Articles | Volume 13, issue 12
Geosci. Model Dev., 13, 6303–6323, 2020
https://doi.org/10.5194/gmd-13-6303-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 13, 6303–6323, 2020
https://doi.org/10.5194/gmd-13-6303-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper 11 Dec 2020
Model description paper | 11 Dec 2020
Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model
Bruce Rolstad Denby et al.
Related authors
Peter Wind, Bruce Rolstad Denby, and Michael Gauss
Geosci. Model Dev., 13, 1623–1634, https://doi.org/10.5194/gmd-13-1623-2020, https://doi.org/10.5194/gmd-13-1623-2020, 2020
Short summary
Short summary
We present a new method for individually quantifying the contributions from different sources to local air pollution. The method can be used to distinguish the sources of local air pollution for any position in one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence, it can be used for time-critical operational services by providing scientific information as input for local policy decisions on air pollution abatement.
Ana Stojiljkovic, Mari Kauhaniemi, Jaakko Kukkonen, Kaarle Kupiainen, Ari Karppinen, Bruce Rolstad Denby, Anu Kousa, Jarkko V. Niemi, and Matthias Ketzel
Atmos. Chem. Phys., 19, 11199–11212, https://doi.org/10.5194/acp-19-11199-2019, https://doi.org/10.5194/acp-19-11199-2019, 2019
Short summary
Short summary
Nordic countries experience the deterioration of air quality in springtime due to high PM10 concentrations. Non-exhaust emissions from vehicular traffic are regarded as the most significant source of particulate air pollution during this time of year. The results from this study demonstrate the fact that changes in winter tyre types and adjustments to road maintenance could substantially reduce non-exhaust emissions.
J. Kukkonen, M. Karl, M. P. Keuken, H. A. C. Denier van der Gon, B. R. Denby, V. Singh, J. Douros, A. Manders, Z. Samaras, N. Moussiopoulos, S. Jonkers, M. Aarnio, A. Karppinen, L. Kangas, S. Lützenkirchen, T. Petäjä, I. Vouitsis, and R. S. Sokhi
Geosci. Model Dev., 9, 451–478, https://doi.org/10.5194/gmd-9-451-2016, https://doi.org/10.5194/gmd-9-451-2016, 2016
Short summary
Short summary
For analyzing the health effects of particulate matter, it is necessary to consider not only the mass of particles, but also their sizes and composition. A simple measure for the former is the number concentration of particles. We present particle number concentrations in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008, based mainly on modelling. The concentrations of PN were mostly influenced by the emissions from local vehicular traffic.
Sinikka T. Lennartz, Michael Gauss, Marc von Hobe, and Christa A. Marandino
Earth Syst. Sci. Data, 13, 2095–2110, https://doi.org/10.5194/essd-13-2095-2021, https://doi.org/10.5194/essd-13-2095-2021, 2021
Short summary
Short summary
This study provides a marine emission inventory for the sulphur gases carbonyl sulphide (OCS) and carbon disulphide (CS2), derived from a numerical model of the surface ocean at monthly resolution for the period 2000–2019. Comparison with a database of seaborne observations reveals very good agreement for OCS. Interannual variability in both gases seems to be mainly driven by the amount of chromophoric dissolved organic matter present in surface water.
Jérôme Barré, Hervé Petetin, Augustin Colette, Marc Guevara, Vincent-Henri Peuch, Laurence Rouil, Richard Engelen, Antje Inness, Johannes Flemming, Carlos Pérez García-Pando, Dene Bowdalo, Frederik Meleux, Camilla Geels, Jesper H. Christensen, Michael Gauss, Anna Benedictow, Svetlana Tsyro, Elmar Friese, Joanna Struzewska, Jacek W. Kaminski, John Douros, Renske Timmermans, Lennart Robertson, Mario Adani, Oriol Jorba, Mathieu Joly, and Rostislav Kouznetsov
Atmos. Chem. Phys., 21, 7373–7394, https://doi.org/10.5194/acp-21-7373-2021, https://doi.org/10.5194/acp-21-7373-2021, 2021
Short summary
Short summary
This study provides a comprehensive assessment of air quality changes across the main European urban areas induced by the COVID-19 lockdown using satellite observations, surface site measurements, and the forecasting system from the Copernicus Atmospheric Monitoring Service (CAMS). We demonstrate the importance of accounting for weather and seasonal variability when calculating such estimates.
Felipe Toledo, Martial Haeffelin, Eivind Wærsted, and Jean-Charles Dupont
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1314, https://doi.org/10.5194/acp-2020-1314, 2021
Revised manuscript under review for ACP
Short summary
Short summary
The article presents a new paradigm to describe the temporal evolution of continental fog layers, based on seven years of fog measurements performed at the SIRTA observatory. This paradigm consists of a conceptual model that relates the liquid water path of fog with its thickness and surface liquid water content. The model provides diagnostic variables that could substantially improve the reliability of fog dissipation nowcasting at local scale, based on real-time profiling observations.
Jan Eiof Jonson, Michael Gauss, Michael Schulz, Jukka-Pekka Jalkanen, and Hilde Fagerli
Atmos. Chem. Phys., 20, 11399–11422, https://doi.org/10.5194/acp-20-11399-2020, https://doi.org/10.5194/acp-20-11399-2020, 2020
Short summary
Short summary
We have calculated the effects of air pollution in Europe from shipping on levels of PM2.5 and ozone and depositions of oxidised nitrogen and sulfur from individual sea areas and from all global shipping. Model results are shown for Europe as a whole but also focusing on select, mainly coastal, countries. Calculations are made using 2017 emissions supplemented by calculations reducing sulfur emissions from ships by about 80 % following the implementation of the 2020 global sulfur cap.
Matthieu Pommier, Hilde Fagerli, Michael Schulz, Alvaro Valdebenito, Richard Kranenburg, and Martijn Schaap
Geosci. Model Dev., 13, 1787–1807, https://doi.org/10.5194/gmd-13-1787-2020, https://doi.org/10.5194/gmd-13-1787-2020, 2020
Short summary
Short summary
The EMEP and LOTOS-EUROS models comprise the operational source contribution prediction system for the European cities within the Copernicus Atmosphere Monitoring Service (CAMS). This study presents a first evaluation of this system, with hourly resolution, by focusing on one PM10 episode in December 2016, dominated by the influence of domestic emissions. It shows that the system provides valuable information on the composition and contributions of different countries to PM10.
Peter Wind, Bruce Rolstad Denby, and Michael Gauss
Geosci. Model Dev., 13, 1623–1634, https://doi.org/10.5194/gmd-13-1623-2020, https://doi.org/10.5194/gmd-13-1623-2020, 2020
Short summary
Short summary
We present a new method for individually quantifying the contributions from different sources to local air pollution. The method can be used to distinguish the sources of local air pollution for any position in one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence, it can be used for time-critical operational services by providing scientific information as input for local policy decisions on air pollution abatement.
Giancarlo Ciarelli, Mark R. Theobald, Marta G. Vivanco, Matthias Beekmann, Wenche Aas, Camilla Andersson, Robert Bergström, Astrid Manders-Groot, Florian Couvidat, Mihaela Mircea, Svetlana Tsyro, Hilde Fagerli, Kathleen Mar, Valentin Raffort, Yelva Roustan, Maria-Teresa Pay, Martijn Schaap, Richard Kranenburg, Mario Adani, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Cornelis Cuvelier, Arineh Cholakian, Bertrand Bessagnet, Peter Wind, and Augustin Colette
Geosci. Model Dev., 12, 4923–4954, https://doi.org/10.5194/gmd-12-4923-2019, https://doi.org/10.5194/gmd-12-4923-2019, 2019
Short summary
Short summary
The novel multi-model EURODELTA-Trends exercise provided 21 years of continuous PM components and their gas-phase precursor concentrations over Europe from the year 1990. The models’ capabilities to reproduce PM components and gas-phase PM precursor trends over the 1990–2010 period is the key focus of this study. The models were able to reproduce the observed trends relatively well, indicating a possible shift in the thermodynamic equilibrium between gas and particle phases.
