Articles | Volume 17, issue 20
https://doi.org/10.5194/gmd-17-7513-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-7513-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
29 Oct 2024
Development and technical paper |
| 29 Oct 2024
| 29 Oct 2024
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 182 00 Prague 8, Czech Republic
Petra Bauerová
Czech Hydrometeorological Institue, Na Šabatce 2050/17, 143 00 Prague 12, Czech Republic
Michal Belda
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University Prague, V Holešovičkách 2, 180 00 Prague 8, Czech Republic
Martin Bureš
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 182 00 Prague 8, Czech Republic
ATEM – Studio of ecological models, Roztylská 1860/1, 148 00 Prague 4, Czech Republic
Kryštof Eben
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 182 00 Prague 8, Czech Republic
Vladimír Fuka
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University Prague, V Holešovičkách 2, 180 00 Prague 8, Czech Republic
Jan Geletič
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 182 00 Prague 8, Czech Republic
Radek Jareš
ATEM – Studio of ecological models, Roztylská 1860/1, 148 00 Prague 4, Czech Republic
Jan Karel
ATEM – Studio of ecological models, Roztylská 1860/1, 148 00 Prague 4, Czech Republic
Josef Keder
Czech Hydrometeorological Institue, Na Šabatce 2050/17, 143 00 Prague 12, Czech Republic
Pavel Krč
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 182 00 Prague 8, Czech Republic
William Patiño
Czech Hydrometeorological Institue, Na Šabatce 2050/17, 143 00 Prague 12, Czech Republic
Jelena Radović
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University Prague, V Holešovičkách 2, 180 00 Prague 8, Czech Republic
ATEM – Studio of ecological models, Roztylská 1860/1, 148 00 Prague 4, Czech Republic
Hynek Řezníček
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 182 00 Prague 8, Czech Republic
Matthias Sühring
Institute for Meteorology and Climatology, Leibniz University Hannover, Herrenhäuser Straße 2, 30419 Hanover, Germany
Pecanode GmbH, Peterstraße 30, 38640 Goslar, Germany
Adriana Šindelářová
Czech Hydrometeorological Institue, Na Šabatce 2050/17, 143 00 Prague 12, Czech Republic
Ondřej Vlček
Czech Hydrometeorological Institue, Na Šabatce 2050/17, 143 00 Prague 12, Czech Republic
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Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
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Stefan Metzger, David Durden, Sreenath Paleri, Matthias Sühring, Brian J. Butterworth, Christopher Florian, Matthias Mauder, David M. Plummer, Luise Wanner, Ke Xu, and Ankur R. Desai
Atmos. Meas. Tech., 14, 6929–6954, https://doi.org/10.5194/amt-14-6929-2021, https://doi.org/10.5194/amt-14-6929-2021, 2021
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Geosci. Model Dev., 14, 5435–5465, https://doi.org/10.5194/gmd-14-5435-2021, https://doi.org/10.5194/gmd-14-5435-2021, 2021
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Geosci. Model Dev., 14, 4797–4842, https://doi.org/10.5194/gmd-14-4797-2021, https://doi.org/10.5194/gmd-14-4797-2021, 2021
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Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021, https://doi.org/10.5194/gmd-14-4443-2021, 2021
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Geosci. Model Dev., 14, 3511–3519, https://doi.org/10.5194/gmd-14-3511-2021, https://doi.org/10.5194/gmd-14-3511-2021, 2021
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The impact of buildings on the urban climate is defined by different physical building parameters with different technical facilities for ventilation, heating and cooling.
Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch
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Pavel Krč, Jaroslav Resler, Matthias Sühring, Sebastian Schubert, Mohamed H. Salim, and Vladimír Fuka
Geosci. Model Dev., 14, 3095–3120, https://doi.org/10.5194/gmd-14-3095-2021, https://doi.org/10.5194/gmd-14-3095-2021, 2021
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Basit Khan, Sabine Banzhaf, Edward C. Chan, Renate Forkel, Farah Kanani-Sühring, Klaus Ketelsen, Mona Kurppa, Björn Maronga, Matthias Mauder, Siegfried Raasch, Emmanuele Russo, Martijn Schaap, and Matthias Sühring
Geosci. Model Dev., 14, 1171–1193, https://doi.org/10.5194/gmd-14-1171-2021, https://doi.org/10.5194/gmd-14-1171-2021, 2021
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An atmospheric chemistry model has been implemented in the microscale PALM model system 6.0. This article provides a detailed description of the model, its structure, input requirements, various features and limitations. Several pre-compiled ready-to-use chemical mechanisms are included in the chemistry model code; however, users can also easily implement other mechanisms. A case study is presented to demonstrate the application of the new chemistry model in the urban environment.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
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Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Jan Karlický, Peter Huszár, Tereza Nováková, Michal Belda, Filip Švábik, Jana Ďoubalová, and Tomáš Halenka
Atmos. Chem. Phys., 20, 15061–15077, https://doi.org/10.5194/acp-20-15061-2020, https://doi.org/10.5194/acp-20-15061-2020, 2020
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Cities are characterized by their impact on various meteorological variables. Our study aims to generalize these modifications into a single phenomenon – the urban meteorology island (UMI). A wide ensemble of Weather Research and Forecasting (WRF) and Regional Climate Model (RegCM) simulations investigated urban-induced modifications as individual UMI components. Significant changes are found in most of the discussed meteorological variables with a strong impact of specific model simulations.
Wieke Heldens, Cornelia Burmeister, Farah Kanani-Sühring, Björn Maronga, Dirk Pavlik, Matthias Sühring, Julian Zeidler, and Thomas Esch
Geosci. Model Dev., 13, 5833–5873, https://doi.org/10.5194/gmd-13-5833-2020, https://doi.org/10.5194/gmd-13-5833-2020, 2020
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For realistic microclimate simulations in urban areas with PALM 6.0, detailed description of surface types, buildings and vegetation is required. This paper shows how such input data sets can be derived with the example of three German cities. Various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. The collection and preparation of input data sets is tedious. Future research aims therefore at semi-automated tools to support users.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Tereza Nováková, Kateřina Šindelářová, Filip Švábik, Michal Belda, Tomáš Halenka, and Michal Žák
Atmos. Chem. Phys., 20, 11655–11681, https://doi.org/10.5194/acp-20-11655-2020, https://doi.org/10.5194/acp-20-11655-2020, 2020
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The paper shows how extreme meteorological conditions change due to the urban land-cover forcing and how this translates to the impact on the extreme air pollution over central European cities. It focuses on ozone, nitrogen dioxide, and particulate matter with a diameter of less than 2.5 μm and shows that, while for the extreme daily maximum 8 h ozone, changes are same as for the mean ones, much larger modifications are calculated for extreme NO2 and PM2.5 compared to their mean changes.
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
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In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Kateřina Šindelářová, Tereza Nováková, Michal Belda, Tomáš Halenka, Michal Žák, and Petr Pišoft
Atmos. Chem. Phys., 20, 1977–2016, https://doi.org/10.5194/acp-20-1977-2020, https://doi.org/10.5194/acp-20-1977-2020, 2020
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Urban surfaces alter meteorological conditions which consequently alter air pollution due to modified transport and chemical reactions. Here, we focus on a major component of this influence, enhanced vertical eddy diffusion. Using a regional climate model coupled to a chemistry transport model, we investigate how different representations of turbulent transport translate to urban canopy impact on ozone and PM2.5 concentrations and whether turbulence remains the most important component.
Peter Huszar, Michal Belda, Jan Karlický, Tatsiana Bardachova, Tomas Halenka, and Petr Pisoft
Atmos. Chem. Phys., 18, 14059–14078, https://doi.org/10.5194/acp-18-14059-2018, https://doi.org/10.5194/acp-18-14059-2018, 2018
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The impact of meteorological changes introduced by urbanization on aerosol concentration using a regional climate model and a chemistry transport model over central Europe is investigated. We found a strong increase of temperature and turbulence and a decrease of humidity and wind speed due to urban surfaces. This resulted in a clear decrease of aerosol concentrations near the surface: PM2.5 concentrations were reduced by 3 μg/m3. The dominating effect is the increased turbulent transport.
Jan Karlický, Peter Huszár, Tomáš Halenka, Michal Belda, Michal Žák, Petr Pišoft, and Jiří Mikšovský
Atmos. Chem. Phys., 18, 10655–10674, https://doi.org/10.5194/acp-18-10655-2018, https://doi.org/10.5194/acp-18-10655-2018, 2018
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Our work presents a comparison of modelled and observed urban-induced meteorological changes in long-term perspective using 10-year simulations. It contains an evaluation of models' urban parameterizations, investigations of the benefits of more sophisticated urban parameterizations with respect to simple approaches and evaluation of urban-induced meteorological changes from the perspective of pollutant dispersion.
