Articles | Volume 11, issue 8
https://doi.org/10.5194/gmd-11-3427-2018
© Author(s) 2018. 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-11-3427-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
24 Aug 2018
Model description paper |
| 24 Aug 2018
| 24 Aug 2018
The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory
Mohamed H. Salim
CORRESPONDING AUTHOR
Meteorological Institute, CEN, University of Hamburg, Hamburg, Germany
now at: Faculty of Energy Engineering, Aswan University, Aswan, Egypt
K. Heinke Schlünzen
Meteorological Institute, CEN, University of Hamburg, Hamburg, Germany
David Grawe
Meteorological Institute, CEN, University of Hamburg, Hamburg, Germany
Marita Boettcher
Meteorological Institute, CEN, University of Hamburg, Hamburg, Germany
Andrea M. U. Gierisch
Meteorological Institute, CEN, University of Hamburg, Hamburg, Germany
now at: Finnish Meteorological Institute, Marine Research, Helsinki,
Finland
Björn H. Fock
Meteorological Institute, CEN, University of Hamburg, Hamburg, Germany
now at: Met Office, Exeter, UK
Related authors
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
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Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
Pavel Krč, Jaroslav Resler, Matthias Sühring, Sebastian Schubert, Mohamed H. Salim, and Vladimír Fuka
Geosci. Model Dev., 14, 3095–3120, https://doi.org/10.5194/gmd-14-3095-2021, https://doi.org/10.5194/gmd-14-3095-2021, 2021
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The adverse effects of an urban environment, e.g. heat stress and air pollution, pose a risk to health and well-being. Precise modelling of the urban climate is crucial to mitigate these effects. Conventional atmospheric models are inadequate for modelling the complex structures of the urban environment; in particular, they lack a 3-D model of radiation and its interaction with surfaces and the plant canopy. The new RTM simulates these processes within the PALM-4U urban climate model.
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
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In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
Karolin Sarah Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck
EGUsphere, https://doi.org/10.5194/egusphere-2024-2464, https://doi.org/10.5194/egusphere-2024-2464, 2025
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A microscale, obstacle-resolving meteorological model has been extended with a snow cover and precipitation scheme making it the first model of its kind that includes rain and snow. The model allows first estimates on the influence of different city characteristics on precipitation heterogeneities. The performance of the model extension is assessed by comparing the results of different model versions. For the comparisons, threshold values were derived based on computational accuracy.
Bogi Hansen, Karin M. H. Larsen, Hjálmar Hátún, Steffen M. Olsen, Andrea M. U. Gierisch, Svein Østerhus, and Sólveig R. Ólafsdóttir
Ocean Sci., 19, 1225–1252, https://doi.org/10.5194/os-19-1225-2023, https://doi.org/10.5194/os-19-1225-2023, 2023
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Based on in situ observations combined with sea level anomaly (SLA) data from satellite altimetry, volume as well as heat (relative to 0 °C) transport of the Iceland–Faroe warm-water inflow towards the Arctic (IF inflow) increased from 1993 to 2021. The reprocessed SLA data released in December 2021 represent observed variations accurately. The IF inflow crosses the Iceland–Faroe Ridge in two branches, with retroflection in between. The associated coupling to overflow reduces predictability.
Ronny Badeke, Volker Matthias, Matthias Karl, and David Grawe
Geosci. Model Dev., 15, 4077–4103, https://doi.org/10.5194/gmd-15-4077-2022, https://doi.org/10.5194/gmd-15-4077-2022, 2022
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For air quality modeling studies, it is very important to distribute pollutants correctly into the model system. This has not yet been done for shipping pollution in great detail. We studied the effects of different vertical distributions of shipping pollutants on the urban air quality and derived advanced formulas for it. These formulas take weather conditions and ship-specific parameters like the exhaust gas temperature into account.
Imke Sievers, Andrea M. U. Gierisch, Till A. S. Rasmussen, Robinson Hordoir, and Lars Stenseng
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-84, https://doi.org/10.5194/tc-2022-84, 2022
Preprint withdrawn
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To predict Arctic sea ice models are used. Many ice models exists. They all are skill full, but give different results. Often this differences result from forcing as for example air temperature. Other differences result from the way the physical equations are solved in the model. In this study two commonly used models are compared under equal forcing, to find out how much the models differ under similar external forcing. The results are compared to observations and to eachother.