Jan Eiof Jonson, Michael Gauss, Jukka-Pekka Jalkanen, and Lasse Johansson
Atmos. Chem. Phys., 19, 13469–13487, https://doi.org/10.5194/acp-19-13469-2019, https://doi.org/10.5194/acp-19-13469-2019, 2019
Short summary
Short summary
Calculations have been made with the regional-scale EMEP chemical transport model covering Europe and the sea areas surrounding Europe, including much of the North Atlantic. The main focus is on the effects on air pollution as well as depositions of sulfur and nitrogen following the implementation of stricter sulfur emission regulations from 1 January 2015 for ships operating in the Baltic Sea. We also include a study on the effects of future (2030) emissions changes.
Ana Stojiljkovic, Mari Kauhaniemi, Jaakko Kukkonen, Kaarle Kupiainen, Ari Karppinen, Bruce Rolstad Denby, Anu Kousa, Jarkko V. Niemi, and Matthias Ketzel
Atmos. Chem. Phys., 19, 11199–11212, https://doi.org/10.5194/acp-19-11199-2019, https://doi.org/10.5194/acp-19-11199-2019, 2019
Short summary
Short summary
Nordic countries experience the deterioration of air quality in springtime due to high PM10 concentrations. Non-exhaust emissions from vehicular traffic are regarded as the most significant source of particulate air pollution during this time of year. The results from this study demonstrate the fact that changes in winter tyre types and adjustments to road maintenance could substantially reduce non-exhaust emissions.
Anna Katinka Petersen, Guy P. Brasseur, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Ying Xie, Jianming Xu, and Guangqiang Zhou
Geosci. Model Dev., 12, 1241–1266, https://doi.org/10.5194/gmd-12-1241-2019, https://doi.org/10.5194/gmd-12-1241-2019, 2019
Short summary
Short summary
An operational multi-model forecasting system for air quality is providing daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas of China. The paper presents the evaluation of the different forecasts performed during the first year of operation.
Mark R. Theobald, Marta G. Vivanco, Wenche Aas, Camilla Andersson, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Mihaela Mircea, Maria-Teresa Pay, Svetlana Tsyro, Mario Adani, Robert Bergström, Bertrand Bessagnet, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Hilde Fagerli, Kathleen Mar, Noelia Otero, Valentin Raffort, Yelva Roustan, Martijn Schaap, Peter Wind, and Augustin Colette
Atmos. Chem. Phys., 19, 379–405, https://doi.org/10.5194/acp-19-379-2019, https://doi.org/10.5194/acp-19-379-2019, 2019
Short summary
Short summary
Model estimates of the mean European wet deposition of nitrogen and sulfur for 1990 to 2010 were within 40 % of the observed values. As a result of systematic biases, the models were better at estimating relative trends for the periods 1990–2000 and 2000–2010 than the absolute trends. Although the predominantly decreasing trends were mostly due to emission reductions, they were partially offset by other factors (e.g. changes in precipitation) during the first period, but not the second.
Guy P. Brasseur, Ying Xie, Anna Katinka Petersen, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Jianming Xu, and Guangqiang Zhou
Geosci. Model Dev., 12, 33–67, https://doi.org/10.5194/gmd-12-33-2019, https://doi.org/10.5194/gmd-12-33-2019, 2019
Short summary
Short summary
An operational multi-model forecasting system for air quality provides daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas in China. The paper presents an intercomparison of the different forecasts performed during a specific period of time and highlights recurrent differences between the model output. Pathways to improve the forecasts by the multi-model system are suggested.
Noelia Otero, Jana Sillmann, Kathleen A. Mar, Henning W. Rust, Sverre Solberg, Camilla Andersson, Magnuz Engardt, Robert Bergström, Bertrand Bessagnet, Augustin Colette, Florian Couvidat, Cournelius Cuvelier, Svetlana Tsyro, Hilde Fagerli, Martijn Schaap, Astrid Manders, Mihaela Mircea, Gino Briganti, Andrea Cappelletti, Mario Adani, Massimo D'Isidoro, María-Teresa Pay, Mark Theobald, Marta G. Vivanco, Peter Wind, Narendra Ojha, Valentin Raffort, and Tim Butler
Atmos. Chem. Phys., 18, 12269–12288, https://doi.org/10.5194/acp-18-12269-2018, https://doi.org/10.5194/acp-18-12269-2018, 2018
Short summary
Short summary
This paper evaluates the capability of air-quality models to capture the observed relationship between surface ozone concentrations and meteorology over Europe. The air-quality models tended to overestimate the influence of maximum temperature and surface solar radiation. None of the air-quality models captured the strength of the observed relationship between ozone and relative humidity appropriately, underestimating the effect of relative humidity, a key factor in the ozone removal processes.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
Short summary
Short summary
European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Matthieu Pommier, Hilde Fagerli, Michael Gauss, David Simpson, Sumit Sharma, Vinay Sinha, Sachin D. Ghude, Oskar Landgren, Agnes Nyiri, and Peter Wind
Atmos. Chem. Phys., 18, 103–127, https://doi.org/10.5194/acp-18-103-2018, https://doi.org/10.5194/acp-18-103-2018, 2018
Short summary
Short summary
India has to cope with a poor air quality, and this work shows a predicted increase in pollution (O3 & PM2.5) if no further policy efforts are made in the future. Climate change will modify the soil moisture leading to changes in O3. Changes in PM2.5 are related to changes in precipitation, biogenic emissions and wind speed. It is also shown that in the 2050s, the secondary inorganic aerosols will become the main component of PM2.5 over India related to the increase in anthropogenic emissions.
Augustin Colette, Camilla Andersson, Astrid Manders, Kathleen Mar, Mihaela Mircea, Maria-Teresa Pay, Valentin Raffort, Svetlana Tsyro, Cornelius Cuvelier, Mario Adani, Bertrand Bessagnet, Robert Bergström, Gino Briganti, Tim Butler, Andrea Cappelletti, Florian Couvidat, Massimo D'Isidoro, Thierno Doumbia, Hilde Fagerli, Claire Granier, Chris Heyes, Zig Klimont, Narendra Ojha, Noelia Otero, Martijn Schaap, Katarina Sindelarova, Annemiek I. Stegehuis, Yelva Roustan, Robert Vautard, Erik van Meijgaard, Marta Garcia Vivanco, and Peter Wind
Geosci. Model Dev., 10, 3255–3276, https://doi.org/10.5194/gmd-10-3255-2017, https://doi.org/10.5194/gmd-10-3255-2017, 2017
Short summary
Short summary
The EURODELTA-Trends numerical experiment has been designed to assess the capability of chemistry-transport models to capture the evolution of surface air quality over the 1990–2010 period in Europe. It also includes sensitivity experiments in order to analyse the relative contribution of (i) emission changes, (ii) meteorological variability, and (iii) boundary conditions to air quality trends. The article is a detailed presentation of the experiment design and participating models.
Birthe M. Steensen, Michael Schulz, Peter Wind, Álvaro M. Valdebenito, and Hilde Fagerli
Geosci. Model Dev., 10, 1927–1943, https://doi.org/10.5194/gmd-10-1927-2017, https://doi.org/10.5194/gmd-10-1927-2017, 2017
Short summary
Short summary
The operational emergency version of the EMEP MSC-W model for dispersion calculations of volcanic SO2 and ash is described. Additions and changes to the standard EMEP MSC-W are presented. Grid resolution dependencies for meteorological data and numerical diffusion are studied by investigating model results driven by ensemble meteorological data for volcanic SO2 emissions. The vertical ash layer sensitivity on gravitational settling is evaluated by comparing model results to lidar observations.
J. Kukkonen, M. Karl, M. P. Keuken, H. A. C. Denier van der Gon, B. R. Denby, V. Singh, J. Douros, A. Manders, Z. Samaras, N. Moussiopoulos, S. Jonkers, M. Aarnio, A. Karppinen, L. Kangas, S. Lützenkirchen, T. Petäjä, I. Vouitsis, and R. S. Sokhi
Geosci. Model Dev., 9, 451–478, https://doi.org/10.5194/gmd-9-451-2016, https://doi.org/10.5194/gmd-9-451-2016, 2016
Short summary
Short summary
For analyzing the health effects of particulate matter, it is necessary to consider not only the mass of particles, but also their sizes and composition. A simple measure for the former is the number concentration of particles. We present particle number concentrations in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008, based mainly on modelling. The concentrations of PN were mostly influenced by the emissions from local vehicular traffic.
