110 results on '"Bergman, Tommi"'
Search Results
2. ESM data-set on multiple ocean NET simulations
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Partanen, Antti-Ilari, Bergman, Tommi, Partanen, Antti-Ilari, and Bergman, Tommi
- Abstract
This dataset, resulting from Task 4.5 quantifies the potential of ocean-based negative emission technologies (NETs) using Earth System Models (ESMs). The dataset consists of simulations of ocean liming and direct CO2 removal from seawater. The ocean liming scenarios utilize excess CaO and cement production capacities from the EU, China, and the US, exploring their application for ocean alkalinization and gauging termination effects. Simulations ran from 2015-2100 using NorESM2-LM, EC-Earth3-CC, and AWI-CM models. This comprehensive dataset informs on the efficacy of ocean-based NETs and provides insights for future climate mitigation strategies, aligning with the Paris Agreement goals. It facilitates further analysis and supports ongoing research in global carbon cycle feedbacks of ocean-based NETs.
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- 2024
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3. Biomass burning aerosols in most climate models are too absorbing
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Brown, Hunter, Liu, Xiaohong, Pokhrel, Rudra, Murphy, Shane, Lu, Zheng, Saleh, Rawad, Mielonen, Tero, Kokkola, Harri, Bergman, Tommi, Myhre, Gunnar, Skeie, Ragnhild B., Watson-Paris, Duncan, Stier, Philip, Johnson, Ben, Bellouin, Nicolas, Schulz, Michael, Vakkari, Ville, Beukes, Johan Paul, van Zyl, Pieter Gideon, Liu, Shang, and Chand, Duli
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- 2021
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4. Biomass Burning Emissions Analysis Based on MODIS AOD and AeroCom Multi-Model Simulations.
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Petrenko, Mariya, Kahn, Ralph, Mian Chin, Bauer, Susanne E., Bergman, Tommi, Huisheng Bian, Curci, Gabriele, Johnson, Ben, Kaiser, Johannes W., Kipling, Zak, Kokkola, Harri, Xiaohong Liu, Mezuman, Keren, Mielonen, Tero, Myhre, Gunnar, Xiaohua Pan, Protonotariou, Anna, Remy, Samuel, Skeie, Ragnhild Bieltvedt, and Stier, Philip
- Abstract
We assessed the performance of 11 AeroCom models in simulating biomass burning (BB) smoke aerosol optical depth (AOD) in the vicinity of fires over 13 regions globally. By comparing multi-model outputs and satellite observations, we aim to: (1) assess the factors affecting model-simulated, BB AOD performance using a common emissions inventory, (2) identify regions where the emission inventory might underestimate or overestimate smoke sources, and (3) identify anomalies that might point to model-specific smoke emission, dispersion, or removal, issues. Using satellite-derived AOD snapshots to constrain source strength works best where BB smoke from active sources dominates background aerosol, such as in boreal forest regions and over South America and southern-hemisphere Africa. The comparison is poor where 40 the total AOD is low, as in many agricultural burning areas or where background, non-BB AOD is high, such as parts of India and China. Many inter-model BB AOD differences can be traced to differences in model-assumed values for the mass ratio of organic aerosol to organic carbon, the BB aerosol mass extinction efficiency, and the aerosol loss-rate. The results point to the need for increased numbers of available BB cases for study in some regions, and especially to the need for more extensive, regional45 to-global-scale measurements of aerosol loss rates and of detailed microphysical and optical properties; this would better constrain models and help distinguish BB from other aerosols in satellite retrievals. More generally, there is the need for additional efforts at constraining aerosol source strength and other model attributes with multi-platform observations. [ABSTRACT FROM AUTHOR]
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- 2024
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5. Building on Communities to Further Software Sustainability
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Fouilloux, Anne, primary, Iaquinta, Jean, additional, Gupta, Alok Kumar, additional, Struthers, Hamish, additional, Landgren, Oskar, additional, Dwarakanath, Prashanth, additional, Bergman, Tommi, additional, and He, Yanchun, additional
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- 2023
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6. Building on Communities to Further Software Sustainability
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Fouilloux, Anne, Iaquinta, Jean, Gupta, Alok Kumar, Struthers, Hamish, Landgren, Oskar, Dwarakanath Rao, Prashanth, Bergman, Tommi, He, Yanchun, Fouilloux, Anne, Iaquinta, Jean, Gupta, Alok Kumar, Struthers, Hamish, Landgren, Oskar, Dwarakanath Rao, Prashanth, Bergman, Tommi, and He, Yanchun
- Abstract
The Nordic e-Infrastructure Collaboration on Earth System Modeling Tools is a small community comprising members with diverse backgrounds, skills, and interests. Largely dependent on temporary staff to develop, operate, and maintain large scientific codes, this community devised strategies to enhance software reusability and sustainability. These strategies include collaborating with other communities for support, adopting Open Science as well as findable, accessible, interoperable, and reusable principles to optimize resource usage, growing essential knowledge within the community, and setting up a community of practice to facilitate onboarding and offboarding. The strategies also promote inclusiveness, foster external collaboration, and recognize technical contributions., Funding Agencies|Nordic e-Infrastructure Collaboration; EOSC-Nordic Horizon 2020 project [857652]
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- 2023
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7. Earth system impacts of a realistic ocean alkalinization deployment scenario
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Bergman, Tommi, primary, Bourgeois, Timothée, additional, Schwinger, Jörg, additional, Foteinis, Spyros, additional, Renforth, Phil, additional, and Partanen, Antti-Ilari, additional
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- 2023
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8. Towards understanding the effect of parametric aerosol uncertainty on climate using a chemical transport model perturbed parameter ensemble.
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Bouchahmoud, Meryem, primary, Bergman, Tommi, additional, and Williamson, Christina, additional
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- 2023
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9. Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation
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Fanourgakis, George S, Kanakidou, Maria, Nenes, Athanasios, Bauer, Susanne E, Bergman, Tommi, Carslaw, Ken S, Grini, Alf, Hamilton, Douglas S, Johnson, Jill S, Karydis, Vlassis A, Kirkevag, Alf, Kodros, John K, Lohmann, Ulrike, Luo, Gan, Makkonen, Risto, Matsui, Hitoshi, Neubauer, David, Pierce, Jeffrey R, Schmale, Julia, Stier, Philip, Tsigaridis, Kostas, van Noije, Twan, Wang, Hailong, Watson-Parris, Duncan, Westervelt, Daniel M, Yang, Yang, Yoshioka, Masaru, Daskalakis, Nikos, Decesari, Stefano, Gysel-Beer, Martin, Kalivitis, Nikos, Liu, Xiaohong, Mahowald, Natalie M, Myriokefalitakis, Stelios, Schrodner, Roland, Sfakianaki, Maria, Tsimpidi, Alexandra P, Wu, Mingxuan, and Yu, Fangqun
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Meteorology And Climatology - Abstract
A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.