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022, https://doi.org/10.5194/gmd-15-1269-2022, 2022
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In this study, we developed NEMO-Bohai, an ocean–ice model for the Bohai Sea, China. This study presented the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of ocean and sea ice. NEMO-Bohai is intended to be a valuable tool for long-term ocean and ice simulations and climate change studies.
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
Short summary
Short summary
Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
Pavel Krč, Jaroslav Resler, Matthias Sühring, Sebastian Schubert, Mohamed H. Salim, and Vladimír Fuka
Geosci. Model Dev., 14, 3095–3120, https://doi.org/10.5194/gmd-14-3095-2021, https://doi.org/10.5194/gmd-14-3095-2021, 2021
Short summary
Short summary
The adverse effects of an urban environment, e.g. heat stress and air pollution, pose a risk to health and well-being. Precise modelling of the urban climate is crucial to mitigate these effects. Conventional atmospheric models are inadequate for modelling the complex structures of the urban environment; in particular, they lack a 3-D model of radiation and its interaction with surfaces and the plant canopy. The new RTM simulates these processes within the PALM-4U urban climate model.
Ronny Badeke, Volker Matthias, and David Grawe
Atmos. Chem. Phys., 21, 5935–5951, https://doi.org/10.5194/acp-21-5935-2021, https://doi.org/10.5194/acp-21-5935-2021, 2021
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This work aims to describe the physical distribution of ship exhaust gases in the near field, e.g., inside of a harbor. Results were calculated with a mathematical model for different meteorological and technical conditions. It has been shown that large vessels like cruise ships have a significant effect of up to 55 % downward movement of exhaust gas, as they can disturb the ground near wind circulation. This needs to be considered in urban air pollution studies.
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
Short summary
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In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
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Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Kostas Tsigaridis, Andrew S. Ackerman, Igor Aleinov, Mark A. Chandler, Thomas L. Clune, Christopher M. Colose, Anthony D. Del Genio, Maxwell Kelley, Nancy Y. Kiang, Anthony Leboissetier, Jan P. Perlwitz, Reto A. Ruedy, Gary L. Russell, Linda E. Sohl, Michael J. Way, and Eric T. Wolf
EGUsphere, https://doi.org/10.5194/egusphere-2025-925, https://doi.org/10.5194/egusphere-2025-925, 2025
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We present the second generation of ROCKE-3D, a generalized 3-dimensional model for use in Solar System and exoplanetary simulations of rocky planet climates. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169, https://doi.org/10.5194/egusphere-2025-169, 2025
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Satellites have observed earth's emission of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about the earth and atmosphere. We present a tool that runs alongside global climate models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Maria Vittoria Struglia, Alessandro Anav, Marta Antonelli, Sandro Calmanti, Franco Catalano, Alessandro Dell'Aquila, Emanuela Pichelli, and Giovanna Pisacane
EGUsphere, https://doi.org/10.5194/egusphere-2025-387, https://doi.org/10.5194/egusphere-2025-387, 2025
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We present the results of downscaling global climate projections for the Mediterranean and Italian regions aiming to produce high-resolution climate information for the assessment of climate change signals, focusing on extreme events. A general warming is foreseen by the end of century with a mean precipitation reduction accompanied, over Italian Peninsula, by a strong increase in the intensity of extreme precipitation events, particularly relevant for the high emissions scenario during autumn
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Katherine Grayson, Stephan Thober, Aleksander Lacima-Nadolnik, Ehsan Sharifi, Llorenç Lledó, and Francisco Doblas-Reyes
EGUsphere, https://doi.org/10.5194/egusphere-2025-28, https://doi.org/10.5194/egusphere-2025-28, 2025
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To provide the most accurate climate adaptation information, climate models are being run with finer grid resolution, resulting in larger data output. This paper presents intelligent data reduction algorithms that act on streamed data, a novel way of processing climate data as soon as it is produced. Using these algorithms to calculate statistics, we show that the accuracy provided is well within acceptable bounds while still providing memory savings that bypass unfeasible storage requirements.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Hui Wan, Abhishek Yenpure, Berk Geveci, Richard C. Easter, Philip J. Rasch, Kai Zhang, and Xubin Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2024-4020, https://doi.org/10.5194/egusphere-2024-4020, 2025
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In E3SMv2 and many other global climate models, the simulated anthropogenic aerosol influence on the Earth's energy balance is sensitive to the presence of clouds with very low droplet number concentrations. Numerical experiments conducted in this study suggest that mid- and high-latitude low-level stratus occurring under weak turbulence is an important cloud regime for understanding the causes of very low cloud droplet number concentrations in global climate simulations.
