Articles | Volume 6, issue 3
https://doi.org/10.5194/gmd-6-721-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-721-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
03 Jun 2013
Development and technical paper |
| 03 Jun 2013
Source apportionment using LOTOS-EUROS: module description and evaluation
R. Kranenburg
TNO, P.O. Box 80015, 3508 TA, Utrecht, the Netherlands
A. J. Segers
TNO, P.O. Box 80015, 3508 TA, Utrecht, the Netherlands
C. Hendriks
TNO, P.O. Box 80015, 3508 TA, Utrecht, the Netherlands
M. Schaap
TNO, P.O. Box 80015, 3508 TA, Utrecht, the Netherlands
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S. Banzhaf, M. Schaap, R. Kranenburg, A. M. M. Manders, A. J. Segers, A. J. H. Visschedijk, H. A. C. Denier van der Gon, J. J. P. Kuenen, E. van Meijgaard, L. H. van Ulft, J. Cofala, and P. J. H. Builtjes
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Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Bufan Xu, Wei Han, Mijie Pang, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-301, https://doi.org/10.5194/gmd-2022-301, 2023
Preprint under review for GMD
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Machine learning model have gained great popularity in air quality prediction. However, they are only available at the air quality monitoring stations. In contrast, chemical transport models (CTM) provide forecasts that are continuous in 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional-feature-selection machine learning prediction (RFSML v1.0) and a CTM forecast.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2023-35, https://doi.org/10.5194/acp-2023-35, 2023
Preprint under review for ACP
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Lea Fink, Matthias Karl, Volker Matthias, Sonia Oppo, Richard Kranenburg, Jeroen Kuenen, Jana Moldanova, Sara Jutterström, Jukka-Pekka Jalkanen, and Elisa Majamäki
Atmos. Chem. Phys., 23, 1825–1862, https://doi.org/10.5194/acp-23-1825-2023, https://doi.org/10.5194/acp-23-1825-2023, 2023
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Potential ship impact on air pollution in the Mediterranean Sea was simulated with five chemistry transport models. An evaluation of the results for NO2 and O3 air concentrations and dry deposition is presented. Emission data, modeled year and domain were the same. Model run outputs were compared to measurements from background stations. We focused on comparing model outputs regarding the concentration of regulatory pollutants and the relative ship impact on total air pollution concentrations.
Jianbing Jin, Bas Henzing, and Arjo Segers
Atmos. Chem. Phys., 23, 1641–1660, https://doi.org/10.5194/acp-23-1641-2023, https://doi.org/10.5194/acp-23-1641-2023, 2023
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Aerosol models and satellite retrieval algorithms rely on different aerosol size assumptions. In practice, differences between simulations and observations do not always reflect the difference in aerosol amount. To avoid inconsistencies, we designed a hybrid assimilation approach. Different from a standard aerosol optical depth (AOD) assimilation that directly assimilates AODs, the hybrid one estimates aerosol size parameters by assimilating Ängström observations before assimilating the AODs.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, Richard Kranenburg, and Christian Brümmer
Biogeosciences, 19, 5287–5311, https://doi.org/10.5194/bg-19-5287-2022, https://doi.org/10.5194/bg-19-5287-2022, 2022
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For the first time, we compared four methods for estimating the annual dry deposition of total reactive nitrogen into a low-polluted forest ecosystem. In our analysis, we used 2.5 years of flux measurements, an in situ modeling approach, a large-scale chemical transport model (CTM), and canopy budget models. Annual nitrogen dry deposition budgets ranged between 4.3 and 6.7 kg N ha−1 a−1, depending on the applied method.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
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Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
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We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Sudhanshu Pandey, Sander Houweling, and Arjo Segers
Geosci. Model Dev., 15, 4555–4567, https://doi.org/10.5194/gmd-15-4555-2022, https://doi.org/10.5194/gmd-15-4555-2022, 2022
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Inversions are used to calculate methane emissions using atmospheric mole-fraction measurements. Multidecadal inversions are needed to extract information from the long measurement records of methane. However, multidecadal inversion computations can take months to finish. Here, we demonstrate an order of magnitude improvement in wall clock time for an iterative multidecadal inversion by physical parallelization of chemical transport model.
Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao
Atmos. Chem. Phys., 22, 6393–6410, https://doi.org/10.5194/acp-22-6393-2022, https://doi.org/10.5194/acp-22-6393-2022, 2022
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Super dust storms reappeared in East Asia last spring after being absent for one and a half decades. Accurate simulation of such super sandstorms is valuable, but challenging due to imperfect emissions. In this study, the emissions of these dust storms are estimated by assimilating multiple observations. The results reveal that emissions originated from both China and Mongolia. However, for northern China, long-distance transport from Mongolia contributes much more dust than Chinese deserts.
Christian Brümmer, Jeremy J. Rüffer, Jean-Pierre Delorme, Pascal Wintjen, Frederik Schrader, Burkhard Beudert, Martijn Schaap, and Christof Ammann
Earth Syst. Sci. Data, 14, 743–761, https://doi.org/10.5194/essd-14-743-2022, https://doi.org/10.5194/essd-14-743-2022, 2022
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Field campaigns were carried out to investigate the biosphere–atmosphere exchange of selected reactive nitrogen compounds over different land surfaces using two different analytical devices for ammonia and total reactive nitrogen. The datasets improve our understanding of the temporal variability of surface–atmosphere exchange in different ecosystems, thereby providing validation opportunities for inferential models simulating the exchange of reactive nitrogen.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, and Christian Brümmer
Biogeosciences, 19, 389–413, https://doi.org/10.5194/bg-19-389-2022, https://doi.org/10.5194/bg-19-389-2022, 2022
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Fluxes of total reactive nitrogen (∑Nr) over a low polluted forest were analyzed with regard to their temporal dynamics. Mostly deposition was observed with median fluxes ranging from −15 to −5 ng N m−2 s−1, corresponding to a range of deposition velocities from 0.2 to 0.5 cm s−1. While seasonally changing contributions of NH3 and NOx to the ∑Nr signal were found, we estimate an annual total N deposition (dry+wet) of 12.2 and 10.9 kg N ha−1 a−1 in the 2 years of observation.
Shelley van der Graaf, Enrico Dammers, Arjo Segers, Richard Kranenburg, Martijn Schaap, Mark W. Shephard, and Jan Willem Erisman
Atmos. Chem. Phys., 22, 951–972, https://doi.org/10.5194/acp-22-951-2022, https://doi.org/10.5194/acp-22-951-2022, 2022
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CrIS NH3 satellite observations are assimilated into the LOTOS-EUROS model using two different methods. In the first method the data are used to fit spatially varying NH3 emission time factors. In the second method a local ensemble transform Kalman filter is used. Compared to in situ observations, combining both methods led to the most significant improvements in the modeled concentrations and deposition, illustrating the usefulness of CrIS NH3 to improve the spatiotemporal distribution of NH3.
