Articles | Volume 11, issue 1
https://doi.org/10.5194/gmd-11-257-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-257-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
18 Jan 2018
Model description paper |
| 18 Jan 2018
The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1
Piet Termonia
CORRESPONDING AUTHOR
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent university, Ghent, Belgium
Claude Fischer
CNRM/GMAP, Météo-France, Toulouse, France
Eric Bazile
CNRM/GMAP, Météo-France, Toulouse, France
François Bouyssel
CNRM/GMAP, Météo-France, Toulouse, France
Radmila Brožková
Czech Hydrometeorological Institute, Prague, Czech Republic
Pierre Bénard
CNRM/GMAP, Météo-France, Toulouse, France
Bogdan Bochenek
Institute of Meteorology and Water Management – State Research Institute of Poland, Krakow, Poland
Daan Degrauwe
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent university, Ghent, Belgium
Mariá Derková
Slovak Hydrometeorological Institute, Bratislava, Slovakia
Ryad El Khatib
CNRM/GMAP, Météo-France, Toulouse, France
Rafiq Hamdi
Royal Meteorological Institute, Brussels, Belgium
Ján Mašek
Czech Hydrometeorological Institute, Prague, Czech Republic
Patricia Pottier
CNRM/GMAP, Météo-France, Toulouse, France
Neva Pristov
Slovenian Environment Agency, Ljubljana, Slovenia
Yann Seity
CNRM/GMAP, Météo-France, Toulouse, France
Petra Smolíková
Czech Hydrometeorological Institute, Prague, Czech Republic
Oldřich Španiel
Slovak Hydrometeorological Institute, Bratislava, Slovakia
Martina Tudor
Meteorological and Hydrological Service, Zagreb, Croatia
Yong Wang
Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
Christoph Wittmann
Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
Alain Joly
CNRM/GMAP, Météo-France, Toulouse, France
Related authors
Anouk Dierickx, Wout Dewettinck, Bert Van Schaeybroeck, Lesley De Cruz, Steven Caluwaerts, Piet Termonia, and Hans Van de Vyver
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-30, https://doi.org/10.5194/essd-2025-30, 2025
Preprint under review for ESSD
Short summary
Short summary
This study introduces the EURO-SUPREME dataset consisting of extreme precipitation events selected from a large ensemble of climate models over Europe. The dataset contains information on extreme precipitation events with a precipitation duration of 1 hour to 72 hours that can lead to flooding, high mortality rates and infrastructure damage. We highlight the usefulness of the dataset as a benchmark for improving high-resolution climate models for risk assessment of future extreme floods.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
EGUsphere, https://doi.org/10.5194/egusphere-2024-4057, https://doi.org/10.5194/egusphere-2024-4057, 2025
Short summary
Short summary
We use deposition measurements to trace the source of the radioactive isotope Ru-106 released into the atmosphere in 2017, which led to detections in Europe and other parts of the northern hemisphere. Most frequently, measurements of air concentration are used for such purposes. Our research shows that while air concentration data can provide more precise results, deposition measurements can still effectively pinpoint the release location, offering a less costly and more versatile alternative.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Geosci. Model Dev., 16, 5323–5338, https://doi.org/10.5194/gmd-16-5323-2023, https://doi.org/10.5194/gmd-16-5323-2023, 2023
Short summary
Short summary
Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Michiel Van Ginderachter, Daan Degrauwe, Stéphane Vannitsem, and Piet Termonia
Nonlin. Processes Geophys., 27, 187–207, https://doi.org/10.5194/npg-27-187-2020, https://doi.org/10.5194/npg-27-187-2020, 2020
Short summary
Short summary
A generic methodology is developed to estimate the model error and simulate the model uncertainty related to a specific physical process. The method estimates the model error by comparing two different representations of the physical process in otherwise identical models. The found model error can then be used to perturb the model and simulate the model uncertainty. When applying this methodology to deep convection an improvement in the probabilistic skill of the ensemble forecast is found.
Julie Berckmans, Olivier Giot, Rozemien De Troch, Rafiq Hamdi, Reinhart Ceulemans, and Piet Termonia
Geosci. Model Dev., 10, 223–238, https://doi.org/10.5194/gmd-10-223-2017, https://doi.org/10.5194/gmd-10-223-2017, 2017
Short summary
Short summary
The regional climate of western Europe was simulated using an atmospheric and land surface model. This study aims at improving the coupling of the models, by applying an alternative method for the update frequency of the atmospheric and soil parameters. The results show that a daily update of the atmosphere and soil outperforms a continuous approach. However, keeping the land surface continuous but having daily atmospheric updates is preferable at times, as it benefits from soil moisture memory.
Daan Degrauwe, Yann Seity, François Bouyssel, and Piet Termonia
Geosci. Model Dev., 9, 2129–2142, https://doi.org/10.5194/gmd-9-2129-2016, https://doi.org/10.5194/gmd-9-2129-2016, 2016
Short summary
Short summary
In its purest essence, numerical weather prediction boils down to solving the fundamental laws of nature with computers. Such fundamental laws are the conservation of energy and the conservation of mass. In this paper, a framework is presented that allows to respect these laws more accurately, which should lead to weather forecasts that correspond better to reality. Under specific circumstances, such as heavy precipitation, the proposed framework has a significant impact on the forecast.
Olivier Giot, Piet Termonia, Daan Degrauwe, Rozemien De Troch, Steven Caluwaerts, Geert Smet, Julie Berckmans, Alex Deckmyn, Lesley De Cruz, Pieter De Meutter, Annelies Duerinckx, Luc Gerard, Rafiq Hamdi, Joris Van den Bergh, Michiel Van Ginderachter, and Bert Van Schaeybroeck
Geosci. Model Dev., 9, 1143–1152, https://doi.org/10.5194/gmd-9-1143-2016, https://doi.org/10.5194/gmd-9-1143-2016, 2016
Short summary
Short summary
The Royal Meteorological Institute of Belgium and Ghent University have performed two simulations with different horizontal resolutions of the past observed climate of Europe for the period 1979–2010. Of special interest is the new way of handling convective precipitation in the model that was used. Results show that the model is capable of representing the European climate and comparison with other models reveals that precipitation patterns are well represented.
A. Duerinckx, R. Hamdi, J.-F. Mahfouf, and P. Termonia
Geosci. Model Dev., 8, 845–863, https://doi.org/10.5194/gmd-8-845-2015, https://doi.org/10.5194/gmd-8-845-2015, 2015
R. Hamdi, D. Degrauwe, A. Duerinckx, J. Cedilnik, V. Costa, T. Dalkilic, K. Essaouini, M. Jerczynki, F. Kocaman, L. Kullmann, J.-F. Mahfouf, F. Meier, M. Sassi, S. Schneider, F. Váňa, and P. Termonia
Geosci. Model Dev., 7, 23–39, https://doi.org/10.5194/gmd-7-23-2014, https://doi.org/10.5194/gmd-7-23-2014, 2014
Danaé Préaux, Ingrid Dombrowski-Etchevers, Isabelle Gouttevin, and Yann Seity
EGUsphere, https://doi.org/10.5194/egusphere-2025-708, https://doi.org/10.5194/egusphere-2025-708, 2025
Short summary
Short summary
Structural inhomogeneities of the valleys and mountains observational network contribute to the misrepresentation of near-surface air temperature and should be considered both when evaluating the model performances and in assimilation.
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.