V. Marécal, V.-H. Peuch, C. Andersson, S. Andersson, J. Arteta, M. Beekmann, A. Benedictow, R. Bergström, B. Bessagnet, A. Cansado, F. Chéroux, A. Colette, A. Coman, R. L. Curier, H. A. C. Denier van der Gon, A. Drouin, H. Elbern, E. Emili, R. J. Engelen, H. J. Eskes, G. Foret, E. Friese, M. Gauss, C. Giannaros, J. Guth, M. Joly, E. Jaumouillé, B. Josse, N. Kadygrov, J. W. Kaiser, K. Krajsek, J. Kuenen, U. Kumar, N. Liora, E. Lopez, L. Malherbe, I. Martinez, D. Melas, F. Meleux, L. Menut, P. Moinat, T. Morales, J. Parmentier, A. Piacentini, M. Plu, A. Poupkou, S. Queguiner, L. Robertson, L. Rouïl, M. Schaap, A. Segers, M. Sofiev, L. Tarasson, M. Thomas, R. Timmermans, Á. Valdebenito, P. van Velthoven, R. van Versendaal, J. Vira, and A. Ung
Geosci. Model Dev., 8, 2777–2813, https://doi.org/10.5194/gmd-8-2777-2015, https://doi.org/10.5194/gmd-8-2777-2015, 2015
Short summary
Short summary
This paper describes the air quality forecasting system over Europe put in place in the Monitoring Atmospheric Composition and Climate projects. It provides daily and 4-day forecasts and analyses for the previous day for major gas and particulate pollutants and their main precursors. These products are based on a multi-model approach using seven state-of-the-art models developed in Europe. An evaluation of the performance of the system is discussed in the paper.
J. E. Jonson, J. P. Jalkanen, L. Johansson, M. Gauss, and H. A. C. Denier van der Gon
Atmos. Chem. Phys., 15, 783–798, https://doi.org/10.5194/acp-15-783-2015, https://doi.org/10.5194/acp-15-783-2015, 2015
Short summary
Short summary
In order to assess the effects of ship emissions in and around the
Baltic Sea and the North Sea, regional model calculations are made
with the EMEP air pollution model. Ship emissions are based on
accurate ship positioning data. The effects on depositions and air
pollution and the resulting number of years of life lost (YOLLs)
are calculated by comparing model calculations with and without
ship emissions, with ship emissions before and after 2010, and for future
projections.
D. Simpson, C. Andersson, J.H. Christensen, M. Engardt, C. Geels, A. Nyiri, M. Posch, J. Soares, M. Sofiev, P. Wind, and J. Langner
Atmos. Chem. Phys., 14, 6995–7017, https://doi.org/10.5194/acp-14-6995-2014, https://doi.org/10.5194/acp-14-6995-2014, 2014
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
Ø. Hodnebrog, T. K. Berntsen, O. Dessens, M. Gauss, V. Grewe, I. S. A. Isaksen, B. Koffi, G. Myhre, D. Olivié, M. J. Prather, F. Stordal, S. Szopa, Q. Tang, P. van Velthoven, and J. E. Williams
Atmos. Chem. Phys., 12, 12211–12225, https://doi.org/10.5194/acp-12-12211-2012, https://doi.org/10.5194/acp-12-12211-2012, 2012
Related subject area
Atmospheric sciences
A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1)
OpenIFS@home version 1: a citizen science project for ensemble weather and climate forecasting
Regional CO2 inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2
Evaluation of the dynamic core of the PALM model system 6.0 in a neutrally stratified urban environment: comparison between LES and wind-tunnel experiments
Implementing a sectional scheme for early aerosol growth from new particle formation in the Norwegian Earth System Model v2: comparison to observations and climate impacts
Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)
Simulation of O3 and NOx in São Paulo street urban canyons with VEIN (v0.2.2) and MUNICH (v1.0)
A case study of wind farm effects using two wake parameterizations in the Weather Research and Forecasting (WRF) model (V3.7.1) in the presence of low-level jets
Radiative Transfer Model 3.0 integrated into the PALM model system 6.0
Development and evaluation of CO2 transport in MPAS-A v6.3
Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019
A new gas absorption optical depth parameterisation for RTTOV version 13
The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation
Development and evaluation of spectral nudging strategy for the simulation of summer precipitation over the Tibetan Plateau using WRF (v4.0)
Combining homogeneous and heterogeneous chemistry to model inorganic compound concentrations in indoor environments: the H2I model (v1.0)
Interpol-IAGOS: a new method for assessing long-term chemistry–climate simulations in the UTLS based on IAGOS data, and its application to the MOCAGE CCMI REF-C1SD simulation
The Environment and Climate Change Canada Carbon Assimilation System (EC-CAS v1.0): demonstration with simulated CO observations
WRF4PALM v1.0: a mesoscale dynamical driver for the microscale PALM model system 6.0
pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python
Comparison of three aerosol representations of NHM-Chem (v1.0) for the simulations of air quality and climate-relevant variables
JlBox v1.1: a Julia-based multi-phase atmospheric chemistry box model
A new Lagrangian in-time particle simulation module (Itpas v1) for atmospheric particle dispersion
Effects of black carbon morphology on brown carbon absorption estimation: from numerical aspects
Simulation of the evolution of biomass burning organic aerosol with different volatility basis set schemes in PMCAMx-SRv1.0
Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0
Evaluation of ECMWF IFS-AER (CAMS) operational forecasts during cycle 41r1–46r1 with calibrated ceilometer profiles over Germany
Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50
Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates
MLAir (v1.0) – a tool to enable fast and flexible machine learning on air data time series
snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
On the suitability of second-order accurate finite-volume solvers for the simulation of atmospheric boundary layer flow
An urban large-eddy-simulation-based dispersion model for marginal grid resolutions: CAIRDIO v1.0
Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation for the COSMO model (v5.07)
On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2
Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model
Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications
The Vertical City Weather Generator (VCWG v1.3.2)
A zero-dimensional view of atmospheric degradation of levoglucosan (LEVCHEM_v1) using numerical chamber simulations
WRF-GC (v2.0): online two-way coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.7.2) for modeling regional atmospheric chemistry-meteorology interactions
The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates
Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1
Development of WRF/CUACE v1.0 model and its preliminary application in simulating air quality in China
PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers
Surface representation impacts on turbulent heat fluxes in WRF (v.4.1.3)
A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54
Investigating the importance of sub-grid particle formation in point source plumes over eastern China using IAP-AACM with a sub-grid parameterization
Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module
FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 2: Model validation
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
Short summary
Short summary
A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
Sarah Sparrow, Andrew Bowery, Glenn D. Carver, Marcus O. Köhler, Pirkka Ollinaho, Florian Pappenberger, David Wallom, and Antje Weisheimer
Geosci. Model Dev., 14, 3473–3486, https://doi.org/10.5194/gmd-14-3473-2021, https://doi.org/10.5194/gmd-14-3473-2021, 2021
Short summary
Short summary
This paper describes how the research version of the European Centre for Medium-Range Weather Forecasts’ Integrated Forecast System is combined with climateprediction.net’s public volunteer computing resource to develop OpenIFS@home. Thousands of volunteer personal computers simulated slightly different realizations of Tropical Cyclone Karl to demonstrate the performance of the large-ensemble forecast. OpenIFS@Home offers researchers a new tool to study weather forecasts and related questions.
Guillaume Monteil and Marko Scholze
Geosci. Model Dev., 14, 3383–3406, https://doi.org/10.5194/gmd-14-3383-2021, https://doi.org/10.5194/gmd-14-3383-2021, 2021
Short summary
Short summary
LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to perform regional atmospheric CO2 inversions. The inversions rely on coupling the regional transport model FLEXPART and the global transport model TM5. The paper presents the modeling setup and some first results, and it introduces the LUMIA Python package as a toolbox for inversions beyond the use case presented in the paper.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
Short summary
Short summary
The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
Tobias Gronemeier, Kerstin Surm, Frank Harms, Bernd Leitl, Björn Maronga, and Siegfried Raasch
Geosci. Model Dev., 14, 3317–3333, https://doi.org/10.5194/gmd-14-3317-2021, https://doi.org/10.5194/gmd-14-3317-2021, 2021
Short summary
Short summary
We demonstrate the capability of the PALM model system version 6.0 to simulate urban boundary layers. The studied situation includes a real-world building setup of the HafenCity area in Hamburg, Germany. We evaluate the simulation results against wind-tunnel measurements utilizing PALM's virtual measurement module. The comparison reveals an overall high agreement between simulation results and wind-tunnel measurements including mean wind speed and direction as well as turbulence statistics.