Vilma Kangasaho, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, Ed Dlugokencky, Sylvia Michel, James White, and Tuula Aalto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-843, https://doi.org/10.5194/acp-2021-843, 2021
Revised manuscript not accepted
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Understanding the composition of carbon isotopes can help to better understand the changes in methane budgets. This study investigates how methane sources affect the seasonal cycle of the methane carbon-13 isotope during 2000–2012 using an atmospheric transport model. We found that emissions from both anthropogenic and natural sources contribute. The findings raise a need to revise the magnitudes, proportion, and seasonal cycles of anthropogenic sources and northern wetland emissions.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622, https://doi.org/10.5194/gmd-14-5607-2021, https://doi.org/10.5194/gmd-14-5607-2021, 2021
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When discussing the accuracy of a dust forecast, the shape and position of the plume as well as the intensity are key elements. The position forecast determines which locations will be affected, while the intensity only describes the actual dust level. A dust forecast with position misfit directly results in incorrect timing profiles of dust loads. In this paper, an image-morphing-based data assimilation is designed for realigning a simulated dust plume to correct for the position error.
Ioanna Skoulidou, Maria-Elissavet Koukouli, Astrid Manders, Arjo Segers, Dimitris Karagkiozidis, Myrto Gratsea, Dimitris Balis, Alkiviadis Bais, Evangelos Gerasopoulos, Trisevgeni Stavrakou, Jos van Geffen, Henk Eskes, and Andreas Richter
Atmos. Chem. Phys., 21, 5269–5288, https://doi.org/10.5194/acp-21-5269-2021, https://doi.org/10.5194/acp-21-5269-2021, 2021
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The performance of LOTOS-EUROS v2.2.001 regional chemical transport model NO2 simulations is investigated over Greece from June to December 2018. Comparison with in situ NO2 measurements shows a spatial correlation coefficient of 0.86, while the model underestimates the concentrations mostly during daytime (12 to 15:00 local time). Further, the simulated tropospheric NO2 columns are evaluated against ground-based MAX-DOAS NO2 measurements and S5P/TROPOMI observations for July and December 2018.
Maria-Elissavet Koukouli, Ioanna Skoulidou, Andreas Karavias, Isaak Parcharidis, Dimitris Balis, Astrid Manders, Arjo Segers, Henk Eskes, and Jos van Geffen
Atmos. Chem. Phys., 21, 1759–1774, https://doi.org/10.5194/acp-21-1759-2021, https://doi.org/10.5194/acp-21-1759-2021, 2021
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In recent years, satellite observations have contributed to monitoring air quality. During the first COVID-19 lockdown, lower levels of nitrogen dioxide were observed over Greece by S5P/TROPOMI for March and April 2020 (than the preceding year) due to decreased transport emissions. Taking meteorology into account, using LOTOS-EUROS CTM simulations, the resulting decline due to the lockdown was estimated to range between 0 % and −37 % for the five largest Greek cities, with an average of ~ −10 %.
Xinrui Ge, Martijn Schaap, Richard Kranenburg, Arjo Segers, Gert Jan Reinds, Hans Kros, and Wim de Vries
Atmos. Chem. Phys., 20, 16055–16087, https://doi.org/10.5194/acp-20-16055-2020, https://doi.org/10.5194/acp-20-16055-2020, 2020
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This article is about improving the modeling of agricultural ammonia emissions. By considering land use, meteorology and agricultural practices, ammonia emission totals officially reported by countries are distributed in space and time. We illustrated the first step for a better understanding of the variability of ammonia emission, with the possibility of being applied at a European scale, which is of great significance for ammonia budget research and future policy-making.
Jianbing Jin, Arjo Segers, Hong Liao, Arnold Heemink, Richard Kranenburg, and Hai Xiang Lin
Atmos. Chem. Phys., 20, 15207–15225, https://doi.org/10.5194/acp-20-15207-2020, https://doi.org/10.5194/acp-20-15207-2020, 2020
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Data assimilation provides a powerful tool to estimate emission inventories by feeding observations. This emission inversion relies on the correct assumption about the emission uncertainty, which describes the potential spatiotemporal spreads of sources. However, an unrepresentative uncertainty is unavoidable. Especially in the complex dust emission, the uncertainties can hardly all be taken into account. This study reports how adjoint can be used to detect errors in the emission uncertainty.
Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
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The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Shelley C. van der Graaf, Richard Kranenburg, Arjo J. Segers, Martijn Schaap, and Jan Willem Erisman
Geosci. Model Dev., 13, 2451–2474, https://doi.org/10.5194/gmd-13-2451-2020, https://doi.org/10.5194/gmd-13-2451-2020, 2020
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Chemical transport models (CTMs) are important tools to determine the fate of reactive nitrogen (Nr) emissions. The parameterization of the surface–atmosphere exchange in CTMs is often only linked to fixed, land-use-dependent values. In this paper, we present an approach to derive more realistic, dynamic leaf area index (LAI) and roughness length (z0) input maps using multiple satellite products. We evaluate the effect on Nr concentration and deposition fields modelled in the LOTOS-EUROS CTM.
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
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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.
Anne-Marlene Blechschmidt, Joaquim Arteta, Adriana Coman, Lyana Curier, Henk Eskes, Gilles Foret, Clio Gielen, Francois Hendrick, Virginie Marécal, Frédérik Meleux, Jonathan Parmentier, Enno Peters, Gaia Pinardi, Ankie J. M. Piters, Matthieu Plu, Andreas Richter, Arjo Segers, Mikhail Sofiev, Álvaro M. Valdebenito, Michel Van Roozendael, Julius Vira, Tim Vlemmix, and John P. Burrows
Atmos. Chem. Phys., 20, 2795–2823, https://doi.org/10.5194/acp-20-2795-2020, https://doi.org/10.5194/acp-20-2795-2020, 2020
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MAX-DOAS tropospheric NO2 vertical column retrievals from a set of European measurement stations are compared to regional air quality models which contribute to the operational Copernicus Atmosphere Monitoring Service (CAMS). Correlations are on the order of 35 %–75 %; large differences occur for individual pollution plumes. The results demonstrate that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.
Samuel Quesada-Ruiz, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, Andrea Piacentini, Mathieu Joly, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Christiaan Plechelmus Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 131–152, https://doi.org/10.5194/amt-13-131-2020, https://doi.org/10.5194/amt-13-131-2020, 2020
Emmanuele Russo, Ingo Kirchner, Stephan Pfahl, Martijn Schaap, and Ulrich Cubasch
Geosci. Model Dev., 12, 5229–5249, https://doi.org/10.5194/gmd-12-5229-2019, https://doi.org/10.5194/gmd-12-5229-2019, 2019
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This is an investigation of COSMO-CLM 5.0 sensitivity for the CORDEX Central Asia domain, with the main goal of evaluating general model performances for the area, proposing a model optimal configuration to be used in projection studies.
Results show that the model seems to be particularly sensitive to those parameterizations that deal with soil and surface features and that could positively affect the repartition of incoming radiation.
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
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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.
Miguel Escudero, Arjo Segers, Richard Kranenburg, Xavier Querol, Andrés Alastuey, Rafael Borge, David de la Paz, Gotzon Gangoiti, and Martijn Schaap
Atmos. Chem. Phys., 19, 14211–14232, https://doi.org/10.5194/acp-19-14211-2019, https://doi.org/10.5194/acp-19-14211-2019, 2019
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In this work we optimise LOTOS-EUROS CTM for simulating tropospheric O3 during summer in the Madrid metropolitan area, one of the largest conurbations in the Mediterranean. Comparing the outputs from five set-ups with different combinations of spatial resolution, meteorological data and vertical structure, we conclude that the model benefits from fine horizontal resolution and highly resolved vertical structure. Running optimized configuration run, we interpret O3 variability during July 2016.
