Articles | Volume 9, issue 5
https://doi.org/10.5194/gmd-9-1647-2016
© Author(s) 2016. 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-9-1647-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
03 May 2016
Model description paper |
| 03 May 2016
The libRadtran software package for radiative transfer calculations (version 2.0.1)
Meteorological Institute, Ludwig-Maximilians-University,
Theresienstr. 37, 80333 Munich, Germany
Robert Buras-Schnell
Schnell Algorithms, Am Erdäpfelgarten 1, 82205 Gilching, Germany
Arve Kylling
NILU – Norwegian Institute for Air Research, Kjeller, Norway
Bernhard Mayer
Meteorological Institute, Ludwig-Maximilians-University,
Theresienstr. 37, 80333 Munich, Germany
Josef Gasteiger
Meteorological Institute, Ludwig-Maximilians-University,
Theresienstr. 37, 80333 Munich, Germany
Ulrich Hamann
MeteoSwiss, Radar, Satellite and Nowcasting Division, Via ai
Monti 146, Locarno, Switzerland
Jonas Kylling
NILU – Norwegian Institute for Air Research, Kjeller, Norway
Department of Mathematics, Faculty of Mathematics and
Natural Sciences, University of Oslo, Oslo, Norway
Bettina Richter
Meteorological Institute, Ludwig-Maximilians-University,
Theresienstr. 37, 80333 Munich, Germany
Christian Pause
Meteorological Institute, Ludwig-Maximilians-University,
Theresienstr. 37, 80333 Munich, Germany
Timothy Dowling
Dept. of Physics & Astronomy, University of Louisville, Louisville, KY 40292, USA
Luca Bugliaro
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Wessling, Germany
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Short summary
Short summary
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James Barry, Stefanie Meilinger, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Christopher Schirrmeister, Rone Yousif, Tina Buchmann, Johannes Grabenstein, Hartwig Deneke, Jonas Witthuhn, Claudia Emde, Felix Gödde, Bernhard Mayer, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, and Matthias Struck
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A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean from geostationary meteorological satellites is proposed and successfully evaluated with reference ground-based and satellite data. The high-temporal-resolution aerosol observations that are obtained from the EUMETSAT Meteosat Second Generation mission are unprecedented and open the door to studies that cannot be conducted with the once-a-day observations available from low-Earth-orbit satellites.
Ziming Wang, Luca Bugliaro, Tina Jurkat-Witschas, Romy Heller, Ulrike Burkhardt, Helmut Ziereis, Georgios Dekoutsidis, Martin Wirth, Silke Groß, Simon Kirschler, Stefan Kaufmann, and Christiane Voigt
Atmos. Chem. Phys., 23, 1941–1961, https://doi.org/10.5194/acp-23-1941-2023, https://doi.org/10.5194/acp-23-1941-2023, 2023
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Differences in the microphysical properties of contrail cirrus and natural cirrus in a contrail outbreak situation during the ML-CIRRUS campaign over the North Atlantic flight corridor can be observed from in situ measurements. The cirrus radiative effect in the area of the outbreak, derived from satellite observation-based radiative transfer modeling, is warming in the early morning and cooling during the day.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Huan Yu, Claudia Emde, Arve Kylling, Ben Veihelmann, Bernhard Mayer, Kerstin Stebel, and Michel Van Roozendael
Atmos. Meas. Tech., 15, 5743–5768, https://doi.org/10.5194/amt-15-5743-2022, https://doi.org/10.5194/amt-15-5743-2022, 2022
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In this study, we have investigated the impact of 3D clouds on the tropospheric NO2 retrieval from UV–visible sensors. We applied standard NO2 retrieval methods including cloud corrections to synthetic data generated by the 3D radiative transfer model. A sensitivity study was done for synthetic data, and dependencies on various parameters were investigated. Possible mitigation strategies were investigated and compared based on 3D simulations and observed data.
Arve Kylling, Claudia Emde, Huan Yu, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer
Atmos. Meas. Tech., 15, 3481–3495, https://doi.org/10.5194/amt-15-3481-2022, https://doi.org/10.5194/amt-15-3481-2022, 2022
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Atmospheric trace gases such as nitrogen dioxide (NO2) may be measured by satellite instruments sensitive to solar ultraviolet–visible radiation reflected from Earth and its atmosphere. For a single pixel, clouds in neighbouring pixels may affect the radiation and hence the retrieved trace gas amount. We found that for a solar zenith angle less than about 40° this cloud-related NO2 bias is typically below 10 %, while for larger solar zenith angles the NO2 bias is on the order of tens of percent.