Sara M. Blichner, Moa K. Sporre, Risto Makkonen, and Terje K. Berntsen
Geosci. Model Dev., 14, 3335–3359, https://doi.org/10.5194/gmd-14-3335-2021, https://doi.org/10.5194/gmd-14-3335-2021, 2021
Short summary
Short summary
Aerosol–cloud interactions are the largest contributor to climate forcing uncertainty. In this study we combine two common approaches to aerosol representation in global models: a sectional scheme, which is closer to first principals, for the smallest particles forming in the atmosphere and a log-modal scheme, which is faster, for the larger particles. With this approach, we improve the aerosol representation compared to observations, while only increasing the computational cost by 15 %.
Timothy Glotfelty, Diana Ramírez-Mejía, Jared Bowden, Adrian Ghilardi, and J. Jason West
Geosci. Model Dev., 14, 3215–3249, https://doi.org/10.5194/gmd-14-3215-2021, https://doi.org/10.5194/gmd-14-3215-2021, 2021
Short summary
Short summary
Land use and land cover change is a major contributor to climate change in Africa. Here we document deficiencies in how a weather model represents the land surface of Africa and how we modify a common land surface model to overcome these deficiencies. Our tests reveal that the default weather model does not accurately predict and transition the properties of different African biomes and growing cycles. This paper demonstrates that our modified model addresses these limitations.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
Short summary
Short summary
The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
Xiaoli G. Larsén and Jana Fischereit
Geosci. Model Dev., 14, 3141–3158, https://doi.org/10.5194/gmd-14-3141-2021, https://doi.org/10.5194/gmd-14-3141-2021, 2021
Short summary
Short summary
For the first time, turbulent kinetic energy (TKE) calculated from the explicit wake parameterization (EWP) in WRF is examined using high-frequency measurements over a wind farm and compared with that calculated using the Fitch et al. (2012) scheme. We examined the effect of farm-induced TKE advection in connection with the Fitch scheme. Through a case study with a low-level jet (LLJ), we analyzed the key features of LLJs and raised the issue of interaction between wind farms and LLJs.
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
Short summary
Short summary
The adverse effects of an urban environment, e.g. heat stress and air pollution, pose a risk to health and well-being. Precise modelling of the urban climate is crucial to mitigate these effects. Conventional atmospheric models are inadequate for modelling the complex structures of the urban environment; in particular, they lack a 3-D model of radiation and its interaction with surfaces and the plant canopy. The new RTM simulates these processes within the PALM-4U urban climate model.
Tao Zheng, Sha Feng, Kenneth J. Davis, Sandip Pal, and Josep-Anton Morguí
Geosci. Model Dev., 14, 3037–3066, https://doi.org/10.5194/gmd-14-3037-2021, https://doi.org/10.5194/gmd-14-3037-2021, 2021
Short summary
Short summary
Carbon dioxide is the most important greenhouse gas. We develop the numerical model that represents carbon dioxide transport in the atmosphere. This model development is based on the MPAS model, which has a variable-resolution capability. The purpose of developing carbon dioxide transport in MPAS is to allow for high-resolution transport model simulation that is not limited by the lateral boundaries. It will also form the base for a future development of MPAS-based carbon inversion system.
Audrey Fortems-Cheiney, Isabelle Pison, Grégoire Broquet, Gaëlle Dufour, Antoine Berchet, Elise Potier, Adriana Coman, Guillaume Siour, and Lorenzo Costantino
Geosci. Model Dev., 14, 2939–2957, https://doi.org/10.5194/gmd-14-2939-2021, https://doi.org/10.5194/gmd-14-2939-2021, 2021
Short summary
Short summary
Up-to-date and accurate emission inventories for air pollutants are essential for understanding their role in the formation of tropospheric ozone and particulate matter, for anticipating pollution peaks and for identifying the key drivers that could help mitigate their emissions. Complementarily with bottom-up inventories, the system described here aims at updating and improving the knowledge on the high spatiotemporal variability of emissions of air pollutants.
James Hocking, Jérôme Vidot, Pascal Brunel, Pascale Roquet, Bruna Silveira, Emma Turner, and Cristina Lupu
Geosci. Model Dev., 14, 2899–2915, https://doi.org/10.5194/gmd-14-2899-2021, https://doi.org/10.5194/gmd-14-2899-2021, 2021
Short summary
Short summary
RTTOV is a fast radiative transfer model for simulating passive satellite-based observations at visible, infrared, and microwave wavelengths. A core part of the model is a parameterisation of the absorption of radiation by the various gases present in the atmosphere. We present a new parameterisation that performs well compared to the existing one in terms of accuracy and can be developed further more easily. The new parameterisation is implemented in the latest release, RTTOV v13.0.
K. Wyat Appel, Jesse O. Bash, Kathleen M. Fahey, Kristen M. Foley, Robert C. Gilliam, Christian Hogrefe, William T. Hutzell, Daiwen Kang, Rohit Mathur, Benjamin N. Murphy, Sergey L. Napelenok, Christopher G. Nolte, Jonathan E. Pleim, George A. Pouliot, Havala O. T. Pye, Limei Ran, Shawn J. Roselle, Golam Sarwar, Donna B. Schwede, Fahim I. Sidi, Tanya L. Spero, and David C. Wong
Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, https://doi.org/10.5194/gmd-14-2867-2021, 2021
Short summary
Short summary
This paper details the scientific updates in the recently released CMAQ version 5.3 (and v5.3.1) and also includes operational and diagnostic evaluations of CMAQv5.3.1 against observations and the previous version of the CMAQ (v5.2.1). This work was done to improve the underlying science in CMAQ. This article is used to inform the CMAQ modeling community of the updates to the modeling system and the expected change in model performance from these updates (versus the previous model version).
Ziyu Huang, Lei Zhong, Yaoming Ma, and Yunfei Fu
Geosci. Model Dev., 14, 2827–2841, https://doi.org/10.5194/gmd-14-2827-2021, https://doi.org/10.5194/gmd-14-2827-2021, 2021
Short summary
Short summary
Spectral nudging is an effective dynamical downscaling method used to improve precipitation simulations of regional climate models (RCMs). However, the biases of the driving fields over the Tibetan Plateau (TP) would possibly introduce extra biases when spectral nudging is applied. The results show that the precipitation simulations were significantly improved when limiting the application of spectral nudging toward the potential temperature and water vapor mixing ratio over the TP.
Eve-Agnès Fiorentino, Henri Wortham, and Karine Sartelet
Geosci. Model Dev., 14, 2747–2780, https://doi.org/10.5194/gmd-14-2747-2021, https://doi.org/10.5194/gmd-14-2747-2021, 2021
Short summary
Short summary
Indoor air quality (IAQ) is strongly influenced by reactivity with surfaces, which is called heterogeneous reactivity. To date, this reactivity is barely integrated into numerical models due to the strong uncertainties it is subjected to. In this work, an open-source IAQ model, called the H2I model, is developed to consider both gas-phase and heterogeneous reactivity and simulate indoor concentrations of inorganic compounds.
Yann Cohen, Virginie Marécal, Béatrice Josse, and Valérie Thouret
Geosci. Model Dev., 14, 2659–2689, https://doi.org/10.5194/gmd-14-2659-2021, https://doi.org/10.5194/gmd-14-2659-2021, 2021
Short summary
Short summary
Assessing long-term chemistry–climate simulations with in situ and frequent observations near the tropopause is possible with the IAGOS commercial aircraft data set. This study presents a method that distributes the IAGOS data (ozone and CO) on a monthly model grid, limiting the impact of resolution for the evaluation of the modelled chemical fields. We applied it to the CCMI REF-C1SD simulation from the MOCAGE CTM and notably highlighted well-reproduced O3 behaviour in the lower stratosphere.
Vikram Khade, Saroja M. Polavarapu, Michael Neish, Pieter L. Houtekamer, Dylan B. A. Jones, Seung-Jong Baek, Tai-Long He, and Sylvie Gravel
Geosci. Model Dev., 14, 2525–2544, https://doi.org/10.5194/gmd-14-2525-2021, https://doi.org/10.5194/gmd-14-2525-2021, 2021
Short summary
Short summary
A new modeling system has been developed at Environment and Climate Change Canada to ingest observations of carbon monoxide (CO) into a coupled weather and constituent transport model. We show that accounting for the uncertainty in surface flux leads to a better estimate of CO distributions. The benefit of assimilating observations from different simulated networks varies with region. This is the first step towards developing a state and flux estimation system for greenhouse gases.