Renske Timmermans, Arjo Segers, Lyana Curier, Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Henk Eskes, Johan de Haan, Jukka Kujanpää, William Lahoz, Albert Oude Nijhuis, Samuel Quesada-Ruiz, Philippe Ricaud, Pepijn Veefkind, and Martijn Schaap
Atmos. Chem. Phys., 19, 12811–12833, https://doi.org/10.5194/acp-19-12811-2019, https://doi.org/10.5194/acp-19-12811-2019, 2019
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We present an evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for air quality analyses of NO2. For this, synthetic observations for both missions are generated and combined with a chemistry transport model. While hourly Sentinel-4 NO2 observations over Europe benefit modelled NO2 analyses throughout the entire day, daily Sentinel-5P NO2 observations with global coverage show an impact up to 3–6 h after overpass. This supports the need for a combination of missions.
Enrico Dammers, Chris A. McLinden, Debora Griffin, Mark W. Shephard, Shelley Van Der Graaf, Erik Lutsch, Martijn Schaap, Yonatan Gainairu-Matz, Vitali Fioletov, Martin Van Damme, Simon Whitburn, Lieven Clarisse, Karen Cady-Pereira, Cathy Clerbaux, Pierre Francois Coheur, and Jan Willem Erisman
Atmos. Chem. Phys., 19, 12261–12293, https://doi.org/10.5194/acp-19-12261-2019, https://doi.org/10.5194/acp-19-12261-2019, 2019
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Ammonia is an essential molecule in the environment, but at its current levels it is unsustainable. However, the emissions are highly uncertain. We explore the use of satellites to estimate the ammonia lifetime and emissions around point sources to help improve the budget. The same method applied to different satellite instruments shows consistent results. Comparison to the emission inventories shows that those are underestimating emissions of point sources by on average a factor of 2.5.
Jianbing Jin, Hai Xiang Lin, Arjo Segers, Yu Xie, and Arnold Heemink
Atmos. Chem. Phys., 19, 10009–10026, https://doi.org/10.5194/acp-19-10009-2019, https://doi.org/10.5194/acp-19-10009-2019, 2019
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
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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
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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
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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.
Christine D. Groot Zwaaftink, Stephan Henne, Rona L. Thompson, Edward J. Dlugokencky, Toshinobu Machida, Jean-Daniel Paris, Motoki Sasakawa, Arjo Segers, Colm Sweeney, and Andreas Stohl
Geosci. Model Dev., 11, 4469–4487, https://doi.org/10.5194/gmd-11-4469-2018, https://doi.org/10.5194/gmd-11-4469-2018, 2018
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A Lagrangian particle dispersion model is used to simulate global fields of methane, constrained by observations through nudging. We show that this rather simple and computationally inexpensive method can give results similar to or as good as a computationally expensive Eulerian chemistry transport model with a data assimilation scheme. The three-dimensional methane fields are of interest to applications such as inverse modelling and satellite retrievals.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
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Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Simon Chabrillat, Corinne Vigouroux, Yves Christophe, Andreas Engel, Quentin Errera, Daniele Minganti, Beatriz M. Monge-Sanz, Arjo Segers, and Emmanuel Mahieu
Atmos. Chem. Phys., 18, 14715–14735, https://doi.org/10.5194/acp-18-14715-2018, https://doi.org/10.5194/acp-18-14715-2018, 2018
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Mean age of stratospheric air is computed for the period 1989–2015 with a kinematic transport model which uses surface pressure and wind fields from five reanalyses: ERA-I, MERRA-2, MERRA, CFSR, JRA-55. The spread between the resulting datasets is as large as in climate model intercomparisons; the age trends have large disagreement and depend strongly on the considered period. We highlight the need for similar studies using diabatic transport models which also use temperature and heating rates.
Shelley C. van der Graaf, Enrico Dammers, Martijn Schaap, and Jan Willem Erisman
Atmos. Chem. Phys., 18, 13173–13196, https://doi.org/10.5194/acp-18-13173-2018, https://doi.org/10.5194/acp-18-13173-2018, 2018
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A combination of NH3 satellite observations from IASI and the LOTOS-EUROS model is used to derive NH3 surface concentrations and dry deposition fluxes over Europe. The results were evaluated using surface measurements (EMEP, LML, MAN) and a sensitivity study. This is a first step in further integration of surface measurements, satellite observations and an atmospheric transport model to derive accurate NH3 surface concentrations and dry deposition fluxes on a large scale.
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
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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.
Martijn Schaap, Sabine Banzhaf, Thomas Scheuschner, Markus Geupel, Carlijn Hendriks, Richard Kranenburg, Hans-Dieter Nagel, Arjo J. Segers, Angela von Schlutow, Roy Wichink Kruit, and Peter J. H. Builtjes
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-491, https://doi.org/10.5194/bg-2017-491, 2017
Revised manuscript has not been submitted
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Deposition of nitrogen and sulfur from the atmosphere on ecosystems causes a loss of biodiversity. We used a combination of atmospheric modelling and deposition observations to estimate the deposition to ecosystems across Germany. We estimate that 70 % of the ecosystems in Germany receive too much nitrogen from deposition. The results are used to determine whether economic activities causing nitrogen emissions are allowed in sensitive areas.
Astrid M. M. Manders, Peter J. H. Builtjes, Lyana Curier, Hugo A. C. Denier van der Gon, Carlijn Hendriks, Sander Jonkers, Richard Kranenburg, Jeroen J. P. Kuenen, Arjo J. Segers, Renske M. A. Timmermans, Antoon J. H. Visschedijk, Roy J. Wichink Kruit, W. Addo J. van Pul, Ferd J. Sauter, Eric van der Swaluw, Daan P. J. Swart, John Douros, Henk Eskes, Erik van Meijgaard, Bert van Ulft, Peter van Velthoven, Sabine Banzhaf, Andrea C. Mues, Rainer Stern, Guangliang Fu, Sha Lu, Arnold Heemink, Nils van Velzen, and Martijn Schaap
Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, https://doi.org/10.5194/gmd-10-4145-2017, 2017
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The regional-scale air quality model LOTOS–EUROS has been developed by a consortium of Dutch institutes. Recently, version 2.0 of the model was released as an open-source version. Next to a technical description and model evaluation for 2012, this paper presents the model developments in context of the history of air quality modelling and provides an outlook for future directions. Key and innovative applications of LOTOS–EUROS are also highlighted.
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017, https://doi.org/10.5194/acp-17-12341-2017, 2017
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This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
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
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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.
Enrico Dammers, Mark W. Shephard, Mathias Palm, Karen Cady-Pereira, Shannon Capps, Erik Lutsch, Kim Strong, James W. Hannigan, Ivan Ortega, Geoffrey C. Toon, Wolfgang Stremme, Michel Grutter, Nicholas Jones, Dan Smale, Jacob Siemons, Kevin Hrpcek, Denis Tremblay, Martijn Schaap, Justus Notholt, and Jan Willem Erisman
Atmos. Meas. Tech., 10, 2645–2667, https://doi.org/10.5194/amt-10-2645-2017, https://doi.org/10.5194/amt-10-2645-2017, 2017
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Presented here is the validation of the CrIS fast physical retrieval (CFPR) NH3 column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Furthermore, we find that CrIS and FTIR profile comparison differences are mostly within the range of the estimated retrieval uncertainties, with differences in the range of ~ 20 to 40 %.