Marilena Teri, Thomas Müller, Josef Gasteiger, Sara Valentini, Helmuth Horvath, Roberta Vecchi, Paulus Bauer, Adrian Walser, and Bernadett Weinzierl
Atmos. Meas. Tech., 15, 3161–3187, https://doi.org/10.5194/amt-15-3161-2022, https://doi.org/10.5194/amt-15-3161-2022, 2022
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We performed an extensive closure study including laboratory and simulated experiments to evaluate various angular corrections for the Aurora 4000 polar nephelometer, focusing on irregularly shaped aerosols such as mineral dust. We describe the impact of particle size, refractive index, and shape on the determination of the particle scattering coefficient and propose a guideline to establish the most appropriate angular correction depending on the aerosol type and the investigated size range.
Mireia Papke Chica, Valerian Hahn, Tiziana Braeuer, Elena de la Torre Castro, Florian Ewald, Mathias Gergely, Simon Kirschler, Luca Bugliaro Goggia, Stefanie Knobloch, Martina Kraemer, Johannes Lucke, Johanna Mayer, Raphael Maerkl, Manuel Moser, Laura Tomsche, Tina Jurkat-Witschas, Martin Zoeger, Christian von Savigny, and Christiane Voigt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-255, https://doi.org/10.5194/acp-2022-255, 2022
Preprint withdrawn
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The mixed-phase temperature regime in convective clouds challenges our understanding of microphysical and radiative cloud properties. We provide a rare and unique dataset of aircraft in situ measurements in a strong mid-latitude convective system. We find that mechanisms initiating ice nucleation and growth strongly depend on temperature, relative humidity, and vertical velocity and variate within the measured system, resulting in altitude dependent changes of the cloud liquid and ice fraction.
Luca Bugliaro, Dennis Piontek, Stephan Kox, Marius Schmidl, Bernhard Mayer, Richard Müller, Margarita Vázquez-Navarro, Daniel M. Peters, Roy G. Grainger, Josef Gasteiger, and Jayanta Kar
Nat. Hazards Earth Syst. Sci., 22, 1029–1054, https://doi.org/10.5194/nhess-22-1029-2022, https://doi.org/10.5194/nhess-22-1029-2022, 2022
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The monitoring of ash dispersion in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. We present an AI-based method that retrieves the spatial extension and properties of volcanic ash clouds with high temporal resolution during day and night by means of geostationary satellite measurements. This algorithm, trained on realistic observations simulated with a radiative transfer model, runs operationally at the German Weather Service.
Claudia Emde, Huan Yu, Arve Kylling, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer
Atmos. Meas. Tech., 15, 1587–1608, https://doi.org/10.5194/amt-15-1587-2022, https://doi.org/10.5194/amt-15-1587-2022, 2022
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Retrievals of trace gas concentrations from satellite observations can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. We used a Monte Carlo radiative transfer model to generate synthetic satellite observations, which we used to test retrieval algorithms and to quantify the error of retrieved NO2 vertical column density due to cloud scattering.
Jussi Leinonen, Ulrich Hamann, Urs Germann, and John R. Mecikalski
Nat. Hazards Earth Syst. Sci., 22, 577–597, https://doi.org/10.5194/nhess-22-577-2022, https://doi.org/10.5194/nhess-22-577-2022, 2022
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We evaluate the usefulness of different data sources and variables to the short-term prediction (
nowcasting) of severe thunderstorms using machine learning. Machine-learning models are trained with data from weather radars, satellite images, lightning detection and weather forecasts and with terrain elevation data. We analyze the benefits provided by each of the data sources to predicting hazards (heavy precipitation, lightning and hail) caused by the thunderstorms.
Matthieu Plu, Guillaume Bigeard, Bojan Sič, Emanuele Emili, Luca Bugliaro, Laaziz El Amraoui, Jonathan Guth, Beatrice Josse, Lucia Mona, and Dennis Piontek
Nat. Hazards Earth Syst. Sci., 21, 3731–3747, https://doi.org/10.5194/nhess-21-3731-2021, https://doi.org/10.5194/nhess-21-3731-2021, 2021
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Volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010, may have huge economic consequences due to flight cancellations. In this article, we demonstrate the benefits of source term improvement and of data assimilation for quantifying volcanic ash concentrations. The work, which was supported by the EUNADICS-AV project, is the first one, to our knowledge, that demonstrates the benefit of the assimilation of ground-based lidar data over Europe during an eruption.
