Articles | Volume 6, issue 6
https://doi.org/10.5194/gmd-6-1961-2013
© Author(s) 2013. 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-6-1961-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
08 Nov 2013
Development and technical paper |
| 08 Nov 2013
EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models
K. Zink
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
A. Pauling
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
M. W. Rotach
Institute for Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
H. Vogel
Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
P. Kaufmann
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
B. Clot
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
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Lisa Janina Muth, Sascha Bierbauer, Corinna Hoose, Bernhard Vogel, Heike Vogel, and Gholam Ali Hoshyaripour
EGUsphere, https://doi.org/10.5194/egusphere-2025-402, https://doi.org/10.5194/egusphere-2025-402, 2025
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Our study explores how intense wildfires created thunderstorm-like clouds that can affect weather and climate globally. Using simulations with high resolution, we found that fire heat and moisture help form these clouds, lifting particles high into the atmosphere. This process is crucial for understanding how fires impact the environment. Despite some differences with observational data, our findings align well over time, showing the importance of fire-induced heat in cloud formation.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Sophie Erb, Elias Graf, Yanick Zeder, Simone Lionetti, Alexis Berne, Bernard Clot, Gian Lieberherr, Fiona Tummon, Pascal Wullschleger, and Benoît Crouzy
Atmos. Meas. Tech., 17, 441–451, https://doi.org/10.5194/amt-17-441-2024, https://doi.org/10.5194/amt-17-441-2024, 2024
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In this study, we focus on an automatic bioaerosol measurement instrument and investigate the impact of using its fluorescence measurement for pollen identification. The fluorescence signal is used together with a pair of images from the same instrument to identify single pollen grains via neural networks. We test whether considering fluorescence as a supplementary input improves the pollen identification performance by comparing three different neural networks.
Matthias Göbel, Stefano Serafin, and Mathias W. Rotach
Weather Clim. Dynam., 4, 725–745, https://doi.org/10.5194/wcd-4-725-2023, https://doi.org/10.5194/wcd-4-725-2023, 2023
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On summer days over mountains, upslope winds transport moist air towards mountain tops and beyond, making local rain showers more likely. We use idealized simulations to investigate how mountain steepness affects this mechanism. We find that steeper mountains lead to a delayed onset and lower intensity of the storms, because less moisture accumulates over the ridges and the thermal updraft zone at the top is narrower and thus more prone to the intrusion of dry air from the environment.
Axel Seifert, Vanessa Bachmann, Florian Filipitsch, Jochen Förstner, Christian M. Grams, Gholam Ali Hoshyaripour, Julian Quinting, Anika Rohde, Heike Vogel, Annette Wagner, and Bernhard Vogel
Atmos. Chem. Phys., 23, 6409–6430, https://doi.org/10.5194/acp-23-6409-2023, https://doi.org/10.5194/acp-23-6409-2023, 2023
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We investigate how mineral dust can lead to the formation of cirrus clouds. Dusty cirrus clouds lead to a reduction in solar radiation at the surface and, hence, a reduced photovoltaic power generation. Current weather prediction systems are not able to predict this interaction between mineral dust and cirrus clouds. We have developed a new physical description of the formation of dusty cirrus clouds. Overall we can show a considerable improvement in the forecast quality of clouds and radiation.
Hetal P. Dabhi, Mathias W. Rotach, and Michael Oberguggenberger
Hydrol. Earth Syst. Sci., 27, 2123–2147, https://doi.org/10.5194/hess-27-2123-2023, https://doi.org/10.5194/hess-27-2123-2023, 2023
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Spatiotemporally consistent high-resolution precipitation data on climate are needed for climate change impact assessments, but obtaining these data is challenging for areas with complex topography. We present a model that generates synthetic gridded daily precipitation data at a 1 km spatial resolution using observed meteorological station data as input, thereby providing data where historical observations are unavailable. We evaluate this model for a mountainous region in the European Alps.
Cornelius Immanuel Weiß, Alexander Gohm, Mathias Walter Rotach, and Thomas Torora Minda
Weather Clim. Dynam., 3, 1003–1019, https://doi.org/10.5194/wcd-3-1003-2022, https://doi.org/10.5194/wcd-3-1003-2022, 2022
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Two gap flow events in the Great Rift Valley in Ethiopia were investigated based on observations, ERA5 reanalysis data, and simulations with the numerical weather prediction model WRF. The main focus was on strong winds in the area around Lake Abaya since the winds may generate waves on the lake which help to sustain the lake's ecology. That is important in terms of food supply for the local population. The gap winds exhibit a diurnal cycle and a seasonal dependence.