Guangliang Fu, Hai Xiang Lin, Arnold Heemink, Sha Lu, Arjo Segers, Nils van Velzen, Tongchao Lu, and Shiming Xu
Geosci. Model Dev., 10, 1751–1766, https://doi.org/10.5194/gmd-10-1751-2017, https://doi.org/10.5194/gmd-10-1751-2017, 2017
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We propose a mask-state algorithm (MS) which records the sparsity information of the full ensemble state matrix and transforms the full matrix into a relatively small one. It will reduce the computational cost in the analysis step for plume assimilation applications. Ensemble-based DA with the mask-state algorithm is generic and flexible, because it implements exactly the standard DA without any approximation and it realizes the satisfying performance without any change of the full model.
Guangliang Fu, Fred Prata, Hai Xiang Lin, Arnold Heemink, Arjo Segers, and Sha Lu
Atmos. Chem. Phys., 17, 1187–1205, https://doi.org/10.5194/acp-17-1187-2017, https://doi.org/10.5194/acp-17-1187-2017, 2017
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A Satellite Observational Operator (SOO) is proposed to translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The SOO makes the analysis step of assimilation comparable in the 3-D model space, and thus it avoids the artificial vertical correlations by not involving the integral operator in directly assimilating 2-D data. The results show that satellite data assimilation with SOO can efficiently improve the estimate of volcanic ash state and the forecast.
Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Philippe Ricaud, William Lahoz, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, https://doi.org/10.5194/acp-17-1081-2017, 2017
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A detailed Observing System Simulation Experiment is performed to quantify the impact of future satellite instrument S-5P carbon monoxide (CO) on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode. S-5P is able to capture the CO from forest fires that occurred in Portugal. Furthermore, our results provide evidence of S-5P CO benefits for monitoring processes contributing to atmospheric pollution.
Monique F. M. A. Albert, Magdalena D. Anguelova, Astrid M. M. Manders, Martijn Schaap, and Gerrit de Leeuw
Atmos. Chem. Phys., 16, 13725–13751, https://doi.org/10.5194/acp-16-13725-2016, https://doi.org/10.5194/acp-16-13725-2016, 2016
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Sea spray source functions (SSSFs) predict production of sea salt aerosol, important for climate. Sea spray originates from bubble bursting within whitecaps, mainly formed by wind speed (U). Using satellite-based whitecap fraction (W) data analyzed on global and regional scale and explicitly accounting for sea surface temperature (T) we derive a new W(U, T) parameterization. We use it to evaluate influence of secondary factors on a SSSF via W.
Bertrand Bessagnet, Guido Pirovano, Mihaela Mircea, Cornelius Cuvelier, Armin Aulinger, Giuseppe Calori, Giancarlo Ciarelli, Astrid Manders, Rainer Stern, Svetlana Tsyro, Marta García Vivanco, Philippe Thunis, Maria-Teresa Pay, Augustin Colette, Florian Couvidat, Frédérik Meleux, Laurence Rouïl, Anthony Ung, Sebnem Aksoyoglu, José María Baldasano, Johannes Bieser, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Sandro Finardi, Richard Kranenburg, Camillo Silibello, Claudio Carnevale, Wenche Aas, Jean-Charles Dupont, Hilde Fagerli, Lucia Gonzalez, Laurent Menut, André S. H. Prévôt, Pete Roberts, and Les White
Atmos. Chem. Phys., 16, 12667–12701, https://doi.org/10.5194/acp-16-12667-2016, https://doi.org/10.5194/acp-16-12667-2016, 2016
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The EURODELTA III exercise allows a very comprehensive intercomparison and evaluation of air quality models' performance. On average, the models provide a rather good picture of the particulate matter (PM) concentrations over Europe even if the highest concentrations are underestimated. The meteorology is responsible for model discrepancies, while the lack of emissions, particularly in winter, is mentioned as the main reason for the underestimations of PM.
E. N. Koffi, P. Bergamaschi, U. Karstens, M. Krol, A. Segers, M. Schmidt, I. Levin, A. T. Vermeulen, R. E. Fisher, V. Kazan, H. Klein Baltink, D. Lowry, G. Manca, H. A. J. Meijer, J. Moncrieff, S. Pal, M. Ramonet, H. A. Scheeren, and A. G. Williams
Geosci. Model Dev., 9, 3137–3160, https://doi.org/10.5194/gmd-9-3137-2016, https://doi.org/10.5194/gmd-9-3137-2016, 2016
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We evaluate the capability of the TM5 model to reproduce observations of the boundary layer dynamics and the associated variability of trace gases close to the surface, using 222Rn. Focusing on the European scale, we compare the TM5 boundary layer heights with observations from radiosondes, lidar, and ceilometer. Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe, with 222Rn harmonized measurements from 10 stations.
Enrico Dammers, Mathias Palm, Martin Van Damme, Corinne Vigouroux, Dan Smale, Stephanie Conway, Geoffrey C. Toon, Nicholas Jones, Eric Nussbaumer, Thorsten Warneke, Christof Petri, Lieven Clarisse, Cathy Clerbaux, Christian Hermans, Erik Lutsch, Kim Strong, James W. Hannigan, Hideaki Nakajima, Isamu Morino, Beatriz Herrera, Wolfgang Stremme, Michel Grutter, Martijn Schaap, Roy J. Wichink Kruit, Justus Notholt, Pierre-F. Coheur, and Jan Willem Erisman
Atmos. Chem. Phys., 16, 10351–10368, https://doi.org/10.5194/acp-16-10351-2016, https://doi.org/10.5194/acp-16-10351-2016, 2016
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Atmospheric ammonia (NH3) measured by the IASI satellite instrument is compared to observations from ground-based FTIR instruments. The seasonal cycles of NH3 in both datasets are consistent for most sites. Correlations are found to be high at sites with considerable NH3 levels, whereas correlations are lower at sites with low NH3 levels close to the detection limit of the IASI instrument. The study's results further indicate that the IASI-NH3 product performs better than earlier estimates.
Guangliang Fu, Arnold Heemink, Sha Lu, Arjo Segers, Konradin Weber, and Hai-Xiang Lin
Atmos. Chem. Phys., 16, 9189–9200, https://doi.org/10.5194/acp-16-9189-2016, https://doi.org/10.5194/acp-16-9189-2016, 2016
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Assimilating aircraft in situ measurements can significantly improve aviation advice on distal part of volcanic ash plume.
Marje Prank, Mikhail Sofiev, Svetlana Tsyro, Carlijn Hendriks, Valiyaveetil Semeena, Xavier Vazhappilly Francis, Tim Butler, Hugo Denier van der Gon, Rainer Friedrich, Johannes Hendricks, Xin Kong, Mark Lawrence, Mattia Righi, Zissis Samaras, Robert Sausen, Jaakko Kukkonen, and Ranjeet Sokhi
Atmos. Chem. Phys., 16, 6041–6070, https://doi.org/10.5194/acp-16-6041-2016, https://doi.org/10.5194/acp-16-6041-2016, 2016
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Aerosol composition in Europe was simulated by four chemistry transport models and compared to observations to identify the most prominent areas for model improvement. Notable differences were found between the models' predictions, attributable to different treatment or omission of aerosol sources and processes. All models underestimated the observed concentrations by 10–60 %, mostly due to under-predicting the carbonaceous and mineral particles and omitting the aerosol-bound water.