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- 2019
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10. Ions and Charged Aerosol Particles in a Native Australian Eucalypt Forest
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Suni, Tanja, Kulmala, Markku, Sogacheva, L., Hirsikko, Anne, Bergman, Tommi, Aalto, Pasi, Vana, Marko, Horrak, Urmas, Mirme, Aadu, Mirme, S., Laakso, Lauri, Dal Maso, Miikka, Leuning, Ray, Cleugh, Helen, Zegelin, Steve, Hughes, Dale, Hurley, Richard, van Gorsel, Eva, Kitchen, Mark, Keywood, Melita, Ward, Jason, Hakola, Hannele, Bäck, Jaana, Tadros, Carol, Twining, John, Paatero, Jussi, O'Dowd, Colin D., editor, and Wagner, Paul E., editor
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- 2007
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11. Comparison of particle number size distribution trends in ground measurements and climate models
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Leinonen, Ville, Kokkola, Harri, Yli-Juuti, Taina, Mielonen, Tero, Kühn, Thomas, Nieminen, Tuomo, Heikkinen, Simo, Miinalainen, Tuuli, Bergman, Tommi, Carslaw, Ken, Decesari, Stefano, Fiebig, Markus, Hussein, Tareq, Kivekäs, Niku, Krejci, Radovan, Kulmala, Markku, Leskinen, Ari, Massling, Andreas, Mihalopoulos, Nikos, Mulcahy, Jane P., Noe, Steffen M., van Noije, Twan, O'Connor, Fiona M., O'Dowd, Colin, Olivie, Dirk, Pernov, Jakob B., Petäjä, Tuukka, Seland, Øyvind, Schulz, Michael, Scott, Catherine E., Skov, Henrik, Swietlicki, Erik, Tuch, Thomas, Wiedensohler, Alfred, Virtanen, Annele, Mikkonen, Santtu, Global Atmosphere-Earth surface feedbacks, Institute for Atmospheric and Earth System Research (INAR), and Air quality research group
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SECTIONAL AEROSOL MODULE ,1171 Geosciences ,GLOBAL ANALYSIS ,WIND-SPEED ,LONG-TERM ,ATMOSPHERIC AEROSOL ,SULFUR EMISSIONS ,DECADAL TRENDS ,ORGANIC AEROSOL ,114 Physical sciences ,LIFE-CYCLE ,1172 Environmental sciences ,GAS-EXCHANGE - Abstract
Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.
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- 2022
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12. Comparison of particle number size distribution trends in ground measurements and climate models
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Leinonen, Ville, primary, Kokkola, Harri, additional, Yli-Juuti, Taina, additional, Mielonen, Tero, additional, Kühn, Thomas, additional, Nieminen, Tuomo, additional, Heikkinen, Simo, additional, Miinalainen, Tuuli, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Decesari, Stefano, additional, Fiebig, Markus, additional, Hussein, Tareq, additional, Kivekäs, Niku, additional, Krejci, Radovan, additional, Kulmala, Markku, additional, Leskinen, Ari, additional, Massling, Andreas, additional, Mihalopoulos, Nikos, additional, Mulcahy, Jane P., additional, Noe, Steffen M., additional, van Noije, Twan, additional, O'Connor, Fiona M., additional, O'Dowd, Colin, additional, Olivie, Dirk, additional, Pernov, Jakob B., additional, Petäjä, Tuukka, additional, Seland, Øyvind, additional, Schulz, Michael, additional, Scott, Catherine E., additional, Skov, Henrik, additional, Swietlicki, Erik, additional, Tuch, Thomas, additional, Wiedensohler, Alfred, additional, Virtanen, Annele, additional, and Mikkonen, Santtu, additional
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- 2022
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13. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Tintó Prims, Oriol, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Madsen, Marianne Sloth, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, Zhang, Qiong, Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Tintó Prims, Oriol, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Madsen, Marianne Sloth, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, and Zhang, Qiong
- Abstract
The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
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- 2022
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14. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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UCL - SST/ELI/ELIC - Earth & Climate, Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, v. Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Prims, Oriol Tintó, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Sloth Madsen, Marianne, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, Zhang, Qiong, UCL - SST/ELI/ELIC - Earth & Climate, Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, v. Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Prims, Oriol Tintó, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Sloth Madsen, Marianne, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, and Zhang, Qiong
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- 2022
15. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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Döscher, Ralf, primary, Acosta, Mario, additional, Alessandri, Andrea, additional, Anthoni, Peter, additional, Arsouze, Thomas, additional, Bergman, Tommi, additional, Bernardello, Raffaele, additional, Boussetta, Souhail, additional, Caron, Louis-Philippe, additional, Carver, Glenn, additional, Castrillo, Miguel, additional, Catalano, Franco, additional, Cvijanovic, Ivana, additional, Davini, Paolo, additional, Dekker, Evelien, additional, Doblas-Reyes, Francisco J., additional, Docquier, David, additional, Echevarria, Pablo, additional, Fladrich, Uwe, additional, Fuentes-Franco, Ramon, additional, Gröger, Matthias, additional, v. Hardenberg, Jost, additional, Hieronymus, Jenny, additional, Karami, M. Pasha, additional, Keskinen, Jukka-Pekka, additional, Koenigk, Torben, additional, Makkonen, Risto, additional, Massonnet, François, additional, Ménégoz, Martin, additional, Miller, Paul A., additional, Moreno-Chamarro, Eduardo, additional, Nieradzik, Lars, additional, van Noije, Twan, additional, Nolan, Paul, additional, O'Donnell, Declan, additional, Ollinaho, Pirkka, additional, van den Oord, Gijs, additional, Ortega, Pablo, additional, Prims, Oriol Tintó, additional, Ramos, Arthur, additional, Reerink, Thomas, additional, Rousset, Clement, additional, Ruprich-Robert, Yohan, additional, Le Sager, Philippe, additional, Schmith, Torben, additional, Schrödner, Roland, additional, Serva, Federico, additional, Sicardi, Valentina, additional, Sloth Madsen, Marianne, additional, Smith, Benjamin, additional, Tian, Tian, additional, Tourigny, Etienne, additional, Uotila, Petteri, additional, Vancoppenolle, Martin, additional, Wang, Shiyu, additional, Wårlind, David, additional, Willén, Ulrika, additional, Wyser, Klaus, additional, Yang, Shuting, additional, Yepes-Arbós, Xavier, additional, and Zhang, Qiong, additional
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- 2022