Anouk Dierickx, Wout Dewettinck, Bert Van Schaeybroeck, Lesley De Cruz, Steven Caluwaerts, Piet Termonia, and Hans Van de Vyver
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-30, https://doi.org/10.5194/essd-2025-30, 2025
Preprint under review for ESSD
Short summary
Short summary
This study introduces the EURO-SUPREME dataset consisting of extreme precipitation events selected from a large ensemble of climate models over Europe. The dataset contains information on extreme precipitation events with a precipitation duration of 1 hour to 72 hours that can lead to flooding, high mortality rates and infrastructure damage. We highlight the usefulness of the dataset as a benchmark for improving high-resolution climate models for risk assessment of future extreme floods.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
EGUsphere, https://doi.org/10.5194/egusphere-2024-4057, https://doi.org/10.5194/egusphere-2024-4057, 2025
Short summary
Short summary
We use deposition measurements to trace the source of the radioactive isotope Ru-106 released into the atmosphere in 2017, which led to detections in Europe and other parts of the northern hemisphere. Most frequently, measurements of air concentration are used for such purposes. Our research shows that while air concentration data can provide more precise results, deposition measurements can still effectively pinpoint the release location, offering a less costly and more versatile alternative.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Philippe Ricaud, Massimo Del Guasta, Angelo Lupi, Romain Roehrig, Eric Bazile, Pierre Durand, Jean-Luc Attié, Alessia Nicosia, and Paolo Grigioni
Atmos. Chem. Phys., 24, 613–630, https://doi.org/10.5194/acp-24-613-2024, https://doi.org/10.5194/acp-24-613-2024, 2024
Short summary
Short summary
Clouds affect the Earth's climate in ways that depend on the type of cloud (solid/liquid water). From observations at Concordia (Antarctica), we show that in supercooled liquid water (liquid water for temperatures below 0°C) clouds (SLWCs), temperature and SLWC radiative forcing increase with liquid water (up to 70 W m−2). We extrapolated that the maximum SLWC radiative forcing can reach 40 W m−2 over the Antarctic Peninsula, highlighting the importance of SLWCs for global climate prediction.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
Short summary
Short summary
The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Geosci. Model Dev., 16, 5323–5338, https://doi.org/10.5194/gmd-16-5323-2023, https://doi.org/10.5194/gmd-16-5323-2023, 2023
Short summary
Short summary
Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
Short summary
Short summary
Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
Short summary
Short summary
The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Patrick Le Moigne, Eric Bazile, Anning Cheng, Emanuel Dutra, John M. Edwards, William Maurel, Irina Sandu, Olivier Traullé, Etienne Vignon, Ayrton Zadra, and Weizhong Zheng
The Cryosphere, 16, 2183–2202, https://doi.org/10.5194/tc-16-2183-2022, https://doi.org/10.5194/tc-16-2183-2022, 2022
Short summary
Short summary
This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are, under certain conditions, able to reproduce the surface temperature just as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.
Linye Song, Shangfeng Chen, Wen Chen, Jianping Guo, Conglan Cheng, and Yong Wang
Atmos. Chem. Phys., 22, 1669–1688, https://doi.org/10.5194/acp-22-1669-2022, https://doi.org/10.5194/acp-22-1669-2022, 2022
Short summary
Short summary
This study shows that in most years when haze pollution (HP) over the North China Plain (NCP) is more (less) serious in winter, air conditions in the following spring are also worse (better) than normal. Conversely, there are some years when HP in the following spring is opposed to that in winter. It is found that North Atlantic sea surface temperature (SST) anomalies play important roles in HP evolution over the NCP. Thus North Atlantic SST is an important preceding signal for NCP HP evolution.
Sara Top, Lola Kotova, Lesley De Cruz, Svetlana Aniskevich, Leonid Bobylev, Rozemien De Troch, Natalia Gnatiuk, Anne Gobin, Rafiq Hamdi, Arne Kriegsmann, Armelle Reca Remedio, Abdulla Sakalli, Hans Van De Vyver, Bert Van Schaeybroeck, Viesturs Zandersons, Philippe De Maeyer, Piet Termonia, and Steven Caluwaerts
Geosci. Model Dev., 14, 1267–1293, https://doi.org/10.5194/gmd-14-1267-2021, https://doi.org/10.5194/gmd-14-1267-2021, 2021
Short summary
Short summary
Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.
Michiel Van Ginderachter, Daan Degrauwe, Stéphane Vannitsem, and Piet Termonia
Nonlin. Processes Geophys., 27, 187–207, https://doi.org/10.5194/npg-27-187-2020, https://doi.org/10.5194/npg-27-187-2020, 2020
Short summary
Short summary
A generic methodology is developed to estimate the model error and simulate the model uncertainty related to a specific physical process. The method estimates the model error by comparing two different representations of the physical process in otherwise identical models. The found model error can then be used to perturb the model and simulate the model uncertainty. When applying this methodology to deep convection an improvement in the probabilistic skill of the ensemble forecast is found.
Philippe Ricaud, Massimo Del Guasta, Eric Bazile, Niramson Azouz, Angelo Lupi, Pierre Durand, Jean-Luc Attié, Dana Veron, Vincent Guidard, and Paolo Grigioni
Atmos. Chem. Phys., 20, 4167–4191, https://doi.org/10.5194/acp-20-4167-2020, https://doi.org/10.5194/acp-20-4167-2020, 2020
Short summary
Short summary
Thin (~ 100 m) supercooled liquid water (SLW, water staying in liquid phase below 0 °C) clouds have been detected, analysed, and modelled over the Dome C (Concordia, Antarctica) station during the austral summer 2018–2019 using observations and meteorological analyses. The SLW clouds were observed at the top of the planetary boundary layer and the SLW content was always strongly underestimated by the model indicating an incorrect simulation of the surface energy budget of the Antarctic Plateau.
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, https://doi.org/10.5194/gmd-12-4425-2019, 2019
Short summary
Short summary
This paper presents an overview of the ESCAPE project. Dwarfs (key patterns in terms of computation and communication) are identified in weather prediction models. They are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain-specific languages. Different numerical techniques are compared in terms of energy efficiency and performance for a variety of computing technologies.
Martin Belluš, Florian Weidle, Christoph Wittmann, Yong Wang, Simona Taşku, and Martina Tudor
Adv. Sci. Res., 16, 63–68, https://doi.org/10.5194/asr-16-63-2019, https://doi.org/10.5194/asr-16-63-2019, 2019
Short summary
Short summary
A meso-scale ensemble system Aire Limitée Adaptation dynamique Développement InterNational - Limited Area Ensemble Forecasting (ALADIN-LAEF) based on the limited area model ALADIN has been developed in the framework of Regional Cooperation for Limited Area modelling in Central Europe (RC LACE) consortium, focusing on short range probabilistic forecasts and profiting from advanced multi-scale ALARO physics. Its main purpose is to provide probabilistic forecast on daily basis for the national weat
Clemens Wastl, Yong Wang, Aitor Atencia, and Christoph Wittmann
Geosci. Model Dev., 12, 261–273, https://doi.org/10.5194/gmd-12-261-2019, https://doi.org/10.5194/gmd-12-261-2019, 2019
Short summary
Short summary
Ensemble forecasting at the convection-permitting scale (< 3 km) requires new methodologies in representing model uncertainties. In this paper a new stochastic scheme is proposed and tested in the complex terrain of the Alps. In this scheme the tendencies of the physical parametrizations are perturbed separately, which sustains a physically consistent relationship between the processes. This scheme increases the stability of the model and leads to improvements in the probabilistic performance.