E. Dammers, C. Vigouroux, M. Palm, E. Mahieu, T. Warneke, D. Smale, B. Langerock, B. Franco, M. Van Damme, M. Schaap, J. Notholt, and J. W. Erisman
Atmos. Chem. Phys., 15, 12789–12803, https://doi.org/10.5194/acp-15-12789-2015, https://doi.org/10.5194/acp-15-12789-2015, 2015
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We present a new retrieval method for ammonia (NH3) concentrations and total columns from ground-based Fourier transform infrared (FTIR) observations. Observations from Bremen, Lauder, Réunion and Jungfraujoch are used to show the capabilities of the new retrieval. The developed retrieval provides a new way of obtaining time-resolved measurements and will be useful for understanding the dynamics of ammonia concentrations in the atmosphere and for satellite and model validation.
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
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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.
S. Fuzzi, U. Baltensperger, K. Carslaw, S. Decesari, H. Denier van der Gon, M. C. Facchini, D. Fowler, I. Koren, B. Langford, U. Lohmann, E. Nemitz, S. Pandis, I. Riipinen, Y. Rudich, M. Schaap, J. G. Slowik, D. V. Spracklen, E. Vignati, M. Wild, M. Williams, and S. Gilardoni
Atmos. Chem. Phys., 15, 8217–8299, https://doi.org/10.5194/acp-15-8217-2015, https://doi.org/10.5194/acp-15-8217-2015, 2015
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Particulate matter (PM) constitutes one of the most challenging problems both for air quality and climate change policies. This paper reviews the most recent scientific results on the issue and the policy needs that have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-PM interactions and the effects of PM on human health and the environment.
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
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The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
S. Banzhaf, M. Schaap, R. Kranenburg, A. M. M. Manders, A. J. Segers, A. J. H. Visschedijk, H. A. C. Denier van der Gon, J. J. P. Kuenen, E. van Meijgaard, L. H. van Ulft, J. Cofala, and P. J. H. Builtjes
Geosci. Model Dev., 8, 1047–1070, https://doi.org/10.5194/gmd-8-1047-2015, https://doi.org/10.5194/gmd-8-1047-2015, 2015
T. Vlemmix, H. J. Eskes, A. J. M. Piters, M. Schaap, F. J. Sauter, H. Kelder, and P. F. Levelt
Atmos. Chem. Phys., 15, 1313–1330, https://doi.org/10.5194/acp-15-1313-2015, https://doi.org/10.5194/acp-15-1313-2015, 2015
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Ground-based remote sensing measurements of nitrogen dioxide are compared to the Lotos-Euros air quality (AQ) model. Measurements were taken in the Netherlands with a UV-Vis spectrometer which observes scattered sunlight under different elevation viewing angles. On average, a surprisingly good agreement is found. Perhaps most striking is the agreement between model and observations as a function of wind direction. This demonstrates the quality of the AQ model and underlying emission inventory.
P. Bergamaschi, M. Corazza, U. Karstens, M. Athanassiadou, R. L. Thompson, I. Pison, A. J. Manning, P. Bousquet, A. Segers, A. T. Vermeulen, G. Janssens-Maenhout, M. Schmidt, M. Ramonet, F. Meinhardt, T. Aalto, L. Haszpra, J. Moncrieff, M. E. Popa, D. Lowry, M. Steinbacher, A. Jordan, S. O'Doherty, S. Piacentino, and E. Dlugokencky
Atmos. Chem. Phys., 15, 715–736, https://doi.org/10.5194/acp-15-715-2015, https://doi.org/10.5194/acp-15-715-2015, 2015
M. Alexe, P. Bergamaschi, A. Segers, R. Detmers, A. Butz, O. Hasekamp, S. Guerlet, R. Parker, H. Boesch, C. Frankenberg, R. A. Scheepmaker, E. Dlugokencky, C. Sweeney, S. C. Wofsy, and E. A. Kort
Atmos. Chem. Phys., 15, 113–133, https://doi.org/10.5194/acp-15-113-2015, https://doi.org/10.5194/acp-15-113-2015, 2015
T. P. C. van Noije, P. Le Sager, A. J. Segers, P. F. J. van Velthoven, M. C. Krol, W. Hazeleger, A. G. Williams, and S. D. Chambers
Geosci. Model Dev., 7, 2435–2475, https://doi.org/10.5194/gmd-7-2435-2014, https://doi.org/10.5194/gmd-7-2435-2014, 2014
J. Soares, A. Kousa, J. Kukkonen, L. Matilainen, L. Kangas, M. Kauhaniemi, K. Riikonen, J.-P. Jalkanen, T. Rasila, O. Hänninen, T. Koskentalo, M. Aarnio, C. Hendriks, and A. Karppinen
Geosci. Model Dev., 7, 1855–1872, https://doi.org/10.5194/gmd-7-1855-2014, https://doi.org/10.5194/gmd-7-1855-2014, 2014
A. Mues, J. Kuenen, C. Hendriks, A. Manders, A. Segers, Y. Scholz, C. Hueglin, P. Builtjes, and M. Schaap
Atmos. Chem. Phys., 14, 939–955, https://doi.org/10.5194/acp-14-939-2014, https://doi.org/10.5194/acp-14-939-2014, 2014
S. Banzhaf, M. Schaap, R. J. Wichink Kruit, H. A. C. Denier van der Gon, R. Stern, and P. J. H. Builtjes
Atmos. Chem. Phys., 13, 11675–11693, https://doi.org/10.5194/acp-13-11675-2013, https://doi.org/10.5194/acp-13-11675-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
Related subject area
Atmospheric sciences
SCIATRAN software package (V4.6): update and further development of aerosol, clouds, surface reflectance databases and models
Deep learning models for generation of precipitation maps based on numerical weather prediction
An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing
On the use of Infrared Atmospheric Sounding Interferometer (IASI) spectrally resolved radiances to test the EC-Earth climate model (v3.3.3) in clear-sky conditions
Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation
The impact of altering emission data precision on compression efficiency and accuracy of simulations of the community multiscale air quality model
AerSett v1.0: a simple and straightforward model for the settling speed of big spherical atmospheric aerosols
Optimization of weather forecasting for cloud cover over the European domain using the meteorological component of the Ensemble for Stochastic Integration of Atmospheric Simulations version 1.0
Bayesian transdimensional inverse reconstruction of the Fukushima Daiichi caesium 137 release
Implementation of HONO into the chemistry–climate model CHASER (V4.0): roles in tropospheric chemistry
Isoprene and monoterpene simulations using the chemistry–climate model EMAC (v2.55) with interactive vegetation from LPJ-GUESS (v4.0)
A modern-day Mars climate in the Met Office Unified Model: dry simulations
The AirGAM 2022r1 air quality trend and prediction model
Evaluation of a cloudy cold-air pool in the Columbia River basin in different versions of the High-Resolution Rapid Refresh (HRRR) model
Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble
Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium
Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range
ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application
ISAT v2.0: An integrated tool for nested domain configurations and model-ready emission inventories for WRF-AQM
Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM
The E3SM Diagnostics Package (E3SM Diags v2.7): a Python-based diagnostics package for Earth system model evaluation
A method for transporting cloud-resolving model variance in a multiscale modeling framework
The Mission Support System (MSS v7.0.4) and its use in planning for the SouthTRAC aircraft campaign
GENerator of reduced Organic Aerosol mechanism (GENOA v1.0): an automatic generation tool of semi-explicit mechanisms
Representing chemical history in ozone time-series predictions – a model experiment study building on the MLAir (v1.5) deep learning framework
Evaluation of high-resolution predictions of fine particulate matter and its composition in an urban area using PMCAMx-v2.0
A local data assimilation method (Local DA v1.0) and its application in a simulated typhoon case
Improved advection, resolution, performance, and community access in the new generation (version 13) of the high-performance GEOS-Chem global atmospheric chemistry model (GCHP)