Jaroslav Resler, Pavel Krč, Michal Belda, Pavel Juruš, Nina Benešová, Jan Lopata, Ondřej Vlček, Daša Damašková, Kryštof Eben, Přemysl Derbek, Björn Maronga, and Farah Kanani-Sühring
Geosci. Model Dev., 10, 3635–3659, https://doi.org/10.5194/gmd-10-3635-2017, https://doi.org/10.5194/gmd-10-3635-2017, 2017
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A realistic numerical modelling of urban climate still poses a serious challenge. The paper describes a new urban surface model (USM), integrated into large-eddy simulation model PALM. The USM covers the most important urban canopy processes (e.g. radiation, energy balance on surfaces, thermal diffusion). The model was tested in the real conditions of a city and shows good agreement with observations. The USM is optimized for high-performance computing systems and is freely available.
Peter Huszár, Michal Belda, Jan Karlický, Petr Pišoft, and Tomáš Halenka
Atmos. Chem. Phys., 16, 12993–13013, https://doi.org/10.5194/acp-16-12993-2016, https://doi.org/10.5194/acp-16-12993-2016, 2016
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Using an online coupled system of a regional climate model and chemistry transport model we investigated the radiative/climate impact of short-lived pollutants directly emitted by urban areas and those secondarily formed, focusing on the area of central Europe. We found that the direct/indirect effects of aerosols dominate, causing small but statistically significant cooling in summer and winter (up to −0.04 K). The radiative impact of ozone changes remains negligible.
P. Huszar, M. Belda, and T. Halenka
Atmos. Chem. Phys., 16, 1331–1352, https://doi.org/10.5194/acp-16-1331-2016, https://doi.org/10.5194/acp-16-1331-2016, 2016
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The study is dealing with the present day air quality impacts of the urban emissions, focusing on central Europe. Using a coupled regional climate/chemistry model we showed that urban centers impact largely (by up to 10–20 %) the regional air quality but the urban air quality itself is affected by local emission by only 50 % and the rural (non-urban) emissions and long-range transport play an important role in urban air pollution. This has to be taken into account in air quality control measures.
B. Maronga, M. Gryschka, R. Heinze, F. Hoffmann, F. Kanani-Sühring, M. Keck, K. Ketelsen, M. O. Letzel, M. Sühring, and S. Raasch
Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, https://doi.org/10.5194/gmd-8-2515-2015, 2015
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The paper gives a detailed description of the PArallelized Large-eddy simulation Model (PALM) version 4.0 for the simulation of turbulent atmospheric and oceanic boundary layer flows. The model is optimized for use on massively parallel computer architectures and has been applied for various boundary-layer research studies over the last 15 years by various work groups all over the world. Besides the model description, we outline past PALM applications and also discuss future perspectives.
P. Huszar, T. Halenka, M. Belda, M. Zak, K. Sindelarova, and J. Miksovsky
Atmos. Chem. Phys., 14, 12393–12413, https://doi.org/10.5194/acp-14-12393-2014, https://doi.org/10.5194/acp-14-12393-2014, 2014
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The impact of cities and urban surfaces on climate of central Europe is examined using a regional climate model coupled to a single-layer urban canopy model. Results show a significant impact on temperature (up to 1.5K increase in summer), the boundary layer height, surface wind with a winter decrease and precipitation (a summer decrease). Applying the urban canopy model, the regional climate model exhibits a decreased model bias when compared to observations.
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
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
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
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.
