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.
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
Related authors
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
Short summary
Short summary
We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Anthony Jones, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, Noah Asch, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2024-3376, https://doi.org/10.5194/egusphere-2024-3376, 2024
Short summary
Short summary
We study aerosol-fog interactions near Paris using a weather and climate model with high spatial resolution. We show that our model can simulate fog lifecycle effectively. We find that the fog droplet number concentrations, the amount of liquid water in the fog, and the vertical structure of the fog are highly sensitive to the parameterization that simulates droplet formation and growth. The changes we propose could improve fog forecasts significantly without increasing computational costs.
Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2024-3397, https://doi.org/10.5194/egusphere-2024-3397, 2024
Short summary
Short summary
We study the lifecycle of fog events in Europe using a weather and climate model. By incorporating droplet formation and growth driven by radiative cooling, our model better simulates the total liquid water in foggy atmospheric columns. We show that both adiabatic and radiative cooling play significant, often equally important roles in driving droplet formation and growth. We discuss strategies to address droplet number overpredictions, by improving model physics and addressing model artifacts.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, https://doi.org/10.5194/gmd-16-1713-2023, 2023
Short summary
Short summary
Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the UK. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
Short summary
Short summary
This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
Short summary
Short summary
We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Rachel E. Hawker, Annette K. Miltenberger, Jill S. Johnson, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Paul R. Field, Benjamin J. Murray, and Ken S. Carslaw
Atmos. Chem. Phys., 21, 17315–17343, https://doi.org/10.5194/acp-21-17315-2021, https://doi.org/10.5194/acp-21-17315-2021, 2021
Short summary
Short summary
We find that ice-nucleating particles (INPs), aerosols that can initiate the freezing of cloud droplets, cause substantial changes to the properties of radiatively important convectively generated anvil cirrus. The number concentration of INPs had a large effect on ice crystal number concentration while the INP temperature dependence controlled ice crystal size and cloud fraction. The results indicate information on INP number and source is necessary for the representation of cloud glaciation.
Craig Poku, Andrew N. Ross, Adrian A. Hill, Alan M. Blyth, and Ben Shipway
Atmos. Chem. Phys., 21, 7271–7292, https://doi.org/10.5194/acp-21-7271-2021, https://doi.org/10.5194/acp-21-7271-2021, 2021
Short summary
Short summary
We present a new aerosol activation scheme suitable for modelling both fog and convective clouds. Most current activation schemes are designed for convective clouds, and we demonstrate that using them to model fog can negatively impact its life cycle. Our scheme has been used to model an observed fog case in the UK, where we demonstrate that a more physically based representation of aerosol activation is required to capture the transition to a deeper layer – more in line with observations.
Rachel E. Hawker, Annette K. Miltenberger, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Zhiqiang Cui, Richard J. Cotton, Ken S. Carslaw, Paul R. Field, and Benjamin J. Murray
Atmos. Chem. Phys., 21, 5439–5461, https://doi.org/10.5194/acp-21-5439-2021, https://doi.org/10.5194/acp-21-5439-2021, 2021
Short summary
Short summary
The impact of aerosols on clouds is a large source of uncertainty for future climate projections. Our results show that the radiative properties of a complex convective cloud field in the Saharan outflow region are sensitive to the temperature dependence of ice-nucleating particle concentrations. This means that differences in the aerosol source or composition, for the same aerosol size distribution, can cause differences in the outgoing radiation from regions dominated by tropical convection.
Mike Bush, Tom Allen, Caroline Bain, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Humphrey Lean, Adrian Lock, James Manners, Marion Mittermaier, Cyril Morcrette, Rachel North, Jon Petch, Chris Short, Simon Vosper, David Walters, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 13, 1999–2029, https://doi.org/10.5194/gmd-13-1999-2020, https://doi.org/10.5194/gmd-13-1999-2020, 2020
Short summary
Short summary
In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against.
