Articles | Volume 18, issue 14
https://doi.org/10.5194/gmd-18-4353-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-4353-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
21 Jul 2025
Model description paper |
| 21 Jul 2025
| 21 Jul 2025
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
German Space Operations Center, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany
Deutsches Fernerkundungsdatenzentrum, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany
Institut für Physik, Universität Augsburg, Augsburg, Germany
Carsten Schmidt
Deutsches Fernerkundungsdatenzentrum, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany
Patrick Hannawald
Deutsches Fernerkundungsdatenzentrum, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany
Wolfgang Kausch
Institut für Astro- und Teilchenphysik, Universität Innsbruck, Innsbruck, Austria
Stefan Kimeswenger
Institut für Astro- und Teilchenphysik, Universität Innsbruck, Innsbruck, Austria
Instituto de Astronomía, Universidad Católica del Norte, Antofagasta, Chile
Related authors
Stefan Noll, John M. C. Plane, Wuhu Feng, Konstantinos S. Kalogerakis, Wolfgang Kausch, Carsten Schmidt, Michael Bittner, and Stefan Kimeswenger
Atmos. Chem. Phys., 24, 1143–1176, https://doi.org/10.5194/acp-24-1143-2024, https://doi.org/10.5194/acp-24-1143-2024, 2024
Short summary
Short summary
The Earth's nighttime radiation in the range from the near-UV to the near-IR mainly originates between 75 and 105 km and consists of lines of different species, which are important indicators of the chemistry and dynamics at these altitudes. Based on astronomical spectra, we have characterised the structure and variability of a pseudo-continuum of a high number of faint lines and discovered a new emission process in the near-IR. By means of simulations, we identified HO2 as the likely emitter.
Stefan Noll, Holger Winkler, Oleg Goussev, and Bastian Proxauf
Atmos. Chem. Phys., 20, 5269–5292, https://doi.org/10.5194/acp-20-5269-2020, https://doi.org/10.5194/acp-20-5269-2020, 2020
Short summary
Short summary
Line emission from hydroxyl (OH) molecules at altitudes of about 90 km strongly contributes to the Earth's night-sky brightness and is therefore used as an important indicator of atmospheric chemistry and dynamics. However, interpreting the measurements can be ambiguous since necessary molecular parameters and the internal state of OH are not well known. Based on high-quality spectral data, we investigated these issues and found solutions for a better understanding of the OH line intensities.
Konstantinos S. Kalogerakis, Daniel Matsiev, Philip C. Cosby, James A. Dodd, Stefano Falcinelli, Jonas Hedin, Alexander A. Kutepov, Stefan Noll, Peter A. Panka, Constantin Romanescu, and Jérôme E. Thiebaud
Ann. Geophys., 36, 13–24, https://doi.org/10.5194/angeo-36-13-2018, https://doi.org/10.5194/angeo-36-13-2018, 2018
Short summary
Short summary
The question of whether mesospheric rotational population distributions of vibrationally excited OH are in equilibrium with the local kinetic temperature has been debated over several decades. We examine the relationship of multi-quantum relaxation pathways with the behavior exhibited by OH(v) rotational population distributions and find that the effective rotational temperatures of mesospheric OH(v) deviate from local thermodynamic equilibrium for all observed vibrational levels.
Stefanie Unterguggenberger, Stefan Noll, Wuhu Feng, John M. C. Plane, Wolfgang Kausch, Stefan Kimeswenger, Amy Jones, and Sabine Moehler
Atmos. Chem. Phys., 17, 4177–4187, https://doi.org/10.5194/acp-17-4177-2017, https://doi.org/10.5194/acp-17-4177-2017, 2017
Short summary
Short summary
This study focuses on the analysis of astronomical medium-resolution spectra from the VLT in Chile to measure airglow pseudo-continuum emission of FeO in the optical regime. Compared to OH or Na emissions, this emission is difficult to measure. Using 3.5 years of spectroscopic data, we found annual and semi-annual variations of the FeO emission. Furthermore, we used WACCM to determine the quantum yield of the FeO-producing Fe + O3 reaction in the atmosphere, which has not been done before.