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.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Cited articles
Ardeshiri, H., Cassiani, M., Park, S. Y., Stohl, A., Pisso, I., and Dinger, A. S.: On the convergence and capability of the large-eddy simulation of concentration fluctuations in passive plumes for a neutral boundary layer at infinite Reynolds number, Bound.-Lay. Meteorol., 176, 291–327, https://doi.org/10.1007/s10546-020-00537-6, 2020. a, b
Bauerová, P., Keder, J., Šindelářová, A., Vlček, O., Patiño, W., Resler, J., Krč, P., Geletič, J., Řezníček, H., Bureš, M., Eben, K., Belda, M., Radović, J., Fuka, V., Jareš, R., and Ezau, I.: Measurement report: TURBAN observation campaign combining street-level low-cost air quality sensors and meteorological profile measurements in Prague, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-1222, 2024a. a, b
Bauerová, P., Šindelářová, A., Keder, J., Vlček, O., Patiño, W., Resler, J., Krč, P., Řezníček, H., Geletič, J., Bureš, M., Eben, K., Belda, M., Radović, J., Fuka, V., Jareš, R., and Ezau, I.: TURDATA: a database of low-cost air quality and remote sensing measurements for the validation of micro-scale models in the real Prague urban environments (0.1), Zenodo [data set], https://doi.org/10.5281/zenodo.10655033, 2024b. a
Belda, M., Resler, J., Geletič, J., Krč, P., Maronga, B., Sühring, M., Kurppa, M., Kanani-Sühring, F., Fuka, V., Eben, K., Benešová, N., and Auvinen, M.: Sensitivity analysis of the PALM model system 6.0 in the urban environment, Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021, 2021. a, b
Belda, M., Krč, P., Resler, J., Huszár, P., Benešová, N., Karlický, J., and Juruš, P.: FUME-dev/fume: Official 2.0 release (2.0), Zenodo [code], https://doi.org/10.5281/zenodo.10142912, 2023. a
Belda, M., Benešová, N., Resler, J., Huszár, P., Vlček, O., Krč, P., Karlický, J., Juruš, P., and Eben, K.: FUME 2.0 – Flexible Universal processor for Modeling Emissions, Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, 2024. a
Blocken, B.: Computational Fluid Dynamics for urban physics: Importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations, Build. Environ., 91, 219–245, https://doi.org/10.1016/j.buildenv.2015.02.015, 2015. a
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Borna, M., Turci, G., Marchetti, M., and Schiano-Phan, R.: Evaluating the Influence of Urban Blocks on Air Pollution Concentration Levels: The Case Study of Golden Lane Estate in London, Sustainability, 16, 696, https://doi.org/10.3390/su16020696, 2024. a
Brožková, R., Bučánek, A., Mašek, J., Smolíková, P., and Trojáková, A.: Nová provozní konfigurace modelu Aladin ve vysokém rozlišení, Meteorologické Zprávy, 72, 129–139, https://www.chmi.cz/files/portal/docs/reditel/SIS/casmz/assets/2019/chmu_mz_5-19.pdf (last access: 23 October 2024), 2019 (in Czech). a
Byun, D. W., Young, J., and Pleim, J.: CMAQ Science Doc, Chapter 7: Numerical Transport Algorithms for CMAQ Chemical Transport Model in Generalized Coordinates, https://www.cmascenter.org/cmaq/science_documentation/pdf/ch07.pdf (last access: 23 October 2024), 1999. a
CAMS: Regional Production, Updated documentation covering all regional operational systems and the ENSEMBLE. Following U2 upgrade, February 2020, CAMS Report METEO-FRANCE, https://atmosphere.copernicus.eu/sites/default/files/2020-09/CAMS50_2018SC2_D2.0.2-U2_Models_documentation_202003_v2.pdf (last access: 21 April 2024), 2020. a
Cichowicz, R., Wielgosiński, G., and Fetter, W.: Effect of wind speed on the level of particulate matter PM10 concentration in atmospheric air during winter season in vicinity of large combustion plant, J. Atmos. Chem., 77, 35–48, https://doi.org/10.1007/s10874-020-09401-w, 2020. a
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Couvreux, F., Bazile, E., Rodier, Q., Maronga, B., Matheou, G., Chinita, M. J., Edwards, J., van Stratum, B. J. H., van Heerwaarden, C. C., Huang, J., Moene, A. F., Cheng, A., Fuka, V., Basu, S., Bou-Zeid, E., Canut, G., and Vignon, E.: Intercomparison of large-eddy simulations of the Antarctic boundary layer for very stable stratification, Bound.-Lay. Meteorol., 176, 369–400, https://doi.org/10.1007/s10546-020-00539-4, 2020. a, b
Dai, Y., Basu, S., Maronga, B., and de Roode, S. R.: Addressing the grid-size sensitivity issue in large-eddy simulations of stable boundary layers, Bound.-Lay. Meteorol., 178, 63–89, https://doi.org/10.1007/s10546-020-00558-1, 2021. a
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Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Detailed modeling of urban air quality in stable conditions is a challenge. We show the...
