Articles | Volume 15, issue 6
https://doi.org/10.5194/gmd-15-2711-2022
https://doi.org/10.5194/gmd-15-2711-2022
Model description paper
 | 
01 Apr 2022
Model description paper |  | 01 Apr 2022

Bedymo: a combined quasi-geostrophic and primitive equation model in σ coordinates

Clemens Spensberger, Trond Thorsteinsson, and Thomas Spengler

Related authors

Spatio-temporal filtering of jets obscures the reinforcement of baroclinicity by latent heating
Henrik Auestad, Clemens Spensberger, Andrea Marcheggiani, Paulo Ceppi, Thomas Spengler, and Tim Woollings
EGUsphere, https://doi.org/10.5194/egusphere-2024-597,https://doi.org/10.5194/egusphere-2024-597, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
WCD Ideas: Teleconnections through weather rather than stationary waves
Clemens Spensberger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2353,https://doi.org/10.5194/egusphere-2023-2353, 2023
Short summary
Dynamical drivers of Greenland blocking in climate models
Clio Michel, Erica Madonna, Clemens Spensberger, Camille Li, and Stephen Outten
Weather Clim. Dynam., 2, 1131–1148, https://doi.org/10.5194/wcd-2-1131-2021,https://doi.org/10.5194/wcd-2-1131-2021, 2021
Short summary
Smoother versus sharper Gulf Stream and Kuroshio sea surface temperature fronts: effects on cyclones and climatology
Leonidas Tsopouridis, Thomas Spengler, and Clemens Spensberger
Weather Clim. Dynam., 2, 953–970, https://doi.org/10.5194/wcd-2-953-2021,https://doi.org/10.5194/wcd-2-953-2021, 2021
Short summary
Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020,https://doi.org/10.5194/gmd-13-6165-2020, 2020
Short summary

Related subject area

Atmospheric sciences
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024,https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024,https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024,https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024,https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024,https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary

Cited articles

Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical processes of the UCLA general circulation model, Methods in Computational Physics, 17, 173–265, 1977. a
Charney, J. G. and Phillips, N. A.: Numerical Integration of the Quasi-Geostrophic Equations for Barotropic and Simple Baroclinic Flows, J. Meteorology, 10, 71–99, https://doi.org/10.1175/1520-0469(1953)010<0071:NIOTQG>2.0.CO;2, 1953. a, b, c
Codron, F.: Ekman heat transport for slab oceans, Clim. Dynam., 38, 379–389, https://doi.org/10.1007/s00382-011-1031-3, 2012. a
Frierson, D. M. W., Held, I. M., and Zurita-Gotor, P.: A Gray-Radiation Aquaplanet Moist GCM. Part I: Static Stability and Eddy Scale, J. Atmos. Sci., 63, 2548–2566, https://doi.org/10.1175/JAS3753.1, 2006. a
Gill, A. E.: Some simple solutions for heat-induced tropical circulation, Q. J. Roy. Meteor. Soc., 106, 447–462, https://doi.org/10.1002/qj.49710644905, 1980. a, b, c, d, e, f, g
Download
Short summary
In order to understand the atmosphere, we rely on a hierarchy of models ranging from very simple to very complex. Comparing different steps in this hierarchy usually entails comparing different models. Here we combine two such steps that are commonly used in one modelling framework. This makes comparisons both much easier and much more direct.