Lightning assimilation in the WRF model (Version 4.1.1): technique updates and assessment of the applications from regional to hemispheric scales
Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a)
Development of an LSTM broadcasting deep-learning framework for regional air pollution forecast improvement
A local particle filter and its Gaussian mixture extension implemented with minor modifications to the LETKF
A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions
Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)
An Improved Parameterization of Sea Spray-Mediated Heat Flux Using Gaussian Quadrature: Case Studies with a Coupled CFSv2.0-WW3 System
Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona city: a case study with CALIOPE-Urban v1.0
Evaluation of the NAQFC driven by the NOAA Global Forecast System (version 16): comparison with the WRF-CMAQ during the summer 2019 FIREX-AQ campaign
A machine learning emulator for Lagrangian particle dispersion model footprints: a case study using NAME
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation
Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China
A lumped species approach for the simulation of secondary organic aerosol production from intermediate-volatility organic compounds (IVOCs): application to road transport in PMCAMx-iv (v1.0)
Accelerating models for multiphase chemical kinetics through machine learning with polynomial chaos expansion and neural networks
TrackMatcher – a tool for finding intercepts in tracks of geographical positions
Recovery of sparse urban greenhouse gas emissions
A method for generating a quasi-linear convective system suitable for observing system simulation experiments
A dynamic ammonia emission model and the online coupling with WRF-Chem (WRF-SoilN-Chem v1.0): development and evaluation
Tropospheric transport and unresolved convection: numerical experiments with CLaMS 2.0/MESSy
AMORE-Isoprene v1.0: A new reduced mechanism for gas-phase isoprene oxidation
MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling
A preliminary evaluation of FY-4A visible radiance data assimilation by the WRF (ARW v4.1.1)/DART (Manhattan release v9.8.0)-RTTOV (v12.3) system for a tropical storm case
Linlu Mei, Vladimir Rozanov, Alexei Rozanov, and John P. Burrows
Geosci. Model Dev., 16, 1511–1536, https://doi.org/10.5194/gmd-16-1511-2023, https://doi.org/10.5194/gmd-16-1511-2023, 2023
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This paper summarizes recent developments of aerosol, cloud and surface reflectance databases and models in the framework of the software package SCIATRAN. These updates and developments extend the capabilities of the radiative transfer modeling, especially by accounting for different kinds of vertical inhomogeneties. Vertically inhomogeneous clouds and different aerosol types can be easily accounted for within SCIATRAN (V4.6). The widely used surface models and databases are now available.
Adrian Rojas-Campos, Michael Langguth, Martin Wittenbrink, and Gordon Pipa
Geosci. Model Dev., 16, 1467–1480, https://doi.org/10.5194/gmd-16-1467-2023, https://doi.org/10.5194/gmd-16-1467-2023, 2023
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Our paper presents an alternative approach for generating high-resolution precipitation maps based on the nonlinear combination of the complete set of variables of the numerical weather predictions. This process combines the super-resolution task with the bias correction in a single step, generating high-resolution corrected precipitation maps with a lead time of 3 h. We used using deep learning algorithms to combine the input information and increase the accuracy of the precipitation maps.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev., 16, 1459–1466, https://doi.org/10.5194/gmd-16-1459-2023, https://doi.org/10.5194/gmd-16-1459-2023, 2023
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We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry–climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated with aviation ozone is 7.6 % higher when using the less recent version of the data.
Stefano Della Fera, Federico Fabiano, Piera Raspollini, Marco Ridolfi, Ugo Cortesi, Flavio Barbara, and Jost von Hardenberg
Geosci. Model Dev., 16, 1379–1394, https://doi.org/10.5194/gmd-16-1379-2023, https://doi.org/10.5194/gmd-16-1379-2023, 2023
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The long-term comparison between observed and simulated outgoing longwave radiances represents a strict test to evaluate climate model performance. In this work, 9 years of synthetic spectrally resolved radiances, simulated online on the basis of the atmospheric fields predicted by the EC-Earth global climate model (v3.3.3) in clear-sky conditions, are compared to IASI spectral radiance climatology in order to detect model biases in temperature and humidity at different atmospheric levels.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023, https://doi.org/10.5194/gmd-16-1359-2023, 2023
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Aerosol has a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosol. We present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the Cloud-Aerosol Lidar with Orthogonal Polarization overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Ocean.
Michael S. Walters and David C. Wong
Geosci. Model Dev., 16, 1179–1190, https://doi.org/10.5194/gmd-16-1179-2023, https://doi.org/10.5194/gmd-16-1179-2023, 2023
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A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
Sylvain Mailler, Laurent Menut, Arineh Cholakian, and Romain Pennel
Geosci. Model Dev., 16, 1119–1127, https://doi.org/10.5194/gmd-16-1119-2023, https://doi.org/10.5194/gmd-16-1119-2023, 2023
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Large or even
giantparticles of mineral dust exist in the atmosphere but, so far, solving an non-linear equation was needed to calculate the speed at which they fall in the atmosphere. The model we present, AerSett v1.0 (AERosol SETTling version 1.0), provides a new and simple way of calculating their free-fall velocity in the atmosphere, which will be useful to anyone trying to understand and represent adequately the transport of giant dust particles by the wind.
Yen-Sen Lu, Garrett H. Good, and Hendrik Elbern
Geosci. Model Dev., 16, 1083–1104, https://doi.org/10.5194/gmd-16-1083-2023, https://doi.org/10.5194/gmd-16-1083-2023, 2023
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The Weather Forecasting and Research (WRF) model consists of many parameters and options that can be adapted to different conditions. This expansive sensitivity study uses a large-scale simulation system to determine the most suitable options for predicting cloud cover in Europe for deterministic and probabilistic weather predictions for day-ahead forecasting simulations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Phuc Thi Minh Ha, Yugo Kanaya, Fumikazu Taketani, Maria Dolores Andrés Hernández, Benjamin Schreiner, Klaus Pfeilsticker, and Kengo Sudo
Geosci. Model Dev., 16, 927–960, https://doi.org/10.5194/gmd-16-927-2023, https://doi.org/10.5194/gmd-16-927-2023, 2023
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HONO affects tropospheric oxidizing capacity; thus, it is implemented into the chemistry–climate model CHASER. The model substantially underpredicts daytime HONO, while nitrate photolysis on surfaces can supplement the daytime HONO budget. Current HONO chemistry predicts reductions of 20.4 % for global tropospheric NOx, 40–67 % for OH, and 30–45 % for O3 in the summer North Pacific. In contrast, OH and O3 winter levels in China are greatly enhanced.