Julie Berckmans, Roeland Van Malderen, Eric Pottiaux, Rosa Pacione, and Rafiq Hamdi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1097, https://doi.org/10.5194/acp-2018-1097, 2018
Preprint withdrawn
Short summary
Short summary
The use of ground-based observations is suitable for the assessment of atmospheric water vapour in climate models. We used water vapour observations from 100 European sites to evaluate two models: a reanalysis product and a regional climate model. The results reveal patterns in the water vapour distribution both in time and space that are relevant as water vapour plays a key role in the feedback process of a changing climate.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Bert Van Schaeybroeck, Lesley De Cruz, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Quentin Laffineur, Crist Amelynck, Niels Schoon, Bernard Heinesch, Thomas Holst, Almut Arneth, Reinhart Ceulemans, Arturo Sanchez-Lorenzo, and Alex Guenther
Biogeosciences, 15, 3673–3690, https://doi.org/10.5194/bg-15-3673-2018, https://doi.org/10.5194/bg-15-3673-2018, 2018
Short summary
Short summary
Biogenic isoprene fluxes are simulated over Europe with the MEGAN–MOHYCAN model for the recent past and end-of-century climate at high spatiotemporal resolution (0.1°, 3 min). Due to climate change, fluxes increased by 40 % over 1979–2014. Climate scenarios for 2070–2099 suggest an increase by 83 % due to climate, and an even stronger increase when the potential impact of CO2 fertilization is considered (up to 141 %). Accounting for CO2 inhibition cancels out a large part of these increases.
Philippe Ricaud, Eric Bazile, Massimo del Guasta, Christian Lanconelli, Paolo Grigioni, and Achraf Mahjoub
Atmos. Chem. Phys., 17, 5221–5237, https://doi.org/10.5194/acp-17-5221-2017, https://doi.org/10.5194/acp-17-5221-2017, 2017
Short summary
Short summary
The novelty of the paper is to combine a large set of measurements and meteorological models to study the genesis of thick cloud and diamond dust/ice fog (ice crystals) episodes above Dome C, Antarctica. The originality of the work is to attribute the presence of thick cloud and diamond dust/ice fog to advection and microphysical processes with oceanic and continental origin of air masses, respectively. Thick cloud episodes are reproduced by the models but not diamond dust/ice fog episode.
Julie Berckmans, Olivier Giot, Rozemien De Troch, Rafiq Hamdi, Reinhart Ceulemans, and Piet Termonia
Geosci. Model Dev., 10, 223–238, https://doi.org/10.5194/gmd-10-223-2017, https://doi.org/10.5194/gmd-10-223-2017, 2017
Short summary
Short summary
The regional climate of western Europe was simulated using an atmospheric and land surface model. This study aims at improving the coupling of the models, by applying an alternative method for the update frequency of the atmospheric and soil parameters. The results show that a daily update of the atmosphere and soil outperforms a continuous approach. However, keeping the land surface continuous but having daily atmospheric updates is preferable at times, as it benefits from soil moisture memory.
Theresa Schellander-Gorgas, Yong Wang, Florian Meier, Florian Weidle, Christoph Wittmann, and Alexander Kann
Geosci. Model Dev., 10, 35–56, https://doi.org/10.5194/gmd-10-35-2017, https://doi.org/10.5194/gmd-10-35-2017, 2017
Short summary
Short summary
Ensemble forecasting offers a useful method to simulate the uncertainty of a numerical forecast model for each individual forecast run. This study compares ALADIN-LAEF, a 16-member ensemble with a resolution of 11 km that combines several perturbation methods, with AROME-EPS, which downscales the members of ALADIN-LAEF to 2.5 km resolution. The verification shows that there are benefits of a higher-resolution ensemble, especially for highly localized precipitation and for mountainous terrain.
Hossein Tabari, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Sajjad Saeed, Erwan Brisson, Nicole Van Lipzig, and Patrick Willems
Hydrol. Earth Syst. Sci., 20, 3843–3857, https://doi.org/10.5194/hess-20-3843-2016, https://doi.org/10.5194/hess-20-3843-2016, 2016
Fleur Couvreux, Eric Bazile, Guylaine Canut, Yann Seity, Marie Lothon, Fabienne Lohou, Françoise Guichard, and Erik Nilsson
Atmos. Chem. Phys., 16, 8983–9002, https://doi.org/10.5194/acp-16-8983-2016, https://doi.org/10.5194/acp-16-8983-2016, 2016
Short summary
Short summary
This study evaluates the ability of operational models to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence field campaign. The models succeed in reproducing the variability from one day to another in terms of cloud cover, temperature and boundary-layer depth. However, they exhibit some systematic biases. The high-resolution model reproduces the vertical structures better.
Jan Douša, Galina Dick, Michal Kačmařík, Radmila Brožková, Florian Zus, Hugues Brenot, Anastasia Stoycheva, Gregor Möller, and Jan Kaplon
Atmos. Meas. Tech., 9, 2989–3008, https://doi.org/10.5194/amt-9-2989-2016, https://doi.org/10.5194/amt-9-2989-2016, 2016
Short summary
Short summary
GNSS products provide observations of atmospheric water vapour. Advanced tropospheric products focus on ultra-fast and high-resolution zenith total delays (ZTDs), horizontal gradients and slant delays, all suitable for rapid-cycle numerical weather prediction (NWP) and severe weather event monitoring. The GNSS4SWEC Benchmark provides a complex data set for developing and assessing these products, with initial focus on reference ZTDs and gradients derived from several NWP and dense GNSS networks.
Daan Degrauwe, Yann Seity, François Bouyssel, and Piet Termonia
Geosci. Model Dev., 9, 2129–2142, https://doi.org/10.5194/gmd-9-2129-2016, https://doi.org/10.5194/gmd-9-2129-2016, 2016
Short summary
Short summary
In its purest essence, numerical weather prediction boils down to solving the fundamental laws of nature with computers. Such fundamental laws are the conservation of energy and the conservation of mass. In this paper, a framework is presented that allows to respect these laws more accurately, which should lead to weather forecasts that correspond better to reality. Under specific circumstances, such as heavy precipitation, the proposed framework has a significant impact on the forecast.
Emily Gleeson, Velle Toll, Kristian Pagh Nielsen, Laura Rontu, and Ján Mašek
Atmos. Chem. Phys., 16, 5933–5948, https://doi.org/10.5194/acp-16-5933-2016, https://doi.org/10.5194/acp-16-5933-2016, 2016
Short summary
Short summary
The direct shortwave (SW) radiative effect of aerosols under clear-sky conditions in the ALADIN-HIRLAM numerical weather prediction system was investigated using three SW radiation schemes in diagnostic single-column experiments. Each scheme accurately simulates the direct SW effect when observed aerosols are used, particularly for heavy pollution scenarios.
Olivier Giot, Piet Termonia, Daan Degrauwe, Rozemien De Troch, Steven Caluwaerts, Geert Smet, Julie Berckmans, Alex Deckmyn, Lesley De Cruz, Pieter De Meutter, Annelies Duerinckx, Luc Gerard, Rafiq Hamdi, Joris Van den Bergh, Michiel Van Ginderachter, and Bert Van Schaeybroeck
Geosci. Model Dev., 9, 1143–1152, https://doi.org/10.5194/gmd-9-1143-2016, https://doi.org/10.5194/gmd-9-1143-2016, 2016
Short summary
Short summary
The Royal Meteorological Institute of Belgium and Ghent University have performed two simulations with different horizontal resolutions of the past observed climate of Europe for the period 1979–2010. Of special interest is the new way of handling convective precipitation in the model that was used. Results show that the model is capable of representing the European climate and comparison with other models reveals that precipitation patterns are well represented.