Natalia E. Chubarova, Heike Vogel, Elizaveta E. Androsova, Alexander A. Kirsanov, Olga B. Popovicheva, Bernhard Vogel, and Gdaliy S. Rivin
Atmos. Chem. Phys., 22, 10443–10466, https://doi.org/10.5194/acp-22-10443-2022, https://doi.org/10.5194/acp-22-10443-2022, 2022
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Effects of urban aerosol pollution in Moscow were analyzed using the COSMO-ART chemical transport model and intensive measurement campaigns. We show that urban aerosol comprises about 15–20% of columnar aerosol content, consisting mainly of fine aerosol mode. The black carbon (BC) fraction is about 5 %, depending on particle dispersion intensity (IPD). The BC fraction low value explains weak absorbing properties of the Moscow atmosphere. IPD also defines the daily cycle of urban aerosol species.
Helen Claire Ward, Mathias Walter Rotach, Alexander Gohm, Martin Graus, Thomas Karl, Maren Haid, Lukas Umek, and Thomas Muschinski
Atmos. Chem. Phys., 22, 6559–6593, https://doi.org/10.5194/acp-22-6559-2022, https://doi.org/10.5194/acp-22-6559-2022, 2022
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This study examines how cities and their surroundings influence turbulent exchange processes responsible for weather and climate. Analysis of a 4-year observational dataset for the Alpine city of Innsbruck reveals several similarities with other (flat) city centre sites. However, the mountain setting leads to characteristic daily and seasonal flow patterns (valley winds) and downslope windstorms that have a marked effect on temperature, wind speed, turbulence and pollutant concentration.
Matthias Göbel, Stefano Serafin, and Mathias W. Rotach
Geosci. Model Dev., 15, 669–681, https://doi.org/10.5194/gmd-15-669-2022, https://doi.org/10.5194/gmd-15-669-2022, 2022
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We present WRFlux, an open-source software that allows numerically consistent, time-averaged budget evaluation of prognostic variables for the numerical weather prediction model WRF as well as the transformation of the budget equations from the terrain-following grid of the model to the Cartesian coordinate system. We demonstrate the performance and a possible application of WRFlux and illustrate the detrimental effects of approximations that are inconsistent with the model numerics.
Gian Lieberherr, Kevin Auderset, Bertrand Calpini, Bernard Clot, Benoît Crouzy, Martin Gysel-Beer, Thomas Konzelmann, José Manzano, Andrea Mihajlovic, Alireza Moallemi, David O'Connor, Branko Sikoparija, Eric Sauvageat, Fiona Tummon, and Konstantina Vasilatou
Atmos. Meas. Tech., 14, 7693–7706, https://doi.org/10.5194/amt-14-7693-2021, https://doi.org/10.5194/amt-14-7693-2021, 2021
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Today there is no standard procedure to validate bioaerosol and pollen monitors. Three instruments were tested, focusing on detecting particles of different sizes. Only one instrument was able to detect the smallest particles (0.5 µm Ø), whereas the others performed best at the largest tested particles (10 µm Ø). These results are the first step towards a standardised validation procedure. The need for a reference counting method for larger particles (pollen grains: 10–200 µm Ø) was emphasised.
Hengheng Zhang, Frank Wagner, Harald Saathoff, Heike Vogel, Gholam Ali Hoshyaripour, Vanessa Bachmann, Jochen Förstner, and Thomas Leisner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-193, https://doi.org/10.5194/amt-2021-193, 2021
Revised manuscript not accepted
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The evolution and the properties of Saharan dust plume were characterized by LIDARs, a sun photometer, and a regional transport model. Comparison between LIDAR measurements, sun photometer and ICON-ART predictions shows a good agreement for dust arrival time, dust layer height, and dust structure but also that the model overestimates the backscatter coefficients by a factor of (2.2 ± 0.16) and underestimate aerosol optical depth by a factor of (1.5 ± 0.11).
