Articles | Volume 12, issue 3
https://doi.org/10.5194/gmd-12-979-2019
© Author(s) 2019. 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-12-979-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
15 Mar 2019
Model description paper |
| 15 Mar 2019
| 15 Mar 2019
Development of a dynamic dust source map for NMME-DREAM v1.0 model based on MODIS Normalized Difference Vegetation Index (NDVI) over the Arabian Peninsula
Stavros Solomos
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens, Athens, Greece
Department of Geography and Urban Planning, National Space Science and Technology Center, United Arab Emirates University, United Arab Emirates
Abdelgadir Abuelgasim
CORRESPONDING AUTHOR
Department of Geography and Urban Planning, National Space Science and Technology Center, United Arab Emirates University, United Arab Emirates
Christos Spyrou
Department of Geography, Harokopio University of Athens (HUA), El. Venizelou Str. 70, 17671 Athens, Greece
Ioannis Binietoglou
National Institute of R&D for Optoelectronics, 409 Atomiştilor Str., Magurele 77125, Romania
Slobodan Nickovic
Republic Hydrometeorological Service of Serbia, 11000 Belgrade, Serbia
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Antonis Gkikas, Anna Gialitaki, Ioannis Binietoglou, Eleni Marinou, Maria Tsichla, Nikolaos Siomos, Peristera Paschou, Anna Kampouri, Kalliopi Artemis Voudouri, Emmanouil Proestakis, Maria Mylonaki, Christina-Anna Papanikolaou, Konstantinos Michailidis, Holger Baars, Anne Grete Straume, Dimitris Balis, Alexandros Papayannis, Tomasso Parrinello, and Vassilis Amiridis
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Abderrazak Bannari and Abdelgader Abuelgasim
SOIL Discuss., https://doi.org/10.5194/soil-2021-55, https://doi.org/10.5194/soil-2021-55, 2021
Manuscript not accepted for further review
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The study aims to analyze the ability of vegetation indices (VI’s) to map soil salt contents compared to the potential of evaporite mineral indices (EMI). The method used is based on simulated and satellite data acquired over two study areas: Kuwait-State and Omongwa salt-pan in Namibia. The obtained results demonstrated that it is impossible for VI’s to discriminate or to predict soil salinity. While, the EMI performed very well for the salt-affected soil classes mapping.
Anna Gialitaki, Alexandra Tsekeri, Vassilis Amiridis, Romain Ceolato, Lucas Paulien, Anna Kampouri, Antonis Gkikas, Stavros Solomos, Eleni Marinou, Moritz Haarig, Holger Baars, Albert Ansmann, Tatyana Lapyonok, Anton Lopatin, Oleg Dubovik, Silke Groß, Martin Wirth, Maria Tsichla, Ioanna Tsikoudi, and Dimitris Balis
Atmos. Chem. Phys., 20, 14005–14021, https://doi.org/10.5194/acp-20-14005-2020, https://doi.org/10.5194/acp-20-14005-2020, 2020
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Stratospheric smoke particles are found to significantly depolarize incident light, while this effect is also accompanied by a strong spectral dependence. We utilize scattering simulations to show that this behaviour can be attributed to the near-spherical shape of the particles. We also examine whether an extension of the current AERONET scattering model to include the near-spherical shapes could be of benefit to the AERONET retrieval for stratospheric smoke associated with enhanced PLDR.
Nikolaos Papagiannopoulos, Giuseppe D'Amico, Anna Gialitaki, Nicolae Ajtai, Lucas Alados-Arboledas, Aldo Amodeo, Vassilis Amiridis, Holger Baars, Dimitris Balis, Ioannis Binietoglou, Adolfo Comerón, Davide Dionisi, Alfredo Falconieri, Patrick Fréville, Anna Kampouri, Ina Mattis, Zoran Mijić, Francisco Molero, Alex Papayannis, Gelsomina Pappalardo, Alejandro Rodríguez-Gómez, Stavros Solomos, and Lucia Mona
Atmos. Chem. Phys., 20, 10775–10789, https://doi.org/10.5194/acp-20-10775-2020, https://doi.org/10.5194/acp-20-10775-2020, 2020
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Volcanic and desert dust particles affect human activities in manifold ways; consequently, mitigation tools are important. Their early detection and the issuance of early warnings are key elements in the initiation of operational response procedures. A methodology for the early warning of these hazards using European Aerosol Research Lidar Network (EARLINET) data is presented. The tailored product is investigated during a volcanic eruption and mineral dust advected in the eastern Mediterranean.