M. Mokhtari, P. Tulet, C. Fischer, Y. Bouteloup, F. Bouyssel, and O. Brachemi
Atmos. Chem. Phys., 15, 9063–9082, https://doi.org/10.5194/acp-15-9063-2015, https://doi.org/10.5194/acp-15-9063-2015, 2015
Short summary
Short summary
The seasonal cycle and optical properties of mineral dust aerosols in northern Africa were simulated for the period from 2006 to 2010 using the numerical atmospheric model ALADIN (Aire Limitée Adaptation dynamique Développement InterNational) coupled to the surface scheme SURFEX (SURFace EXternalisée). These simulations aim to quantify the dust emission and deposition and establish a three-dimensional dust aerosol distribution and extinction climatology over northern Africa.
F. Besson, E. Bazile, C. Soci, J.-M. Soubeyroux, G. Ouzeau, and M. Perrin
Adv. Sci. Res., 12, 137–140, https://doi.org/10.5194/asr-12-137-2015, https://doi.org/10.5194/asr-12-137-2015, 2015
Short summary
Short summary
Due to the evolution of the observation network, hourly 2m temperature analysis performed by reanalysis systems shows temporal inhomogeneities. In this study, the diurnal temperature cycle has been reconstructed for stations which only record extreme temperatures to produce new “pseudo” hourly temperature observations. Then they are provided to analysis systems; the results have shown that it enables reducing the bias in temperature analysis.
A. Duerinckx, R. Hamdi, J.-F. Mahfouf, and P. Termonia
Geosci. Model Dev., 8, 845–863, https://doi.org/10.5194/gmd-8-845-2015, https://doi.org/10.5194/gmd-8-845-2015, 2015
M. Lothon, F. Lohou, D. Pino, F. Couvreux, E. R. Pardyjak, J. Reuder, J. Vilà-Guerau de Arellano, P Durand, O. Hartogensis, D. Legain, P. Augustin, B. Gioli, D. H. Lenschow, I. Faloona, C. Yagüe, D. C. Alexander, W. M. Angevine, E Bargain, J. Barrié, E. Bazile, Y. Bezombes, E. Blay-Carreras, A. van de Boer, J. L. Boichard, A. Bourdon, A. Butet, B. Campistron, O. de Coster, J. Cuxart, A. Dabas, C. Darbieu, K. Deboudt, H. Delbarre, S. Derrien, P. Flament, M. Fourmentin, A. Garai, F. Gibert, A. Graf, J. Groebner, F. Guichard, M. A. Jiménez, M. Jonassen, A. van den Kroonenberg, V. Magliulo, S. Martin, D. Martinez, L. Mastrorillo, A. F. Moene, F. Molinos, E. Moulin, H. P. Pietersen, B. Piguet, E. Pique, C. Román-Cascón, C. Rufin-Soler, F. Saïd, M. Sastre-Marugán, Y. Seity, G. J. Steeneveld, P. Toscano, O. Traullé, D. Tzanos, S. Wacker, N. Wildmann, and A. Zaldei
Atmos. Chem. Phys., 14, 10931–10960, https://doi.org/10.5194/acp-14-10931-2014, https://doi.org/10.5194/acp-14-10931-2014, 2014
W. M. Angevine, E. Bazile, D. Legain, and D. Pino
Atmos. Chem. Phys., 14, 8165–8172, https://doi.org/10.5194/acp-14-8165-2014, https://doi.org/10.5194/acp-14-8165-2014, 2014
R. Hamdi, D. Degrauwe, A. Duerinckx, J. Cedilnik, V. Costa, T. Dalkilic, K. Essaouini, M. Jerczynki, F. Kocaman, L. Kullmann, J.-F. Mahfouf, F. Meier, M. Sassi, S. Schneider, F. Váňa, and P. Termonia
Geosci. Model Dev., 7, 23–39, https://doi.org/10.5194/gmd-7-23-2014, https://doi.org/10.5194/gmd-7-23-2014, 2014
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
Related subject area
Atmospheric sciences
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
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
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
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
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
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
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
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
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
Short summary
Short summary
Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
Short summary
Short summary
The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
Short summary
Short summary
This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
Short summary
Short summary
We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
Short summary
Short summary
Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
Short summary
We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Short summary
Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary
Short summary
The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
Short summary
Short summary
The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
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.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
Short summary
Short summary
Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
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.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
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.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
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.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
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.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
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.
Cited articles
ALADIN international team: The ALADIN project: Mesoscale modelling seen as a basic tool for weather forecasting and atmospheric research, WMO Bull., 46, 317–324, 1997.
Amodei, M., Sanchez, I., and Stein, J.: Verification of the French operational high-resolution model AROME with the regional Brier probability score, Meteorol. Appl., 22, 731–745, https://doi.org/10.1002/met.1510, 2015.
Auger, L., Dupont, O., Hagelin, S., Brousseau, P., and Brovelli, P.: AROME–NWC: a new nowcasting tool based on an operational mesoscale forecasting system, Q. J. Roy. Meteor. Soc., 141, 1603–1611, https://doi.org/10.1002/qj.2463, 2015.
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015.
Bazile, E., Marquet, P., Bouteloup, Y., and Bouyssel, F.: The Turbulent Kinetic Energy (TKE) scheme in the NWP models at Météo-France, ECMWF Workshop Proceedings, Workshop on Diurnal cycles and the stable boundary layer, 7–10 November 2011, Reading, UK, 127–136, 2011.
Bechtold, P., Cuijpers, J., Mascart, P., and Trouilhet, P.: Modelling of trade-wind cumuli with a low-order turbulence model–toward a unified description of Cu and Sc clouds in meteorological models, J. Atmos. Sci., 52, 455–463, 1995.
Bechtold, P., Bazile, E., Guichard, F., Mascart, P., and Richard, E.: A mass flux convection scheme for regional and global models, Q. J. Roy. Meteor. Soc., 127, 869–886, 2001.
Belamari, S. and Pirani, A.: Validation of the optimal heat and momentum fluxes using the ORCA2-LIM global ocean-ice model. Marine environment and security for the European area. Integrated Project (MERSEA IP), Deliverable D4.1.3, 88 pp., 2007.
Bénard, P.: Stability of Semi-Implicit and Iterative Centered-Implicit Time Discretizations for Various Equation Systems Used in NWP, Mon. Weather Rev., 131, 2479–2491, 2003.
Bénard, P., Laprise, R., Vivoda, J., and Smolíková, P.: Stability of Leapfrog Constant-Coefficients Semi-Implicit Schemes for the Fully Elastic System of Euler Equations: Flat-Terrain Case, Mon. Weather Rev., 132, 1306–1318, 2004.
Bénard, P., Mašek, J., and Smolíková, P.: Stability of leapfrog constant-coefficient semi-implicit schemes for the fully elastic system of Euler equations: Case with orography, Mon. Weather Rev., 133, 1065–1075, 2005.
Bénard, P., Vivoda, J., Mašek, J., Smolíková, P., Yessad, K., Smith, C., Brožková, R., and Geleyn, J.-F.: Dynamical kernel of the Aladin-NH spectral limited-area model: Revised formulation and sensitivity experiments., Q. J. Roy. Meteor. Soc., 136, 155–169, 2010.
Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W., Gleeson, E., Hansen-Sass, B., Homleid, M., Hortal, M., Ivarsson, K.-I., Lenderik, G., Niemelä, S., Nielsen, K. P., Onvlee, J., Rontu, L., Samuelsson, P., Muñoz, D. S., Subias, A., Tijm, S., Tol, V., Yang, X., and Køltzow, M. Ø.: The HARMONIE-AROME model configuration in the ALADIN-HIRLAM NWP system, Mon. Weather Rev., 145, 1919–1935, https://doi.org/10.1175/MWR-D-16-0417.1, 2017.