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16. A novel parameterization for wildfire plumes in LPJ-GUESS
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Nieradzik, Lars, primary and Bergman, Tommi, additional
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- 2022
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17. Supplementary material to "Comparison of particle number size distribution trends in ground measurements and climate models"
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Leinonen, Ville, primary, Kokkola, Harri, additional, Yli-Juuti, Taina, additional, Mielonen, Tero, additional, Kühn, Thomas, additional, Nieminen, Tuomo, additional, Heikkinen, Simo, additional, Miinalainen, Tuuli, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Decesari, Stefano, additional, Fiebig, Markus, additional, Hussein, Tareq, additional, Kivekäs, Niku, additional, Kulmala, Markku, additional, Leskinen, Ari, additional, Massling, Andreas, additional, Mihalopoulos, Nikos, additional, Mulcahy, Jane P., additional, Noe, Steffen M., additional, van Noije, Twan, additional, O'Connor, Fiona M., additional, O'Dowd, Colin, additional, Olivie, Dirk, additional, Pernov, Jakob B., additional, Petäjä, Tuukka, additional, Seland, Øyvind, additional, Schulz, Michael, additional, Scott, Catherine E., additional, Skov, Henrik, additional, Swietlicki, Erik, additional, Tuch, Thomas, additional, Wiedensohler, Alfred, additional, Virtanen, Annele, additional, and Mikkonen, Santtu, additional
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- 2022
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18. What Controls the Vertical Distribution of Aerosol? Relationships Between Process Sensitivity in HadGEM3-UKCA and Inter-Model Variation from AeroCom Phase II
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Kipling, Zak, Stier, Philip, Johnson, Colin E, Mann, Graham W, Bellouin, Nicolas, Bauer, Susanne E, Bergman, Tommi, Chin, Mian, Diehl, Thomas, Ghan, Steven J, and Tsigaridis, Kostas
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Meteorology And Climatology - Abstract
The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3-UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3-UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN >3 nm), while the profiles of larger particles (e.g. CN>100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. We also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.
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- 2016
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19. Description and evaluation of a secondary organic aerosol and new particle formation scheme within TM5-MP v1.2
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Bergman, Tommi, primary, Makkonen, Risto, additional, Schrödner, Roland, additional, Swietlicki, Erik, additional, Phillips, Vaughan T. J., additional, Le Sager, Philippe, additional, and van Noije, Twan, additional
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- 2022
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20. EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6
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van Noije, Twan, primary, Bergman, Tommi, additional, Le Sager, Philippe, additional, O'Donnell, Declan, additional, Makkonen, Risto, additional, Gonçalves-Ageitos, María, additional, Döscher, Ralf, additional, Fladrich, Uwe, additional, von Hardenberg, Jost, additional, Keskinen, Jukka-Pekka, additional, Korhonen, Hannele, additional, Laakso, Anton, additional, Myriokefalitakis, Stelios, additional, Ollinaho, Pirkka, additional, Pérez García-Pando, Carlos, additional, Reerink, Thomas, additional, Schrödner, Roland, additional, Wyser, Klaus, additional, and Yang, Shuting, additional
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- 2021
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21. Evaluation of natural aerosols in CRESCENDO Earth system models (ESMs): mineral dust
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Checa-Garcia, Ramiro, primary, Balkanski, Yves, additional, Albani, Samuel, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Cozic, Anne, additional, Dearden, Chris, additional, Marticorena, Beatrice, additional, Michou, Martine, additional, van Noije, Twan, additional, Nabat, Pierre, additional, O'Connor, Fiona M., additional, Olivié, Dirk, additional, Prospero, Joseph M., additional, Le Sager, Philippe, additional, Schulz, Michael, additional, and Scott, Catherine, additional
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- 2021
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22. Reply on RC2
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Bergman, Tommi, primary
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- 2021
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23. Summary of research paper published in Nature Communications titled: Biomass burning aerosols in most climate models are too absorbing
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Brown, Hunter, primary, Liu, Xiaohong, additional, Pokhrel, Rudra, additional, Murphy, Shane, additional, Lu, Zheng, additional, Saleh, Rawad, additional, Mielonen, Tero, additional, Kokkola, Harri, additional, Bergman, Tommi, additional, Myhre, Gunnar, additional, Skeie, Ragnhild B., additional, Watson-Parris, Duncan, additional, Stier, Philip, additional, Johnson, Ben, additional, Bellouin, Nicolas, additional, Schulz, Michael, additional, Vakkari, Ville, additional, Beukes, Johan Paul, additional, Van Zyl, Pieter Gideon, additional, Liu, Shang, additional, and Chand, Duli, additional
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- 2021
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24. EC-Earth3-AerChem : a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6
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van Noije, Twan, Bergman, Tommi, Le Sager, Philippe, O'Donnell, Declan, Makkonen, Risto, Goncalves-Ageitos, Maria, Doescher, Ralf, Fladrich, Uwe, von Hardenberg, Jost, Keskinen, Jukka-Pekka, Korhonen, Hannele, Laakso, Anton, Myriokefalitakis, Stelios, Ollinaho, Pirkka, Garcia-Pando, Carlos Perez, Reerink, Thomas, Schrodner, Roland, Wyser, Klaus, Yang, Shuting, van Noije, Twan, Bergman, Tommi, Le Sager, Philippe, O'Donnell, Declan, Makkonen, Risto, Goncalves-Ageitos, Maria, Doescher, Ralf, Fladrich, Uwe, von Hardenberg, Jost, Keskinen, Jukka-Pekka, Korhonen, Hannele, Laakso, Anton, Myriokefalitakis, Stelios, Ollinaho, Pirkka, Garcia-Pando, Carlos Perez, Reerink, Thomas, Schrodner, Roland, Wyser, Klaus, and Yang, Shuting
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- 2021
