Articles | Volume 16, issue 19
https://doi.org/10.5194/gmd-16-5601-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5601-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
10 Oct 2023
Model description paper |
| 10 Oct 2023
| 10 Oct 2023
Simulations of idealised 3D atmospheric flows on terrestrial planets using LFRic-Atmosphere
Department of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK
Nathan J. Mayne
Department of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK
Thomas Bendall
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Ian A. Boutle
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Department of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK
Alex Brown
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Iva Kavčič
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
James Kent
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Krisztian Kohary
Department of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK
James Manners
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Thomas Melvin
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Enrico Olivier
Research Software Engineering, University of Exeter, Exeter, EX4 4QE, UK
Lokesh K. Ragta
Department of Information Technology, University of Leicester, University Road, Leicester, LE1 7RH, UK
Ben Shipway
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Jon Wakelin
Department of Information Technology, University of Leicester, University Road, Leicester, LE1 7RH, UK
Nigel Wood
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Mohamed Zerroukat
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
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Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
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Annette K. Miltenberger, Paul R. Field, Adrian A. Hill, Ben J. Shipway, and Jonathan M. Wilkinson
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Ian Boutle, Jeremy Price, Innocent Kudzotsa, Harri Kokkola, and Sami Romakkaniemi
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Daniel T. McCoy, Paul R. Field, Anja Schmidt, Daniel P. Grosvenor, Frida A.-M. Bender, Ben J. Shipway, Adrian A. Hill, Jonathan M. Wilkinson, and Gregory S. Elsaesser
Atmos. Chem. Phys., 18, 5821–5846, https://doi.org/10.5194/acp-18-5821-2018, https://doi.org/10.5194/acp-18-5821-2018, 2018
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Here we use a combination of global convection-permitting models, satellite observations and the Holuhraun volcanic eruption to demonstrate that aerosol enhances the cloud liquid content and brightness of midlatitude cyclones. This is important because the strength of anthropogenic radiative forcing is uncertain, leading to uncertainty in the climate sensitivity consistent with observed temperature record.
Annette K. Miltenberger, Paul R. Field, Adrian A. Hill, Phil Rosenberg, Ben J. Shipway, Jonathan M. Wilkinson, Robert Scovell, and Alan M. Blyth
Atmos. Chem. Phys., 18, 3119–3145, https://doi.org/10.5194/acp-18-3119-2018, https://doi.org/10.5194/acp-18-3119-2018, 2018
Daniel P. Grosvenor, Paul R. Field, Adrian A. Hill, and Benjamin J. Shipway
Atmos. Chem. Phys., 17, 5155–5183, https://doi.org/10.5194/acp-17-5155-2017, https://doi.org/10.5194/acp-17-5155-2017, 2017
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We used a weather model to simulate low-level layer clouds that lie off the coast of Chile and tested how they would be affected by airborne particulate matter (aerosols) according to the model. We found that as aerosols were increased, the clouds reflected more and more of the sun’s incoming energy due to the combined effects of the cloud droplets becoming smaller, the thickening of clouds, and increased areal coverage. However, the latter two effects were only important at low aerosol levels.
David Walters, Ian Boutle, Malcolm Brooks, Thomas Melvin, Rachel Stratton, Simon Vosper, Helen Wells, Keith Williams, Nigel Wood, Thomas Allen, Andrew Bushell, Dan Copsey, Paul Earnshaw, John Edwards, Markus Gross, Steven Hardiman, Chris Harris, Julian Heming, Nicholas Klingaman, Richard Levine, James Manners, Gill Martin, Sean Milton, Marion Mittermaier, Cyril Morcrette, Thomas Riddick, Malcolm Roberts, Claudio Sanchez, Paul Selwood, Alison Stirling, Chris Smith, Dan Suri, Warren Tennant, Pier Luigi Vidale, Jonathan Wilkinson, Martin Willett, Steve Woolnough, and Prince Xavier
Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, https://doi.org/10.5194/gmd-10-1487-2017, 2017
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
B. J. Shipway
Atmos. Chem. Phys., 15, 3803–3814, https://doi.org/10.5194/acp-15-3803-2015, https://doi.org/10.5194/acp-15-3803-2015, 2015
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A new parametrization for cloud droplet nucleation is described. This revised approach makes use of a simple look-up table which is very efficient and computationally very cheap. Adopting this approach further allows for a more accurate treatment of the necessary approximations of supersaturation evolution and ultimately leads to a more accurate calculation of peak supersaturation and hence droplet nucleation.