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Ioannis Binietoglou, Albert Ansmann, Ulla Wandinger, Julian Hofer, John Yorks, Edward Nowottnick, Abduvosit Makhmudov, Alexandros Papayannis, Aleksander Pietruczuk, Anna Gialitaki, Arnoud Apituley, Artur Szkop, Constantino Muñoz Porcar, Daniele Bortoli, Davide Dionisi, Dietrich Althausen, Dimitra Mamali, Dimitris Balis, Doina Nicolae, Eleni Tetoni, Gian Luigi Liberti, Holger Baars, Ina Mattis, Iwona Sylwia Stachlewska, Kalliopi Artemis Voudouri, Lucia Mona, Maria Mylonaki, Maria Rita Perrone, Maria João Costa, Michael Sicard, Nikolaos Papagiannopoulos, Nikolaos Siomos, Pasquale Burlizzi, Rebecca Pauly, Ronny Engelmann, Sabur Abdullaev, and Gelsomina Pappalardo
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Eleni Marinou, Matthias Tesche, Athanasios Nenes, Albert Ansmann, Jann Schrod, Dimitra Mamali, Alexandra Tsekeri, Michael Pikridas, Holger Baars, Ronny Engelmann, Kalliopi-Artemis Voudouri, Stavros Solomos, Jean Sciare, Silke Groß, Florian Ewald, and Vassilis Amiridis
Atmos. Chem. Phys., 19, 11315–11342, https://doi.org/10.5194/acp-19-11315-2019, https://doi.org/10.5194/acp-19-11315-2019, 2019
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We assess the feasibility of ground-based and spaceborne lidars to retrieve profiles of cloud-relevant aerosol concentrations and ice-nucleating particles. The retrieved profiles are in good agreement with airborne in situ measurements. Our methodology will be applied to satellite observations in the future so as to provide a global 3D product of cloud-relevant properties.
Nikolaos Papagiannopoulos, Lucia Mona, Aldo Amodeo, Giuseppe D'Amico, Pilar Gumà Claramunt, Gelsomina Pappalardo, Lucas Alados-Arboledas, Juan Luís Guerrero-Rascado, Vassilis Amiridis, Panagiotis Kokkalis, Arnoud Apituley, Holger Baars, Anja Schwarz, Ulla Wandinger, Ioannis Binietoglou, Doina Nicolae, Daniele Bortoli, Adolfo Comerón, Alejandro Rodríguez-Gómez, Michaël Sicard, Alex Papayannis, and Matthias Wiegner
Atmos. Chem. Phys., 18, 15879–15901, https://doi.org/10.5194/acp-18-15879-2018, https://doi.org/10.5194/acp-18-15879-2018, 2018
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A stand-alone automatic method for typing observations of the European Aerosol Research Lidar Network (EARLINET) is presented. The method compares the observations to model distributions that were constructed using EARLINET pre-classified data. The algorithm’s versatility and adaptability makes it suitable for network-wide typing studies.
Doina Nicolae, Jeni Vasilescu, Camelia Talianu, Ioannis Binietoglou, Victor Nicolae, Simona Andrei, and Bogdan Antonescu
Atmos. Chem. Phys., 18, 14511–14537, https://doi.org/10.5194/acp-18-14511-2018, https://doi.org/10.5194/acp-18-14511-2018, 2018
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A new aerosol typing algorithm based on artificial neural networks (ANNs) has been developed. The algorithm is providing the most probable aerosol type based on EARLINET LIDAR profiles. The ANNs used by the algorithm were trained using synthetic data, for which a new aerosol model has been developed. Blind tests on EARLINET data samples showed the capability of the algorithm to retrieve the aerosol type from a large variety of data, with different quality and physical content.