Dongqi Lin, Basit Khan, Marwan Katurji, Leroy Bird, Ricardo Faria, and Laura E. Revell
Geosci. Model Dev., 14, 2503–2524, https://doi.org/10.5194/gmd-14-2503-2021, https://doi.org/10.5194/gmd-14-2503-2021, 2021
Short summary
Short summary
We present an open-source toolbox WRF4PALM, which enables weather dynamics simulation within urban landscapes. WRF4PALM passes meteorological information from the popular Weather Research and Forecasting (WRF) model to the turbulence-resolving PALM model system 6.0. WRF4PALM can potentially extend the use of WRF and PALM with realistic boundary conditions to any part of the world. WRF4PALM will help study air pollution dispersion, wind energy prospecting, and high-impact wind forecasting.
Daniel M. Gilford
Geosci. Model Dev., 14, 2351–2369, https://doi.org/10.5194/gmd-14-2351-2021, https://doi.org/10.5194/gmd-14-2351-2021, 2021
Short summary
Short summary
Potential intensity (PI) is a tropical cyclone's maximum speed limit given by modeling the storm as a thermal heat engine. pyPI is the first software package fully documenting the PI algorithm and translating it to Python. This study details/validates the underlying PI model and demonstrates its use in tropical cyclone intensity research. pyPI supports open science and transparency in the tropical meteorological community and is ideally suited for ongoing community development and improvement.
Mizuo Kajino, Makoto Deushi, Tsuyoshi Thomas Sekiyama, Naga Oshima, Keiya Yumimoto, Taichu Yasumichi Tanaka, Joseph Ching, Akihiro Hashimoto, Tetsuya Yamamoto, Masaaki Ikegami, Akane Kamada, Makoto Miyashita, Yayoi Inomata, Shin-ichiro Shima, Pradeep Khatri, Atsushi Shimizu, Hitoshi Irie, Kouji Adachi, Yuji Zaizen, Yasuhito Igarashi, Hiromasa Ueda, Takashi Maki, and Masao Mikami
Geosci. Model Dev., 14, 2235–2264, https://doi.org/10.5194/gmd-14-2235-2021, https://doi.org/10.5194/gmd-14-2235-2021, 2021
Short summary
Short summary
This study compares performance of aerosol representation methods of the Japan Meteorological Agency's regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). It indicates separate treatment of sea salt and dust in coarse mode and that of light-absorptive and non-absorptive particles in fine mode could provide accurate assessments on aerosol feedback processes.
Langwen Huang and David Topping
Geosci. Model Dev., 14, 2187–2203, https://doi.org/10.5194/gmd-14-2187-2021, https://doi.org/10.5194/gmd-14-2187-2021, 2021
Short summary
Short summary
As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. With this in mind we present JlBox v1.1, written in Julia.
Matthias Faust, Ralf Wolke, Steffen Münch, Roger Funk, and Kerstin Schepanski
Geosci. Model Dev., 14, 2205–2220, https://doi.org/10.5194/gmd-14-2205-2021, https://doi.org/10.5194/gmd-14-2205-2021, 2021
Short summary
Short summary
Trajectory dispersion models are powerful and intuitive tools for tracing air pollution through the atmosphere. But the turbulent nature of the atmospheric boundary layer makes it challenging to provide accurate predictions near the surface. To overcome this, we propose an approach using wind and turbulence information at high temporal resolution. Finally, we demonstrate the strength of our approach in a case study on dust emissions from agriculture.
Jie Luo, Yongming Zhang, and Qixing Zhang
Geosci. Model Dev., 14, 2113–2126, https://doi.org/10.5194/gmd-14-2113-2021, https://doi.org/10.5194/gmd-14-2113-2021, 2021
Short summary
Short summary
In this work, we developed a numerical method to investigate the effects of black carbon (BC) morphology on the estimation of brown carbon (BrC) absorption using the absorption Ångström exponent (AAE) method. We found that BC morphologies have significant impacts on the estimated BrC absorptions. Moreover, we have demonstrated under what conditions the AAE methods can provide good or bad estimations and explored the reasons for why the good or bad estimations were caused.
Georgia N. Theodoritsi, Giancarlo Ciarelli, and Spyros N. Pandis
Geosci. Model Dev., 14, 2041–2055, https://doi.org/10.5194/gmd-14-2041-2021, https://doi.org/10.5194/gmd-14-2041-2021, 2021
Short summary
Short summary
Two schemes based on the volatility basis set were used for the simulation of biomass burning organic aerosol (bbOA) in the continental US. The first is the default scheme of the PMCAMx-SR model, and the second is a recently developed scheme based on laboratory experiments. The alternative bbOA scheme predicts much higher concentrations. The default scheme performed better during summer and fall, while the alternative scheme was a little better during spring.
Dana L. McGuffin, Yuanlong Huang, Richard C. Flagan, Tuukka Petäjä, B. Erik Ydstie, and Peter J. Adams
Geosci. Model Dev., 14, 1821–1839, https://doi.org/10.5194/gmd-14-1821-2021, https://doi.org/10.5194/gmd-14-1821-2021, 2021
Short summary
Short summary
Atmospheric particle formation, emissions, and growth process rates are significant sources of uncertainty in predicting climate change. We aim to reduce that uncertainty by using measurements from several ground-based sites across Europe. We developed an estimation technique to adapt the governing process rates so model–measurement bias decays. The estimation framework developed has potential to improve model predictions while providing insight into the underlying atmospheric particle physics.
Harald Flentje, Ina Mattis, Zak Kipling, Samuel Rémy, and Werner Thomas
Geosci. Model Dev., 14, 1721–1751, https://doi.org/10.5194/gmd-14-1721-2021, https://doi.org/10.5194/gmd-14-1721-2021, 2021
Short summary
Short summary
Atmospheric aerosols crucially impact air quality, climate and weather. Thus, global model forecasts of atmospheric constituents are published daily on the ECMWF website and are regularly verified by the CAMS service team. The IFS-AER model is largely able to reproduce observed 3-D distributions of the important particle types over Germany. The particle concentration is mostly captured within several tens of percent, but quantification of some specific processes still remains a challenge.
Jianhui Jiang, Imad El Haddad, Sebnem Aksoyoglu, Giulia Stefenelli, Amelie Bertrand, Nicolas Marchand, Francesco Canonaco, Jean-Eudes Petit, Olivier Favez, Stefania Gilardoni, Urs Baltensperger, and André S. H. Prévôt
Geosci. Model Dev., 14, 1681–1697, https://doi.org/10.5194/gmd-14-1681-2021, https://doi.org/10.5194/gmd-14-1681-2021, 2021
Short summary
Short summary
We developed a box model with a volatility basis set to simulate organic aerosol (OA) from biomass burning and optimized the vapor-wall-loss-corrected OA yields with a genetic algorithm. The optimized parameterizations were then implemented in the air quality model CAMx v6.5. Comparisons with ambient measurements indicate that the vapor-wall-loss-corrected parameterization effectively improves the model performance in predicting OA, which reduced the mean fractional bias from −72.9 % to −1.6 %.
Oliver Branch, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, Michael Weston, Josipa Milovac, and Volker Wulfmeyer
Geosci. Model Dev., 14, 1615–1637, https://doi.org/10.5194/gmd-14-1615-2021, https://doi.org/10.5194/gmd-14-1615-2021, 2021
Short summary
Short summary
Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates where extreme events like heat waves, flash floods, and dust storms are becoming more severe. This study employs a high-resolution simulation with the WRF-NOAHMP model, and the output is compared with seasonal observation data from 50 weather stations. This type of verification is vital to identify model deficiencies and improve forecasting systems for arid regions.