D. N. Walters, K. D. Williams, I. A. Boutle, A. C. Bushell, J. M. Edwards, P. R. Field, A. P. Lock, C. J. Morcrette, R. A. Stratton, J. M. Wilkinson, M. R. Willett, N. Bellouin, A. Bodas-Salcedo, M. E. Brooks, D. Copsey, P. D. Earnshaw, S. C. Hardiman, C. M. Harris, R. C. Levine, C. MacLachlan, J. C. Manners, G. M. Martin, S. F. Milton, M. D. Palmer, M. J. Roberts, J. M. Rodríguez, W. J. Tennant, and P. L. Vidale
Geosci. Model Dev., 7, 361–386, https://doi.org/10.5194/gmd-7-361-2014, https://doi.org/10.5194/gmd-7-361-2014, 2014
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
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Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOX emissions using synthetic NO2 satellite column retrievals derived from high-resolution model simulations. The FDA accurately reproduced NOX emissions when column observations were limited to the boundary layer and when the variability of NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
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This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Cited articles
Adams, S., Ford, R., Hambley, M., Hobson, J., Kavčič, I., Maynard, C.,
Melvin, T., Müller, E., Mullerworth, S., Porter, A., Rezny, M., Shipway, B.,
and Wong, R.: LFRic: Meeting the challenges of scalability and
performance portability in Weather and Climate models, J.
Parall. Distr. Com., 132, 383–396,
https://doi.org/10.1016/j.jpdc.2019.02.007, 2019. a, b, c, d, e, f, g, h, i, j
Amundsen, D. S., Mayne, N. J., Baraffe, I., Manners, J., Tremblin, P.,
Drummond, B., Smith, C., Acreman, D. M., and Homeier, D.: The UK Met
Office global circulation model with a sophisticated radiation scheme
applied to the hot Jupiter HD 209458b, Astron. Astrophys., 595, A36,
https://doi.org/10.1051/0004-6361/201629183, 2016. a, b
Balaji, V., Couvreux, F., Deshayes, J., Gautrais, J., Hourdin, F., and Rio, C.:
Are general circulation models obsolete?, P. Natl. Acad.
Sci. USA, 119, e2202075119, https://doi.org/10.1073/pnas.2202075119, 2022. a
Barnes, R.: Tidal locking of habitable exoplanets, Celest. Mech.
Dyn. Astr., 129, 509–536, https://doi.org/10.1007/s10569-017-9783-7, 2017. a
Bendall, T. M., Gibson, T. H., Shipton, J., Cotter, C. J., and Shipway, B.: A
compatible finite-element discretisation for the moist compressible Euler
equations, Q. J. Roy. Meteor. Soc., 146,
3187–3205, https://doi.org/10.1002/qj.3841, 2020. a
Bendall, T. M., Wood, N., Thuburn, J., and Cotter, C. J.: A solution to the
trilemma of the moist Charney–Phillips staggering, Q. J.
Roy. Meteor. Soc., 149, 262–276, https://doi.org/10.1002/qj.4406, 2022. a
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a, b
Boutle, I. A., Eyre, J. E. J., and Lock, A. P.: Seamless Stratocumulus
Simulation across the Turbulent Gray Zone, Mon. Weather Rev.,
142, 1655–1668, https://doi.org/10.1175/MWR-D-13-00229.1, 2014. a
Boutle, I. A., Mayne, N. J., Drummond, B., Manners, J., Goyal, J.,
Hugo Lambert, F., Acreman, D. M., and Earnshaw, P. D.: Exploring the climate
of Proxima B with the Met Office Unified Model, Astron.
Astrophys., 601, A120, https://doi.org/10.1051/0004-6361/201630020, 2017. a
Boutle, I. A., Joshi, M., Lambert, F. H., Mayne, N. J., Lyster, D., Manners,
J., Ridgway, R., and Kohary, K.: Mineral dust increases the habitability of
terrestrial planets but confounds biomarker detection, Nat. Commun.,
11, 2731, https://doi.org/10.1038/s41467-020-16543-8, 2020. a, b
Braam, M., Palmer, P. I., Decin, L., Ridgway, R. J., Zamyatina, M., Mayne,
N. J., Sergeev, D. E., and Abraham, N. L.: Lightning-induced chemistry on
tidally-locked Earth-like exoplanets, Mon. Not. R.
Astron. Soc., 517, 2383–2402, https://doi.org/10.1093/mnras/stac2722, 2022. a, b
Brown, A. R., Beare, R. J., Edwards, J. M., Lock, A. P., Keogh, S. J., Milton,
S. F., and Walters, D. N.: Upgrades to the Boundary-Layer Scheme in the
Met Office Numerical Weather Prediction Model, Bound.-Lay.
Meteorol., 128, 117–132, https://doi.org/10.1007/s10546-008-9275-0,
2008. a
Carone, L., Keppens, R., and Decin, L.: Connecting the dots – II. Phase
changes in the climate dynamics of tidally locked terrestrial exoplanets,
Mon. Not. R.
Astron. Soc., 453, 2413–2438,
https://doi.org/10.1093/mnras/stv1752, 2015. a
Carone, L., Keppens, R., and Decin, L.: Connecting the dots – III.