Bougeault, P.: Cloud-ensemble relations based on the gamma probability distribution for the higher-order models of the planetary boundary layer, J. Atmos. Sci., 39, 2691–2700, 1982.
Bougeault, P.: A simple parameterization of the large-scale effects of cumulus convection, Mon. Weather Rev., 113, 2108–2121, https://doi.org/10.1175/1520-0493(1985)113<2108:ASPOTL>2.0.CO;2, 1985.
Bougeault, P. and Lacarrere, P.: Parameterization of orography-induced turbulence in a meso-beta-scale model, Mon. Weather Rev., 117, 1870–1888, 1989.
Bouteloup, Y. and Toth, H.: Refinements in the parameterisation of radiative exchanges, ALADIN Newsletter, 23, 178–183, 2003.
Bouteloup, Y., Bouyssel, F., and Marquet, P.: Improvements of Lopez's progonostic large scale cloud and precipitation scheme, Météo-France, ALADIN Newsletter, 28, 66–73, 2005.
Bouteloup, Y., Seity, Y., and Bazile, E.: Description of the sedimentation scheme used operationally in all Météo-France NWP models, Tellus A, 63, 300–311, 2011.
Bouttier, F., Raynaud, L., Nuissier, O., and Ménétrier, B.: Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX, Q. J. Roy. Meteor. Soc., 142, 390–403, https://doi.org/10.1002/qj.2622, 2016.
Boyd, J. P.: Limited-Area Fourier Spectral Models and Data Analysis Schemes: Windows, Fourier Extension, Davies Relaxation, and All That, Mon. Weather Rev., 133, 2030–2042, https://doi.org/10.1175/MWR2960.1, 2005.
Brousseau, P., Seity, Y., Ricard, D., and Léger, J.: Improvement of the forecast of convective activity from the AROME-France system, Q. J. Roy. Meteor. Soc., 142, 2231–2243, 2016.
Bubnová, R., Hello, G., Bénard, P., and Geleyn, J.-F.: Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of the arpege/aladin nwp system, Mon. Weather Rev., 123, 515–535, 1995.
Canuto, V. M., Cheng, Y., and Howard, A. M.: Non-local ocean mixing model and a new plume model for deep convection, Ocean Model., 16, 28–46, https://doi.org/10.1016/j.ocemod.2006.07.003, 2007.
Canuto, V. M., Cheng, Y., Howard, A. M., and Esau, I. N.: Stably stratified flows: A model with no Ri(cr), J. Atmos. Sci., 65, 2437–2447, https://doi.org/10.1175/2007JAS2470.1, 2008.
Carabajal, C., Harding, D., Boy, J.-P., Danielson, J. , Gesch, D., and Suchdeo, V.: Evaluation of the global multi-resolution terrain elevation data 2010 (GMTED2010) using ICESat geodetic control, in: SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, Nanjing, China, 2011.
Catry, B., Geleyn, J.-F., Tudor, M., Bénard, P., and Trojáková, A.: Flux-conservative thermodynamic equations in a mass-weighted framework, Tellus A, 59, 71–79, 2007.
Catry, B., Geleyn, J.-F., Bouyssel, F., Cedilnik, J., Brožková, R., Derková, M., and Mladek, R.: A new sub-grid scale lift formulation in a mountain drag parameterisation scheme, Meteorol. Z., 17, 193–208, https://doi.org/10.1127/0941-2948/2008/0272, 2008.
Charnock, H.: Wind stress over a water surface, Q. J. Roy. Meteor. Soc., 81, 639–640, 1955.
Cheng, Y., Canuto, V. M., and Howard, A. M.: An improved model for the turbulent PBL, J. Atmos. Sci., 59, 1550–1565, https://doi.org/10.1175/1520-0469(2002)059<1550:AIMFTT>2.0.CO;2, 2002.
Coiffier, J.: Fundamentals of Numerical Weather Prediction, Cambridge University Press, Cambridge, UK, https://doi.org/10.1017/CBO9780511734458, 2011.
Colin, J., Déqué, M., Radu, R., and Somot, S.: Sensitivity study of heavy precipitations in Limited Area Model climate simulation: influence of the size of the domain and the use of the spectral nudging technique, Tellus A, 62, 591–604, https://doi.org/10.1111/j.1600-0870.2010.00467.x, 2010.
Courtier, P. and Geleyn, J.-F.: A global numerical weather prediction model with variable resolution: Application to the shallow model equations, Q. J. Roy. Meteor. Soc., 114, 1321–1346, 1988.
Courtier, P., Freydier, C., Geleyn, J.-F., Rabier, F., and Rochas, M.: The ARPEGE project at Météo-France, Proceedings of 1991 ECMWF Seminar on Numerical Methods in Atmospheric Models, ECMWF, Reading, UK, 193–231, 1991.
Cuxart, J., Bougeault, P., and Redelsberger, J.-L.: A turbulence scheme allowing for mesoscale and large-eddy simulations, Q. J. Roy. Meteor. Soc., 126, 1–30, 2000.
Davies, H. C.: A lateral boundary formulation for multilevel prediction models, Q. J. Roy. Meteor. Soc., 102, 405–418, 1976.
Davies, H. C.: Limitations of some common lateral boundary schemes used in regional NWP models, Mon. Weather Rev., 111, 1002–1012, 1983.
Degrauwe, D., Caluwaerts, S., Voitus, F., Hamdi, R., and Termonia, P.: Application of Boyd's Periodization and Relaxation Method in a Spectral Atmospheric Limited-Area Model. Part II: Accuracy Analysis and Detailed Study of the Operational Impact, Mon. Weather Rev., 140, 3149–3162, https://doi.org/10.1175/MWR-D-12-00032.1, 2012.
Degrauwe, D., Seity, Y., Bouyssel, F., and Termonia, P.: Generalization and application of the flux-conservative thermodynamic equations in the AROME model of the ALADIN system, Geosci. Model Dev., 9, 2129–2142, https://doi.org/10.5194/gmd-9-2129-2016, 2016.
Delobbe, L. and Holleman, I.: Uncertainties in radar echo top heights used for hail detection, Meteor. Appl., 13, 361–374, https://doi.org/10.1017/S1350482706002374, 2006.
De Meutter, P., Gerard, L., Smet, G., Hamid, K., Hamdi, R., Degrauwe, D., and Termonia, P.: Predicting Small-Scale, Short-Lived Downbursts: Case Study with the NWP Limited-Area ALARO Model for the Pukkelpop Thunderstorm, Mon. Weather Rev., 143, 742–756, https://doi.org/10.1175/MWR-D-14-00290.1, 2015.
Déqué, M. and Somot, S.: Extreme precipitation and high resolution with Aladin, Idöjaras Quaterly Journal of the Hungarian Meteorological Service, 112, 179–190, 2008.
de Rooy, W., de Bruijn, C., Tijm, S., Neggers, R., Siebesma, P., and Barkmeijer, J.: Experiences with HARMONIE at KNMI, HIRLAM Newsletter, 56, 21–29, 2010.
De Troch, R., Hamdi, R., Van de Vyver, H., Geleyn, J.-F., and Termonia, P.: Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium, J. Climate, 26, 8895–8915, https://doi.org/10.1175/JCLI-D-12-00844.1, 2013.
Ďurán, I. B., Geleyn, J., and Váňa, F.: A Compact Model for the Stability Dependency of TKE Production–Destruction–Conversion Terms Valid for the Whole Range of Richardson Numbers, J. Atmos. Sci., 71, 3004–3026, https://doi.org/10.1175/JAS-D-13-0203.1, 2014.