Antonis Gkikas, Vincenzo Obiso, Carlos Pérez García-Pando, Oriol Jorba, Nikos Hatzianastassiou, Lluis Vendrell, Sara Basart, Stavros Solomos, Santiago Gassó, and José Maria Baldasano
Atmos. Chem. Phys., 18, 8757–8787, https://doi.org/10.5194/acp-18-8757-2018, https://doi.org/10.5194/acp-18-8757-2018, 2018
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The present study investigates the direct radiative effects (DREs), induced during 20 intense Mediterranean desert dust outbreaks, based on regional short-term numerical simulations of the NMMB-MONARCH model: more specifically, (i) the DREs and their associated impacts on temperature and surface sensible and latent heat fluxes, (ii) the feedbacks on dust AOD and dust emissions, and (iii) the possible improvements in short-term forecasts (up to 84 h) of temperature and radiation.
Dimitra Mamali, Eleni Marinou, Jean Sciare, Michael Pikridas, Panagiotis Kokkalis, Michael Kottas, Ioannis Binietoglou, Alexandra Tsekeri, Christos Keleshis, Ronny Engelmann, Holger Baars, Albert Ansmann, Vassilis Amiridis, Herman Russchenberg, and George Biskos
Atmos. Meas. Tech., 11, 2897–2910, https://doi.org/10.5194/amt-11-2897-2018, https://doi.org/10.5194/amt-11-2897-2018, 2018
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The paper's scope is to evaluate the performance of in situ atmospheric aerosol instrumentation on board unmanned aerial vehicles (UAVs) and the performance of algorithms used to calculate the aerosol mass from remote sensing instruments by comparing the two independent techniques to each other. Our results indicate that UAV-based aerosol measurements (using specific in situ and remote sensing instrumentation) can provide reliable ways to determine the aerosol mass throughout the atmosphere.
Lev D. Labzovskii, Alexandros Papayannis, Ioannis Binietoglou, Robert F. Banks, Jose M. Baldasano, Florica Toanca, Chris G. Tzanis, and John Christodoulakis
Ann. Geophys., 36, 213–229, https://doi.org/10.5194/angeo-36-213-2018, https://doi.org/10.5194/angeo-36-213-2018, 2018
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This study aims to evaluate synergetic methods for relative humidity vertical profiling based on lidar–radiometer and lidar–simulation combinations. We demonstrate the effectiveness of combined lidar-based methods for relative humidity profiling in comparison with radiometer observations or WRF simulations and assess temperature-related uncertainties in resulting relative humidity profiles. All results are acquired during the HygrA-CD campaign in Athens (Greece) in 2014.
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Aristeidis K. Georgoulias, Stavros Solomos, Stelios Kazadzis, Julien Chimot, Huizheng Che, Georgia Alexandri, Ioannis Binietoglou, Vasiliki Daskalopoulou, Konstantinos A. Kourtidis, Gerrit de Leeuw, and Ronald J. van der A
Atmos. Chem. Phys., 18, 1337–1362, https://doi.org/10.5194/acp-18-1337-2018, https://doi.org/10.5194/acp-18-1337-2018, 2018
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We provide a 3-D climatology of desert dust aerosols over South and East Asia, based on 9 years of CALIPSO observations and an EARLINET methodology. The results provide the horizontal, vertical and seasonal distribution of dust aerosols over SE Asia along with the change in dust transport pathways. The dataset is unique for its potential applications, including evaluation and assimilation activities in atmospheric simulations and the estimation of the climatic impact of dust aerosols.
Alexandra Tsekeri, Anton Lopatin, Vassilis Amiridis, Eleni Marinou, Julia Igloffstein, Nikolaos Siomos, Stavros Solomos, Panagiotis Kokkalis, Ronny Engelmann, Holger Baars, Myrto Gratsea, Panagiotis I. Raptis, Ioannis Binietoglou, Nikolaos Mihalopoulos, Nikolaos Kalivitis, Giorgos Kouvarakis, Nikolaos Bartsotas, George Kallos, Sara Basart, Dirk Schuettemeyer, Ulla Wandinger, Albert Ansmann, Anatoli P. Chaikovsky, and Oleg Dubovik
Atmos. Meas. Tech., 10, 4995–5016, https://doi.org/10.5194/amt-10-4995-2017, https://doi.org/10.5194/amt-10-4995-2017, 2017
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The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean.