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25. EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, van Noije, Twan, Bergman, Tommi, Le Sager, Philippe, O'Donnell, Declan, Makkonen, Risto, Gonçalves Ageitos, María, Döscher, Ralf, Fladrich, Uwe, von Hardenberg, Jost, Keskinen, Jukka-Pekka, Korhonen, Hannele, Laakso, Anton, Myriokefalitakis, Stelios, Ollinaho, Pirkka, Pérez García-Pando, Carlos, Reerink, Thomas, Schrödner, Roland, Wyser, Klaus, Yang, Shuting, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, van Noije, Twan, Bergman, Tommi, Le Sager, Philippe, O'Donnell, Declan, Makkonen, Risto, Gonçalves Ageitos, María, Döscher, Ralf, Fladrich, Uwe, von Hardenberg, Jost, Keskinen, Jukka-Pekka, Korhonen, Hannele, Laakso, Anton, Myriokefalitakis, Stelios, Ollinaho, Pirkka, Pérez García-Pando, Carlos, Reerink, Thomas, Schrödner, Roland, Wyser, Klaus, and Yang, Shuting
- Abstract
This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average −0.09 W m−2 with a standard deviation due to interannual variability of 0.25 W m−2, showing no significant drift. The global surface air temperature in the simulation is on average 14.08 ∘C with an interannual standard deviation of 0.17 ∘C, exhibiting a small drift of 0.015 ± 0.005 ∘C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 ∘C, and its transient climate response is estimated at 2.1 ∘C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995–2014 has an average bias of −0.86 ± 0.05 ∘C with a standard deviation across ensemble members of 0.35 ∘C in the Northern Hemisphere and 1.29 ± 0.02 ∘C with a c, The development of EC-Earth3 and ECEarth3-AerChem has benefitted from services provided by the ISENES3 project, which received funding from the European Union’s Horizon 2020 Research and Innovation program (grant agreement no. 824084). Jukka-Pekka Keskinen and Risto Makkonen wish to acknowledge the IT Center for Science, Finland (CSC) for software support and computational resources. María Gonçalves-Ageitos and Carlos Pérez García-Pando acknowledge the Partnership for Advanced Computing in Europe (PRACE) and the Spanish Supercomputing Network (RES) for awarding access to MareNostrum at the Barcelona Supercomputing Center (BSC). Financial support. Twan van Noije, Tommi Bergman, Philippe Le Sager, and Jost von Hardenberg acknowledge funding from the European Union’s Horizon 2020 Research and Innovation program (CRESCENDO, grant agreement no. 641816). María GonçalvesAgeitos and Carlos Pérez García-Pando acknowledge funding from the European Research Council (FRAGMENT, grant agreement no. 773051); the AXA Research Fund; and the Spanish Ministry of Science, Innovation and Universities (grant agreement nos. RYC-2015- 18690 and CGL2017-88911-R). Roland Schrödner acknowledges funding from the strategic research area MERGE (Modelling the Regional and Global Earth system)., Peer Reviewed, Objectius de Desenvolupament Sostenible::13 - Acció per al Clima::13.3 - Millorar l’educació, la conscienciació i la capacitat humana i institucional en relació amb la mitigació del canvi climàtic, l’adaptació a aquest, la reducció dels efectes i l’alerta primerenca, Objectius de Desenvolupament Sostenible::13 - Acció per al Clima, Postprint (published version)
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26. Reply on CEC1
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Bergman, Tommi, primary
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- 2021
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27. Description and Evaluation of a Secondary Organic Aerosol and New Particle Formation Scheme within TM5-MP v1.1
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Bergman, Tommi, primary, Makkonen, Risto, additional, Schrödner, Roland, additional, Swietlicki, Erik, additional, Phillips, Vaughan T. J., additional, Le Sager, Philippe, additional, and van Noije, Twan, additional
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- 2021
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28. Supplementary material to "Description and Evaluation of a Secondary Organic Aerosol and New Particle Formation Scheme within TM5-MP v1.1"
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Bergman, Tommi, primary, Makkonen, Risto, additional, Schrödner, Roland, additional, Swietlicki, Erik, additional, Phillips, Vaughan T. J., additional, Le Sager, Philippe, additional, and van Noije, Twan, additional
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- 2021
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29. EC-Earth3-AerChem, a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6
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van Noije, Twan, primary, Bergman, Tommi, additional, Le Sager, Philippe, additional, O'Donnell, Declan, additional, Makkonen, Risto, additional, Gonçalves-Ageitos, María, additional, Döscher, Ralf, additional, Fladrich, Uwe, additional, von Hardenberg, Jost, additional, Keskinen, Jukka-Pekka, additional, Korhonen, Hannele, additional, Laakso, Anton, additional, Myriokefalitakis, Stelios, additional, Ollinaho, Pirkka, additional, Pérez García-Pando, Carlos, additional, Reerink, Thomas, additional, Schrödner, Roland, additional, Wyser, Klaus, additional, and Yang, Shuting, additional
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- 2020
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30. Evaluation of natural aerosols in CRESCENDO-ESMs: Mineral Dust
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Checa-Garcia, Ramiro, primary, Balkanski, Yves, additional, Albani, Samuel, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Cozic, Anne, additional, Dearden, Chris, additional, Marticorena, Beatrice, additional, Michou, Martine, additional, van Noije, Twan, additional, Nabat, Pierre, additional, O'Connor, Fionna, additional, Olivié, Dirk, additional, Prospero, Joseph M., additional, Le Sager, Philippe, additional, Schulz, Michael, additional, and Scott, Catherine, additional
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- 2020
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31. Supplementary material to "Evaluation of natural aerosols in CRESCENDO-ESMs: Mineral Dust"
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Checa-Garcia, Ramiro, primary, Balkanski, Yves, additional, Albani, Samuel, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Cozic, Anne, additional, Dearden, Chris, additional, Marticorena, Beatrice, additional, Michou, Martine, additional, van Noije, Twan, additional, Nabat, Pierre, additional, O'Connor, Fionna, additional, Olivié, Dirk, additional, Prospero, Joseph M., additional, Le Sager, Philippe, additional, Schulz, Michael, additional, and Scott, Catherine, additional
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- 2020
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32. Description and evaluation of a detailed gas-phase chemistry scheme in the TM5-MP global chemistry transport model (r112)