Alexandra Tsekeri, Vassilis Amiridis, Alexandros Louridas, George Georgoussis, Volker Freudenthaler, Spiros Metallinos, George Doxastakis, Josef Gasteiger, Nikolaos Siomos, Peristera Paschou, Thanasis Georgiou, George Tsaknakis, Christos Evangelatos, and Ioannis Binietoglou
Atmos. Meas. Tech., 14, 7453–7474, https://doi.org/10.5194/amt-14-7453-2021, https://doi.org/10.5194/amt-14-7453-2021, 2021
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Dust orientation in the Earth's atmosphere has been an ongoing investigation in recent years, and its potential proof will be a paradigm shift for dust remote sensing. We have designed and developed a polarization lidar that provides direct measurements of dust orientation, as well as more detailed information of the particle microphysics. We provide a description of its design as well as its first measurements.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
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The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
Atmos. Meas. Tech., 14, 6469–6482, https://doi.org/10.5194/amt-14-6469-2021, https://doi.org/10.5194/amt-14-6469-2021, 2021
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NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Matthieu Plu, Barbara Scherllin-Pirscher, Delia Arnold Arias, Rocio Baro, Guillaume Bigeard, Luca Bugliaro, Ana Carvalho, Laaziz El Amraoui, Kurt Eschbacher, Marcus Hirtl, Christian Maurer, Marie D. Mulder, Dennis Piontek, Lennart Robertson, Carl-Herbert Rokitansky, Fritz Zobl, and Raimund Zopp
Nat. Hazards Earth Syst. Sci., 21, 2973–2992, https://doi.org/10.5194/nhess-21-2973-2021, https://doi.org/10.5194/nhess-21-2973-2021, 2021
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Past volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010, forced the cancellation of thousands of flights and had huge economic consequences.
In this article, an international team in the H2020 EU-funded EUNADICS-AV project has designed a probabilistic model approach to quantify ash concentrations. This approach is evaluated against measurements, and its potential use to mitigate the impact of future large-scale eruptions is discussed.
Daniel Zawada, Ghislain Franssens, Robert Loughman, Antti Mikkonen, Alexei Rozanov, Claudia Emde, Adam Bourassa, Seth Dueck, Hannakaisa Lindqvist, Didier Ramon, Vladimir Rozanov, Emmanuel Dekemper, Erkki Kyrölä, John P. Burrows, Didier Fussen, and Doug Degenstein
Atmos. Meas. Tech., 14, 3953–3972, https://doi.org/10.5194/amt-14-3953-2021, https://doi.org/10.5194/amt-14-3953-2021, 2021
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Satellite measurements of atmospheric composition often rely on computer tools known as radiative transfer models to model the propagation of sunlight within the atmosphere. Here we have performed a detailed inter-comparison of seven different radiative transfer models in a variety of conditions. We have found that the models agree remarkably well, at a level better than previously reported. This result provides confidence in our understanding of atmospheric radiative transfer.
Ulrich Schumann, Ian Poll, Roger Teoh, Rainer Koelle, Enrico Spinielli, Jarlath Molloy, George S. Koudis, Robert Baumann, Luca Bugliaro, Marc Stettler, and Christiane Voigt
Atmos. Chem. Phys., 21, 7429–7450, https://doi.org/10.5194/acp-21-7429-2021, https://doi.org/10.5194/acp-21-7429-2021, 2021
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The roughly 70 % reduction of air traffic during the COVID-19 pandemic from March–August 2020 compared to 2019 provides a test case for the relationship between air traffic density, contrails, and their radiative forcing of climate change. This paper investigates the induced traffic and contrail changes in a model study. Besides strong weather changes, the model results indicate aviation-induced cirrus and top-of-the-atmosphere irradiance changes, which can be tested with observations.