Nightside cooling and surface friction affect climates of tidally locked
terrestrial planets, Mon. Not. R. Astron. Soc., 461,
1981–2002, https://doi.org/10.1093/mnras/stw1265,
2016. a
Carone, L., Keppens, R., Decin, L., and Henning, T.: Stratosphere circulation
on tidally locked ExoEarths, Mon. Not. R. Astron. Soc., 473, 4672–4685, https://doi.org/10.1093/mnras/stx2732,
Publisher: Oxford Academic, 2018. a, b
Christie, D. A., Mayne, N. J., Lines, S., Parmentier, V., Manners, J., Boutle,
I., Drummond, B., Mikal-Evans, T., Sing, D. K., and Kohary, K.: The impact of
mixing treatments on cloud modelling in 3D simulations of hot Jupiters,
Mon. Not. R. Astron. Soc., 506, 4500–4515,
https://doi.org/10.1093/mnras/stab2027, 2021. a, b
Christie, D. A., Lee, E. K. H., Innes, H., Noti, P. A., Charnay, B., Fauchez,
T. J., Mayne, N. J., Deitrick, R., Ding, F., Greco, J. J., Hammond, M.,
Malsky, I., Mandell, A., Rauscher, E., Roman, M. T., Sergeev, D. E., Sohl,
L., Steinrueck, M. E., Turbet, M., Wolf, E. T., Zamyatina, M., and Carone,
L.: CAMEMBERT: A Mini-Neptunes General Circulation Model
Intercomparison, Protocol Version 1.0.A CUISINES Model
Intercomparison Project, Planet. Sci. J., 3, 261,
https://doi.org/10.3847/PSJ/ac9dfe, 2022. a, b
Cohen, M., Bollasina, M. A., Palmer, P. I., Sergeev, D. E., Boutle, I. A.,
Mayne, N. J., and Manners, J.: Longitudinally Asymmetric Stratospheric
Oscillation on a Tidally Locked Exoplanet, Astrophys. J.,
930, 152, https://doi.org/10.3847/1538-4357/ac625d, 2022. a, b
Cotter, C. and Shipton, J.: Mixed finite elements for numerical weather
prediction, J. Comput. Phys., 231, 7076–7091,
https://doi.org/10.1016/j.jcp.2012.05.020, 2012. a
Dressing, C. D. and Charbonneau, D.: The occurrence of potentially
habitable planets orbiting m dwarfs estimated from the full
Kepler dataset and an empirical measurement of the
detection sensitivity, Astrophys. J., 807, 45,
https://doi.org/10.1088/0004-637X/807/1/45, 2015. a
Drummond, B., Hébrard, E., Mayne, N. J., Venot, O., Ridgway, R. J., Changeat,
Q., Tsai, S.-M., Manners, J., Tremblin, P., Abraham, N. L., Sing, D., and
Kohary, K.: Implications of three-dimensional chemical transport in hot
Jupiter atmospheres: Results from a consistently coupled
chemistry-radiation-hydrodynamics model, Astron. Astrophys., 636, A68,
https://doi.org/10.1051/0004-6361/201937153, 2020. a
Eager-Nash, J. K., Reichelt, D. J., Mayne, N. J., Lambert, F. H., Sergeev,
D. E., Ridgway, R. J., Manners, J., Boutle, I. A., Lenton, T. M., and Kohary,
K.: Implications of different stellar spectra for the climate of tidally
locked Earth-like exoplanets, Astron. Astrophys., 639, A99,
https://doi.org/10.1051/0004-6361/202038089, 2020. a, b
Edson, A., Lee, S., Bannon, P., Kasting, J. F., and Pollard, D.: Atmospheric
circulations of terrestrial planets orbiting low-mass stars, Icarus, 212,
1–13, https://doi.org/10.1016/j.icarus.2010.11.023, 2011. a
Edwards, J. M. and Slingo, A.: Studies with a flexible new radiation code. I:
Choosing a configuration for a large-scale model, Q. J.
Roy. Meteor. Soc., 122, 689–719, https://doi.org/10.1002/qj.49712253107,
1996. a
Fauchez, T. J., Turbet, M., Wolf, E. T., Boutle, I., Way, M. J., Del Genio, A. D., Mayne, N. J., Tsigaridis, K., Kopparapu, R. K., Yang, J., Forget, F., Mandell, A., and Domagal Goldman, S. D.: TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI): motivations and protocol version 1.0, Geosci. Model Dev., 13, 707–716, https://doi.org/10.5194/gmd-13-707-2020, 2020. a, b, c, d, e, f, g, h
Fauchez, T. J., Turbet, M., Sergeev, D. E., Mayne, N. J., Spiga, A., Sohl, L.,
Saxena, P., Deitrick, R., Gilli, G., Domagal-Goldman, S. D., Forget, F.,
Consentino, R., Barnes, R., Haqq-Misra, J., Way, M. J., Wolf, E. T., Olson,
S., Crouse, J. S., Janin, E., Bolmont, E., Leconte, J., Chaverot, G., Jaziri,
Y., Tsigaridis, K., Yang, J., Pidhorodetska, D., Kopparapu, R. K., Chen, H.,
Boutle, I. A., Lefevre, M., Charnay, B., Burnett, A., Cabra, J., and Bouldin,
N.: TRAPPIST Habitable Atmosphere Intercomparison (THAI) Workshop
Report, Planet. Sci. J., 2, 106, https://doi.org/10.3847/PSJ/abf4df,
2021. a, b, c, d
Fauchez, T. J., Villanueva, G. L., Sergeev, D. E., Turbet, M., Boutle, I. A.,
Tsigaridis, K., Way, M. J., Wolf, E. T., Domagal-Goldman, S. D., Forget, F.,
Haqq-Misra, J., Kopparapu, R. K., Manners, J., and Mayne, N. J.: The
TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). III.