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Myriokefalitakis, Stelios, primary, Daskalakis, Nikos, additional, Gkouvousis, Angelos, additional, Hilboll, Andreas, additional, van Noije, Twan, additional, Williams, Jason E., additional, Le Sager, Philippe, additional, Huijnen, Vincent, additional, Houweling, Sander, additional, Bergman, Tommi, additional, Nüß, Johann Rasmus, additional, Vrekoussis, Mihalis, additional, Kanakidou, Maria, additional, and Krol, Maarten C., additional
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- 2020
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33. Climate and air quality impacts due to mitigation of non-methane near-term climate forcers
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Allen, Robert J., primary, Turnock, Steven, additional, Nabat, Pierre, additional, Neubauer, David, additional, Lohmann, Ulrike, additional, Olivié, Dirk, additional, Oshima, Naga, additional, Michou, Martine, additional, Wu, Tongwen, additional, Zhang, Jie, additional, Takemura, Toshihiko, additional, Schulz, Michael, additional, Tsigaridis, Kostas, additional, Bauer, Susanne E., additional, Emmons, Louisa, additional, Horowitz, Larry, additional, Naik, Vaishali, additional, van Noije, Twan, additional, Bergman, Tommi, additional, Lamarque, Jean-Francois, additional, Zanis, Prodromos, additional, Tegen, Ina, additional, Westervelt, Daniel M., additional, Le Sager, Philippe, additional, Good, Peter, additional, Shim, Sungbo, additional, O'Connor, Fiona, additional, Akritidis, Dimitris, additional, Georgoulias, Aristeidis K., additional, Deushi, Makoto, additional, Sentman, Lori T., additional, John, Jasmin G., additional, Fujimori, Shinichiro, additional, and Collins, William J., additional
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- 2020
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34. Large difference in aerosol radiative effects from BVOC-SOA treatment in three Earth system models
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Sporre, Moa K., primary, Blichner, Sara M., additional, Schrödner, Roland, additional, Karset, Inger H. H., additional, Berntsen, Terje K., additional, van Noije, Twan, additional, Bergman, Tommi, additional, O'Donnell, Declan, additional, and Makkonen, Risto, additional
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- 2020
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35. Supplementary material to "Description and evaluation of a detailed gas-phase chemistry scheme in the TM5-MP global chemistry transport model (r112)"
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Myriokefalitakis, Stelios, primary, Daskalakis, Nikos, additional, Gkouvousis, Angelos, additional, Hilboll, Andreas, additional, van Noije, Twan, additional, Williams, Jason E., additional, Le Sager, Philippe, additional, Huijnen, Vincent, additional, Houweling, Sander, additional, Bergman, Tommi, additional, Nüß, Johann Rasmus, additional, Vrekoussis, Mihalis, additional, Kanakidou, Maria, additional, and Krol, Maarten C., additional
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- 2020
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36. How well do the latest Earth System Models capture the behaviour of biogenic secondary organic aerosol in the atmosphere?
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Scott, Catherine, primary, Yoshioka, Masaru, additional, Dearden, Chris, additional, Carslaw, Ken, additional, Spracklen, Dominick, additional, O'Connor, Fiona, additional, Folberth, Gerd, additional, Dalvi, Mohit, additional, Mulcahy, Jane, additional, Balkanski, Yves, additional, Checa-Garcia, Ramiro, additional, Olivie, Dirk, additional, Schulz, Michael, additional, van Noije, Twan, additional, le Sager, Philippe, additional, Michou, Martine, additional, Nabat, Pierre, additional, Nieradzik, Lars, additional, Bergman, Tommi, additional, and O'Donnell, Declan, additional
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- 2020
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37. Properties and challenges of mineral dust aerosol modelling in the latest Earth System Models
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Checa-Garcia, Ramiro, primary, Balkanski, Yves, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Dalvi, Mohit, additional, Marticorena, Beatrice, additional, Michou, Martine, additional, Nabat, Pierre, additional, Nieradzik, Lars, additional, Noije, Twan van, additional, O’Donnell, Declan, additional, Olivie, Dirk, additional, O'Connor, Fiona, additional, Schulz, Michael, additional, and Scott, Catherine, additional
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- 2020
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38. Re-assessment of pre-industrial fires in CMIP6 models and the implications for radiative forcing
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Carslaw, Ken, primary, Scott, Cat, additional, Yoshioka, Masaru, additional, Hamilton, Douglas, additional, O’Connor, Fiona, additional, Folberth, Gerd, additional, Mulcahy, Jane, additional, Dalvi, Mohit, additional, Balkanski, Yves, additional, Checa-Garcia, Ramiro, additional, Olivie, Dirk, additional, Schulz, Michael, additional, Michou, Martine, additional, Nabat, Pierre, additional, Nieradzik, Lars, additional, van Noije, Twan, additional, and Bergman, Tommi, additional
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- 2020
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39. Supplementary material to "Climate and air quality impacts due to mitigation of non-methane near-term climate forcers"
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Allen, Robert J., primary, Turnock, Steven, additional, Nabat, Pierre, additional, Neubauer, David, additional, Lohmann, Ulrike, additional, Olivie, Dirk, additional, Oshima, Naga, additional, Michou, Martine, additional, Wu, Tongwen, additional, Zhang, Jie, additional, Takemura, Toshihiko, additional, Schulz, Michael, additional, Tsigaridis, Kostas, additional, Bauer, Susanne E., additional, Emmons, Louisa, additional, Horowitz, Larry, additional, Naik, Vaishali, additional, van Noije, Twan, additional, Bergman, Tommi, additional, Lamarque, Jean-Francois, additional, Zanis, Prodromos, additional, Tegen, Ina, additional, Westervelt, Daniel M., additional, Le Sager, Philippe, additional, Good, Peter, additional, Shim, Sungbo, additional, O'Connor, Fiona, additional, Akritidis, Dimitris, additional, Georgoulias, Aristeidis K., additional, Deushi, Makoto, additional, Sentman, Lori T., additional, Fujimori, Shinichiro, additional, and Collins, William J., additional
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- 2020
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40. Large difference in aerosol radiative effects from BVOC-SOA treatment in three ESMs