Harald Rybka, Ulrike Burkhardt, Martin Köhler, Ioanna Arka, Luca Bugliaro, Ulrich Görsdorf, Ákos Horváth, Catrin I. Meyer, Jens Reichardt, Axel Seifert, and Johan Strandgren
Atmos. Chem. Phys., 21, 4285–4318, https://doi.org/10.5194/acp-21-4285-2021, https://doi.org/10.5194/acp-21-4285-2021, 2021
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Estimating the impact of convection on the upper-tropospheric water budget remains a problem for models employing resolutions of several kilometers or more. A sub-kilometer high-resolution model is used to study summertime convection. The results suggest mostly close agreement with ground- and satellite-based observational data while slightly overestimating total frozen water path and anvil lifetime. The simulations are well suited to supplying information for parameterization development.
Marc Schwaerzel, Claudia Emde, Dominik Brunner, Randulph Morales, Thomas Wagner, Alexis Berne, Brigitte Buchmann, and Gerrit Kuhlmann
Atmos. Meas. Tech., 13, 4277–4293, https://doi.org/10.5194/amt-13-4277-2020, https://doi.org/10.5194/amt-13-4277-2020, 2020
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Horizontal homogeneity is often assumed for trace gases remote sensing, although it is not valid where trace gas concentrations have high spatial variability, e.g., in cities. We show the importance of 3D effects for MAX-DOAS and airborne imaging spectrometers using 3D-box air mass factors implemented in the MYSTIC radiative transfer solver. In both cases, 3D information is invaluable for interpreting the measurements, as not considering 3D effects can lead to misinterpretation of measurements.
Antonio Spanu, Maximilian Dollner, Josef Gasteiger, T. Paul Bui, and Bernadett Weinzierl
Atmos. Meas. Tech., 13, 1963–1987, https://doi.org/10.5194/amt-13-1963-2020, https://doi.org/10.5194/amt-13-1963-2020, 2020
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This study investigates how the airflow around wing-mounted instruments on fast-flying aircraft affects aerosol and cloud measurements. It combines airborne data with numerical simulations and shows that particle speed, particle concentration, and shape of water droplets are modified by the airflow. The proposed correction strategy for optical particle counters and optical array probes considers airflow effects and significantly reduces errors of derived ambient aerosol and cloud properties.
Paul Ockenfuß, Claudia Emde, Bernhard Mayer, and Germar Bernhard
Atmos. Chem. Phys., 20, 1961–1976, https://doi.org/10.5194/acp-20-1961-2020, https://doi.org/10.5194/acp-20-1961-2020, 2020
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We model solar radiation as it would be measured on the Earth's surface in the core shadow of a total solar eclipse. Subsequently, we compare our results to observations during the total eclipse 2017 for ultraviolet, visible and near-infrared wavelengths. Moreover, we analyze the effect of the surface reflectance, the ozone profile, aerosol and the topography and give a visualization of the prevailing photons paths in the atmosphere during the eclipse.
Hans Grob, Claudia Emde, Matthias Wiegner, Meinhard Seefeldner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 13, 239–258, https://doi.org/10.5194/amt-13-239-2020, https://doi.org/10.5194/amt-13-239-2020, 2020
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Polarimetry has been established as an enhancement to classical photometry in aerosol remote sensing over the past years. We propose a fast and exact radiometric and polarimetric calibration method for polarized photometers. Additionally, a technique for correcting an alt-azimuthal mount is introduced.
These methods are applied to measurements obtained with our SSARA instrument during the A-LIFE field campaign. For 2 d, the data are subjected to an inversion of aerosol optical properties.
Carlos Toledano, Benjamín Torres, Cristian Velasco-Merino, Dietrich Althausen, Silke Groß, Matthias Wiegner, Bernadett Weinzierl, Josef Gasteiger, Albert Ansmann, Ramiro González, David Mateos, David Farrel, Thomas Müller, Moritz Haarig, and Victoria E. Cachorro
Atmos. Chem. Phys., 19, 14571–14583, https://doi.org/10.5194/acp-19-14571-2019, https://doi.org/10.5194/acp-19-14571-2019, 2019
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Ground-based sun photometers have been used to analyze the properties of long-range transported Saharan dust over Barbados. The measurements were carried out as part of the Saharan Aerosol Long-Range Transport and Aerosol–Cloud-Interaction Experiment (SALTRACE), carried out in the Caribbean in 2013. A variety of instruments, ground-based and airborne, were used in this research. In this paper, the sun photometer data are presented and related to data collected from other co-located instruments.