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680, https://doi.org/10.5194/gmd-14-1657-2021, https://doi.org/10.5194/gmd-14-1657-2021, 2021
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This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Lukas O. Muser, Gholam Ali Hoshyaripour, Julia Bruckert, Ákos Horváth, Elizaveta Malinina, Sandra Wallis, Fred J. Prata, Alexei Rozanov, Christian von Savigny, Heike Vogel, and Bernhard Vogel
Atmos. Chem. Phys., 20, 15015–15036, https://doi.org/10.5194/acp-20-15015-2020, https://doi.org/10.5194/acp-20-15015-2020, 2020
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Volcanic aerosols endanger aircraft and thus disrupt air travel globally. For aviation safety, it is vital to know the location and lifetime of such aerosols in the atmosphere. Here we show that the interaction of volcanic particles with each other eventually reduces their atmospheric lifetime. Moreover, we demonstrate that sunlight heats these particles, which lifts them several kilometers in the atmosphere. These findings support a more reliable forecast of volcanic aerosol dispersion.
Bettina Richter, Alec van Herwijnen, Mathias W. Rotach, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 20, 2873–2888, https://doi.org/10.5194/nhess-20-2873-2020, https://doi.org/10.5194/nhess-20-2873-2020, 2020
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We investigated the sensitivity of modeled snow instability to uncertainties in meteorological input, typically found in complex terrain. The formation of the weak layer was very robust due to the long dry period, indicated by a widespread avalanche problem. Once a weak layer has formed, precipitation mostly determined slab and weak layer properties and hence snow instability. When spatially assessing snow instability for avalanche forecasting, accurate precipitation patterns have to be known.
Alima Dajuma, Kehinde O. Ogunjobi, Heike Vogel, Peter Knippertz, Siélé Silué, Evelyne Touré N'Datchoh, Véronique Yoboué, and Bernhard Vogel
Atmos. Chem. Phys., 20, 5373–5390, https://doi.org/10.5194/acp-20-5373-2020, https://doi.org/10.5194/acp-20-5373-2020, 2020
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A modeling study through COSMO-ART was used to investigate the implication of downward mixing induced by clouds in transporting biomass burning aerosols from central and southern Africa located between 2 and 4 km into the PBL over southern West Africa. Results showed that individual mixing events south of the coast of Côte d’Ivoire due to mid-level convective clouds injects part of the biomass burning plume into the PBL. 15 % of CO mass from the 2–4 km layer is mixed below 1 km.
Eric Sauvageat, Yanick Zeder, Kevin Auderset, Bertrand Calpini, Bernard Clot, Benoît Crouzy, Thomas Konzelmann, Gian Lieberherr, Fiona Tummon, and Konstantina Vasilatou
Atmos. Meas. Tech., 13, 1539–1550, https://doi.org/10.5194/amt-13-1539-2020, https://doi.org/10.5194/amt-13-1539-2020, 2020
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We present the first validation of the only operational automatic pollen monitoring system based on holography, the Swisens Poleno. The device produces real-time images of coarse aerosols, and by applying a machine learning algorithm we identify a range of pollen taxa with accuracy >90 %. The device was further validated in controlled chamber experiments to verify the counting ability and the performance of additional fluorescence measurements, which can further be used in pollen identification.
Bettina Richter, Jürg Schweizer, Mathias W. Rotach, and Alec van Herwijnen
The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, https://doi.org/10.5194/tc-13-3353-2019, 2019
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Information on snow stability is important for avalanche forecasting. To improve the stability estimation in the snow cover model SNOWPACK, we suggested an improved parameterization for the critical crack length. We compared 3 years of field data to SNOWPACK simulations. The match between observed and modeled critical crack lengths greatly improved, and critical weak layers appear more prominently in the modeled vertical profile of critical crack length.
Xiaoli Shen, Heike Vogel, Bernhard Vogel, Wei Huang, Claudia Mohr, Ramakrishna Ramisetty, Thomas Leisner, André S. H. Prévôt, and Harald Saathoff
Atmos. Chem. Phys., 19, 13189–13208, https://doi.org/10.5194/acp-19-13189-2019, https://doi.org/10.5194/acp-19-13189-2019, 2019
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This study provides good insight into the chemical nature and complex origin of aerosols by combining comprehensive field observations and transport modelling. We suggest that factors related to topography, metrological conditions, local emissions, in situ formation and growth, regional transport, and the interaction of biogenic and anthropogenic compounds need to be considered for a comprehensive understanding of aerosol processes.
