C., Bretherton, C. S., Bacmeister, J. T., Kiehl, J. T., Held, I. M.,
Zhao, M., Klein, S. A., and Soden, B. J.: A comparison of low-latitude cloud
properties and their response to climate change in three AGCMs sorted into
regimes using mid-tropospheric vertical velocity, Clim. Dynam., 27,
261–279, https://doi.org/10.1007/s00382-006-0138-4, 2006a. a
Wyant, M. C., Khairoutdinov, M., and Bretherton, C. S.: Climate sensitivity and
cloud response of a GCM with a superparameterization, Geophys. Res.
Lett., 33, L06714, https://doi.org/10.1029/2005GL025464, 2006b. a, b
Wyant, M. C., Bretherton, C. S., and Blossey, P. N.: Subtropical Low Cloud
Response to a Warmer Climate in a Superparameterized Climate Model. Part I:
Regime Sorting and Physical Mechanisms, J. Adv. Model. Earth
Syst., 1, 7, https://doi.org/10.3894/JAMES.2009.1.7, 2009. a, b
Yang, S. and Smith, E. A.: Mechanisms for Diurnal Variability of Global
Tropical Rainfall Observed from TRMM, J. Climate, 19, 5190–5226,
https://doi.org/10.1175/JCLI3883.1, 2006.
a, b
Yashiro, H., Kajikawa, Y., Miyamoto, Y., Yamaura, T., Yoshida, R., and Tomita, H.: Resolution Dependence of the Diurnal Cycle of Precipitation Simulated by a Global Cloud-System Resolving Model, SOLA, 12, 272–276,
https://doi.org/10.2151/sola.2016-053, 2016. a
Zhang, G. J. and McFarlane, N. A.: Sensitivity of Climate Simulations To the
Parameterization of Cumulus Convection In the Canadian Climate Center
General-circulation Model, Atmos.-Ocean, 33, 407–446, 1995. a
Zhang, T., Zhang, M., Lin, W., Lin, Y., Xue, W., Yu, H., He, J., Xin, X., Ma, H.-Y., Xie, S., and Zheng, W.: Automatic tuning of the Community Atmospheric Model (CAM5) by using short-term hindcasts with an improved downhill simplex optimization method, Geosci. Model Dev., 11, 5189–5201, https://doi.org/10.5194/gmd-11-5189-2018, 2018. a
Zhang, Y., Klein, S. A., Liu, C., Tian, B., Marchand, R. T., Haynes, J. M.,
McCoy, R. B., Zhang, Y., and Ackerman, T. P.: On the diurnal cycle of deep
convection, high-level cloud, and upper troposphere water vapor in the
Multiscale Modeling Framework, J. Geophys. Res.-Atmos.,
113, D16105, https://doi.org/10.1029/2008JD009905, 2008. a, b
Short summary
Simulating cloud processes and their interactions with their environment is one of the biggest challenges in atmospheric science. This study couples a cloud-resolving model with a global climate model to improve the representation of small-scale processes for climate simulations. Unlike conventional approaches, tropical precipitation is better simulated with the new model setup. However, the diurnal cycle of precipitation and cloud amounts can be significantly influenced by the chosen setup.
Simulating cloud processes and their interactions with their environment is one of the biggest...