Matthias Wiegner, Ina Mattis, Margit Pattantyús-Ábrahám, Juan Antonio Bravo-Aranda, Yann Poltera, Alexander Haefele, Maxime Hervo, Ulrich Görsdorf, Ronny Leinweber, Josef Gasteiger, Martial Haeffelin, Frank Wagner, Jan Cermak, Katerina Komínková, Mike Brettle, Christoph Münkel, and Kornelia Pönitz
Atmos. Meas. Tech., 12, 471–490, https://doi.org/10.5194/amt-12-471-2019, https://doi.org/10.5194/amt-12-471-2019, 2019
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Many ceilometers are influenced by water vapor absorption in the spectral range around 910 nm. Thus, a correction is required to retrieve aerosol optical properties. Validation of this correction scheme was performed in the framework of CeiLinEx2015 for several ceilometers with good agreement for Vaisala's CL51 ceilometer. For future applications we recommend monitoring the emitted wavelength and providing
darkmeasurements on a regular basis to be able to correct for signal artifacts.
Ka Lok Chan, Matthias Wiegner, Harald Flentje, Ina Mattis, Frank Wagner, Josef Gasteiger, and Alexander Geiß
Geosci. Model Dev., 11, 3807–3831, https://doi.org/10.5194/gmd-11-3807-2018, https://doi.org/10.5194/gmd-11-3807-2018, 2018
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The paper presents the comparison of ECMWF-IFS model simulation of aerosol backscatter profiles to long-term measurements of an extended ceilometer network. A significant influence of the numerical description of the hygroscopic growth of sea salt aerosols on the agreement between model and observations was found. Consideration of the nonsphericity of dust particles in the model reduced the attenuated backscatter of dust by ~&thinp;30 % and improved the agreement between model and observations.
Josef Gasteiger and Matthias Wiegner
Geosci. Model Dev., 11, 2739–2762, https://doi.org/10.5194/gmd-11-2739-2018, https://doi.org/10.5194/gmd-11-2739-2018, 2018
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A software package has been developed to model optical properties of atmospheric aerosol ensembles based on a pre-calculated single particle data set. Spherical particles, spheroids, and a small set of irregular shapes are covered. A flexible and intuitive web interface is provided for online calculations of user-defined ensembles. The paper describes the package and outlines several applications, e.g., optical properties for aerosol size bins of an aerosol transport model.
Moritz Haarig, Albert Ansmann, Josef Gasteiger, Konrad Kandler, Dietrich Althausen, Holger Baars, Martin Radenz, and David A. Farrell
Atmos. Chem. Phys., 17, 14199–14217, https://doi.org/10.5194/acp-17-14199-2017, https://doi.org/10.5194/acp-17-14199-2017, 2017
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The depolarization ratio and the backscatter coefficient of marine particles are correlated with the relative humidity. The measurements were performed under atmospheric conditions with a multi-wavelength lidar system in pure marine conditions over Barbados in February 2014. For RH < 50 % the sea salt particles have a cubic-like shape resulting in an enhanced depolarization ratio of up to 0.15. This agrees with model results of cubic sea salt. The extinction enhancement f(RH) factor was derived.
Adrian Walser, Daniel Sauer, Antonio Spanu, Josef Gasteiger, and Bernadett Weinzierl
Atmos. Meas. Tech., 10, 4341–4361, https://doi.org/10.5194/amt-10-4341-2017, https://doi.org/10.5194/amt-10-4341-2017, 2017
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We present a new approach to model the response of optical particle counters (OPCs) including a simple parametrization for artificial broadening of size spectra induced by the non-ideal behavior of real OPCs. We show a self-consistent way to evaluate calibration measurements and outline how particle number size distributions with realistic uncertainty estimates can be derived. The innovations will improve the accuracy of OPC-derived size distributions and allow to assess their precision.
Johan Strandgren, Jennifer Fricker, and Luca Bugliaro
Atmos. Meas. Tech., 10, 4317–4339, https://doi.org/10.5194/amt-10-4317-2017, https://doi.org/10.5194/amt-10-4317-2017, 2017
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We characterise the the performance of a set of artificial neural networks used for the remote sensing of cirrus clouds from the geostationary Meteosat Second Generation satellites. The retrievals show little interference with the underlying land surface type as well as with possible liquid water clouds or aerosol layers below the cirrus cloud. We also characterise the retrievals as a funtion of optical thickness and top height and gain better understanding of the retrival uncertainties of CiPS
Johan Strandgren, Luca Bugliaro, Frank Sehnke, and Leon Schröder
Atmos. Meas. Tech., 10, 3547–3573, https://doi.org/10.5194/amt-10-3547-2017, https://doi.org/10.5194/amt-10-3547-2017, 2017
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The new algorithm CiPS is presented and validated. CiPS detects cirrus clouds, identifies opaque pixels and retrieves the corresponding optical thickness, cloud top height and ice water path from the geostationary imager MSG/SEVIRI. CiPS utilises a set of four artificial neural networks trained with space-borne lidar data, thermal MSG/SEVIRI observations, model data and auxiliary data.