Cited articles
Arakawa, A. and Vivian, R. L.: Computational Design of the Basic Dynamical
Processes of the UCLA General Circulation Model, Method. Comput. Phys., 17,
173–265, 1977.
Briscolini, M. and Santangelo, P.: Development of the Mask Method for
Incompressible Unsteady Flows, J. Comput. Phys., 84, 57–75, 1989.
Bruse, M. and Fleer, H.: Simulating Surface–plant–air Interactions inside
Urban Environments with a Three Dimensional Numerical Model, Environ. Model.
Softwa., 13, 373–84, 1998.
Brutsaert, W.: The Roughness Length for Water Vapor Sensible Heat, and Other
Scalars, J. Atmos. Sci., 32, 2028–31, 1975.
Brutsaert, W.: Evaporation into the Atmosphere: Theory, History and
Applications, Vol. 1, Springer Science & Business Media, 302 pp.,
https://doi.org/10.1007/978-94-017-1497-6, 2013.
Clark, T. L.: A Small-Scale Dynamic Model Using a Terrain-Following
Coordinate Transformation, J. Comput. Phys., 24, 186–215, 1977.
Deardorff, J. W.: Efficient Prediction of Ground Surface Temperature and
Moisture, with Inclusion of a Layer of Vegetation, J. Geophys. Res.-Oceans,
83, 1889–1903, 1978.
Deardorff, J. W.: Stratocumulus-capped mixed layers derived from a
three-dimensional model, Bound.-Lay. Meteorol., 18, 495–527, 1980.
Detering, H. W.: Mixing Length and Turbulent Diffusion Coefficient in
Atmospheric Simulation models, Thesis, Technische Univ., Hanover, Germany,
1985.
Durran, D. R. and Joseph, B. K.: The Effects of Moisture on Trapped Mountain
Lee Waves, J. Atmos. Sci., 39, 2490–2506, 1982.
Dyer, A. J.: A Review of Flux-Profile Relationships, Bound.-Lay. Meteorol.,
7, 363–372, 1974.
Eichhorn, J.: Entwicklung und Anwendung einesdDreidimensionalen mikroskaligen
Stadtklima-Modells, PhD dissertation, University of Mainz, Mainz, Germany,
1989.
Eichhorn, J. and Kniffka, A.: The Numerical Flow Model MISKAM: State of
Development and Evaluation of the Basic Version, Meteorol. Z., 19, 81–90,
2010.
El Kasmi, A. and Christian M.: An Extended K–ε Model for
Turbulent Flow through Horizontal-Axis Wind Turbines, J. Wind Eng. Ind.
Aerod., 96, 103–22, 2008.
Etling, D.: The Planetary Boundary Layer PBL, in: Landolt-Börnstein –
Group V Geophysics, Meteorology – Climatology, Part 1, edited by: Fischer,
G., Group V, 4, 151–88, https://doi.org/10.1007/10356990_33, 1987.
Fischereit, J., Schlünzen, K. H., Gierisch, A. M. U., Grawe, D., and
Petrik, R.: Modelling tidal influence on sea breezes with models of different
complexity, Meteorol. Z., 25, 343–355, https://doi.org/10.1127/metz/2016/0703, 2016.
Fock, B. H.: RANS versus LES Models for Investigations of the Urban Climate,
Thesis, University of Hamburg, Hamburg, Germany, available at:
http://ediss.sub.uni-hamburg.de/volltexte/2015/7171/pdf/Dissertation.pdf
(last access: 27 July 2018), 2015.