Stefan Noll, Wolfgang Kausch, Stefan Kimeswenger, Stefanie Unterguggenberger, and Amy M. Jones
Atmos. Chem. Phys., 16, 5021–5042, https://doi.org/10.5194/acp-16-5021-2016, https://doi.org/10.5194/acp-16-5021-2016, 2016
Short summary
Short summary
We compare temperatures derived from simultaneous observations of 25 OH and two O2 mesospheric airglow bands taken with the X-shooter spectrograph at the Very Large Telescope in Chile. Considering emission and temperature profile data from the radiometer SABER on the TIMED satellite, we find significant time-dependent non-thermal contributions to the OH-based temperatures, especially for bands originating from high vibrational levels. Many studies of the mesopause region are affected.
S. Noll, W. Kausch, S. Kimeswenger, S. Unterguggenberger, and A. M. Jones
Atmos. Chem. Phys., 15, 3647–3669, https://doi.org/10.5194/acp-15-3647-2015, https://doi.org/10.5194/acp-15-3647-2015, 2015
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We discuss a high-quality data set of simultaneous observations of 25 OH bands with an astronomical echelle spectrograph. These data allowed us to analyse band-dependent OH populations and temperatures. In particular, we could find different non-LTE contributions to OH rotational temperatures depending on band, line set, and observing time. This is critical for mesopause studies that use these temperatures as a proxy of the true temperatures.
Stefan Noll, John M. C. Plane, Wuhu Feng, Konstantinos S. Kalogerakis, Wolfgang Kausch, Carsten Schmidt, Michael Bittner, and Stefan Kimeswenger
Atmos. Chem. Phys., 24, 1143–1176, https://doi.org/10.5194/acp-24-1143-2024, https://doi.org/10.5194/acp-24-1143-2024, 2024
Short summary
Short summary
The Earth's nighttime radiation in the range from the near-UV to the near-IR mainly originates between 75 and 105 km and consists of lines of different species, which are important indicators of the chemistry and dynamics at these altitudes. Based on astronomical spectra, we have characterised the structure and variability of a pseudo-continuum of a high number of faint lines and discovered a new emission process in the near-IR. By means of simulations, we identified HO2 as the likely emitter.
Carsten Schmidt, Lisa Küchelbacher, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 16, 4331–4356, https://doi.org/10.5194/amt-16-4331-2023, https://doi.org/10.5194/amt-16-4331-2023, 2023
Short summary
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Two identical instruments in a parallel setup were used to observe the mesospheric OH airglow for more than 10 years (2009–2020) at 47.42°N, 10.98°E. This allows unique analyses of data quality aspects and their impact on the obtained results. During solar cycle 24 the influence of the sun was strong (∼6 K per 100 sfu). A quasi-2-year oscillation (QBO) of ±1 K is observed mainly during the maximum of the solar cycle. Unlike the stratospheric QBO the variation has a period of or below 24 months.
René Sedlak, Andreas Welscher, Patrick Hannawald, Sabine Wüst, Rainer Lienhart, and Michael Bittner
Atmos. Meas. Tech., 16, 3141–3153, https://doi.org/10.5194/amt-16-3141-2023, https://doi.org/10.5194/amt-16-3141-2023, 2023
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We show that machine learning can help in classifying images of the OH* airglow, a thin layer in the middle atmosphere (ca. 86 km height) emitting infrared radiation, in an efficient way. By doing this,
dynamicepisodes of strong movement in the OH* airglow caused predominantly by waves can be extracted automatically from large data sets. Within these dynamic episodes, turbulent wave breaking can also be found. We use these observations of turbulence to derive the energy released by waves.
René Sedlak, Patrick Hannawald, Carsten Schmidt, Sabine Wüst, Michael Bittner, and Samo Stanič
Atmos. Meas. Tech., 14, 6821–6833, https://doi.org/10.5194/amt-14-6821-2021, https://doi.org/10.5194/amt-14-6821-2021, 2021
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High-resolution images of the OH* airglow layer (ca. 87 km height) acquired at Otlica Observatory, Slovenia, have been analysed. A statistical analysis of small-scale wave structures with horizontal wavelengths up to 4.5 km suggests strong presence of instability features in the upper mesosphere or lower thermosphere. The dissipated energy of breaking gravity waves is derived from observations of turbulent vortices. It is concluded that dynamical heating plays a vital role in the atmosphere.