To demonstrate the capabilities of CiPS, the life cycle of a thin cirrus cloud is analysed.
Moritz Haarig, Albert Ansmann, Dietrich Althausen, André Klepel, Silke Groß, Volker Freudenthaler, Carlos Toledano, Rodanthi-Elisavet Mamouri, David A. Farrell, Damien A. Prescod, Eleni Marinou, Sharon P. Burton, Josef Gasteiger, Ronny Engelmann, and Holger Baars
Atmos. Chem. Phys., 17, 10767–10794, https://doi.org/10.5194/acp-17-10767-2017, https://doi.org/10.5194/acp-17-10767-2017, 2017
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Our measurements performed with a lidar on Barbados give a vertical profile of Saharan dust, which was transported over 5000 km across the Atlantic. The new triple-wavelength depolarization technique reveals more information about the shape and size of dust, which will improve our understanding of the aging process of dust in the atmosphere and its representation in dust models. Changing properties of dust particles influence the solar radiation and the cloud properties and thus our climate.
Tobias Sirch, Luca Bugliaro, Tobias Zinner, Matthias Möhrlein, and Margarita Vazquez-Navarro
Atmos. Meas. Tech., 10, 409–429, https://doi.org/10.5194/amt-10-409-2017, https://doi.org/10.5194/amt-10-409-2017, 2017
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A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the geostationary satellite MSG is presented. The basis of the algorithm is an optical flow method to derive cloud motion vectors for low and high level clouds separately. DNI is calculated from the forecasted optical thickness of the clouds. Validation against MSG observations shows good performance: compared to persistence an improvement of forecast horizon by a factor of 2 is reached for 2 h forecasts.
Josef Gasteiger, Silke Groß, Daniel Sauer, Moritz Haarig, Albert Ansmann, and Bernadett Weinzierl
Atmos. Chem. Phys., 17, 297–311, https://doi.org/10.5194/acp-17-297-2017, https://doi.org/10.5194/acp-17-297-2017, 2017
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To study aerosol transport in the Saharan Air Layer (SAL) from Africa to the Caribbean, we combine advanced optical models of Saharan aerosols with Stokes settling and two hypotheses about the occurrence of vertical mixing. By testing our hypotheses with lidar and in situ profiles measured near the top of the transported SAL, we find strong evidence that vertical mixing occurs in the SAL over the Atlantic with significant consequences for size distribution of the transported Saharan aerosols.
Tobias Zinner, Petra Hausmann, Florian Ewald, Luca Bugliaro, Claudia Emde, and Bernhard Mayer
Atmos. Meas. Tech., 9, 4615–4632, https://doi.org/10.5194/amt-9-4615-2016, https://doi.org/10.5194/amt-9-4615-2016, 2016
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A new retrieval of optical thickness and effective particle size of ice clouds over a wide range of optical thickness from transmittance measurements is presented. A visible range spectral slope is used to resolve the transmittance optical thickness ambiguity. Retrieval sensitivity to ice crystal habit, aerosol, albedo, sensor accuracy and lookup table interpolation is presented as well as an application of the method and comparison to satellite products for 2 days.
Silke Groß, Josef Gasteiger, Volker Freudenthaler, Thomas Müller, Daniel Sauer, Carlos Toledano, and Albert Ansmann
Atmos. Chem. Phys., 16, 11535–11546, https://doi.org/10.5194/acp-16-11535-2016, https://doi.org/10.5194/acp-16-11535-2016, 2016
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Dual-wavelength depolarization sensitive Raman lidar measurements were used to characterize the optical properties of the dust loaded convective boundary layer over the Caribbean. Furthermore we derived the dust volume fraction and dust mass concentration within the convective boundary layer.