Ebert, E. and Curry, J. A.: A parameterization of ice cloud optical properties for climate models, J. Geophys. Res., 97, 3831–3835, 1992.
Field, P. R., Brožková, R., Chen, M., Dudhia, J., Lac, C., Hara, T., Honnert, R., Olson, J., Siebesma, P., de Roode, S., Tomassini, L., Hill, A., and McTagart-Cowan, R.: Exploring the convective grey zone with regional simulations of a cold air outbreak, Q. J. Roy. Meteor. Soc., 143, 2537–2555, https://doi.org/10.1002/qj.3105, 2017.
Fischer, C., Montmerle, T., Berre, L., Auger, L., and Ştefǎnescu, S. E.: An overview of the variational assimilation in the ALADIN/France numerical weather-prediction system, Q. J. Roy. Meteor. Soc., 131, 3477–3492, https://doi.org/10.1256/qj.05.115, 2005.
Fouquart, Y. and Bonnel, B.: Computations of solar heating of the earth's atmosphere: A new parameterization, Beitr. Phys. Atmos., 53, 35–62, 1980.
Geleyn, J.-F., Váňa, F., Cedilnik, J., Tudor, M., and Catry, B.: An intermediate solution between diagnostic exchange coefficients and prognostic TKE methods for vertical turbulent transport, in: CAS/JSC WGNE “Blue Book” annual report: Research Activities in Atmospheric and Ocean Modelling, edited by: Côté, J., 4.11–4.12, 2006.
Geleyn, J.-F., Catry, B., Bouteloup, Y., and Brožková, R.: A statistical approach for sedimentation inside a micro-physical precipitation scheme, Tellus A, 60, 649–662, 2008.
Geleyn, J.-F., Mašek, J., Brožková, R., Kuma, P., Degrauwe, D., Hello, G., and Pristov, N.: Single interval longwave radiation scheme based on the net exchange rate decomposition with bracketing, Q. J. Roy. Meteor. Soc., 143, 1313–1335, https://doi.org/10.1002/qj.3006, 2017.
Gerard, L.: Bulk Mass-Flux Perturbation Formulation for a Unified Approach of Deep Convection at High Resolution, Mon. Weather Rev., 143, 4038–4063, https://doi.org/10.1175/MWR-D-15-0030.1, 2015.
Gerard, L. and Geleyn, J.-F.: Evolution of a subgrid deep convection parameterization in a limited area model with increasing resolution, Q. J. Roy. Meteor. Soc., 131, 2293–2312, 2005.
Gerard, L., Piriou, J.-M., Brožková, R., Geleyn, J.-F., and Banciu, D.: Cloud and precipitation parameterization in a meso-gamma-scale operational weather prediction model, Mon. Weather Rev., 137, 3960–3977, 2009.
Giot, O., Termonia, P., Degrauwe, D., De Troch, R., Caluwaerts, S., Smet, G., Berckmans, J., Deckmyn, A., De Cruz, L., De Meutter, P., Duerinckx, A., Gerard, L., Hamdi, R., Van den Bergh, J., Van Ginderachter, M., and Van Schaeybroeck, B.: Validation of the ALARO-0 model within the EURO-CORDEX framework, Geosci. Model Dev., 9, 1143–1152, https://doi.org/10.5194/gmd-9-1143-2016, 2016.
Grisogono, B. and Belušić, D.: A review of recent advances in understanding the meso- and microscale properties of the severe Bora wind, Tellus A, 61, 1–16, 2009.
Guérémy, J.-F.: A continuous buoyancy based convection scheme: one- and three dimensional validation, Tellus, 63A, 687–706, https://doi.org/10.1111/j.1600-0870.2011.00521.x, 2011.
Hage, J. V. D.: A parametrization of the Wegener-Bergeron-Findeisen effect, Atmos. Res., 39, 201–214, 1995.
Haiden, T., Kann, A., Wittmann, C., Pistotnik, G., Bica, B., and C, C. G.: The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region, Weather Forecast., 26, 166–183, 2011.
Hamdi, R., Degrauwe, D., Duerinckx, A., Cedilnik, J., Costa, V., Dalkilic, T., Essaouini, K., Jerczynki, M., Kocaman, F., Kullmann, L., Mahfouf, J.-F., Meier, F., Sassi, M., Schneider, S., Váňa, F., and Termonia, P.: Evaluating the performance of SURFEXv5 as a new land surface scheme for the ALADINcy36 and ALARO-0 models, Geosci. Model Dev., 7, 23–39, https://doi.org/10.5194/gmd-7-23-2014, 2014.
Hamrud, M., Saarinen, S., and Salmond, D.: Implementation of the IFS on a highly parallel scalar system, in: Proceedings of the tenth ECMWF workshop on the use of parallel processors in meteorology, 4–8 November 2002, Reading, UK, World Scientific, Singapore, 74–87, 2012.
Haugen, J. E. and Machenhauer, B.: A spectral Limited-Area Model Formulation with Time-Dependent Boundary Conditions Applied to the Shallow-Water Equations, Mon. Weather Rev., 121, 2618–2630, 1993.
Hogan, R. J. and Illingworth, A. J.: Deriving cloud overlap statistics from radar, Q. J. Roy. Meteor. Soc., 126, 2903–2909, https://doi.org/10.1002/qj.49712656914, 2000.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008.
Ivatek-Šahdan, S. and Tudor, M.: Use of high-resolution dynamical adaptation in operational suite and research impact studies, Meteorol. Z., 13, 1–10, 2004.
Jakimow, G., Yakimiw, E., and Robert, A.: An Implicit Formulation for Horizontal Diffusion in Gridpoint Models, Mon. Weather Rev., 120, 124–130, https://doi.org/10.1175/1520-0493(1992)120<0124:AIFFHD>2.0.CO;2, 1992.
Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining/detraining plume model and its application in convective parameterizations, J. Atmos. Sci., 47, 2784–2802, 1990.
Lafore, J. P., Stein, J., Asencio, N., Bougeault, P., Ducrocq, V., Duron, J., Fischer, C., Héreil, P., Mascart, P., Masson, V., Pinty, J. P., Redelsperger, J. L., Richard, E., and Vilà-Guerau de Arellano, J.: The Meso-NH Atmospheric Simulation System. Part I: adiabatic formulation and control simulations, Ann. Geophys., 16, 90–109, https://doi.org/10.1007/s00585-997-0090-6, 1998.
Laprise, R.: The Euler equations of motion with hydrostatic pressure as an independent variable, Mon. Weather Rev., 120, 197–207, 1992.
Lascaux, F., Richard, E., and Pinty, J.-P.: Numerical simulations of three map IOPs and the associated microphysical processes, Q. J. Roy. Meteor. Soc., 132, 1907–1926, 2006.
Laurantin, O.: ANTILOPE: Hourly rainfall analysis merging radar and rain gauge data, Proceedings of the International Symposium on Weather Radar and Hydrology, 2–8, Grenoble, France, 2008.
Li, D. and Shine, K. P.: A 4-dimensional ozone climatology for UGAMP models, UGAMP (UK Universities Global Atmospheric Modelling Programme) Internal Report No. 35, Meteorology Department, Reading University, 1995.
Lopez, P.: Implementation and validation of a new prognostic large-scale cloud and precipitation scheme for climate and data-assimilation purposes, Q. J. Roy. Meteor. Soc., 128, 229–257, https://doi.org/10.1256/00359000260498879, 2002.
Louis, J.-F.: A parametric model of vertical eddy fluxes in the atmosphere, Bound.-Lay. Meteorol., 17, 187–202, https://doi.org/10.1007/BF00117978, 1979.