Ryan Vella, Matthew Forrest, Jos Lelieveld, and Holger Tost
Geosci. Model Dev., 16, 885–906, https://doi.org/10.5194/gmd-16-885-2023, https://doi.org/10.5194/gmd-16-885-2023, 2023
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Biogenic volatile organic compounds (BVOCs) are released by vegetation and have a major impact on atmospheric chemistry and aerosol formation. Non-interacting vegetation constrains the majority of numerical models used to estimate global BVOC emissions, and thus, the effects of changing vegetation on emissions are not addressed. In this work, we replace the offline vegetation with dynamic vegetation states by linking a chemistry–climate model with a global dynamic vegetation model.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
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We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Sam-Erik Walker, Sverre Solberg, Philipp Schneider, and Cristina Guerreiro
Geosci. Model Dev., 16, 573–595, https://doi.org/10.5194/gmd-16-573-2023, https://doi.org/10.5194/gmd-16-573-2023, 2023
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We have developed a statistical model for estimating trends in the daily air quality observations of NO2, O3, PM10 and PM2.5, adjusting for trends and short-term variations in meteorology. The model is general and may also be used for prediction purposes, including forecasting. It has been applied in a recent comprehensive study in Europe. Significant declines are shown for the pollutants from 2005 to 2019, mainly due to reductions in emissions not attributable to changes in meteorology.
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023, https://doi.org/10.5194/gmd-16-597-2023, 2023
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Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold-air pools difficult to integrate into the electrical grid. By evaluating three versions of NOAA’s High-Resolution Rapid Refresh model, we demonstrate how model developments targeted during the second Wind Forecast Improvement Project improve the forecast of a persistent cold-air pool event.
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
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We focus on the challenges associated with comparing atmospheric composition models with satellite products such as tropospheric NO2 columns. The aim is to highlight the methodological difficulties and propose sound ways of doing such comparisons. Building on the comparisons, a new satellite product is proposed and made available, which takes advantage of higher-resolution, regional atmospheric modelling to improve estimates of troposheric NO2 columns over Europe.
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023, https://doi.org/10.5194/gmd-16-479-2023, 2023
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High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and evaluated using meteorological data and in situ, airborne, and spaceborne NO2 measurements. An intercomparison of model, aircraft, and TROPOMI NO2 columns is conducted to characterize biases in versions 1.3.1 and 2.3.1 of the satellite product. A mass balance method is implemented to provide improved emissions for simulating NO2 distribution over the study area.
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023, https://doi.org/10.5194/gmd-16-251-2023, 2023
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The production of wind energy is increasing rapidly and relies heavily on atmospheric conditions. To ensure power grid stability, accurate predictions of wind speed are needed, especially in the short range and for extreme wind speed ranges. In this work, we demonstrate the forecasting skills of a data-driven deep learning model with model adaptations to suit higher wind speed ranges. The resulting model can be applied to other data and parameters, too, to improve nowcasting predictions.
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023, https://doi.org/10.5194/gmd-16-47-2023, 2023
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We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
Kun Wang, Chao Gao, Haofan Wang, Kai Wu, Qingqing Tong, Mo Dan, Kaiyun Liu, and Xiaohui Ji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-266, https://doi.org/10.5194/gmd-2022-266, 2023
Revised manuscript accepted for GMD
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This study established an easy-to-use and integrated framework on model ready emission inventory for Weather Research and Forecasting (WRF)-Air quality numerical model (AQM). A free tool named ISAT (Inventory Spatial Allocation Tool) was developed based on this framework. ISAT help user complete the workflow from WRF nested domain configuration to model ready emission inventory for AQM with regional emission inventory and shapefile for target region.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
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Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Walter Hannah and Kyle Pressel
Geosci. Model Dev., 15, 8999–9013, https://doi.org/10.5194/gmd-15-8999-2022, https://doi.org/10.5194/gmd-15-8999-2022, 2022
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A multiscale modeling framework couples two models of the atmosphere that each cover different scale ranges. Traditionally, fluctuations in the small-scale model are not transported by the flow on the large-scale model grid, but this is hypothesized to be responsible for a persistent, unphysical checkerboard pattern. A method is presented to facilitate the transport of these small-scale fluctuations, analogous to how small-scale clouds and turbulence are transported in the real atmosphere.
Reimar Bauer, Jens-Uwe Grooß, Jörn Ungermann, May Bär, Markus Geldenhuys, and Lars Hoffmann
Geosci. Model Dev., 15, 8983–8997, https://doi.org/10.5194/gmd-15-8983-2022, https://doi.org/10.5194/gmd-15-8983-2022, 2022
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The Mission Support System (MSS) is an open source software package that has been used for planning flight tracks of scientific aircraft in multiple measurement campaigns during the last decade. Here, we describe the MSS software and its use during the SouthTRAC measurement campaign in 2019. As an example for how the MSS software is used in conjunction with many datasets, we describe the planning of a single flight probing orographic gravity waves propagating up into the lower mesosphere.
Zhizhao Wang, Florian Couvidat, and Karine Sartelet
Geosci. Model Dev., 15, 8957–8982, https://doi.org/10.5194/gmd-15-8957-2022, https://doi.org/10.5194/gmd-15-8957-2022, 2022
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Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Felix Kleinert, Lukas H. Leufen, Aurelia Lupascu, Tim Butler, and Martin G. Schultz
Geosci. Model Dev., 15, 8913–8930, https://doi.org/10.5194/gmd-15-8913-2022, https://doi.org/10.5194/gmd-15-8913-2022, 2022
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We examine the effects of spatially aggregated upstream information as input for a deep learning model forecasting near-surface ozone levels. Using aggregated data from one upstream sector (45°) improves the forecast by ~ 10 % for 4 prediction days. Three upstream sectors improve the forecasts by ~ 14 % on the first 2 d only. Our results serve as an orientation for other researchers or environmental agencies focusing on pointwise time-series predictions, for example, due to regulatory purposes.
Brian T. Dinkelacker, Pablo Garcia Rivera, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Geosci. Model Dev., 15, 8899–8912, https://doi.org/10.5194/gmd-15-8899-2022, https://doi.org/10.5194/gmd-15-8899-2022, 2022
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The performance of a chemical transport model in reproducing PM2.5 concentrations and composition was evaluated at the finest scale using measurements from regulatory sites as well as a network of low-cost monitors. Total PM2.5 mass is reproduced well by the model during the winter when compared to regulatory measurements, but in the summer PM2.5 is underpredicted, mainly due to difficulties in reproducing regional secondary organic aerosol levels.
Shizhang Wang and Xiaoshi Qiao
Geosci. Model Dev., 15, 8869–8897, https://doi.org/10.5194/gmd-15-8869-2022, https://doi.org/10.5194/gmd-15-8869-2022, 2022
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A local data assimilation scheme (Local DA v1.0) was proposed to leverage the advantage of hybrid covariance, multiscale localization, and parallel computation. The Local DA can perform covariance localization in model space, observation space, or both spaces. The Local DA that used the hybrid covariance and double-space localization produced the lowest analysis and forecast errors among all observing system simulation experiments.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
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Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
Geosci. Model Dev., 15, 8561–8579, https://doi.org/10.5194/gmd-15-8561-2022, https://doi.org/10.5194/gmd-15-8561-2022, 2022
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A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park
Geosci. Model Dev., 15, 8541–8559, https://doi.org/10.5194/gmd-15-8541-2022, https://doi.org/10.5194/gmd-15-8541-2022, 2022
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The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.
Haochen Sun, Jimmy C. H. Fung, Yiang Chen, Zhenning Li, Dehao Yuan, Wanying Chen, and Xingcheng Lu
Geosci. Model Dev., 15, 8439–8452, https://doi.org/10.5194/gmd-15-8439-2022, https://doi.org/10.5194/gmd-15-8439-2022, 2022
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This study developed a novel deep-learning layer, the broadcasting layer, to build an end-to-end LSTM-based deep-learning model for regional air pollution forecast. By combining the ground observation, WRF-CMAQ simulation, and the broadcasting LSTM deep-learning model, forecast accuracy has been significantly improved when compared to other methods. The broadcasting layer and its variants can also be applied in other research areas to supersede the traditional numerical interpolation methods.