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Sporre, Moa K., primary, Blichner, Sara M., additional, Schrödner, Roland, additional, Karset, Inger H. H., additional, Berntsen, Terje K., additional, van Noije, Twan, additional, Bergman, Tommi, additional, O'Donnell, Declan, additional, and Makkonen, Risto, additional
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- 2020
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41. Supplementary material to "Large difference in aerosol radiative effects from BVOC-SOA treatment in three ESMs"
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Sporre, Moa K., primary, Blichner, Sara M., additional, Schrödner, Roland, additional, Karset, Inger H. H., additional, Berntsen, Terje K., additional, van Noije, Twan, additional, Bergman, Tommi, additional, O'Donnell, Declan, additional, and Makkonen, Risto, additional
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- 2020
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42. Climate and air quality impacts due to mitigation of non-methane near-term climate forcers
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80585836, Allen, Robert J., Turnock, Steven, Nabat, Pierre, Neubauer, David, Lohmann, Ulrike, Olivié, Dirk, Oshima, Naga, Michou, Martine, Wu, Tongwen, Zhang, Jie, Takemura, Toshihiko, Schulz, Michael, Tsigaridis, Kostas, Bauer, Susanne E., Emmons, Louisa, Horowitz, Larry, Naik, Vaishali, van Noije, Twan, Bergman, Tommi, Lamarque, Jean-Francois, Zanis, Prodromos, Tegen, Ina, Westervelt, Daniel M., Le Sager, Philippe, Good, Peter, Shim, Sungbo, O'Connor, Fiona, Akritidis, Dimitris, Georgoulias, Aristeidis K., Deushi, Makoto, Sentman, Lori T., John, Jasmin G., Fujimori, Shinichiro, Collins, William J., 80585836, Allen, Robert J., Turnock, Steven, Nabat, Pierre, Neubauer, David, Lohmann, Ulrike, Olivié, Dirk, Oshima, Naga, Michou, Martine, Wu, Tongwen, Zhang, Jie, Takemura, Toshihiko, Schulz, Michael, Tsigaridis, Kostas, Bauer, Susanne E., Emmons, Louisa, Horowitz, Larry, Naik, Vaishali, van Noije, Twan, Bergman, Tommi, Lamarque, Jean-Francois, Zanis, Prodromos, Tegen, Ina, Westervelt, Daniel M., Le Sager, Philippe, Good, Peter, Shim, Sungbo, O'Connor, Fiona, Akritidis, Dimitris, Georgoulias, Aristeidis K., Deushi, Makoto, Sentman, Lori T., John, Jasmin G., Fujimori, Shinichiro, and Collins, William J.
- Abstract
It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015–2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry–climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with “weak” (SSP3-7.0) versus “strong” (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2.5) and ozone (O3) decrease by −2.2±0.32 µg m−3 and −4.6±0.88 ppb, respectively (changes quoted here are for the entire 2015–2055 time period; uncertainty represents the 95 % confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0.25±0.12 K and 0.03±0.012 mm d−1, respectively. Similarly, increases in extreme weather indices, including the hotte
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- 2020
43. SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0
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Massachusetts Institute of Technology. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Kokkola, Harri, Kühn, Thomas, Laakso, Anton, Bergman, Tommi, Lehtinen, Kari E. J., Mielonen, Tero, Arola, Antti, Stadtler, Scarlet, Korhonen, Hannele, Ferrachat, Sylvaine, Lohmann, Ulrike, Neubauer, David, Tegen, Ina, Siegenthaler-Le Drian, Colombe, Schultz, Martin G., Bey, Isabelle, Stier, Philip, Daskalakis, Nikos, Heald, Colette L., Romakkaniemi, Sami, Massachusetts Institute of Technology. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Kokkola, Harri, Kühn, Thomas, Laakso, Anton, Bergman, Tommi, Lehtinen, Kari E. J., Mielonen, Tero, Arola, Antti, Stadtler, Scarlet, Korhonen, Hannele, Ferrachat, Sylvaine, Lohmann, Ulrike, Neubauer, David, Tegen, Ina, Siegenthaler-Le Drian, Colombe, Schultz, Martin G., Bey, Isabelle, Stier, Philip, Daskalakis, Nikos, Heald, Colette L., and Romakkaniemi, Sami
- Abstract
In this paper, we present the implementation and evaluation of the aerosol microphysics module SALSA2.0 in the framework of the aerosol-chemistry-climate model ECHAM-HAMMOZ. It is an alternative microphysics module to the default modal microphysics scheme M7 in ECHAM-HAMMOZ. The SALSA2.0 implementation within ECHAM-HAMMOZ is evaluated against observations of aerosol optical properties, aerosol mass, and size distributions, comparing also to the skill of the M7 implementation. The largest differences between the implementation of SALSA2.0 and M7 are in the methods used for calculating microphysical processes, i.e., nucleation, condensation, coagulation, and hydration. These differences in the microphysics are reflected in the results so that the largest differences between SALSA2.0 and M7 are evident over regions where the aerosol size distribution is heavily modified by the microphysical processing of aerosol particles. Such regions are, for example, highly polluted regions and regions strongly affected by biomass burning. In addition, in a simulation of the 1991 Mt. Pinatubo eruption in which a stratospheric sulfate plume was formed, the global burden and the effective radii of the stratospheric aerosol are very different in SALSA2.0 and M7. While SALSA2.0 was able to reproduce the observed time evolution of the global burden of sulfate and the effective radii of stratospheric aerosol, M7 strongly overestimates the removal of coarse stratospheric particles and thus underestimates the effective radius of stratospheric aerosol. As the mode widths of M7 have been optimized for the troposphere and were not designed to represent stratospheric aerosol, the ability of M7 to simulate the volcano plume was improved by modifying the mode widths, decreasing the standard deviations of the accumulation and coarse modes from 1.59 and 2.0, respectively, to 1.2 similar to what was observed after the Mt. Pinatubo eruption. Overall, SALSA2.0 shows promise in improving the aerosol de, NOAA (Grant NA17RJ1231), National Science Foundation (Grant ATM-0002035, ATM-0002698 and ATM04-01611)
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- 2020
44. Description and evaluation of a detailed gas-phase chemistry scheme in the TM5-MP global chemistry transport model (r112)
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Myriokefalitakis, Stelios, Daskalakis, Nikos, Gkouvousis, Angelos, Hilboll, Andreas, Van Noije, Twan, Williams, Jason E., Le Sager, Philippe, Huijnen, Vincent, Houweling, Sander, Bergman, Tommi, Rasmus Nüß, Johann, Vrekoussis, Mihalis, Kanakidou, Maria, Krol, Maarten C., Myriokefalitakis, Stelios, Daskalakis, Nikos, Gkouvousis, Angelos, Hilboll, Andreas, Van Noije, Twan, Williams, Jason E., Le Sager, Philippe, Huijnen, Vincent, Houweling, Sander, Bergman, Tommi, Rasmus Nüß, Johann, Vrekoussis, Mihalis, Kanakidou, Maria, and Krol, Maarten C.