Lynch, P.: Initialization using a digital filter, Research Activities in Atmospheric and Ocean Modeling, CAS/JSC Working Group on Numerical Experimentation, Rep. 14, WMO Secretariat, Geneva, Switzerland, 1.5–1.6., 1990.
Lynch, P.: The Dolph–Chebyshev Window: A Simple Optimal Filter, Mon. Weather Rev., 125, 655–660, https://doi.org/10.1175/1520-0493(1997)125<0655:TDCWAS>2.0.CO;2, 1997.
Lynch, P., Giard, D., and Ivanovici, V.: Improving the Efficiency of a Digital Filtering Scheme for Diabatic Initialization, Mon. Weather Rev., 125, 1976–1982, https://doi.org/10.1175/1520-0493(1997)125<1976:ITEOAD>2.0.CO;2, 1997.
Malardel, S. and Ricard, D.: An alternative cell-averaged departure point reconstruction for pointwise semi-Lagrangian transport schemes, Q. J. Roy. Meteor. Soc., 141, 2114–2126, 2015.
Marquet, P. and Geleyn, J.-F.: On a general definition of the squared Brunt–Väisälä frequency associated with the specific moist entropy potential temperature, Q. J. Roy. Meteor. Soc., 139, 85–100, 2013.
Martin, G. M., Johnson, D. W., and Spice, A.: The measurement and parameterization of effective radius of droplets in warm stratocumulus, J. Atmos. Sci., 51, 1823–1842, 1994.
Mašek, J., Geleyn, J.-F., Brožková, R., Giot, O., Achom, H. O., and Kuma, P.: Single interval shortwave radiation scheme with parameterized optical saturation and spectral overlaps, Q. J. Roy. Meteor. Soc., 142, 304–326, https://doi.org/10.1002/qj.2653, 2016.
Masson, V.: A physically-based scheme for the urban energy budget in atmospheric models, Bound.-Lay. Meteorol., 94, 357–397, 2000.
Masson, V., Champeaux, J.-L., Chauvin, F., Meriguet, C., and Lacaze, R.: A Global Database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models, J. Climate, 16, 1261–1282, https://doi.org/10.1175/1520-0442(2003)16<1261:AGDOLS>2.0.CO;2, 2003.
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013.
Mellor, G. L.: Analytic prediction of the properties of stratified planetary surface layers, J. Atmos. Sci., 30, 1061–1069, https://doi.org/10.1175/1520-0469(1973)030<1061:APOTPO>2.0.CO;2, 1973.
Mellor, G. L. and Yamada, T.: A hierarchy of turbulence closure models for planetary boundary layers, J. Atmos. Sci., 31, 1791–1806, https://doi.org/10.1175/1520-0469(1974)031<1791:AHOTCM>2.0.CO;2, 1974.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982.
Michalakes, J., Govett, M., Benson, R., Black, T., Juang, H., Reinecke, A., and Skamarock, B.: NGGPS level-1 benchmarks and software evaluation. Advanced Computing Evaluation Committee Rep., 22 pp., available at: http://www.nws.noaa.gov/ost/nggps/DycoreTestingFiles/AVEC %20Level%201%20Benchmarking%20Report%2008%20 20150602.pdf (last access: 15 January 2018), 2015.
Mlawer, E. J., Taubman, S. J., Brown, P., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102, 16663–16682, 1997.
Morcrette, J.-J.: Revision of the clear-sky and cloud radiative properties in the ECMWF model, ECMWF Newsletter, 61, 3–14, 1993.
Morcrette, J.-J.: The surface longwave radiation in the ECMWF Forecast System, ECMWF Technical Memorandum, 339, ECMWF, Reading, UK, 34 pp., 2001.
Morcrette, J.-J. and Fouquart, Y.: The overlapping of cloud layers in shortwave radiation parameterizations, J. Atmos. Sci., 43, 321–328, 1986.
Noilhan, J. and Planton, S.: A simple parameterization of land surface processes for meteorological models, Mon. Weather Rev., 117, 536–549, 1989.
Oreopoulos, L., Lee, D., Sud, Y. C., and Suarez, M. J.: Radiative impacts of cloud heterogeneity and overlap in an atmospheric General Circulation Model, Atmos. Chem. Phys., 12, 9097–9111, https://doi.org/10.5194/acp-12-9097-2012, 2012.
Ou, S. C. and Liou, K.-N.: Ice microphysics and climatic temperature feedback, Atmos. Res., 35, 127–138, 1995.
Pergaud, J., Masson, V., Malardel, S., and Couvreux, F.: A parameterization of dry thermals and shallow cumuli for mesoscale numerical weather prediction, Bound.-Lay. Meteorol., 132, 83–106, 2009.
Pinty, J.-P. and Jabouille, P.: A mixed-phased cloud parameterization for use in la mesoscale non-hydrostatic model: Simulations of a squall line and of orographic precipitation, Preprints, Conf. on Cloud Physics, 17–21 August 1998, Everett, WA, USA, Am. Meteorol. Soc., 217–220, 1998.
Piriou, J.-M., Redelsperger, J.-L., Geleyn, J.-F., Lafore, J.-P., and Guichard, F.: An approach for convective parameterization with memory, in separating microphysics and transport in grid-scale equations, J. Atmos. Sci., 64, 4127–4139, 2007.
Radnóti, G.: Comments on “A spectral limited-area formulation with time-dependent boundary conditions applied to the shallow-water equations”, Mon. Weather Rev., 123, 3122–3123, 1995.
Radnóti, G., Ajjaji, R., Bubnova, R., Caian, M., Cordoneanu, E., Emde, K., Grill, J.-D., Hoffman, J., Horanyi, A., Issara, S., Ivanovici, V., Janousek, M., Joly, A., Moigne, P. L., and Malardel, S.: The spectral limited area model ARPEGE/ALADIN, PWRP report series, 7, 111–117, 1995.
Raynaud, L. and Bouttier, F.: Comparison of initial perturbation methods for ensemble prediction at convective scale, Q. J. Roy. Meteor. Soc., 142, 854–866, https://doi.org/10.1002/qj.2686, 2016.
Ritchie, H., Temperton, C., Simmons, A., Hortal, M., Davies, T., Dent, D., and Hamrud, M.: Implementation of the Semi-Lagrangian Method in a High-Resolution Version of the ECMWF Forecast Model, Mon. Weather Rev., 123, 489–514, https://doi.org/10.1175/1520-0493(1995)123<0489:IOTSLM>2.0.CO;2, 1995.
Ritter, B. and Geleyn, J.-F.: A comprehensive radiation scheme fornumerical weather prediction models with potential applications in climate simulations, Mon. Weather Rev., 120, 303–325, https://doi.org/10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2, 1992.
Robert, A. J., Henderson, J., and Turnbull, C.: An implicit scheme for baroclinic models of the atmosphere, Mon. Weather Rev., 100, 329–335, 1972.
Schellander-Gorgas, T., Wang, Y., Meier, F., Weidle, F., Wittmann, C., and Kann, A.: On the forecast skill of a convection-permitting ensemble, Geosci. Model Dev., 10, 35–56, https://doi.org/10.5194/gmd-10-35-2017, 2017.
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F., Lac, C., and Masson, V.: The AROME-France Convective-Scale Operational Model, Mon. Weather Rev., 139, 976–991, https://doi.org/10.1175/2010MWR3425.1, 2011.
Senkova, A. V., Rontu, L., and Savijärvi, H.: Parametrization of orographic effects on surface radiation in HIRLAM, Tellus, 59, 279–291, 2007.
Simmons, A. J. and Burridge, D.: An energy and angular-momentum conserving vertical finite-difference scheme and hybrid vertical coordinates, Mon. Weather Rev., 109, 758–766, 1981.