Foken, T.: 50 Years of the Monin–Obukhov Similarity Theory, Bound.-Lay.
Meteorol., 119, 431–47, 2006.
Franke, J., Sturm, M., and Kalmbach, C.: Validation of OpenFOAM 1.6. X with
the German VDI Guideline for Obstacle Resolving Micro-Scale Models, J. Wind
Eng. Ind. Aerod., 104, 350–359, 2012.
Früh, B., Becker, P., Deutschländer, T., Hessel, J. D., Kossmann, M.,
Mieskes, I., Namyslo, J., Roos, M., Sievers, U., Steigerwald, T., and Turau,
H.: Estimation of climate-change impacts on the urban heat load using an
urban climate model and regional climate projections, J. Appl. Meteorol.
Climatol., 50, 167–184, 2011.
Gerz, T., Holzaepfel, F., Darracq, D., de Bruin, A., Elsenaar, A., Speijker,
L., Harris, M., Vaughan, M., and Woodfield, A. A.: Aircraft Wake Vortices –
a Position Paper, Wakenet position paper, WakeNet – the European Thematic
Network on Wake Vortex, 80 pp., 2001.
Gierisch, A.: Mikroskalige Modellierung meteorologischer und anthropogener
Einflüsse auf die Wärmeabgabe eines Gebäudes, Master Thesis,
University of Hamburg, Hamburg, Germany, available at:
https://mi-pub.cen.uni-hamburg.de/fileadmin/files/forschung/techmet/nummod/thesis/diplom_andrea_gierisch.pdf
(last access: 17 July 2018), 2011.
Grawe, D., Schlünzen, K. H., and Pascheke, F.: Comparison of Results of
an Obstacle Resolving Microscale Model with Wind Tunnel Data, Atmos.
Environ., 79, 495–509, 2013.
Grawe, D., Bächlin, W., Brünger, H., Eichhorn, J. Franke, J., Leitl,
B., Müller, W., Öttl, D., Salim, M. H., Schlünzen, H., Winkler,
C., and Zimmer, M.: An Updated Evaluation Guideline for Prognostic Microscale
Wind Field Models, 9th International Conference on Urban Climate, Toulouse,
France, 20–24 July, 2015.
Gross, G.: Effects of Different Vegetation on Temperature in an Urban
Building Environment. Micro-Scale Numerical Experiments, Meteorol. Z., 21,
399–412, 2012.
Harms, F., Leitl, B., Schatzmann, M., and Patnaik, G.: Validating LES-Based
Flow and Dispersion Models, J. Wind Eng. Ind. Aerod., 99, 289–295, 2011.
Kapitza, H. and Eppel, D.: A 3-D Poisson Solver Based on Conjugate Gradients
Compared to Standard Iterative Methods and Its Performance on Vector
Computers, J. Comput. Phys., 68, 474–484, 1987.
Kato, M. and Launder, B. E.: The Modelling of Turbulent flow around
stationary and vibrating square cylinders, 9th Symposium on Turbulent Shear
Flows, Kyoto, Japan, 16–18 August, 1993.
Katul, G.: An Investigation of Higher-Order Closure Models for a Forested
Canopy, Bound.-Lay. Meteorol., 89, 47–74, 1998.
Lalic, B. and Mihailovic, D. T.: An Empirical Relation Describing Leaf-Area
Density inside the Forest for Environmental Modeling, J. Appl. Meteorol., 43,
641–45, 2004.
Lilly, D. K.: On the Numerical Simulation of Buoyant Convection, Tellus, 14,
148–172, 1962.
Linde, M.: Modellierung des Einflusses von Windkraftanlagen auf das umgebende
Windfeld, Master Thesis, University of Hamburg, Hamburg, Germany, available
at:
https://mi-pub.cen.uni-hamburg.de/fileadmin/files/forschung/techmet/nummod/thesis/Diplomarbeit_M_Linde.pdf
(last access: 17 July 2018), 2011.
Liu, J., Chen, J. M., Black, T. A., and Novak, M. D.: E-ε
Modelling of Turbulent Air Flow Downwind of a Model Forest Edge, Bound.-Lay.