Lukas Hubert Leufen, Felix Kleinert, and Martin G. Schultz
Geosci. Model Dev., 14, 1553–1574, https://doi.org/10.5194/gmd-14-1553-2021, https://doi.org/10.5194/gmd-14-1553-2021, 2021
Short summary
Short summary
MLAir provides a coherent end-to-end structure for a typical time series analysis workflow using machine learning (ML). MLAir is adaptable to a wide range of ML use cases, focusing in particular on deep learning. The user has a free hand with the ML model itself and can select from different methods during preprocessing, training, and postprocessing. MLAir offers tools to track the experiment conduction, documents necessary ML parameters, and creates a variety of publication-ready plots.
Davide Ori, Leonie von Terzi, Markus Karrer, and Stefan Kneifel
Geosci. Model Dev., 14, 1511–1531, https://doi.org/10.5194/gmd-14-1511-2021, https://doi.org/10.5194/gmd-14-1511-2021, 2021
Short summary
Short summary
Snowflakes have very complex shapes, and modeling their properties requires vast computing power. We produced a large number of realistic snowflakes and modeled their average properties by leveraging their fractal structure. Our approach allows modeling the properties of big ensembles of snowflakes, taking into account their natural variability, at a much lower cost. This enables the usage of remote sensing instruments, such as radars, to monitor the evolution of clouds and precipitation.
Jaydeep Singh, Narendra Singh, Narendra Ojha, Amit Sharma, Andrea Pozzer, Nadimpally Kiran Kumar, Kunjukrishnapillai Rajeev, Sachin S. Gunthe, and V. Rao Kotamarthi
Geosci. Model Dev., 14, 1427–1443, https://doi.org/10.5194/gmd-14-1427-2021, https://doi.org/10.5194/gmd-14-1427-2021, 2021
Short summary
Short summary
Atmospheric models often have limitations in simulating the geographically complex and climatically important central Himalayan region. In this direction, we have performed regional modeling at high resolutions to improve the simulation of meteorology and dynamics through a better representation of the topography. The study has implications for further model applications to investigate the effects of anthropogenic pressure over the Himalaya.
Beatrice Giacomini and Marco G. Giometto
Geosci. Model Dev., 14, 1409–1426, https://doi.org/10.5194/gmd-14-1409-2021, https://doi.org/10.5194/gmd-14-1409-2021, 2021
Short summary
Short summary
The present work evaluates the suitability of an important class of second-order finite-volume solvers for the large-eddy simulation of atmospheric boundary- layer flows. Results show that these solvers do not capture the dominant mechanisms responsible for momentum transport in boundary layers, leading to a misprediction of relevant flow statistics and to an enhanced sensitivity of the solution to variations in grid resolution.
Michael Weger, Oswald Knoth, and Bernd Heinold
Geosci. Model Dev., 14, 1469–1492, https://doi.org/10.5194/gmd-14-1469-2021, https://doi.org/10.5194/gmd-14-1469-2021, 2021
Short summary
Short summary
A new numerical air-quality transport model for cities is presented, in which buildings are described diffusively. The used diffusive-obstacles approach helps to reduce the computational costs for high-resolution simulations as the grid spacing can be more coarse than in traditional approaches. The research which led to this model development was primarily motivated by the need for a computationally feasible downscaling tool for urban wind and pollution fields from meteorological model output.
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021, https://doi.org/10.5194/gmd-14-1295-2021, 2021
Short summary
Short summary
A new integrated mass-flux adjustment filter is introduced and examined with an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduces the accuracy of background and analysis states; however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it successfully diminishes the imbalance in the analysis considerably and improves the forecasts.
Pieter De Meutter, Ian Hoffman, and Kurt Ungar
Geosci. Model Dev., 14, 1237–1252, https://doi.org/10.5194/gmd-14-1237-2021, https://doi.org/10.5194/gmd-14-1237-2021, 2021
Short summary
Short summary
Inverse atmospheric transport modelling is an important tool in several disciplines. However, the specification of atmospheric transport model error remains challenging. In this paper, we employ a state-of-the-art ensemble technique combined with a state-of-the-art Bayesian inference algorithm to infer point sources. Our research helps to fill the gap in our understanding of model error in the context of inverse atmospheric transport modelling.
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236, https://doi.org/10.5194/gmd-14-1219-2021, https://doi.org/10.5194/gmd-14-1219-2021, 2021
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
Short summary
Short summary
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.
Mohsen Moradi, Benjamin Dyer, Amir Nazem, Manoj K. Nambiar, M. Rafsan Nahian, Bruno Bueno, Chris Mackey, Saeran Vasanthakumar, Negin Nazarian, E. Scott Krayenhoff, Leslie K. Norford, and Amir A. Aliabadi
Geosci. Model Dev., 14, 961–984, https://doi.org/10.5194/gmd-14-961-2021, https://doi.org/10.5194/gmd-14-961-2021, 2021
Short summary
Short summary
The Vertical City Weather Generator (VCWG) is an urban microclimate model developed to predict temporal and vertical variation of potential temperature, wind speed, and specific humidity. VCWG is forced by climate variables at a nearby rural site and coupled to radiation and building energy models. VCWG is evaluated against field observations of the BUBBLE campaign. It is run under exploration mode to assess its performance given urban characteristics, seasonal variations, and climate zones.
Loredana G. Suciu, Robert J. Griffin, and Caroline A. Masiello
Geosci. Model Dev., 14, 907–921, https://doi.org/10.5194/gmd-14-907-2021, https://doi.org/10.5194/gmd-14-907-2021, 2021
Short summary
Short summary
Understanding the atmospheric degradation of biomass burning tracers such as levoglucosan is essential to decreasing uncertainties in the role of biomass burning in air quality, carbon cycling and paleoclimate. Using a 0-D modeling approach and numerical chamber simulations, we found that the multiphase atmospheric degradation of levoglucosan occurs over timescales of hours to days, can form secondary organic aerosols and affects other key tropospheric gases, such as ozone.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, and Qi Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-441, https://doi.org/10.5194/gmd-2020-441, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol-radiation interactions and aerosol-cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology-atmospheric chemistry interactions.
Chihiro Kodama, Tomoki Ohno, Tatsuya Seiki, Hisashi Yashiro, Akira T. Noda, Masuo Nakano, Yohei Yamada, Woosub Roh, Masaki Satoh, Tomoko Nitta, Daisuke Goto, Hiroaki Miura, Tomoe Nasuno, Tomoki Miyakawa, Ying-Wen Chen, and Masato Sugi
Geosci. Model Dev., 14, 795–820, https://doi.org/10.5194/gmd-14-795-2021, https://doi.org/10.5194/gmd-14-795-2021, 2021
Short summary
Short summary
This paper describes the latest stable version of NICAM, a global atmospheric model, developed for high-resolution climate simulations toward the IPCC Assessment Report. Our model explicitly treats convection, clouds, and precipitation and could reduce the uncertainty of climate change projection. A series of test simulations demonstrated improvements (e.g., high cloud) and issues (e.g., low cloud, precipitation pattern), suggesting further necessity for model improvement and higher resolutions.
Jingyu Wang, Jiwen Fan, Robert A. Houze Jr., Stella R. Brodzik, Kai Zhang, Guang J. Zhang, and Po-Lun Ma
Geosci. Model Dev., 14, 719–734, https://doi.org/10.5194/gmd-14-719-2021, https://doi.org/10.5194/gmd-14-719-2021, 2021
Short summary
Short summary
This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
Lei Zhang, Sunling Gong, Tianliang Zhao, Chunhong Zhou, Yuesi Wang, Jiawei Li, Dongsheng Ji, Jianjun He, Hongli Liu, Ke Gui, Xiaomei Guo, Jinhui Gao, Yunpeng Shan, Hong Wang, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 14, 703–718, https://doi.org/10.5194/gmd-14-703-2021, https://doi.org/10.5194/gmd-14-703-2021, 2021
Short summary
Short summary
Development of chemical transport models with advanced physics and chemical schemes is important for improving air-quality forecasts. This study develops the chemical module CUACE by updating with a new particle dry deposition scheme and adding heterogenous chemical reactions and couples it with the WRF model. The coupled model (WRF/CUACE) was able to capture well the variations of PM2.5, O3, NO2, and secondary inorganic aerosols in eastern China.
Simon Patrick O'Meara, Shuxuan Xu, David Topping, M. Rami Alfarra, Gerard Capes, Douglas Lowe, Yunqi Shao, and Gordon McFiggans
Geosci. Model Dev., 14, 675–702, https://doi.org/10.5194/gmd-14-675-2021, https://doi.org/10.5194/gmd-14-675-2021, 2021
Short summary
Short summary
User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.