- Abstract
This work documents and evaluates the tropospheric gas-phase chemical mechanism MOGUNTIA in the three-dimensional chemistry transport model TM5-MP. Compared to the modified CB05 (mCB05) chemical mechanism previously used in the model, MOGUNTIA includes a detailed representation of the light hydrocarbons (C1-C4) and isoprene, along with a simplified chemistry representation of terpenes and aromatics. Another feature implemented in TM5-MP for this work is the use of the Rosenbrock solver in the chemistry code, which can replace the classical Euler backward integration method of the model. Global budgets of ozone (O3), carbon monoxide (CO), hydroxyl radicals (OH), nitrogen oxides (NOx), and volatile organic compounds (VOCs) are analyzed, and their mixing ratios are compared with a series of surface, aircraft, and satellite observations for the year 2006. Both mechanisms appear to be able to satisfactorily represent observed mixing ratios of important trace gases, with the MOGUNTIA chemistry configuration yielding lower biases than mCB05 compared to measurements in most of the cases. However, the two chemical mechanisms fail to reproduce the observed mixing ratios of light VOCs, indicating insufficient primary emission source strengths, oxidation that is too fast, and/or a low bias in the secondary contribution to C2-C3 organics via VOC atmospheric oxidation. Relative computational memory and time requirements of the different model configurations are also compared and discussed. Overall, the MOGUNTIA scheme simulates a large suite of oxygenated VOCs that are observed in the atmosphere at significant levels. This significantly expands the possible applications of TM5-MP.
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- 2020
45. The Climatic Significance of Biogenic Aerosols in the Boreal Region Now and in the Future
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Mielonen, Tero, primary, Hienola, Anca, additional, Kühn, Thomas, additional, Merikanto, Joonas, additional, Lipponen, Antti, additional, Laakso, Anton, additional, Bergman, Tommi, additional, Korhonen, Hannele, additional, Kolmonen, Pekka, additional, Sogacheva, Larisa, additional, Ghent, Darren, additional, Pitkänen, Mikko, additional, Arola, Antti, additional, de Leeuw, Gerrit, additional, and Kokkola, Harri, additional
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- 2019
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46. Description and Evaluation of a Secondary Organic Aerosol and New Particle Formation Scheme within TM5-MP v1.1.
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Bergman, Tommi, Makkonen, Risto, Schrödner, Roland, Swietlicki, Erik, Phillips, Vaughan T. J., Le Sager, Philippe, and van Noije, Twan
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AEROSOLS , *SEMIVOLATILE organic compounds , *CHEMICAL models , *CARBONACEOUS aerosols , *MICROBIOLOGICAL aerosols - Abstract
We have implemented and evaluated a secondary organic aerosol scheme within the chemistry transport model TM5-MP in this work. In earlier versions of TM5-MP the secondary organic aerosol was emitted as Aitken sized particle mass emulating the condensation. In the current scheme we simulate the formation of SOA from oxidation of isoprene and monoterpenes by ozone and hydroxyl radicals which produce semi-volatile organic compounds and extremely low-volatility compounds. Subsequently, SVOC and ELVOC can condense on particles. Furthermore, we have introduced a new particle formation mechanism depending on the concentration of ELVOCs. For evaluation purposes, we have simulated the year 2010 with the old and new scheme, where we see an increase in simulated production of SOA from 39.9 Tg y-1 with the old scheme to 52.5 Tg y-1 with the new scheme. For more detailed analysis, the particle mass and number concentrations and their influence on the simulated aerosol optical depth are compared to observations. Phenomenologically, the new particle formation scheme implemented here is able to reproduce the occurrence of observed particle formation events. However, the concentrations of formed particles are clearly lower as is the subsequent growth to larger sizes. Compared to the old scheme, the new scheme is increasing the number concentrations across the observation stations while still underestimating the observations. The total aerosol mass concentrations in the US show a much better seasonal cycle and removal of a clear overestimation of concentrations. In Europe the mass concentrations are lowered leading to a larger underestimation of observations. Aerosol optical depth is generally slightly increased except in the northern high latitudes. This brings the simulated annual global mean AOD closer to observational estimate. However, as the increase is rather uniform, biases tend to be reduced only in regions where the model underestimates the AOD. Furthermore, the correlation against satellite retrievals and ground-based sun-photometer observations are improved. Although the process based approach to SOA formation causes reduction in model performance in some areas, overall the new scheme improves the simulated aerosol fields. [ABSTRACT FROM AUTHOR]
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- 2021
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47. Evaluation of global simulations of aerosol particle number and cloud condensation nuclei, and implications for cloud droplet formation
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Fanourgakis, George S., primary, Kanakidou, Maria, additional, Nenes, Athanasios, additional, Bauer, Susanne E., additional, Bergman, Tommi, additional, Carslaw, Ken S., additional, Grini, Alf, additional, Hamilton, Douglas S., additional, Johnson, Jill S., additional, Karydis, Vlassis A., additional, Kirkevåg, Alf, additional, Kodros, John K., additional, Lohmann, Ulrike, additional, Luo, Gan, additional, Makkonen, Risto, additional, Matsui, Hitoshi, additional, Neubauer, David, additional, Pierce, Jeffrey R., additional, Schmale, Julia, additional, Stier, Philip, additional, Tsigaridis, Kostas, additional, van Noije, Twan, additional, Wang, Hailong, additional, Watson-Parris, Duncan, additional, Westervelt, Daniel M., additional, Yang, Yang, additional, Yoshioka, Masaru, additional, Daskalakis, Nikos, additional, Decesari, Stefano, additional, Gysel Beer, Martin, additional, Kalivitis, Nikos, additional, Liu, Xiaohong, additional, Mahowald, Natalie M., additional, Myriokefalitakis, Stelios, additional, Schrödner, Roland, additional, Sfakianaki, Maria, additional, Tsimpidi, Alexandra P., additional, Wu, Mingxuan, additional, and Yu, Fangqun, additional
- Published
- 2019