Panagiotis G. Kosmopoulos, Stelios Kazadzis, Michael Taylor, Eleni Athanasopoulou, Orestis Speyer, Panagiotis I. Raptis, Eleni Marinou, Emmanouil Proestakis, Stavros Solomos, Evangelos Gerasopoulos, Vassilis Amiridis, Alkiviadis Bais, and Charalabos Kontoes
Atmos. Meas. Tech., 10, 2435–2453, https://doi.org/10.5194/amt-10-2435-2017, https://doi.org/10.5194/amt-10-2435-2017, 2017
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We study the impact of dust on solar energy using remote sensing data in conjunction with synergistic modelling and forecasting techniques. Under high aerosol loads, we found great solar energy losses of the order of 80 and 50% for concentrated solar power and photovoltaic installations, respectively. The 1-day forecast presented an overall accuracy within 10% in direct comparison to the real conditions under high energy potential, optimising the efficient energy planning and policies.
Eleni Marinou, Vassilis Amiridis, Ioannis Binietoglou, Athanasios Tsikerdekis, Stavros Solomos, Emannouil Proestakis, Dimitra Konsta, Nikolaos Papagiannopoulos, Alexandra Tsekeri, Georgia Vlastou, Prodromos Zanis, Dimitrios Balis, Ulla Wandinger, and Albert Ansmann
Atmos. Chem. Phys., 17, 5893–5919, https://doi.org/10.5194/acp-17-5893-2017, https://doi.org/10.5194/acp-17-5893-2017, 2017
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We provide a 3D multiyear analysis on the evolution of Saharan dust over Europe, using a dust product retrieved from the CALIPSO satellite and using EARLINET methods. The results reveal for the first time the 9-year 3D seasonal patterns of dust over its transport paths from the Sahara towards the Mediterranean. The dataset is unique with respect to its potential applications, including the evaluation of dust models and the estimation of ice nuclei concentration profiles from space.
Jann Schrod, Daniel Weber, Jaqueline Drücke, Christos Keleshis, Michael Pikridas, Martin Ebert, Bojan Cvetković, Slobodan Nickovic, Eleni Marinou, Holger Baars, Albert Ansmann, Mihalis Vrekoussis, Nikos Mihalopoulos, Jean Sciare, Joachim Curtius, and Heinz G. Bingemer
Atmos. Chem. Phys., 17, 4817–4835, https://doi.org/10.5194/acp-17-4817-2017, https://doi.org/10.5194/acp-17-4817-2017, 2017
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In this paper we present data of ice-nucleating particles (INPs) from a 1-month campaign in the Eastern Mediterranean using unmanned aircraft systems (UASs, drones) and offline sampling with subsequent laboratory analysis. To our knowledge, this is the first time INPs were measured onboard a UAS. We find that INP concentrations were 1 magnitude higher aloft than at the ground, highlighting that surface-based measurement of INP may only be of limited significance for the situation at cloud level.
Stavros Solomos, Albert Ansmann, Rodanthi-Elisavet Mamouri, Ioannis Binietoglou, Platon Patlakas, Eleni Marinou, and Vassilis Amiridis
Atmos. Chem. Phys., 17, 4063–4079, https://doi.org/10.5194/acp-17-4063-2017, https://doi.org/10.5194/acp-17-4063-2017, 2017
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An extreme dust storm affected Middle East and the Eastern Mediterranean in September 2015. This event was produced by a combination of meteorological and land-use properties. Analysis with remote sensing observations and modeling simulations reveals (i) transport of warm moist air from the Red and Arabian seas, (ii) formation of a thermal low over Syria, (iii) convective outflows and haboob formation (i.e. propagating dust walls), and (iv) changes in land-use and dust erodibility due to war.