M. Wiegner and J. Gasteiger
Atmos. Meas. Tech., 8, 3971–3984, https://doi.org/10.5194/amt-8-3971-2015, https://doi.org/10.5194/amt-8-3971-2015, 2015
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For the past few years a large number of autonomous continuously operating single-wavelength backscatter lidars, so called ceilometers, have been installed. Currently the assessment of their potential for aerosol remote sensing is a major research topic. This paper focusses on the need to consider water vapor
absorption if ceilometers emitting at wavelengths in the 905 to 910 nm range are used and proposes a correction scheme to improve the retrieval of the aerosol backscatter coefficient.
N. Hanrieder, S. Wilbert, R. Pitz-Paal, C. Emde, J. Gasteiger, B. Mayer, and J. Polo
Atmos. Meas. Tech., 8, 3467–3480, https://doi.org/10.5194/amt-8-3467-2015, https://doi.org/10.5194/amt-8-3467-2015, 2015
P. Koepke, J. Gasteiger, and M. Hess
Atmos. Chem. Phys., 15, 5947–5956, https://doi.org/10.5194/acp-15-5947-2015, https://doi.org/10.5194/acp-15-5947-2015, 2015
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Desert dust particles in general are not spherical, which changes their scattering functions against that for spheres that often are used for remote-sensing and radiation budget investigations. In the new version of the data base OPAC (Optical Properties of Aerosols and Clouds), which easily allows one to model a large range of microphysical and optical aerosol properties for individually decided component mixtures, now typical non-spherical mineral particles are taken into account.
A. Kylling, N. Kristiansen, A. Stohl, R. Buras-Schnell, C. Emde, and J. Gasteiger
Atmos. Meas. Tech., 8, 1935–1949, https://doi.org/10.5194/amt-8-1935-2015, https://doi.org/10.5194/amt-8-1935-2015, 2015
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Water and ice clouds affect detection and retrieval of volcanic ash clouds by satellite instruments. Synthetic infrared satellite images were generated for the Eyjafjallajokull 2010 and Grimsvotn 2011 eruptions by combining weather forecast, ash transport and radiative transfer modelling. Clouds decreased the number of pixels identified as ash and generally increased the retrieved ash-mass loading compared to the cloudless case; however, large differences were seen between scenes.
J. Gasteiger and V. Freudenthaler
Atmos. Meas. Tech., 7, 3773–3781, https://doi.org/10.5194/amt-7-3773-2014, https://doi.org/10.5194/amt-7-3773-2014, 2014
S. Kox, L. Bugliaro, and A. Ostler
Atmos. Meas. Tech., 7, 3233–3246, https://doi.org/10.5194/amt-7-3233-2014, https://doi.org/10.5194/amt-7-3233-2014, 2014
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
M. Wiegner, F. Madonna, I. Binietoglou, R. Forkel, J. Gasteiger, A. Geiß, G. Pappalardo, K. Schäfer, and W. Thomas
Atmos. Meas. Tech., 7, 1979–1997, https://doi.org/10.5194/amt-7-1979-2014, https://doi.org/10.5194/amt-7-1979-2014, 2014
A. Kreuter, R. Buras, B. Mayer, A. Webb, R. Kift, A. Bais, N. Kouremeti, and M. Blumthaler
Atmos. Chem. Phys., 14, 5989–6002, https://doi.org/10.5194/acp-14-5989-2014, https://doi.org/10.5194/acp-14-5989-2014, 2014
B. Reinhardt, R. Buras, L. Bugliaro, S. Wilbert, and B. Mayer
Atmos. Meas. Tech., 7, 823–838, https://doi.org/10.5194/amt-7-823-2014, https://doi.org/10.5194/amt-7-823-2014, 2014
J.-F. Gayet, V. Shcherbakov, L. Bugliaro, A. Protat, J. Delanoë, J. Pelon, and A. Garnier
Atmos. Chem. Phys., 14, 899–912, https://doi.org/10.5194/acp-14-899-2014, https://doi.org/10.5194/acp-14-899-2014, 2014
U. Schumann, R. Hempel, H. Flentje, M. Garhammer, K. Graf, S. Kox, H. Lösslein, and B. Mayer
Atmos. Meas. Tech., 6, 3597–3612, https://doi.org/10.5194/amt-6-3597-2013, https://doi.org/10.5194/amt-6-3597-2013, 2013
M. Vázquez-Navarro, B. Mayer, and H. Mannstein
Atmos. Meas. Tech., 6, 2627–2640, https://doi.org/10.5194/amt-6-2627-2013, https://doi.org/10.5194/amt-6-2627-2013, 2013