Meteorol., 77, 21–44, 1996.
López, S. D.: Numerische Modellierung Turbulenter Umströmungen von
Gebäuden, Berichte zur Polar-und Meeresforschung (Reports on Polar and
Marine Research) 418, 93 pp., 2002.
López, S. D., Lupkes, C., and Schlünzen, K. H.: The Effect of
Different K-Closures on the Results of a Micro-Scale Model for the Flow in
the Obstacle Layer, Meteorol. Z., 14, 839–848, 2005.
Maronga, B., Gryschka, M., Heinze, R., Hoffmann, F., Kanani-Sühring, F.,
Keck, M., Ketelsen, K., Letzel, M. O., Sühring, M., and Raasch, S.: The
Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric
and oceanic flows: model formulation, recent developments, and future
perspectives, Geosci. Model Dev., 8, 2515–2551,
https://doi.org/10.5194/gmd-8-2515-2015, 2015.
Meng, C.: The integrated urban land model, J. Adv. Model. Earth Sy., 7,
759–773, 2015.
Mikkelsen, R.: Actuator Disc Methods Applied to Wind Turbines, PhD Thesis,
Technical University of Denmark, Copenhagen, Denmark, available at:
http://orbit.dtu.dk/fedora/objects/orbit:85749/datastreams/file_5452244/content
(last access: 17 July 2018), 2003.
Mittal, R. and Iaccarino, G.: Immersed Boundary Methods, Annu. Rev. Fluid
Mech., 37, 239–61, 2005.
Molly, J.-P.: Windenergie in Theorie und Praxis: Grundlagen und Einsatz,
Müller, karlsruhe, Germany, 138 pp., 1978.
Monin, A. S. and Obukhov, A.: Basic Laws of Turbulent Mixing in the Surface
Layer of the Atmosphere, Contrib. Geophys. Inst. Acad. Sci., USSR 151,
163–187, 1954.
Müller, N., Kuttler, W., and Barlag, A.: Counteracting Urban Climate
Change: Adaptation Measures and Their Effect on Thermal Comfort, Theor. Appl.
Climatol., 115, 243–257, 2014.
Murakami, S., Ooka, R., Mochida, A., Yoshida, S., and Kim, S.: CFD Analysis
of Wind Climate from Human Scale to Urban Scale, J. Wind Eng. Ind. Aerod.,
81, 57–81, 1999.
Pielke, R. A.: Mesoscale Meteorological Modeling, Academic press, 676 pp.,
2002.
Roache, P. J.: Scaling of High-Reynolds-Number Weakly Separated Channel
Flows, in: Numerical and Physical Aspects of Aerodynamic Flows, Springer,
87–98, https://doi.org/10.1007/978-3-662-12610-3_6, 1982.
Röber, N., Salim, M. H., Gierisch, A., Böttinger, M., and
Schlünzen, K. H.: Visualization of Urban Micro-Climate Simulations, The
Eurographics Association, 53–57, 2013.
Salim, M. H., Schlünzen, K. H., and Grawe, D.: Including Trees in the
Numerical Simulations of the Wind Flow in Urban Areas: Should We Care?, J.
Wind Eng. Ind. Aerod., 144, 84–95, 2015.
Salim, M. H., Linde, M., Gierisch, A., and Schlünzen, K. H.: Some Recent
Extensions and Applications of the Micro-Scale Model MITRAS, presented at the
10th European Conference on Applications of Meteorology (ECAM)/11th EMS
Annual Meeting, Berlin, Germany, 12–16 September, 2011.
Schafer, K., Emeis, S., Hoffmann, H., Jahn, C., Muller, W., Heits, B., Haase,
D., Drunkenmolle, W. D., Bachlin, W., Schlünzen, K., and Leitl, B.: Field
Measurements within a Quarter of a City Including a Street Canyon to Produce
a Validation Data Set, Int. J. Environ. Pollut., 25, 201–216, 2005.