Simulated Observables – the Return of the Spectrum, Planet.
Sci. J., 3, 213, https://doi.org/10.3847/PSJ/ac6cf1,
2022. a
Ge, H., Li, C., Zhang, X., and Lee, D.: A Global Nonhydrostatic
Atmospheric Model with a Mass- and Energy-conserving Vertically
Implicit Correction (VIC) Scheme, Astrophys. J., 898,
130, https://doi.org/10.3847/1538-4357/ab9ec7, 2020. a
Gillon, M., Triaud, A. H. M. J., Demory, B.-O., Jehin, E., Agol, E., Deck,
K. M., Lederer, S. M., de Wit, J., Burdanov, A., Ingalls, J. G., Bolmont, E.,
Leconte, J., Raymond, S. N., Selsis, F., Turbet, M., Barkaoui, K., Burgasser,
A., Burleigh, M. R., Carey, S. J., Chaushev, A., Copperwheat, C. M., Delrez,
L., Fernandes, C. S., Holdsworth, D. L., Kotze, E. J., Van Grootel, V.,
Almleaky, Y., Benkhaldoun, Z., Magain, P., and Queloz, D.: Seven temperate
terrestrial planets around the nearby ultracool dwarf star TRAPPIST-1,
Nature, 542, 456–460, https://doi.org/10.1038/nature21360, 2017. a
Gregory, D. and Rowntree, P. R.: A Mass Flux Convection Scheme with
Representation of Cloud Ensemble Characteristics and
Stability-Dependent Closure, Mon. Weather Rev., 118, 1483–1506,
https://doi.org/10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2, iSBN: 0027-0644, 1990. a
Hammond, M. and Lewis, N. T.: The rotational and divergent components of
atmospheric circulation on tidally locked planets, P.
Natl. Acad. Sci. USA, 118, e2022705118,
https://doi.org/10.1073/pnas.2022705118, 2021. a
Haqq-Misra, J., Wolf, E. T., Joshi, M., Zhang, X., and Kopparapu, R. K.:
Demarcating Circulation Regimes of Synchronously Rotating
Terrestrial Planets within the Habitable Zone, Astrophys.
J., 852, 67, https://doi.org/10.3847/1538-4357/aa9f1f, 2018. a
Haqq-Misra, J., Wolf, E. T., Fauchez, T. J., Shields, A. L., and Kopparapu,
R. K.: The Sparse Atmospheric Model Sampling Analysis (SAMOSA)
Intercomparison: Motivations and Protocol Version 1.0: A CUISINES
Model Intercomparison Project, Planet. Sci. J., 3, 260,
https://doi.org/10.3847/PSJ/ac9479, 2022. a
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P.,
Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R.,
Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río,
J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy,
T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array
programming with NumPy, Nature, 585, 357–362,
https://doi.org/10.1038/s41586-020-2649-2, 2020a. a
Harris, L., Zhou, L., Lin, S., Chen, J., Chen, X., Gao, K., Morin, M., Rees,
S., Sun, Y., Tong, M., Xiang, B., Bender, M., Benson, R., Cheng, K., Clark,
S., Elbert, O. D., Hazelton, A., Huff, J. J., Kaltenbaugh, A., Liang, Z.,
Marchok, T., Shin, H. H., and Stern, W.: GFDL SHiELD: A Unified
System for Weather-to-Seasonal Prediction, J. Adv.
Model. Earth Sy., 12, e2020MS002223, https://doi.org/10.1029/2020MS002223,
2020b. a
Heng, K. and Vogt, S. S.: Gliese 581g as a scaled-up version of Earth:
atmospheric circulation simulations, Mon. Not. R. Astron. Soc., 415, 2145–2157,
https://doi.org/10.1111/j.1365-2966.2011.18853.x, 2011. a, b
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Comput.
Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Joshi, M. M., Elvidge, A. D., Wordsworth, R., and Sergeev, D.: Earth’s
Polar Night Boundary Layer as an Analog for Dark Side
Inversions on Synchronously Rotating Terrestrial Exoplanets,
Astrophys. J., 892, L33, https://doi.org/10.3847/2041-8213/ab7fb3, 2020. a
Komacek, T. D. and Abbot, D. S.: The Atmospheric Circulation and Climate
of Terrestrial Planets Orbiting Sun-like and M Dwarf Stars over
a Broad Range of Planetary Parameters, Astrophys. J.,
871, 245, https://doi.org/10.3847/1538-4357/aafb33, 2019. a
Komacek, T. D., Gao, P., Thorngren, D. P., May, E. M., and Tan, X.: The
Effect of Interior Heat Flux on the Atmospheric Circulation of
Hot and Ultra-hot Jupiters, Astrophys. J. Lett., 941,
L40, https://doi.org/10.3847/2041-8213/aca975, 2022. a, b
Kopparapu, R. K., Wolf, E. T., Arney, G., Batalha, N. E., Haqq-Misra, J.,
Grimm, S. L., and Heng, K.: Habitable Moist Atmospheres on Terrestrial
Planets near the Inner Edge of the Habitable Zone around M
Dwarfs, Astrophys. J., 845, 5, https://doi.org/10.3847/1538-4357/aa7cf9,
2017. a
Kopparla, P., Deitrick, R., Heng, K., Mendonça, J. M., and Hammond, M.:
General Circulation Model Errors Are Variable across Exoclimate
Parameter Spaces, Astrophys. J., 923, 39,
https://doi.org/10.3847/1538-4357/ac2d27,
2021. a
Lawrence, B. N., Rezny, M., Budich, R., Bauer, P., Behrens, J., Carter, M., Deconinck, W., Ford, R., Maynard, C., Mullerworth, S., Osuna, C., Porter, A., Serradell, K., Valcke, S., Wedi, N., and Wilson, S.: Crossing the chasm: how to develop weather and climate models for next generation computers?, Geosci. Model Dev., 11, 1799–1821, https://doi.org/10.5194/gmd-11-1799-2018, 2018. a
Leconte, J., Forget, F., Charnay, B., Wordsworth, R., Selsis, F., Millour, E.,
and Spiga, A.: 3D climate modeling of close-in land planets: Circulation
patterns, climate moist bistability, and habitability, Astron.
Astrophys., 554, A69, https://doi.org/10.1051/0004-6361/201321042,
2013. a
Lee, E. K. H., Parmentier, V., Hammond, M., Grimm, S. L., Kitzmann, D., Tan,
X., Tsai, S.-M., and Pierrehumbert, R. T.: Simulating gas giant exoplanet
atmospheres with Exo-FMS: Comparing semi-grey, picket fence and
correlated-k radiative-transfer schemes, Mon. Not. R. Astron. Soc., 506, 2695–2711, https://doi.org/10.1093/mnras/stab1851, 2021. a, b, c
Li, C. and Chen, X.: Simulating Nonhydrostatic Atmospheres on Planets
(SNAP): Formulation, Validation, and Application to the Jovian
Atmosphere, Astrophys. J. Suppl. S., 240, 37,
https://doi.org/10.3847/1538-4365/aafdaa,
2019. a
Lines, S., Mayne, N. J., Boutle, I. A., Manners, J., Lee, G. K. H., Helling,
C., Drummond, B., Amundsen, D. S., Goyal, J., Acreman, D. M., Tremblin, P.,
and Kerslake, M.: Simulating the cloudy atmospheres of HD 209458 b and HD
189733 b with the 3D Met Office Unified Model, Astron.
Astrophys., 615, A97, https://doi.org/10.1051/0004-6361/201732278,
2018. a
Lines, S., Mayne, N. J., Manners, J., Boutle, I. A., Drummond, B., Mikal-Evans,
T., Kohary, K., and Sing, D. K.: Overcast on Osiris: 3D
radiative-hydrodynamical simulations of a cloudy hot Jupiter using the
parametrized, phase-equilibrium cloud formation code EddySed, Mon. Not. R. Astron. Soc., 488, 1332–1355,
https://doi.org/10.1093/mnras/stz1788, 2019. a, b
Little, B.: geovista, Zenodo [code], https://doi.org/10.5281/zenodo.7608302, 2023. a
Lock, A. P.: The Numerical Representation of Entrainment in
Parameterizations of Boundary Layer Turbulent Mixing, Mon.