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48. Supplementary material to "Evaluation of global simulations of aerosol particle number and cloud condensation nuclei, and implications for cloud droplet formation"
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Fanourgakis, George S., primary, Kanakidou, Maria, additional, Nenes, Athanasios, additional, Bauer, Susanne E., additional, Bergman, Tommi, additional, Carslaw, Ken S., additional, Grini, Alf, additional, Hamilton, Douglas S., additional, Johnson, Jill S., additional, Karydis, Vlassis A., additional, Kirkevåg, Alf, additional, Kodros, John K., additional, Lohmann, Ulrike, additional, Luo, Gan, additional, Makkonen, Risto, additional, Matsui, Hitoshi, additional, Neubauer, David, additional, Pierce, Jeffrey R., additional, Schmale, Julia, additional, Stier, Philip, additional, Tsigaridis, Kostas, additional, van Noije, Twan, additional, Wang, Hailong, additional, Watson-Parris, Duncan, additional, Westervelt, Daniel M., additional, Yang, Yang, additional, Yoshioka, Masaru, additional, Daskalakis, Nikos, additional, Decesari, Stefano, additional, Gysel Beer, Martin, additional, Kalivitis, Nikos, additional, Liu, Xiaohong, additional, Mahowald, Natalie M., additional, Myriokefalitakis, Stelios, additional, Schrödner, Roland, additional, Sfakianaki, Maria, additional, Tsimpidi, Alexandra P., additional, Wu, Mingxuan, additional, and Yu, Fangqun, additional
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- 2019
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49. EC-Earth3-AerChem, a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6.
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Noije, Twan van, Bergman, Tommi, Sager, Philippe Le, O'Donnell, Declan, Makkonen, Risto, Gonçalves-Ageitos, María, Döscher, Ralf, Fladrich, Uwe, Hardenberg, Jost von, uwe.fladrich@smhi.se, Keskinen, Jukka-Pekka, Korhonen, Hannele, Laakso, Anton, Myriokefalitakis, Stelios, Ollinaho, Pirkka, García-Pando, Carlos Pérez, Reerink, Thomas, Schrödner, Roland, Wyser, Klaus, and Yang, Shuting
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ATMOSPHERIC chemistry , *ATMOSPHERIC models , *ATMOSPHERIC aerosols , *CLIMATE sensitivity , *ATMOSPHERIC temperature - Abstract
This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model and describe in detail how it differs from the other EC-Earth3 configurations, and what the new features are compared to the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under pre-industrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The mean energy imbalance at the top of the atmosphere in the pre-industrial control simulation is -0.10 ± 0.25 W m-2 and shows no significant drift. The corresponding mean global surface air temperature is 14.05 ± 0.16 °C, with a small drift of -0.075 ± 0.009 °C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 °C and its transient climate response at 2.1 °C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread among ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared to the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts, the ensemble mean surface air temperature climatology for 1995-2014 has an average bias of -0.86 ± 0.35 °C in the Northern Hemisphere and 1.29 ± 0.05 °C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant climate effects from the 20th century onwards. For the SSP3-7.0 shared socio-economic pathway, the model gives a global warming at the end of the 21st century (2091-2100) of 4.9 °C above the pre-industrial mean. A 0.5 °C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 °C. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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50. Evaluation of natural aerosols in CRESCENDO-ESMs: Mineral Dust.
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Checa-Garcia, Ramiro, Balkanski, Yves, Albani, Samuel, Bergman, Tommi, Carslaw, Ken, Cozic, Anne, Dearden, Chris, Marticorena, Beatrice, Michou, Martine, van Noije, Twan, Nabat, Pierre, O'Connor, Fionna, Olivié, Dirk, Prospero, Joseph M., Le Sager, Philippe, Schulz, Michael, and Scott, Catherine
- Abstract
This paper presents an analysis of the mineral dust aerosol modelled by five Earth System Models (ESM) within the Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO) project. We quantify the global dust cycle described by each model in terms of global emissions together with dry and wet depositions, reporting large differences in ratio of dry over wet deposition across the models not directly correlated with the range of particle sizes emitted. The multi-model mean dust emissions was 2954 Tg yr
-1 but with a large uncertainty due mainly to the difference in maximum dust particle size emitted. For the subset of ESMs without particles larger than 10 μm we obtained 1664 (σ = 650) Tg yr-1 . Total dust emissions with identical nudged winds from reanalysis give us better consistency between models with 1530 (σ = 282) Tg yr-1 . Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar dust load global budgets can display strong differences in dust optical depths. The comparison against observations has been done in terms of dust optical depths based on MODIS satellite products, showing a global consistency in terms of preferential dust sources and transport across the Atlantic. However, we found regional and seasonal differences between models and observations when we quantified the cross-correlation of time-series over dust emitting regions. To faithfully compare local emissions between models we introduce a re-gridded normalization method, that also can be compared with satellite products derived from dust events frequencies. Dust total depositions are compared with instrumental network to assess global and regional differences. We found that models agree with observations distant from dust sources within a factor 10, but the approximations of dust particle size distribution at emission contributed to a misrepresentation of the actual range of deposition values when instruments are close to dust emitting regions. The observational dust surface concentrations also are reproduced within a factor 10. The comparison of total aerosol optical depths with AERONETv3 stations where dust is dominant shows large differences between models, however with an increase of the inter-model consistency when the simulations are conducted with nudged-winds. The increase of the model ensemble consistency also means a better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONETv3 and MODIS-DOD retrievals). We estimated the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles measured at FENNEC experiment. We introduced a method to ascertain the contributions per mode consistent with the multimodal direct radiative effects. [ABSTRACT FROM AUTHOR]- Published
- 2020
- Full Text
- View/download PDF
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