René Sedlak, Alexandra Zuhr, Carsten Schmidt, Sabine Wüst, Michael Bittner, Goderdzi G. Didebulidze, and Colin Price
Atmos. Meas. Tech., 13, 5117–5128, https://doi.org/10.5194/amt-13-5117-2020, https://doi.org/10.5194/amt-13-5117-2020, 2020
Short summary
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Gravity wave (GW) activity in the UMLT in the period range 6-480 min is calculated by applying a wavelet analysis to nocturnal temperature time series derived from OH* airglow spectrometers. We analyse measurements from eight different locations at different latitudes.
GW activity shows strong period dependence. We find hardly any seasonal variability for periods below 60 min and a semi-annual cycle for periods longer than 60 min that evolves into an annual cycle around a period of 200 min.
Stefan Noll, Holger Winkler, Oleg Goussev, and Bastian Proxauf
Atmos. Chem. Phys., 20, 5269–5292, https://doi.org/10.5194/acp-20-5269-2020, https://doi.org/10.5194/acp-20-5269-2020, 2020
Short summary
Short summary
Line emission from hydroxyl (OH) molecules at altitudes of about 90 km strongly contributes to the Earth's night-sky brightness and is therefore used as an important indicator of atmospheric chemistry and dynamics. However, interpreting the measurements can be ambiguous since necessary molecular parameters and the internal state of OH are not well known. Based on high-quality spectral data, we investigated these issues and found solutions for a better understanding of the OH line intensities.
Sabine Wüst, Carsten Schmidt, Patrick Hannawald, Michael Bittner, Martin G. Mlynczak, and James M. Russell III
Atmos. Chem. Phys., 19, 6401–6418, https://doi.org/10.5194/acp-19-6401-2019, https://doi.org/10.5194/acp-19-6401-2019, 2019
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In winter 2016, the camera system FAIM derived information about the OH* airglow at ca. 86 km height during six flights on board the research aircraft FALCON in northern Scandinavia. Coincident ground- and satellite-based measurements (GRIPS and TIMED-SABER) complete the data set. The data are analysed with respect to the temporal and spatial evolution of small-scale atmospheric dynamics just before a minor stratospheric warming. Special emphasis is placed on possible instability features.
Patrick Hannawald, Carsten Schmidt, René Sedlak, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 12, 457–469, https://doi.org/10.5194/amt-12-457-2019, https://doi.org/10.5194/amt-12-457-2019, 2019
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We use a near-infrared camera for the investigation of gravity waves. The camera observes the airglow layer, which is modulated by the gravity waves. The image processing, including the removal of the stars is explained. We describe the analysis with a 2D fast Fourier transform and automatic derivation of the wave parameters. The results show a clear seasonal and intra-diurnal variability, which is characterised in order to improve our understanding of gravity waves in the middle atmosphere.
Sabine Wüst, Thomas Offenwanger, Carsten Schmidt, Michael Bittner, Christoph Jacobi, Gunter Stober, Jeng-Hwa Yee, Martin G. Mlynczak, and James M. Russell III
Atmos. Meas. Tech., 11, 2937–2947, https://doi.org/10.5194/amt-11-2937-2018, https://doi.org/10.5194/amt-11-2937-2018, 2018
Short summary
Short summary
OH*-spectrometer measurements allow the analysis of gravity wave ground-based periods, but spatial information cannot necessarily be deduced. We combine the approach of Wachter at al. (2015) in order to derive horizontal wavelengths (but based on only one OH* spectrometer) with additional information about wind and temperature and compute vertical wavelengths. Knowledge of these parameters is a precondition for the calculation of further information such as the wave group velocity.
Konstantinos S. Kalogerakis, Daniel Matsiev, Philip C. Cosby, James A. Dodd, Stefano Falcinelli, Jonas Hedin, Alexander A. Kutepov, Stefan Noll, Peter A. Panka, Constantin Romanescu, and Jérôme E. Thiebaud
Ann. Geophys., 36, 13–24, https://doi.org/10.5194/angeo-36-13-2018, https://doi.org/10.5194/angeo-36-13-2018, 2018
Short summary
Short summary
The question of whether mesospheric rotational population distributions of vibrationally excited OH are in equilibrium with the local kinetic temperature has been debated over several decades. We examine the relationship of multi-quantum relaxation pathways with the behavior exhibited by OH(v) rotational population distributions and find that the effective rotational temperatures of mesospheric OH(v) deviate from local thermodynamic equilibrium for all observed vibrational levels.