Christian Mallaun, Andreas Giez, Georg J. Mayr, and Mathias W. Rotach
Atmos. Chem. Phys., 19, 9769–9786, https://doi.org/10.5194/acp-19-9769-2019, https://doi.org/10.5194/acp-19-9769-2019, 2019
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This study presents airborne measurements in shallow convection over land to investigate the dynamic properties of clouds focusing on possible narrow downdraughts in the surrounding of the clouds. A characteristic narrow downdraught region (
subsiding shell) is found directly outside the cloud borders for the mean vertical wind distribution. The
subsiding shellresults from the distribution of the highly variable updraughts and downdraughts in the near vicinity of the cloud.
Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev
Atmos. Meas. Tech., 12, 3435–3452, https://doi.org/10.5194/amt-12-3435-2019, https://doi.org/10.5194/amt-12-3435-2019, 2019
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The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct a first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multistep algorithms with sequential discrimination of pollen can be a possible way forward.
Johannes Horak, Marlis Hofer, Fabien Maussion, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Hydrol. Earth Syst. Sci., 23, 2715–2734, https://doi.org/10.5194/hess-23-2715-2019, https://doi.org/10.5194/hess-23-2715-2019, 2019
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This study presents an in-depth evaluation of the Intermediate Complexity Atmospheric Research (ICAR) model for high-resolution precipitation fields in complex topography. ICAR is evaluated with data from weather stations located in the Southern Alps of New Zealand. While ICAR underestimates rainfall amounts, it clearly improves over a coarser global model and shows potential to generate precipitation fields for long-term impact studies focused on the local impact of a changing global climate.
Konrad Deetz, Heike Vogel, Sophie Haslett, Peter Knippertz, Hugh Coe, and Bernhard Vogel
Atmos. Chem. Phys., 18, 14271–14295, https://doi.org/10.5194/acp-18-14271-2018, https://doi.org/10.5194/acp-18-14271-2018, 2018
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Water uptake can significantly increase the size and therefore alters the optical properties of aerosols. Our model study reveals that the high moisture and aerosol burden in the southern West African monsoon
layer makes it favorable to quantify properties that determine the aerosol liquid water content and its impact on the aerosol optical depth and radiative transfer. Especially in moist tropical environments the relative humidity impact on AOD has to be considered in atmospheric models.
Jennifer Schröter, Daniel Rieger, Christian Stassen, Heike Vogel, Michael Weimer, Sven Werchner, Jochen Förstner, Florian Prill, Daniel Reinert, Günther Zängl, Marco Giorgetta, Roland Ruhnke, Bernhard Vogel, and Peter Braesicke
Geosci. Model Dev., 11, 4043–4068, https://doi.org/10.5194/gmd-11-4043-2018, https://doi.org/10.5194/gmd-11-4043-2018, 2018
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In this paper, we introduce the most up-to-date version of the flexible tracer framework for the ICOsahedral Nonhydrostatic model with
Aerosols and Reactive Trace gases (ICON-ART).
We performed multiple simulations using different ICON physics configurations for weather and climate with ART.
The flexible tracer framework within ICON-ART 2.1 suits the demands of a large variety of different applications ranging from numerical weather prediction to climate integrations.
Konrad Deetz, Heike Vogel, Peter Knippertz, Bianca Adler, Jonathan Taylor, Hugh Coe, Keith Bower, Sophie Haslett, Michael Flynn, James Dorsey, Ian Crawford, Christoph Kottmeier, and Bernhard Vogel
Atmos. Chem. Phys., 18, 9767–9788, https://doi.org/10.5194/acp-18-9767-2018, https://doi.org/10.5194/acp-18-9767-2018, 2018
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Highly resolved process study simulations for 2–3 July are conducted with COSMO-ART to assess the aerosol direct and indirect effect on meteorological conditions over southern West Africa. The meteorological phenomena of Atlantic inflow and stratus-to-cumulus transition are identified as highly susceptible to the aerosol direct effect, leading to a spatial shift of the Atlantic inflow front and a temporal shift of the stratus-to-cumulus transition with changes in the aerosol amount.
Simon Gruber, Simon Unterstrasser, Jan Bechtold, Heike Vogel, Martin Jung, Henry Pak, and Bernhard Vogel
Atmos. Chem. Phys., 18, 6393–6411, https://doi.org/10.5194/acp-18-6393-2018, https://doi.org/10.5194/acp-18-6393-2018, 2018
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A numerical model also used for operational weather forecast was applied to investigate the impact of contrails and contrail cirrus on the radiative fluxes at the earth's surface. Accounting for contrails produced by aircraft enables the model to simulate high clouds that are otherwise missing. In a case study, we find that the effect of these extra clouds is to reduce the incoming shortwave radiation at the surface as well as the production of photovoltaic power by up to 10 %.