Christos S. Zerefos, Kostas Eleftheratos, John Kapsomenakis, Stavros Solomos, Antje Inness, Dimitris Balis, Alberto Redondas, Henk Eskes, Marc Allaart, Vassilis Amiridis, Arne Dahlback, Veerle De Bock, Henri Diémoz, Ronny Engelmann, Paul Eriksen, Vitali Fioletov, Julian Gröbner, Anu Heikkilä, Irina Petropavlovskikh, Janusz Jarosławski, Weine Josefsson, Tomi Karppinen, Ulf Köhler, Charoula Meleti, Christos Repapis, John Rimmer, Vladimir Savinykh, Vadim Shirotov, Anna Maria Siani, Andrew R. D. Smedley, Martin Stanek, and René Stübi
Atmos. Chem. Phys., 17, 551–574, https://doi.org/10.5194/acp-17-551-2017, https://doi.org/10.5194/acp-17-551-2017, 2017
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The paper makes a convincing case that the Brewer network is capable of detecting enhanced SO2 columns, as observed, e.g., after volcanic eruptions. For this reason, large volcanic eruptions of the past decade have been used to detect and forecast SO2 plumes of volcanic origin using the Brewer and other ground-based networks, aided by satellite, trajectory analysis calculations and modelling.
Alexandra Tsekeri, Vassilis Amiridis, Franco Marenco, Athanasios Nenes, Eleni Marinou, Stavros Solomos, Phil Rosenberg, Jamie Trembath, Graeme J. Nott, James Allan, Michael Le Breton, Asan Bacak, Hugh Coe, Carl Percival, and Nikolaos Mihalopoulos
Atmos. Meas. Tech., 10, 83–107, https://doi.org/10.5194/amt-10-83-2017, https://doi.org/10.5194/amt-10-83-2017, 2017
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The In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) provides vertical profiles of aerosol optical, microphysical and hygroscopic properties from airborne in situ and remote sensing measurements. The algorithm is highly advantageous for aerosol characterization in humid conditions, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. IRRA can find valuable applications in aerosol–cloud interaction schemes and in validation of active space-borne sensors.
Rodanthi-Elisavet Mamouri, Albert Ansmann, Argyro Nisantzi, Stavros Solomos, George Kallos, and Diofantos G. Hadjimitsis
Atmos. Chem. Phys., 16, 13711–13724, https://doi.org/10.5194/acp-16-13711-2016, https://doi.org/10.5194/acp-16-13711-2016, 2016
Slobodan Nickovic, Bojan Cvetkovic, Fabio Madonna, Marco Rosoldi, Goran Pejanovic, Slavko Petkovic, and Jugoslav Nikolic
Atmos. Chem. Phys., 16, 11367–11378, https://doi.org/10.5194/acp-16-11367-2016, https://doi.org/10.5194/acp-16-11367-2016, 2016
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Specific physical and mineralogical properties of desert dust particles cause extremely efficient production of ice crystals in clouds, thus influencing climate and weather even in regions far from dust sources. This study describes a methodology for predicting conditions of cold cloud formation due to dust. This approach required development of an integrated dust-atmospheric modelling system, designed to improve operational forecasts of weather in general, and cloud/precipitation in particular.
María José Granados-Muñoz, Francisco Navas-Guzmán, Juan Luis Guerrero-Rascado, Juan Antonio Bravo-Aranda, Ioannis Binietoglou, Sergio Nepomuceno Pereira, Sara Basart, José María Baldasano, Livio Belegante, Anatoli Chaikovsky, Adolfo Comerón, Giuseppe D'Amico, Oleg Dubovik, Luka Ilic, Panos Kokkalis, Constantino Muñoz-Porcar, Slobodan Nickovic, Doina Nicolae, Francisco José Olmo, Alexander Papayannis, Gelsomina Pappalardo, Alejandro Rodríguez, Kerstin Schepanski, Michaël Sicard, Ana Vukovic, Ulla Wandinger, François Dulac, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 16, 7043–7066, https://doi.org/10.5194/acp-16-7043-2016, https://doi.org/10.5194/acp-16-7043-2016, 2016
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This study provides a detailed overview of the Mediterranean region regarding aerosol microphysical properties during the ChArMEx/EMEP campaign in July 2012. An in-depth analysis of the horizontal, vertical, and temporal dimensions is performed using LIRIC, proving the algorithm's ability in automated retrieval of microphysical property profiles within a network. A validation of four dust models is included, obtaining fair good agreement, especially for the vertical distribution of the aerosol.