Stefanie Unterguggenberger, Stefan Noll, Wuhu Feng, John M. C. Plane, Wolfgang Kausch, Stefan Kimeswenger, Amy Jones, and Sabine Moehler
Atmos. Chem. Phys., 17, 4177–4187, https://doi.org/10.5194/acp-17-4177-2017, https://doi.org/10.5194/acp-17-4177-2017, 2017
Short summary
Short summary
This study focuses on the analysis of astronomical medium-resolution spectra from the VLT in Chile to measure airglow pseudo-continuum emission of FeO in the optical regime. Compared to OH or Na emissions, this emission is difficult to measure. Using 3.5 years of spectroscopic data, we found annual and semi-annual variations of the FeO emission. Furthermore, we used WACCM to determine the quantum yield of the FeO-producing Fe + O3 reaction in the atmosphere, which has not been done before.
René Sedlak, Patrick Hannawald, Carsten Schmidt, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 9, 5955–5963, https://doi.org/10.5194/amt-9-5955-2016, https://doi.org/10.5194/amt-9-5955-2016, 2016
Short summary
Short summary
In this paper a SWIR airglow imager is presented. It is especially designed for the observation of small-scale gravity waves and turbulence features in the OH airglow layer with a high spatio-temporal resolution of up to 17 m (at mesopause heights) and 2.5 to 2.8 s. Two case studies show small-scale wave structures with horizontal wavelengths of approximately 550 m as well as vortex formation and decomposition of wave fronts, both indicating the onset of turbulence.
Stefan Noll, Wolfgang Kausch, Stefan Kimeswenger, Stefanie Unterguggenberger, and Amy M. Jones
Atmos. Chem. Phys., 16, 5021–5042, https://doi.org/10.5194/acp-16-5021-2016, https://doi.org/10.5194/acp-16-5021-2016, 2016
Short summary
Short summary
We compare temperatures derived from simultaneous observations of 25 OH and two O2 mesospheric airglow bands taken with the X-shooter spectrograph at the Very Large Telescope in Chile. Considering emission and temperature profile data from the radiometer SABER on the TIMED satellite, we find significant time-dependent non-thermal contributions to the OH-based temperatures, especially for bands originating from high vibrational levels. Many studies of the mesopause region are affected.
Patrick Hannawald, Carsten Schmidt, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 9, 1461–1472, https://doi.org/10.5194/amt-9-1461-2016, https://doi.org/10.5194/amt-9-1461-2016, 2016
Short summary
Short summary
This paper presents a ground-based, short-wave infrared camera system for measurements of the OH airglow originating in the middle atmosphere. The camera has a high temporal and spatial resolution of 0.5 s and 200 m (at 90 km height), which allows for detailed observations of atmospheric waves and other transient phenomena. Details regarding the instrument, calibration and preprocessing are discussed exemplarily for an event of two superposing gravity waves with associated instability structures.
S. Noll, W. Kausch, S. Kimeswenger, S. Unterguggenberger, and A. M. Jones
Atmos. Chem. Phys., 15, 3647–3669, https://doi.org/10.5194/acp-15-3647-2015, https://doi.org/10.5194/acp-15-3647-2015, 2015
Short summary
Short summary
We discuss a high-quality data set of simultaneous observations of 25 OH bands with an astronomical echelle spectrograph. These data allowed us to analyse band-dependent OH populations and temperatures. In particular, we could find different non-LTE contributions to OH rotational temperatures depending on band, line set, and observing time. This is critical for mesopause studies that use these temperatures as a proxy of the true temperatures.
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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
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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
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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.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
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
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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
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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
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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
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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
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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
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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.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
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
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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
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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
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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
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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.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Kasper Skjold Tølløse and Jens Havskov Sørensen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-173, https://doi.org/10.5194/gmd-2024-173, 2025
Preprint under review for GMD
Short summary
Short summary
In this study, we improve the short-scale dispersion modelling capabilities of the Danish Emergency Response Model of the Atmosphere (DERMA) by developing and implementing a new hybrid particle-puff description of turbulent diffusion, as well as updating a few other parameterizations in the model. The new model is evaluated against data from three different tracer gas experiments, and the promising results are an important first step towards using DERMA also for short-range dispersion modelling.
Cited articles
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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, this model is valuable for airglow research and astronomical observatories.
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly...