Weather Rev., 129, 1148–1163,
https://doi.org/10.1175/1520-0493(2001)129<1148:TNROEI>2.0.CO;2, 2001. a
Lock, A. P., Brown, A. R., Bush, M. R., Martin, G. M., and Smith, R. N. B.: A
New Boundary Layer Mixing Scheme. Part I: Scheme
Description and Single-Column Model Tests, Mon. Weather Rev.,
128, 3187–3199, https://doi.org/10.1175/1520-0493(2000)128<3187:ANBLMS>2.0.CO;2,
2000. a
Manners, J., Edwards, J. M., Hill, P., and Thelen, J.-C.: SOCRATES (Suite
Of Community RAdiative Transfer codes based on Edwards and
Slingo) Technical Guide, 1–125,
https://code.metoffice.gov.uk/trac/socrates (last access: 4 September 2023),
2022. a
Maynard, C., Melvin, T., and Müller, E. H.: Multigrid preconditioners for the
mixed finite element dynamical core of the LFRic atmospheric model,
Q. J. Roy. Meteor. Soc., 146, 3917–3936,
https://doi.org/10.1002/qj.3880,
2020. a, b, c
Mayne, N. J., Baraffe, I., Acreman, D. M., Smith, C., Browning, M. K.,
Amundsen, D. S., Wood, N., Thuburn, J., and Jackson, D. R.: The unified
model, a fully-compressible, non-hydrostatic, deep atmosphere global
circulation model, applied to hot Jupiters, Astron. Astrophys., 561,
A1, https://doi.org/10.1051/0004-6361/201322174, 2014a. a, b, c
Mayne, N. J., Baraffe, I., Acreman, D. M., Smith, C., Wood, N., Amundsen, D. S., Thuburn, J., and Jackson, D. R.: Using the UM dynamical cores to reproduce idealised 3-D flows, Geosci. Model Dev., 7, 3059–3087, https://doi.org/10.5194/gmd-7-3059-2014, 2014b. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u
Mayne, N. J., Drummond, B., Debras, F., Jaupart, E., Manners, J., Boutle,
I. A., Baraffe, I., and Kohary, K.: The Limits of the Primitive
Equations of Dynamics for Warm, Slowly Rotating Small Neptunes
and Super Earths, Astrophys. J., 871, 56,
https://doi.org/10.3847/1538-4357/aaf6e9, 2019. a, b
McCulloch, D., Sergeev, D. E., Mayne, N., Bate, M., Manners, J., Boutle, I., Drummond, B., and Kohary, K.: A modern-day Mars climate in the Met Office Unified Model: dry simulations, Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, 2023. a
Melvin, T., Dubal, M., Wood, N., Staniforth, A., and Zerroukat, M.: An
inherently mass-conserving iterative semi-implicit semi-Lagrangian
discretization of the non-hydrostatic vertical-slice equations, Q.
J. Roy. Meteor. Soc., 136, 799–814,
https://doi.org/10.1002/qj.603, 2010. a
Mendonça, J. M.: Mass transport in a moist planetary climate model, Astron.
Astrophys., 659, A43, https://doi.org/10.1051/0004-6361/202141638, 2022. a
Mendonça, J. M., Grimm, S. L., Grosheintz, L., and Heng, K.: THOR: a new
and flexible global circulation model to explore planetary
atmospheres, Astrophys. J., 829, 115,
https://doi.org/10.3847/0004-637X/829/2/115, 2016. a, b
Met Office: Iris: A Python library for analysing and visualising
meteorological and oceanographic data sets,
http://scitools.org.uk/ (last access: 4 September 2023), 2022. a
Met Office: iris-esmf-regrid: A collection of structured and unstructured ESMF regridding schemes for Iris, Github [code], https://github.com/SciTools-incubator/iris-esmf-regrid, last access: 4 September 2023. a
Met Office Science Repository Service: LFRic-Atmosphere, https://code.metoffice.gov.uk, last access: 4 September 2023. a
Molod, A., Takacs, L., Suarez, M., and Bacmeister, J.: Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2, Geosci. Model Dev., 8, 1339–1356, https://doi.org/10.5194/gmd-8-1339-2015, 2015. a
Noda, S., Ishiwatari, M., Nakajima, K., Takahashi, Y., Takehiro, S., Onishi,
M., Hashimoto, G., Kuramoto, K., and Hayashi, Y.-Y.: The circulation pattern
and day-night heat transport in the atmosphere of a synchronously rotating
aquaplanet: Dependence on planetary rotation rate, Icarus, 282, 1–18,
https://doi.org/10.1016/j.icarus.2016.09.004, 2017. a, b, c
Paradise, A., Macdonald, E., Menou, K., Lee, C., and Fan, B. L.: ExoPlaSim:
Extending the Planet Simulator for exoplanets, Mon. Not. R. Astron. Soc., 511, 3272–3303, https://doi.org/10.1093/mnras/stac172,
2022. a, b, c
Polichtchouk, I., Cho, J.-K., Watkins, C., Thrastarson, H., Umurhan, O., and
de la Torre Juárez, M.: Intercomparison of general circulation models for
hot extrasolar planets, Icarus, 229, 355–377,
https://doi.org/10.1016/j.icarus.2013.11.027, 2014. a, b
Rajpurohit, A. S., Reylé, C., Allard, F., Homeier, D., Schultheis, M.,
Bessell, M. S., and Robin, A. C.: The effective temperature scale of M
dwarfs, Astron. Astrophys., 556, A15,
https://doi.org/10.1051/0004-6361/201321346, 2013. a
Ridgway, R. J., Zamyatina, M., Mayne, N. J., Manners, J., Lambert, F. H.,
Braam, M., Drummond, B., Hébrard, E., Palmer, P. I., and Kohary, K.: 3D
modelling of the impact of stellar activity on tidally locked terrestrial
exoplanets: atmospheric composition and habitability, Mon. Not.