Shunji Kotsuki, Takemasa Miyoshi, Keiichi Kondo, and Roland Potthast
Geosci. Model Dev., 15, 8325–8348, https://doi.org/10.5194/gmd-15-8325-2022, https://doi.org/10.5194/gmd-15-8325-2022, 2022
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Data assimilation plays an important part in numerical weather prediction (NWP) in terms of combining forecasted states and observations. While data assimilation methods in NWP usually assume the Gaussian error distribution, some variables in the atmosphere, such as precipitation, are known to have non-Gaussian error statistics. This study extended a widely used ensemble data assimilation algorithm to enable the assimilation of more non-Gaussian observations.
Martin Vojta, Andreas Plach, Rona L. Thompson, and Andreas Stohl
Geosci. Model Dev., 15, 8295–8323, https://doi.org/10.5194/gmd-15-8295-2022, https://doi.org/10.5194/gmd-15-8295-2022, 2022
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In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Ruizi Shi and Fanghua Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-233, https://doi.org/10.5194/gmd-2022-233, 2022
Revised manuscript accepted for GMD
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Based on Gaussian Quadrature method, a fast parameterization scheme of sea spray-mediated heat flux is developed. Compared with the widely-used single-radius scheme, the new scheme shows a better agreement with the full spectrum integral of spray-flux. The new scheme is evaluated in a coupled modeling system, and the simulations of sea surface temperature, wind speed and wave height are improved. Thereby, the new scheme has a great potential to be used in coupled modeling systems.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodríguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
EGUsphere, https://doi.org/10.5194/egusphere-2022-1147, https://doi.org/10.5194/egusphere-2022-1147, 2022
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The goal of this work is to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data-fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study able us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
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This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Elena Fillola, Raul Santos-Rodriguez, Alistair Manning, Simon O'Doherty, and Matt Rigby
EGUsphere, https://doi.org/10.5194/egusphere-2022-1174, https://doi.org/10.5194/egusphere-2022-1174, 2022
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Lagrangian particle dispersion models are used extensively for the estimation of greenhouse gas (GHG) fluxes using atmospheric observations. However, these models do not scale well as data volumes increase. Here, we develop a proof-of-concept machine learning emulator that can produce outputs similar to those of the dispersion model, but 50,000 times faster, using only meteorological inputs. This works demonstrates the potential of machine learning to accelerate GHG estimations across the globe.
Zhiquan Liu, Chris Snyder, Jonathan J. Guerrette, Byoung-Joo Jung, Junmei Ban, Steven Vahl, Yali Wu, Yannick Trémolet, Thomas Auligné, Benjamin Ménétrier, Anna Shlyaeva, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 15, 7859–7878, https://doi.org/10.5194/gmd-15-7859-2022, https://doi.org/10.5194/gmd-15-7859-2022, 2022
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JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the MPAS model, was publicly released for community use. This article describes JEDI-MPAS's implementation of the ensemble–variational DA technique and demonstrates its robustness and credible performance by incrementally adding three types of microwave radiances (clear-sky AMSU-A, all-sky AMSU-A, clear-sky MHS) to a non-radiance DA experiment. We intend to periodically release new and improved versions of JEDI-MPAS in upcoming years.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
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This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Stella E. I. Manavi and Spyros N. Pandis
Geosci. Model Dev., 15, 7731–7749, https://doi.org/10.5194/gmd-15-7731-2022, https://doi.org/10.5194/gmd-15-7731-2022, 2022
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The paper describes the first step towards the development of a simulation framework for the chemistry and secondary organic aerosol production of intermediate-volatility organic compounds (IVOCs). These compounds can be a significant source of organic particulate matter. Our approach treats IVOCs as lumped compounds that retain their chemical characteristics. Estimated IVOC emissions from road transport were a factor of 8 higher than emissions used in previous applications.
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
EGUsphere, https://doi.org/10.5194/egusphere-2022-1093, https://doi.org/10.5194/egusphere-2022-1093, 2022
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Kinetic multi-layer models (KM) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieve high correlations. The surrogate models run orders of magnitudes faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Peter Bräuer and Matthias Tesche
Geosci. Model Dev., 15, 7557–7572, https://doi.org/10.5194/gmd-15-7557-2022, https://doi.org/10.5194/gmd-15-7557-2022, 2022
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This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting of data in the vicinity of intersections to achieve the optimal combination of various data sets.
Benjamin Zanger, Jia Chen, Man Sun, and Florian Dietrich
Geosci. Model Dev., 15, 7533–7556, https://doi.org/10.5194/gmd-15-7533-2022, https://doi.org/10.5194/gmd-15-7533-2022, 2022
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Gaussian priors (GPs) used in least squares inversion do not reflect the true distributions of greenhouse gas emissions well. A method that does not rely on GPs is sparse reconstruction (SR). We show that necessary conditions for SR are satisfied for cities and that the application of a wavelet transform can further enhance sparsity. We apply the theory of compressed sensing to SR. Our results show that SR needs fewer measurements and is superior for assessing unknown emitters compared to GPs.
Jonathan D. Labriola and Louis J. Wicker
EGUsphere, https://doi.org/10.5194/egusphere-2022-1033, https://doi.org/10.5194/egusphere-2022-1033, 2022
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Observing system simulation experiments (OSSEs) are simulated case studies used to understand how different assimilated weather observations impact forecast skill. This study introduces the methods used to create an OSSE for a tornadic quasi-linear convective system event. These steps provide an opportunity to simulate a realistic high-impact weather event and can be used to encourage a more diverse set of OSSEs.
Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-231, https://doi.org/10.5194/gmd-2022-231, 2022
Revised manuscript accepted for GMD
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Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Paul Konopka, Mengchu Tao, Marc von Hobe, Lars Hoffmann, Corinna Kloss, Fabrizio Ravegnani, C. Michael Volk, Valentin Lauther, Andreas Zahn, Peter Hoor, and Felix Ploeger
Geosci. Model Dev., 15, 7471–7487, https://doi.org/10.5194/gmd-15-7471-2022, https://doi.org/10.5194/gmd-15-7471-2022, 2022
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Pure trajectory-based transport models driven by meteorology derived from reanalysis products (ERA5) take into account only the resolved, advective part of transport. That means neither mixing processes nor unresolved subgrid-scale advective processes like convection are included. The Chemical Lagrangian Model of the Stratosphere (CLaMS) includes these processes. We show that isentropic mixing dominates unresolved transport. The second most important transport process is unresolved convection.
Forwood Wiser, Bryan Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-240, https://doi.org/10.5194/gmd-2022-240, 2022
Revised manuscript accepted for GMD
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We developed an automated method, AMORE, to simplify complex chemical mechanisms. We applied AMORE to the oxidation mechanism for isoprene, an abundant biogenic volatile organic compound. Using AMORE with minimal manual adjustments to the output, we created the AMORE-isoprene mechanism, with improved accuracy and similar size to other reduced isoprene mechanisms. AMORE-Isoprene improved the accuracy of EPA’s CMAQ model compared to observations.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Yongbo Zhou, Yubao Liu, Zhaoyang Huo, and Yang Li
Geosci. Model Dev., 15, 7397–7420, https://doi.org/10.5194/gmd-15-7397-2022, https://doi.org/10.5194/gmd-15-7397-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Cited articles
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