Christoph Horat, Manuel Antonetti, Katharina Liechti, Pirmin Kaufmann, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-119, https://doi.org/10.5194/nhess-2018-119, 2018
Publication in NHESS not foreseen
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Two forecasting chains are forced by information from numerical weather predictions. The framework presented in the companion paper by Antonetti et al. has been set up for the Swiss Verzasca basin. The forecasts obtained with the uncalibrated RGM-PRO model are compared to forecasts yielded by the calibrated PREVAH-HRU model. Results shows that the uncalibrated model is able to compete with the calibrated operational prediction system and was consistently superior for
high-flow situations.
Daniel Rieger, Andrea Steiner, Vanessa Bachmann, Philipp Gasch, Jochen Förstner, Konrad Deetz, Bernhard Vogel, and Heike Vogel
Atmos. Chem. Phys., 17, 13391–13415, https://doi.org/10.5194/acp-17-13391-2017, https://doi.org/10.5194/acp-17-13391-2017, 2017
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The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. We investigate the impact of mineral dust on the PV power generation during a Saharan dust outbreak over Germany on 4 April 2014. We find an overall improvement of the PV power forecast for 65 % of the pyranometer stations in Germany.
Eleni Athanasopoulou, Orestis Speyer, Dominik Brunner, Heike Vogel, Bernhard Vogel, Nikolaos Mihalopoulos, and Evangelos Gerasopoulos
Atmos. Chem. Phys., 17, 10597–10618, https://doi.org/10.5194/acp-17-10597-2017, https://doi.org/10.5194/acp-17-10597-2017, 2017
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This work focuses on the impact of residential wood burning on aerosol levels, composition and radiation under the ongoing economic crisis in Greece. The atmospheric model COSMO-ART performed a series of runs during the winter of 2013–2014. Emission inputs were revised according to the detailed aerosol characterization by local measurements. Aerosol levels were found to be elevated and mostly composed of organics, yet the timing of the plume justifies the minor radiative cooling and feedbacks.
Franziska Glassmeier, Anna Possner, Bernhard Vogel, Heike Vogel, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 8651–8680, https://doi.org/10.5194/acp-17-8651-2017, https://doi.org/10.5194/acp-17-8651-2017, 2017
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We compare two chemistry and aerosol schemes – one designed for air-quality, the other for climate applications. For distribution, composition and radiative properties, the choice of aerosol types and processes turns out to be more important than their implementation. For aerosol–cloud interactions, we find cloud processes, in particular ice formation, to be the main obstacle to our understanding.
Michael Weimer, Jennifer Schröter, Johannes Eckstein, Konrad Deetz, Marco Neumaier, Garlich Fischbeck, Lu Hu, Dylan B. Millet, Daniel Rieger, Heike Vogel, Bernhard Vogel, Thomas Reddmann, Oliver Kirner, Roland Ruhnke, and Peter Braesicke
Geosci. Model Dev., 10, 2471–2494, https://doi.org/10.5194/gmd-10-2471-2017, https://doi.org/10.5194/gmd-10-2471-2017, 2017
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In this paper, the recently developed module for trace gas emissions in the online coupled modelling framework ICON-ART for atmospheric chemistry is presented. Algorithms for offline and online calculation of the emissions are described. The module is validated with ground-based as well as airborne measurements of acetone. It is shown that the module performs well and allows the simulation of annual cycles of emission-driven trace gases.
Daniel Leukauf, Alexander Gohm, and Mathias W. Rotach
Atmos. Chem. Phys., 16, 13049–13066, https://doi.org/10.5194/acp-16-13049-2016, https://doi.org/10.5194/acp-16-13049-2016, 2016
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Since populated valleys suffer often from poor air quality, it is of interest to better understand the various mechanisms relevant to remove pollutants from the valley atmosphere. One mechanism is the transport by along-slope flows, which are generated during fair-weather days. In this study we quantify the amount of tracer that is removed from a valley atmosphere and the amount that is re-circulated within the valleys. For this study we are using the numerical weather model WRF.
Carolin Walter, Saulo R. Freitas, Christoph Kottmeier, Isabel Kraut, Daniel Rieger, Heike Vogel, and Bernhard Vogel
Atmos. Chem. Phys., 16, 9201–9219, https://doi.org/10.5194/acp-16-9201-2016, https://doi.org/10.5194/acp-16-9201-2016, 2016
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Buoyancy produced by vegetation fires can lead to substantial plume rise with consequences for the dispersion of aerosol emitted by the fires. To study this effect a 1-D plume rise model was included into the regional online integrated model system COSMO-ART. Comparing model results and satellite data for a case study of 2010 Canadian wildfires shows, that the plume rise model outperforms prescribed emission height. The radiative impact of the aerosol leads to a pronounced temperature change.