M. von Hobe, S. Bekki, S. Borrmann, F. Cairo, F. D'Amato, G. Di Donfrancesco, A. Dörnbrack, A. Ebersoldt, M. Ebert, C. Emde, I. Engel, M. Ern, W. Frey, S. Genco, S. Griessbach, J.-U. Grooß, T. Gulde, G. Günther, E. Hösen, L. Hoffmann, V. Homonnai, C. R. Hoyle, I. S. A. Isaksen, D. R. Jackson, I. M. Jánosi, R. L. Jones, K. Kandler, C. Kalicinsky, A. Keil, S. M. Khaykin, F. Khosrawi, R. Kivi, J. Kuttippurath, J. C. Laube, F. Lefèvre, R. Lehmann, S. Ludmann, B. P. Luo, M. Marchand, J. Meyer, V. Mitev, S. Molleker, R. Müller, H. Oelhaf, F. Olschewski, Y. Orsolini, T. Peter, K. Pfeilsticker, C. Piesch, M. C. Pitts, L. R. Poole, F. D. Pope, F. Ravegnani, M. Rex, M. Riese, T. Röckmann, B. Rognerud, A. Roiger, C. Rolf, M. L. Santee, M. Scheibe, C. Schiller, H. Schlager, M. Siciliani de Cumis, N. Sitnikov, O. A. Søvde, R. Spang, N. Spelten, F. Stordal, O. Sumińska-Ebersoldt, A. Ulanovski, J. Ungermann, S. Viciani, C. M. Volk, M. vom Scheidt, P. von der Gathen, K. Walker, T. Wegner, R. Weigel, S. Weinbruch, G. Wetzel, F. G. Wienhold, I. Wohltmann, W. Woiwode, I. A. K. Young, V. Yushkov, B. Zobrist, and F. Stroh
Atmos. Chem. Phys., 13, 9233–9268, https://doi.org/10.5194/acp-13-9233-2013, https://doi.org/10.5194/acp-13-9233-2013, 2013
A. Kylling, R. Buras, S. Eckhardt, C. Emde, B. Mayer, and A. Stohl
Atmos. Meas. Tech., 6, 649–660, https://doi.org/10.5194/amt-6-649-2013, https://doi.org/10.5194/amt-6-649-2013, 2013
C. A. Randles, S. Kinne, G. Myhre, M. Schulz, P. Stier, J. Fischer, L. Doppler, E. Highwood, C. Ryder, B. Harris, J. Huttunen, Y. Ma, R. T. Pinker, B. Mayer, D. Neubauer, R. Hitzenberger, L. Oreopoulos, D. Lee, G. Pitari, G. Di Genova, J. Quaas, F. G. Rose, S. Kato, S. T. Rumbold, I. Vardavas, N. Hatzianastassiou, C. Matsoukas, H. Yu, F. Zhang, H. Zhang, and P. Lu
Atmos. Chem. Phys., 13, 2347–2379, https://doi.org/10.5194/acp-13-2347-2013, https://doi.org/10.5194/acp-13-2347-2013, 2013
E. Jäkel, M. Wendisch, and B. Mayer
Atmos. Meas. Tech., 6, 527–537, https://doi.org/10.5194/amt-6-527-2013, https://doi.org/10.5194/amt-6-527-2013, 2013
F. Ewald, L. Bugliaro, H. Mannstein, and B. Mayer
Atmos. Meas. Tech., 6, 309–322, https://doi.org/10.5194/amt-6-309-2013, https://doi.org/10.5194/amt-6-309-2013, 2013
Related subject area
Atmospheric sciences
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
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
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
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
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
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)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
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
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
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
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.
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.
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
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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
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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
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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
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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
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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
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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
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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.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
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
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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
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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
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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
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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
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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.
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Short summary
libradtran is a widely used software package for radiative transfer calculations. It allows one to compute (polarized) radiances, irradiance, and actinic fluxes in the solar and thermal spectral regions. This paper gives an overview of libradtran version 2.0 with focus on new features (e.g. polarization, Raman scattering, absorption parameterization, cloud and aerosol optical properties). libRadtran is freely available at http://www.libradtran.org.
libradtran is a widely used software package for radiative transfer calculations. It allows one...