Carlos Román-Cascón, Marie Lothon, Fabienne Lohou, Oscar Hartogensis, Jordi Vila-Guerau de Arellano, David Pino, Carlos Yagüe, and Eric R. Pardyjak
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-371, https://doi.org/10.5194/gmd-2020-371, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
The type of vegetation (or land cover) and its status influence the heat and water transfers between the surface and the air, affecting the processes that develop in the atmosphere at different (but connected) spatiotemporal scales. In this work, we investigate how these transfers are affected by the way the surface is represented in a widely used weather model. The results encourage including realistic high-resolution and updated land-cover databases in models to improve their predictions.
Tamara Emmerichs, Astrid Kerkweg, Huug Ouwersloot, Silvano Fares, Ivan Mammarella, and Domenico Taraborrelli
Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, https://doi.org/10.5194/gmd-14-495-2021, 2021
Short summary
Short summary
Dry deposition to vegetation is a major sink of ground-level ozone. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for global tropospheric ozone. We extended the current model parameterization with a relevant pathway and important meteorological adjustment factors. The comparison with measurements shows that this enables a more realistic model representation of ozone dry deposition velocity. Globally, annual dry deposition loss increases.
Ying Wei, Xueshun Chen, Huansheng Chen, Yele Sun, Wenyi Yang, Huiyun Du, Qizhong Wu, Dan Chen, Xiujuan Zhao, Jie Li, and Zifa Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-430, https://doi.org/10.5194/gmd-2020-430, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
The sub-grid particle formation (SGPF) in plume plays an important role in air pollution and climate effect. We coupled a SGPF scheme into a chemical transport model with aerosol microphysics module and applied it to investigate the SGPF impact over China. The scheme clearly improved the model performance in simulating aerosol components and particle number at typical sites influenced by point sources. The results indicate the significant effects of SGPF on aerosol particles in industrial areas.
Alexander Ukhov, Ravan Ahmadov, Georg Grell, and Georgiy Stenchikov
Geosci. Model Dev., 14, 473–493, https://doi.org/10.5194/gmd-14-473-2021, https://doi.org/10.5194/gmd-14-473-2021, 2021
Short summary
Short summary
We discuss and evaluate the effects of inconsistencies found in the WRF-Chem code when using the GOCART module. First, PM surface concentrations were miscalculated. Second, dust optical depth was underestimated by 25 %–30 %. Third, an inconsistency in the process of gravitational settling led to the overestimation of dust column loadings by 4 %–6 %, PM10 by 2 %–4 %, and the rate of gravitational dust settling by 5 %–10 %. We also presented diagnostics that can be used to estimate these effects.
Andrew T. Prata, Leonardo Mingari, Arnau Folch, Giovanni Macedonio, and Antonio Costa
Geosci. Model Dev., 14, 409–436, https://doi.org/10.5194/gmd-14-409-2021, https://doi.org/10.5194/gmd-14-409-2021, 2021
Short summary
Short summary
This paper presents FALL3D-8.0, the latest version release of an open-source code with a track record of 15+ years and a growing number of users in the volcanological and atmospheric communities. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. This paper details new model applications and validation of FALL3D-8.0 using satellite, ground-deposit load and radionuclide data.
Cited articles
Andersson, C., Langner, J., and Bergström, R.: Interannual variation and
trends in air pollution over Europe due to climate variability during
1958–2001 simulated with a regional CTM coupled to the ERA40 reanalysis,
Tellus, 59B, 77–98, https://doi.org/10.1111/j.1600-0889.2006.00196.x, 2007.
Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., and Young, J. O.: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, 2017.
Bächlin, W., Bösinger, R.: Untersuchungen zu
Stickstoffdioxid-Konzentrationen, Los 1 Überprüfung der
Rombergformel, Ingenieurbüro Lohmeyer GmbH & Co. KG, Karlsruhe,
Projekt 60976-04-01, Stand: Dezember
2008, Gutachten im Auftrag von: Landesamt für Natur, Umwelt und
Verbraucherschutz Nordrhein–Westfalen,
Recklinghausen, 2008.
Benson, P.: A review of the development and application of the CALINE3 and 4
models, Atmos. Environ., 26B:3, 379–390, https://doi.org/10.1016/0957-1272(92)90013-I,
1992.
Benson, P.: CALINE4 – A dispersion model for predicting air pollutant
concentrations near roadways, FHWA/CA/TL-84/15, California Department of
Transportation, Sacramento, CA, available at: https://ntrl.ntis.gov/NTRL/dashboard/searchResults.xhtml?searchQuery=PB85211498 (last access: 8 December 2020), 1984.
Brandt, J., Christensen, J., Frohn, L., and Zlatev, Z.: Operational air
pollution forecast modelling using the THOR system, Phys. Chem. Earth, 26, 117–122,
https://doi.org/10.1016/S1464-1909(00)00227-6, 2001.
CAMS: Copernicus Atmosphere Modelling Service (CAMS), Air quality forecasts
Europe, available at: https://atmosphere.copernicus.eu/, last access: 8 December 2020.
Chaudhry, F. H. and Meroney, R. H.: Similarity theory of diffusion and the
observed vertical spread in the diabatic surface layer, Bound.-Lay.
Meteorol., 3, 405–415, https://doi.org/10.1007/BF01034984, 1973
Cimorelli, A. J., Perry, S. G., Venkatram, A., Weil, J. C., Pain, R. J., Wilson,
R. B., Lee, R. F., Peters, W. D., Brode, R. W., and Paumier, J. O.: AERMOD:
Description of model formulation, EPA-454/R-03-004, available at: http://www3.epa.gov/scram001/7thconf/aermod/aermod_mfd.pdf (last access: 8 December 2020),
2004.
Denby, B. R.: Guide on modelling Nitrogen Dioxide (NO2) for air quality
assessment and planning relevant to the European Air Quality Directive.
ETC/ACM Technical paper 2011/15, available at: https://www.eionet.europa.eu/etcs/etc-atni/products/etc-atni-reports/etcacm_tp_2011_15_fairmode_guide_modelling_no2 (last access: 8 December 2020), 2011.
Denby, B. R.: metno/uEMEP: uEMEPv5 (Version 5.0), Zenodo, https://doi.org/10.5281/zenodo.3756008, 2020a.
Denby, B. R.: uEMEP startup configuration and data file for GMD uEMEP model description publication [Data set], Zenodo, https://doi.org/10.5281/zenodo.3755573, 2020b.
ECMWF: ECMWF home page, available at: http://www.ecmwf.int, last access: 8 December 2020.
Garratt, J. R.: The Atmospheric Boundary Layer, Cambridge Univ. Press,
Cambridge, UK, 316 pp., 1994.
Golder, D.: Relations among stability parameters in the surface layer,
Bound.-Lay. Meteorol., 3, 47–58, https://doi.org/10.1007/BF00769106, 1972.
Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J.. Elguindi, N.,
Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse, C.,
Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere Monitoring
Service global and regional emissions (April 2019 version), Report April
2019 version, https://doi.org/10.24380/d0bn-kx16, 2019.
Green, A. E. S., Singhal, R. P., and Venkateswar, R.: Analytic extensions of the
gaussian plume model, JAPCA J. Air Waste Ma.,
30, 773–776, https://doi.org/10.1080/00022470.1980.10465108, 1980.
Gryning, S., Batchvarova, E., and Brümmer, B.: On the extension of the
wind profile over homogeneous terrain beyond the surface boundary layer,
Bound.-Lay. Meteorol., 124, 251–268,
https://doi.org/10.1007/s10546-007-9166-9 2007.
Hagman, R., Gjerstad, K. I., and Amundsen, A. H.: NO2-utslipp fra
kjøretøyparken i norske storbyer, TØI rapport 1168/2011:
Transportøkonomisk institutt, Oslo, available at:
https://www.toi.no/getfile.php?mmfileid=22618 (last access: 8 December 2020), 2011.
Hanna, S. R.: Lagrangian and Eulerian time-scale in the daytime boundary,
layer, J. Appl. Meteorol., 20, 242–249, 1981.
IFS: Documentation of the Integrated Forecasting System, ECMWF, available at: https://www.ecmwf.int/en/publications/ifs-documentation, last access: 8 December 2020.