Schatzmann, M., Bächlin, W., Emeis, S., Kühlwein, J., Leitl, B.,
Müller, W. J., Schäfer, K., and Schlünzen, H.: Development and
validation of tools for the implementation of european air quality policy in
Germany (Project VALIUM), Atmos. Chem. Phys., 6, 3077–3083,
https://doi.org/10.5194/acp-6-3077-2006, 2006.
Schlünzen, K. H.: Numerical Studies on the Inland Penetration of Sea
Breeze Fronts at a Coastline with Tidally Flooded Mudflats, Contr. Atmos.
Phys., 63, 243–256, 1990.
Schlünzen, K. H., Hinneburg, D., Knoth, O., Lambrecht, M., Leitl, B.,
Lopez, S., Lüpkes, C., Panskus, H., Renner, E., Schatzmann, M., and
Schoenemeyer, T.: Flow and Transport in the Obstacle Layer: First Results of
the Micro-Scale Model MITRAS, J. Atmos. Chem., 44, 113–130, 2003.
Schlünzen, K. H., Boettcher, M., Fock, B. H., Gierisch A., Grawe D., and
Salim, M.: Technical Documentation of the Multiscale Model System M-SYS
(METRAS, MITRAS, MECTM, MICTM, MESIM) Meteorologisches Institut,
Universität Hamburg, MeMi Technical Report 3, 130 pp., 2018a.
Schlünzen, K. H., Boettcher, M., Fock, B. H., Gierisch, A., Grawe, D.,
and Salim, M.: Scientific Documentation of the Multicscale Model System M-SYS
(METRAS, MITRAS, MECTM, MICTM, MESIM) Meteorologisches Institut,
Universität Hamburg, MeMi Technical Report 4, 147 pp., 2018b.
Schlüter, I.: Simulation des Transports biogener Emissionen in und
über einem Waldbestand mit einem mikroskaligen Modellsystem, PhD Thesis,
University of Hamburg, Hamburg, Germany, available at:
https://d-nb.info/98143021X/34 (last access: 17 July 2018), 2006.
Smagorinsky, J.: General Circulation Experiments with The Primitive
Equations: I. The Basic Experiment, Mon. Weather Rev., 91, 99–164, 1963.
Taylor, G. J.: Wake measurements on the Nibe wind turbines in Denmark,
Contractor report ETSU WN 5020, National Power – Technology and Environment
Center, 1990.
Tiedtke, M. and Geleyn, J. F.: The DWD General Circulation Model –
Description of Its Main Features, Beitr. Phys. Atmos., 48, 255–277, 1975.
Trukenmuller, A., Grawe, G., and Schlünzen, K. H.: A Model System for the
Assessment of Ambient Air Quality Conforming to EC Directives, Meteorol. Z.,
13, 387–394, 2004.
Van der Vorst, H. A.: Bi-CGSTAB: A Fast and Smoothly Converging Variant of
Bi-CG for the Solution of Nonsymmetric Linear Systems, SIAM J. Scientific and
Stat. Comp., 13, 631–44, 1992.
VDI: Environmental Meteorology – Prognostic Microscale Wind Field Models –
Evaluation for Flow Around Buildings and Obstacles, Technical Report, VDI
Guideline 3783, Part 9, Commission on Air Pollution Prevention of VDI and
DIN, 2005.
VDI: Environmental Meteorology, Prognostic Microscale Wind Field Models,
Evaluation for Flow around Buildings and Obstacles, VDI-Standard: VDI 3783,
Blatt 9, available at:
http://www.vdi.eu/guidelines/vdi_3783_blatt_9-umweltmeteorologie_prognostische_mikroskalige_windfeldmodelle_evaluierung_fuer_gebaeude_/
(last access: 27 July 2018), 2015.
Wilson, J. D.: A Second-Order Closure Model for Flow through Vegetation,
Bound.-Lay. Meteorol., 42, 371–392, 1988.
Short summary
This paper gives a detailed description of the model theory of the obstacle-resolving microscale meteorological model MITRAS version 2. Detailed descriptions of the model equations and their formulations and approximations are presented. Also, detailed parameterizations of buildings, wind turbines, and vegetation in the model are introduced. Some example applications of the model are shown to demonstrate the model capacities and potential.
This paper gives a detailed description of the model theory of the obstacle-resolving microscale...