Simmons, A. J., Hoskins, B., and Burridge, D.: Stability of the semi-implicit method of time integration, Mon. Weather Rev., 106, 405–412, 1978.
Smith, C.: Stability analysis and precision aspects of the boundary condition formulation in the non-hydrostatic dynamics and exploration of the alternatives for discrete formulation of the vertical acceleration equation both in Eulerian and semi-Lagrangian time marching schemes, ALADIN Newsletter, No. 21/4, Météo-France, Toulouse, France, 46–49, 2002.
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, 1990.
Soares, P. M. M., Miranda, P. M. A., Siebesma, P., and Teixeira, J.: An eddy-diffusivity/mass-flux parameterization for dry and shallow cumulus convection, Q. J. Roy. Meteor. Soc., 130, 3055–3079, 2004.
Sukoriansky, S., Galperin, B., and Staroselsky, I.: A quasinormal scale elimination model of turbulent flows with stable stratification, Phys. Fluids, 17, 085107, https://doi.org/10.1063/1.2009010, 2005.
Tegen, I., Hoorig, P., Chin, M., Fung, I., Jacob, D., and Penner, J.: Contribution of different aerosol species to the global aerosol extinction optical thickness: Estimates from model results, J. Geophys. Res., 102, 23895–23915, 1997.
Temperton, C., Hortal, M., and Simmons, A.: A two-time-level semi-Lagrangian global spectral model, Q. J. Roy. Meteor. Soc., 127, 111–127, 2001.
Termonia, P.: Monitoring the Coupling-Update Frequency of a Limited-Area Model by Means of a Recursive Digital Filter, Mon. Weather Rev., 132, 2130–2141, https://doi.org/10.1175/1520-0493(2004)132<2130:MTCFOA>2.0.CO;2, 2004.
Termonia, P.: Scale-Selective Digital-Filtering Initialization, Mon. Weather Rev., 136, 5246–5255, https://doi.org/10.1175/2008MWR2606.1, 2008.
Termonia, P. and Hamdi, R.: Stability and accuracy of the physics-dynamics coupling in spectral models, Q. J. Roy. Meteor. Soc., 133, 1589–1604, 2007.
Termonia, P., Deckmyn, A., and Hamdi, R.: Study of the Lateral Boundary Condition Temporal Resolution Problem and a Proposed Solution by Means of Boundary Error Restarts, Mon. Weather Rev., 137, 3551–3566, https://doi.org/10.1175/2009MWR2964.1, 2009.
Termonia, P., Degrauwe, D., and Hamdi, R.: Improving the Temporal Resolution Problem by Localized Gridpoint Nudging in Regional Weather and Climate Models, Mon. Weather Rev., 139, 1292–1304, https://doi.org/10.1175/2010MWR3594.1, 2011.
Termonia, P., Voitus, F., Degrauwe, D., Caluwaerts, S., and Hamdi, R.: Application of Boyd's Periodization and Relaxation Method in a Spectral Atmospheric Limited-Area Model. Part I: Implementation and Reproducibility Tests, Mon. Weather Rev., 140, 3137–3148, https://doi.org/10.1175/MWR-D-12-00033.1, 2012.
Tudor, M.: Methods for automatized detection of rapid changes in lateral boundary condition fields for NWP limited area models, Geosci. Model Dev., 8, 2627–2643, https://doi.org/10.5194/gmd-8-2627-2015, 2015.
Tudor, M. and Ivatek-Šahdan, S.: The case study of bura of 1 and 3 February 2007, Meteorol. Z., 19, 453–466, 2010.
Tudor, M. and Termonia, P.: Alternative Formulations for Incorporating Lateral Boundary Data into Limited-Area Models, Mon. Weather Rev., 138, 2867–2882, https://doi.org/10.1175/2010MWR3179.1, 2010.
Untch, A. and Hortal, M.: A finite-element scheme for the vertical discretization of the semi-Lagrangian version of the ECMWF forecast model, Q. J. Roy. Meteor. Soc., 130, 1505–1530, https://doi.org/10.1256/qj.03.173, 2004.
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 re-analysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2005.
Váña, F., Bénard, P., Geleyn, J.-F., Simon, A., and Seity, Y.: Semi-Lagrangian advection scheme with controlled damping: An alternative to nonlinear horizontal diffusion in a numerical weather prediction model, Q. J. Roy. Meteor. Soc., 134, 523–537, https://doi.org/10.1002/qj.220, 2008.
Vié, B., Pinty, J.-P., Berthet, S., and Leriche, M.: LIMA (v1.0): A quasi two-moment microphysical scheme driven by a multimodal population of cloud condensation and ice freezing nuclei, Geosci. Model Dev., 9, 567–586, https://doi.org/10.5194/gmd-9-567-2016, 2016.
Vivoda, J. and Smolíková, P.: Finite elements used in the vertical discretization of the fully compressible forecast model ALADIN-NH, ALADIN/HIRLAM Newsletter, No. 1, Météo-France, Toulouse, France, 31–46, 2013.
Wang, Y., Bellus, M., Wittmann, C., Steinheimer, M., Weidle, F., Kann, A., Ivatek-Šahdan, S., Tian, W., Ma, X., Tascu, S., and Bazile, E.: The Central European limited-area ensemble forecasting system: ALADIN-LAEF, Q. J. Roy. Meteor. Soc., 137, 483–502, 2011.
Wang, Y., Bellus, M., Geleyn, J.-F., Tian, W., Ma, X., and Weidle, F.: A new method for generating initial perturbations in regional ensemble prediction system blending, Mon. Weather Rev., 142, 2043–2059, 2014.
Warner, T. T., Peterson, R. A., and Treadon, R. E.: A Tutorial on Lateral Boundary Conditions as a Basic and Potentially Serious Limitation to Regional Numerical Weather Prediction, B. Am. Meteorol. Soc., 78, 2599–2617, 1997.
Wattrelot, E., Caumont, O., and Mahfouf, J.-F.: Operational Implementation of the 1D + 3D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model, Mon. Weather Rev., 142, 1852–1873, https://doi.org/10.1175/MWR-D-13-00230.1, 2014.
Xu, K.-M. and Randall, D. A.: A semi-empirical cloudiness parameterization for use in climate models, J. Atmos. Sci., 53, 3084–3102, 1996.
Yano, J.-I., Bengtsson, L., Geleyn, J.-F., and Brozkova, R.: Parameterization of Atmospheric Convection, vol. 2: Current Issues and New Theories, Part IV Unification and consistency, chap. 26: Towards a unified and self-consistent parameterization Framework, Series on the Science of Climate Change, Imperial College Press, London, UK, 2016.
Zilitinkevich, S. S., Elperin, T., Kleeorin, N., Rogachevskii, I., and Esau, I.: A hierarchy of energy- and flux-budget (EFB) turbulence closure models for stably-stratified geophysical flows, Bound.-Lay. Meteorol., 146, 341–373, https://doi.org/10.1007/s10546-012-9768-8, 2013.
Zwieflhofer, W., Kreitz, N., and Forecasts, E.: Realizing Teracomputing: Proceedings of the Tenth ECMWF Workshop on the Use of High Performance Computing in Meteorology, 4–8 November 2002, Reading, UK, World Scientific, 2003.
Short summary
This paper describes the ALADIN System that has been developed by the international ALADIN consortium of 16 European and northern African partners since its creation in 1990. The paper also describes how its model configurations are used by the consortium partners for their operational weather forecasting applications and for weather and climate research.
This paper describes the ALADIN System that has been developed by the international ALADIN...