Thomas J. Fauchez, Martin Turbet, Eric T. Wolf, Ian Boutle, Michael J. Way, Anthony D. Del Genio, Nathan J. Mayne, Konstantinos Tsigaridis, Ravi K. Kopparapu, Jun Yang, Francois Forget, Avi Mandell, and Shawn D. Domagal Goldman
Geosci. Model Dev., 13, 707–716, https://doi.org/10.5194/gmd-13-707-2020, https://doi.org/10.5194/gmd-13-707-2020, 2020
Short summary
Short summary
Atmospheric characterization of rocky exoplanets orbiting within the habitable zone of nearby M dwarf stars is around the corner with the James Webb Space Telescope (JWST), expected to be launch in 2021.
Global climate models (GCMs) are powerful tools to model exoplanet atmospheres and to predict their habitability. However, intrinsic differences between the models can lead to various predictions. This paper presents an experiment protocol to evaluate these differences.
David Walters, Anthony J. Baran, Ian Boutle, Malcolm Brooks, Paul Earnshaw, John Edwards, Kalli Furtado, Peter Hill, Adrian Lock, James Manners, Cyril Morcrette, Jane Mulcahy, Claudio Sanchez, Chris Smith, Rachel Stratton, Warren Tennant, Lorenzo Tomassini, Kwinten Van Weverberg, Simon Vosper, Martin Willett, Jo Browse, Andrew Bushell, Kenneth Carslaw, Mohit Dalvi, Richard Essery, Nicola Gedney, Steven Hardiman, Ben Johnson, Colin Johnson, Andy Jones, Colin Jones, Graham Mann, Sean Milton, Heather Rumbold, Alistair Sellar, Masashi Ujiie, Michael Whitall, Keith Williams, and Mohamed Zerroukat
Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, https://doi.org/10.5194/gmd-12-1909-2019, 2019
Short summary
Short summary
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, GA7/GL7, which includes new aerosol and snow schemes and addresses the four critical errors identified in GA6. GA7/GL7 will underpin the UK's contributions to CMIP6, and hence their documentation is important.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
Short summary
Short summary
The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Gary Lloyd, Thomas W. Choularton, Keith N. Bower, Martin W. Gallagher, Jonathan Crosier, Sebastian O'Shea, Steven J. Abel, Stuart Fox, Richard Cotton, and Ian A. Boutle
Atmos. Chem. Phys., 18, 17191–17206, https://doi.org/10.5194/acp-18-17191-2018, https://doi.org/10.5194/acp-18-17191-2018, 2018
Short summary
Short summary
The work deals with cold weather outbreaks at high latitudes that often bring severe weather such as heavy snow, lightning and high winds but are poorly forecast by weather models. Here we made measurements of these events and the clouds associated with them using a research aircraft. We found that the properties of these clouds were often very different to what the models predicted, and these results can potentially be used to bring significant improvement to the forecasting of these events.
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
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
Short summary
Short summary
We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
Annette K. Miltenberger, Paul R. Field, Adrian A. Hill, Ben J. Shipway, and Jonathan M. Wilkinson
Atmos. Chem. Phys., 18, 10593–10613, https://doi.org/10.5194/acp-18-10593-2018, https://doi.org/10.5194/acp-18-10593-2018, 2018
Ian Boutle, Jeremy Price, Innocent Kudzotsa, Harri Kokkola, and Sami Romakkaniemi
Atmos. Chem. Phys., 18, 7827–7840, https://doi.org/10.5194/acp-18-7827-2018, https://doi.org/10.5194/acp-18-7827-2018, 2018
Short summary
Short summary
Aerosol processes are a key mechanism in the development of fog. Poor representation of aerosol–fog interaction can result in large biases in fog forecasts, such as surface temperatures which are too high and fog which is too deep and long lived. A relatively simple representation of aerosol–fog interaction can actually lead to significant improvements in forecasting. Aerosol–fog interaction can have a large effect on the climate system but is poorly represented in climate models.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Related subject area
Atmospheric sciences
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
A Novel Method for Quantifying the Contribution of Regional Transport to PM2.5 in Beijing (2013–2020): Combining Machine Learning with Concentration-Weighted Trajectory Analysis
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals 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 the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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
Short summary
Short summary
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.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
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
Short summary
Short summary
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.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
Short summary
Short summary
The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
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
Short summary
Short summary
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.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-157, https://doi.org/10.5194/gmd-2024-157, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study combines Machine Learning with Concentration-Weighted Trajectory Analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
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
Short summary
Short summary
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.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
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
Short summary
Short summary
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.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
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...