R. Astron. Soc., 518, 2472–2496, https://doi.org/10.1093/mnras/stac3105,
2023. a, b
Saffin, L., Lock, A., Tomassini, L., Blyth, A., Böing, S., Denby, L., and
Marsham, J.: Kilometer-Scale Simulations of Trade-Wind Cumulus
Capture Processes of Mesoscale Organization, J. Adv.
Model. Earth Sy., 15, e2022MS003295, https://doi.org/10.1029/2022MS003295, 2023. a
Sergeev, D. E.: dennissergeev/lfric_exo_bench_code: Version 0, Zenodo [data set and code],
https://doi.org/10.5281/zenodo.7818107, 2023. a, b
Sergeev, D. E. and Zamyatina, M.: Aeolus – a Python library for the analysis
and visualisation of climate model output, Zenodo [code], https://doi.org/10.5281/ZENODO.6478085,
2022. a
Sergeev, D. E., Lambert, F. H., Mayne, N. J., Boutle, I. A., Manners, J., and
Kohary, K.: Atmospheric Convection Plays a Key Role in the Climate
of Tidally Locked Terrestrial Exoplanets: Insights from
High-resolution Simulations, Astrophys. J., 894, 84,
https://doi.org/10.3847/1538-4357/ab8882,
2020. a, b, c, d, e
Sergeev, D. E., Fauchez, T. J., Turbet, M., Boutle, I. A., Tsigaridis, K., Way,
M. J., Wolf, E. T., Domagal-Goldman, S. D., Forget, F., Haqq-Misra, J.,
Kopparapu, R. K., Lambert, F. H., Manners, J., and Mayne, N. J.: The
TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). II.
Moist Cases – The Two Waterworlds, Planet. Sci. J.,
3, 212, https://doi.org/10.3847/PSJ/ac6cf2,
2022a. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u
Shashkin, V. V. and Goyman, G. S.: Semi-Lagrangian shallow water equations
solver on the cubed-sphere grid as a prototype of new-generation global
atmospheric model, J. Phys. Conf. Ser., 1740, 012073,
https://doi.org/10.1088/1742-6596/1740/1/012073, 2021. a
Showman, A. P., Fortney, J. J., Lian, Y., Marley, M. S., Freedman, R. S.,
Knutson, H. A., and Charbonneau, D.: Atmospheric circulation of hot
jupiters: coupled radiative-dynamical general circulation model
simulations of HD 189733b and HD 209458b, Astrophys. J.,
699, 564–584, https://doi.org/10.1088/0004-637X/699/1/564, 2009. a, b
Smith, R. N. B.: A scheme for predicting layer clouds and their water content
in a general circulation model, Q. J. Roy. Meteor. Soc., 116, 435–460, https://doi.org/10.1002/qj.49711649210, 1990. a
Staniforth, A. and Thuburn, J.: Horizontal grids for global weather and climate
prediction models: a review, Q. J. Roy. Meteor.
Soc., 138, 1–26, https://doi.org/10.1002/qj.958, 2012. a, b, c, d
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, Prog. Earth Planet. Sc., 6, 61,
https://doi.org/10.1186/s40645-019-0304-z, 2019. a
Turbet, M., Leconte, J., Selsis, F., Bolmont, E., Forget, F., Ribas, I.,
Raymond, S. N., and Anglada-Escudé, G.: The habitability of Proxima
Centauri b, Astron. Astrophys., 596, A112,
https://doi.org/10.1051/0004-6361/201629577, 2016. a
Turbet, M., Bolmont, E., Bourrier, V., Demory, B.-O., Leconte, J., Owen, J.,
and Wolf, E. T.: A Review of Possible Planetary Atmospheres in the
TRAPPIST-1 System, Space Sci. Rev., 216, 100,
https://doi.org/10.1007/s11214-020-00719-1, 2020. a
Turbet, M., Bolmont, E., Chaverot, G., Ehrenreich, D., Leconte, J., and Marcq,
E.: Day–night cloud asymmetry prevents early oceans on Venus but not on
Earth, Nature, 598, 276–280, https://doi.org/10.1038/s41586-021-03873-w, 2021. a
Turbet, M., Fauchez, T. J., Sergeev, D. E., Boutle, I. A., Tsigaridis, K., Way,
M. J., Wolf, E. T., Domagal-Goldman, S. D., Forget, F., Haqq-Misra, J.,
Kopparapu, R. K., Lambert, F. H., Manners, J., Mayne, N. J., and Sohl, L.:
The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). I.
Dry Cases – The Fellowship of the GCMs, Planet. Sci.