Karamchandani, P., Lohman, K., and Seigneur, C.: Using a sub-grid scale
modeling approach to simulate the transport and fate of toxic air
pollutants, Environ. Fluid Mech., 9, 59–71, https://doi.org/10.1007/s10652-008-9097-0,
2009.
Karl, M., Walker, S.-E., Solberg, S., and Ramacher, M. O. P.: The Eulerian urban dispersion model EPISODE – Part 2: Extensions to the source dispersion and photochemistry for EPISODE–CityChem v1.2 and its application to the city of Hamburg, Geosci. Model Dev., 12, 3357–3399, https://doi.org/10.5194/gmd-12-3357-2019, 2019.
Kim, Y., Wu, Y., Seigneur, C., and Roustan, Y.: Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1.0) by coupling MUNICH (v1.0) and Polair3D (v1.8.1), Geosci. Model Dev., 11, 611–629, https://doi.org/10.5194/gmd-11-611-2018, 2018.
Kranenburg, R., Segers, A. J., Hendriks, C., and Schaap, M.: Source apportionment using LOTOS-EUROS: module description and evaluation, Geosci. Model Dev., 6, 721–733, https://doi.org/10.5194/gmd-6-721-2013, 2013.
Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.: TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976, https://doi.org/10.5194/acp-14-10963-2014, 2014.
Liu, X.,Godbole, A., Lu, C., Michal, G., and Venton, P.: Optimisation of
dispersion parameters of Gaussian plume model for CO2 dispersion,
Environ. Sci. Pollut. R., 22, 18288–18299,
https://doi.org/10.1007/s11356-015-5404-8, 2015.
Maiheu, B., Williams, M. L., Walton, H. A., Janssen, S., Blyth, L.,
Velderman, N., Lefebvre, W., Vanhulzel, M. and Beevers, S. D. Improved
Methodologies for NO2 Exposure Assessment in the EU, Vito Report no.
2017/RMA/R/1250, available at: http://ec.europa.eu/environment/air/publications/models.htm (last access: 8 December 2020), 2017.
Martin, D. O.: Comment on “The Change of Concentration Standard Deviations
with Distance”, JAPCA J. Air Waste Manage., 26,
145–147, https://doi.org/10.1080/00022470.1976.10470238, 1976.
Menut, L., Bessagnet, B., Khvorostyanov, D., Beekmann, M., Blond, N., Colette, A., Coll, I., Curci, G., Foret, G., Hodzic, A., Mailler, S., Meleux, F., Monge, J.-L., Pison, I., Siour, G., Turquety, S., Valari, M., Vautard, R., and Vivanco, M. G.: CHIMERE 2013: a model for regional atmospheric composition modelling, Geosci. Model Dev., 6, 981–1028, https://doi.org/10.5194/gmd-6-981-2013, 2013.
Müller, M., Homleid, M., Ivarsson, K., Køltzow, M. A., Lindskog, M.,
Midtbø, K. H., Andrae, U., Aspelien, T., Berggren, L., Bjørge, D., Dahlgren,
P., Kristiansen, J., Randriamampianina, R., Ridal, M., and Vignes, O.:
AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction,
Model, Weather Forecast., 32, 609–627, https://doi.org/10.1175/WAF-D-16-0099.1, 2017
Nieuwstadt, F. T. M.: Some aspects of the turbulent stable boundary layer,
Bound.-Lay. Meteorol., 30, 31–55, https://doi.org/10.1007/BF00121948, 1984.
Norwegian air quality expert user service: available at:
https://www.miljodirektoratet.no/tjenester/fagbrukertjeneste-for-luftkvalitet/, last access: 8 December 2020.
Norwegian air quality forecasting service: available at: https://luftkvalitet.miljostatus.no/, last access: 8 December 2020.
Romberg E., Bösinger, R., Lohmeyer, A., Ruhnke, R., Röth, R.:
NO-NO2-Umwandlung für die Anwendung bei Immissionsprognosen für Kfz-Abgase, in: Staub-Reinhaltung der Luft,
56, 215–218, 1996.
Sauter, F., van Zanten, M., van der Swaluw, E., Aben, J., de Leeuw, F., van
Jaarsveld, H.: The OPS-model, Description of OPS 4.5.2., available at: https://www.rivm.nl/media/ops/v4.5.2/OPS-model-v4.5.2.pdf (last access: 8 December 2020), 2018.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics
from air pollution to climate change, New York, John Wiley and Sons,
Incorporated, 1998.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Smith, M. E. (Ed.): Recommended Guide for the Prediction of the
Dispersion of Airborne Effluents, Vol. 2, Amer. Soc. Mech. Eng., New York, 85
pp., 1973.
Sofiev, M., Vira, J., Kouznetsov, R., Prank, M., Soares, J., and Genikhovich, E.: Construction of the SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael Galperin, Geosci. Model Dev., 8, 3497–3522, https://doi.org/10.5194/gmd-8-3497-2015, 2015.
Stocker, J., Hood, C., Carruthers, D., and McHugh, C.: ADMS-Urban: developments
in modelling dispersion from the city scale to the local scale, Int. J.
Environ. Pollut., 50, 308–316, https://doi.org/10.1504/IJEP.2012.051202, 2012.
Tarrason, L., Hamer, P., Meleux, F., and Rouil, L.: Interim Annual
Assessment Report. European air quality in 2017, Tech. Rep.
CAMS71_2018SC3_D71.1.1.10_IAAR2017_final, available at: https://policy.atmosphere.copernicus.eu/reports/CAMS71_D71.1.1.10_201807_IAAR2017_final.pdf (last access: 8 December 2020), 2018.
Theobald, M. R., Simpson, D., and Vieno, M.: Improving the spatial resolution of air-quality modelling at a European scale – development and evaluation of the Air Quality Re-gridder Model (AQR v1.1), Geosci. Model Dev., 9, 4475–4489, https://doi.org/10.5194/gmd-9-4475-2016, 2016.
Turner, D. B.: Workbook of Atmospheric Dispersion Estimates: An Introduction
to Dispersion Modeling, 2nd Edn., CRC Press, 192 pp., ISBN 9781566700238, 1994.
van Ulden, A. P.: Simple estimates from vertical dispersion from sources near
the ground, Atmos. Environ., 12, 2125–2129, https://doi.org/10.1016/0004-6981(78)90167-1,
1978.
Venkatram, A: An examination of the Pasquill-Gifford-Turner dispersion
scheme, Atmos. Environ., 30, 1283–1290, https://doi.org/10.1016/1352-2310(95)00367-3,
1996.
Venkatram, A., Strimaitis, D., and Dicristofaro, D.: A semiempirical model to
estimate vertical dispersion of elevated releases in the stable boundary
layer, Atmos. Environ., 18, 923–928, https://doi.org/10.1016/0004-6981(84)90068-4,
1984.
Venkatram, A., Snyder, M .G., Heist, D. K., Perry, S. G., Petersen, W. B., and
Isakov, V.: Re-formulation of plume spread for near-surface dispersion,
Atmos. Environ., 77, 846–855, https://doi.org/10.1016/j.atmosenv.2013.05.073,
2013.
Vizcaino, P. and Lavalle, C.: Development of European NO2 Land Use
Regression Model for present and future exposure assessment: Implications
for policy analysis, Environ. Pollut., 240, 140–154,
https://doi.org/10.1016/j.envpol.2018.03.075, 2018.
Werner, M., Kryza, M., and Wind, P.: High resolution application of the EMEP
MSC-W model over Eastern Europe – Analysis of the EMEP4PL results,
Atmos. Res., 212, 6–22, https://doi.org/10.1016/j.atmosres.2018.04.025, 2018.
Wind, P., Rolstad Denby, B., and Gauss, M.: Local fractions – a method for the calculation of local source contributions to air pollution, illustrated by examples using the EMEP MSC-W model (rv4_33), Geosci. Model Dev., 13, 1623–1634, https://doi.org/10.5194/gmd-13-1623-2020, 2020.
Short summary
Air pollution is both a local and a global problem. Since measurements cannot be made everywhere, mathematical models are used to calculate air quality over cities or countries. Modelling over countries limits the level of detail of the models. For countries, the level of detail is only a few kilometres, so air quality at kerb sides is not properly represented. The uEMEP model is used together with the regional air quality model EMEP MSC-W to model details down to kerb side for all of Norway.
Air pollution is both a local and a global problem. Since measurements cannot be made...