N. Huneeus, S. Basart, S. Fiedler, J.-J. Morcrette, A. Benedetti, J. Mulcahy, E. Terradellas, C. Pérez García-Pando, G. Pejanovic, S. Nickovic, P. Arsenovic, M. Schulz, E. Cuevas, J. M. Baldasano, J. Pey, S. Remy, and B. Cvetkovic
Atmos. Chem. Phys., 16, 4967–4986, https://doi.org/10.5194/acp-16-4967-2016, https://doi.org/10.5194/acp-16-4967-2016, 2016
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Five dust models are evaluated regarding their performance in predicting an intense Saharan dust outbreak affecting western and northern Europe (NE). Models predict the onset and evolution of the event for all analysed lead times. On average, differences among the models are larger than differences in lead times for each model. The models tend to underestimate the long-range transport towards NE. This is partly due to difficulties in simulating the vertical dust distribution and horizontal wind.
Nikolaos Papagiannopoulos, Lucia Mona, Lucas Alados-Arboledas, Vassilis Amiridis, Holger Baars, Ioannis Binietoglou, Daniele Bortoli, Giuseppe D'Amico, Aldo Giunta, Juan Luis Guerrero-Rascado, Anja Schwarz, Sergio Pereira, Nicola Spinelli, Ulla Wandinger, Xuan Wang, and Gelsomina Pappalardo
Atmos. Chem. Phys., 16, 2341–2357, https://doi.org/10.5194/acp-16-2341-2016, https://doi.org/10.5194/acp-16-2341-2016, 2016
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Satellite-derived products must undergo data evaluation with reference data sets in order to identify any possible reasons of discrepancy or to assess their representativity. In that direction, data coming from CALIPSO satellite were compared with observations from the ground. We identified a CALIPSO underestimation that could be linked to an assumption in the satellites' algorithms. The proposed correction improves the performance and could enhance aerosol modeling.
G. D'Amico, A. Amodeo, H. Baars, I. Binietoglou, V. Freudenthaler, I. Mattis, U. Wandinger, and G. Pappalardo
Atmos. Meas. Tech., 8, 4891–4916, https://doi.org/10.5194/amt-8-4891-2015, https://doi.org/10.5194/amt-8-4891-2015, 2015
M. Sicard, G. D'Amico, A. Comerón, L. Mona, L. Alados-Arboledas, A. Amodeo, H. Baars, J. M. Baldasano, L. Belegante, I. Binietoglou, J. A. Bravo-Aranda, A. J. Fernández, P. Fréville, D. García-Vizcaíno, A. Giunta, M. J. Granados-Muñoz, J. L. Guerrero-Rascado, D. Hadjimitsis, A. Haefele, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, R. E. Mamouri, I. Mattis, F. Molero, N. Montoux, A. Muñoz, C. Muñoz Porcar, F. Navas-Guzmán, D. Nicolae, A. Nisantzi, N. Papagiannopoulos, A. Papayannis, S. Pereira, J. Preißler, M. Pujadas, V. Rizi, F. Rocadenbosch, K. Sellegri, V. Simeonov, G. Tsaknakis, F. Wagner, and G. Pappalardo
Atmos. Meas. Tech., 8, 4587–4613, https://doi.org/10.5194/amt-8-4587-2015, https://doi.org/10.5194/amt-8-4587-2015, 2015
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In the framework of the ACTRIS summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. The paper describes the measurement protocol and discusses the delivery of real-time and near-real-time lidar-derived products.