J., 3, 211, https://doi.org/10.3847/PSJ/ac6cf0, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s
Vallis, G. K., Colyer, G., Geen, R., Gerber, E., Jucker, M., Maher, P., Paterson, A., Pietschnig, M., Penn, J., and Thomson, S. I.: Isca, v1.0: a framework for the global modelling of the atmospheres of Earth and other planets at varying levels of complexity, Geosci. Model Dev., 11, 843–859, https://doi.org/10.5194/gmd-11-843-2018, 2018. a, b
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019. a, b, c
Way, M. J., Aleinov, I., Amundsen, D. S., Chandler, M. A., Clune, T. L., Genio,
A. D. D., Fujii, Y., Kelley, M., Kiang, N. Y., Sohl, L., and Tsigaridis, K.:
Resolving Orbital and Climate Keys of Earth and Extraterrestrial
Environments with Dynamics (ROCKE-3D) 1.0: A General
Circulation Model for Simulating the Climates of Rocky Planets,
Astrophys. J. Suppl. S., 231, 12,
https://doi.org/10.3847/1538-4365/aa7a06, 2017. a
Wedi, N. P. and Smolarkiewicz, P. K.: A framework for testing global
non-hydrostatic models, Q. J. Roy. Meteor.
Soc., 135, 469–484, https://doi.org/10.1002/qj.377,
2009. a
White, A. A., Hoskins, B. J., Roulstone, I., and Staniforth, A.: Consistent
approximate models of the global atmosphere: shallow, deep, hydrostatic,
quasi-hydrostatic and non-hydrostatic, Q. J. Roy.
Meteor. Soc., 131, 2081–2107, https://doi.org/10.1256/qj.04.49, 2005. a
Wilson, D. R. and Ballard, S. P.: A microphysically based precipitation scheme
for the UK meteorological office unified model, Q. J.
Roy. Meteor. Soc., 125, 1607–1636, https://doi.org/10.1002/qj.49712555707,
1999. a
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., and
Morcrette, C. J.: PC2: A prognostic cloud fraction and condensation
scheme. I: Scheme description, Q. J. Roy.
Meteor. So., 134, 2093–2107, https://doi.org/10.1002/qj.333, 2008. a
Wiltshire, A. J., Duran Rojas, M. C., Edwards, J. M., Gedney, N., Harper, A. B., Hartley, A. J., Hendry, M. A., Robertson, E., and Smout-Day, K.: JULES-GL7: the Global Land configuration of the Joint UK Land Environment Simulator version 7.0 and 7.2, Geosci. Model Dev., 13, 483–505, https://doi.org/10.5194/gmd-13-483-2020, 2020. a
Wolf, E. T., Kopparapu, R., Haqq-Misra, J., and Fauchez, T. J.: ExoCAM: A
3D Climate Model for Exoplanet Atmospheres, Planet. Sci.
J., 3, 7, https://doi.org/10.3847/PSJ/AC3F3D, 2022. a, b, c
Wood, N., Staniforth, A., White, A., Allen, T., Diamantakis, M., Gross, M.,
Melvin, T., Smith, C., Vosper, S., Zerroukat, M., and Thuburn, J.: An
inherently mass-conserving semi-implicit semi-Lagrangian discretization of
the deep-atmosphere global non-hydrostatic equations, Q. J.
Roy. Meteor. Soc., 140, 1505–1520, https://doi.org/10.1002/qj.2235,
2014. a, b, c, d
Wordsworth, R. and Kreidberg, L.: Atmospheres of Rocky Exoplanets, Annu.
Rev. Astron. Astr., 60, 159–201,
https://doi.org/10.1146/annurev-astro-052920-125632, 2022. a
Wordsworth, R. D., Forget, F., Selsis, F., Millour, E., Charnay, B., and
Madeleine, J.-B.: Gliese 581D is the first discovered
terrestrial-mass exoplanet in the habitable zone,
Astrophys. J., 733, L48, https://doi.org/10.1088/2041-8205/733/2/L48, 2011. a
Yang, J., Cowan, N. B., and Abbot, D. S.: Stabilizing cloud feedback
dramatically expands the habitable zone of tidally locked
planets, Astrophys. J., 771, L45,
https://doi.org/10.1088/2041-8205/771/2/L45, 2013. a
Yang, J., Leconte, J., Wolf, E. T., Merlis, T., Koll, D. D. B., Forget, F., and
Abbot, D. S.: Simulations of Water Vapor and Clouds on Rapidly
Rotating and Tidally Locked Planets: A 3D Model
Intercomparison, Astrophys. J., 875, 46,
https://doi.org/10.3847/1538-4357/ab09f1, 2019. a
Zamyatina, M., Hébrard, E., Drummond, B., Mayne, N. J., Manners, J., Christie,
D. A., Tremblin, P., Sing, D. K., and Kohary, K.: Observability of signatures
of transport-induced chemistry in clear atmospheres of hot gas giant
exoplanets, Mon. Not. R. Astron. Soc., 519,
3129–3153, https://doi.org/10.1093/mnras/stac3432, 2023.
a, b
Zhang, F. (Ed.): The Schur Complement and Its Applications, vol. 4,
Springer-Verlag, New York, https://doi.org/10.1007/b105056, 2005. a
Short summary
Three-dimensional climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
Three-dimensional climate models are one of the best tools we have to study planetary...