N. Kljun, P. Calanca, M. W. Rotach, and H. P. Schmid
Geosci. Model Dev., 8, 3695–3713, https://doi.org/10.5194/gmd-8-3695-2015, https://doi.org/10.5194/gmd-8-3695-2015, 2015
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Flux footprint models describe the surface area of influence of a flux measurement. They are used for designing flux tower sites, and for interpretation of flux measurements. The two-dimensional footprint parameterisation (FFP) presented here is suitable for processing large data sets, and, unlike other fast footprint models, FFP is applicable to daytime or night-time measurements, fluxes from short masts over grassland to tall towers over mature forests, and even to airborne flux measurements.
G. Massaro, I. Stiperski, B. Pospichal, and M. W. Rotach
Atmos. Meas. Tech., 8, 3355–3367, https://doi.org/10.5194/amt-8-3355-2015, https://doi.org/10.5194/amt-8-3355-2015, 2015
J. S. Wagner, A. Gohm, and M. W. Rotach
Atmos. Chem. Phys., 15, 6589–6603, https://doi.org/10.5194/acp-15-6589-2015, https://doi.org/10.5194/acp-15-6589-2015, 2015
M. Hummel, C. Hoose, M. Gallagher, D. A. Healy, J. A. Huffman, D. O'Connor, U. Pöschl, C. Pöhlker, N. H. Robinson, M. Schnaiter, J. R. Sodeau, M. Stengel, E. Toprak, and H. Vogel
Atmos. Chem. Phys., 15, 6127–6146, https://doi.org/10.5194/acp-15-6127-2015, https://doi.org/10.5194/acp-15-6127-2015, 2015
D. Rieger, M. Bangert, I. Bischoff-Gauss, J. Förstner, K. Lundgren, D. Reinert, J. Schröter, H. Vogel, G. Zängl, R. Ruhnke, and B. Vogel
Geosci. Model Dev., 8, 1659–1676, https://doi.org/10.5194/gmd-8-1659-2015, https://doi.org/10.5194/gmd-8-1659-2015, 2015
M. Collaud Coen, C. Praz, A. Haefele, D. Ruffieux, P. Kaufmann, and B. Calpini
Atmos. Chem. Phys., 14, 13205–13221, https://doi.org/10.5194/acp-14-13205-2014, https://doi.org/10.5194/acp-14-13205-2014, 2014
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An operational planetary boundary layer height detection method with several remote sensing instruments (wind profiler, Raman lidar, microwave radiometer) and algorithms (Parcel and bulk Richardson number methods, surface-based temperature inversion, aerosol and humidity gradient analysis) was validated against radio sounding. A comparison with the numerical weather prediction model COSMO-2 and the seasonal cycles of the day- and nighttime PBL for two stations on the Swiss plateau are presented.
H. Vogel, J. Förstner, B. Vogel, T. Hanisch, B. Mühr, U. Schättler, and T. Schad
Atmos. Chem. Phys., 14, 7837–7845, https://doi.org/10.5194/acp-14-7837-2014, https://doi.org/10.5194/acp-14-7837-2014, 2014
E. Athanasopoulou, H. Vogel, B. Vogel, A. P. Tsimpidi, S. N. Pandis, C. Knote, and C. Fountoukis
Atmos. Chem. Phys., 13, 625–645, https://doi.org/10.5194/acp-13-625-2013, https://doi.org/10.5194/acp-13-625-2013, 2013
Related subject area
Atmospheric sciences
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Atmospheric moisture tracking with WAM2layers v3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
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.
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.
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.
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.
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.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
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Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-148, https://doi.org/10.5194/gmd-2024-148, 2024
Revised manuscript accepted for GMD
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In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled chemistry meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the CMA-GFS operational global numerical weather model. The results show that assimilating BC observations can generate analysis increments not only for BC but also for atmospheric variables.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
EGUsphere, https://doi.org/10.5194/egusphere-2024-3401, https://doi.org/10.5194/egusphere-2024-3401, 2024
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We introduce a new version of WAM2layers, a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data became a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent and reliable, and easier to maintain.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
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