I. Binietoglou, S. Basart, L. Alados-Arboledas, V. Amiridis, A. Argyrouli, H. Baars, J. M. Baldasano, D. Balis, L. Belegante, J. A. Bravo-Aranda, P. Burlizzi, V. Carrasco, A. Chaikovsky, A. Comerón, G. D'Amico, M. Filioglou, M. J. Granados-Muñoz, J. L. Guerrero-Rascado, L. Ilic, P. Kokkalis, A. Maurizi, L. Mona, F. Monti, C. Muñoz-Porcar, D. Nicolae, A. Papayannis, G. Pappalardo, G. Pejanovic, S. N. Pereira, M. R. Perrone, A. Pietruczuk, M. Posyniak, F. Rocadenbosch, A. Rodríguez-Gómez, M. Sicard, N. Siomos, A. Szkop, E. Terradellas, A. Tsekeri, A. Vukovic, U. Wandinger, and J. Wagner
Atmos. Meas. Tech., 8, 3577–3600, https://doi.org/10.5194/amt-8-3577-2015, https://doi.org/10.5194/amt-8-3577-2015, 2015
V. Amiridis, E. Marinou, A. Tsekeri, U. Wandinger, A. Schwarz, E. Giannakaki, R. Mamouri, P. Kokkalis, I. Binietoglou, S. Solomos, T. Herekakis, S. Kazadzis, E. Gerasopoulos, E. Proestakis, M. Kottas, D. Balis, A. Papayannis, C. Kontoes, K. Kourtidis, N. Papagiannopoulos, L. Mona, G. Pappalardo, O. Le Rille, and A. Ansmann
Atmos. Chem. Phys., 15, 7127–7153, https://doi.org/10.5194/acp-15-7127-2015, https://doi.org/10.5194/acp-15-7127-2015, 2015
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LIVAS is a 3-D multi-wavelength global aerosol and cloud optical database optimized for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The global database is based on CALIPSO observations at 532nm, while for the conversion at 355nm EARLINET data are utilized.
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette, M. Sicard, G. D'Amico, J. F. Léon, L. Alados-Arboledas, A. Amodeo, P. Augustin, J. Bach, L. Belegante, I. Binietoglou, X. Bush, A. Comerón, H. Delbarre, D. García-Vízcaino, J. L. Guerrero-Rascado, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, F. Molero, N. Montoux, A. Muñoz, C. Muñoz, D. Nicolae, A. Papayannis, G. Pappalardo, J. Preissler, V. Rizi, F. Rocadenbosch, K. Sellegri, F. Wagner, and F. Dulac
Atmos. Chem. Phys., 14, 12031–12053, https://doi.org/10.5194/acp-14-12031-2014, https://doi.org/10.5194/acp-14-12031-2014, 2014
A. Vukovic, M. Vujadinovic, G. Pejanovic, J. Andric, M. R. Kumjian, V. Djurdjevic, M. Dacic, A. K. Prasad, H. M. El-Askary, B. C. Paris, S. Petkovic, S. Nickovic, and W. A. Sprigg
Atmos. Chem. Phys., 14, 3211–3230, https://doi.org/10.5194/acp-14-3211-2014, https://doi.org/10.5194/acp-14-3211-2014, 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
S. Nickovic, A. Vukovic, and M. Vujadinovic
Atmos. Chem. Phys., 13, 9169–9181, https://doi.org/10.5194/acp-13-9169-2013, https://doi.org/10.5194/acp-13-9169-2013, 2013
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter Notebooks included in the library.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2023-2613, https://doi.org/10.5194/egusphere-2023-2613, 2023
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By directly analysing the proximity of precipitation forecasts and observations, a precipitation forecast accuracy score (PAS) method was constructed. This method does not utilize the traditional contingency table-based classification verification, can replace the threat score (TS), equitable threat score (ETS) and other skill score methods, and can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
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Short summary
In this research we developed a time-dependent dust source map for NMME-DREAM v1.0 model based on the MODIS Normalized Digital Vegetation Index (NDVI). Areas with NDVI < 0.1 are classified as active dust sources. The new modeling system is tested for the analysis of dust particle dispersion over SW Asia using a mesoscale model grid increment of 0.1° × 0.1° km for a period of 1 year. Simulated AOD increased compared to the static dust source approach and there was an increase in dust loads.
In this research we developed a time-dependent dust source map for NMME-DREAM v1.0 model based...
