254 results on '"Olivié, Dirk"'
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2. The projected future degradation in air quality is caused by more abundant natural aerosols in a warmer world
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Gomez, James, Allen, Robert J., Turnock, Steven T., Horowitz, Larry W., Tsigaridis, Kostas, Bauer, Susanne E., Olivié, Dirk, Thomson, Erik S., and Ginoux, Paul
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- 2023
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3. Using modelled relationships and satellite observations to attribute modelled aerosol biases over biomass burning regions
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Zhong, Qirui, Schutgens, Nick, van der Werf, Guido R., van Noije, Twan, Bauer, Susanne E., Tsigaridis, Kostas, Mielonen, Tero, Checa-Garcia, Ramiro, Neubauer, David, Kipling, Zak, Kirkevåg, Alf, Olivié, Dirk J. L., Kokkola, Harri, Matsui, Hitoshi, Ginoux, Paul, Takemura, Toshihiko, Le Sager, Philippe, Rémy, Samuel, Bian, Huisheng, and Chin, Mian
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- 2022
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4. Clean air policies are key for successfully mitigating Arctic warming
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von Salzen, Knut, Whaley, Cynthia H., Anenberg, Susan C., Van Dingenen, Rita, Klimont, Zbigniew, Flanner, Mark G., Mahmood, Rashed, Arnold, Stephen R., Beagley, Stephen, Chien, Rong-You, Christensen, Jesper H., Eckhardt, Sabine, Ekman, Annica M. L., Evangeliou, Nikolaos, Faluvegi, Greg, Fu, Joshua S., Gauss, Michael, Gong, Wanmin, Hjorth, Jens L., Im, Ulas, Krishnan, Srinath, Kupiainen, Kaarle, Kühn, Thomas, Langner, Joakim, Law, Kathy S., Marelle, Louis, Olivié, Dirk, Onishi, Tatsuo, Oshima, Naga, Paunu, Ville-Veikko, Peng, Yiran, Plummer, David, Pozzoli, Luca, Rao, Shilpa, Raut, Jean-Christophe, Sand, Maria, Schmale, Julia, Sigmond, Michael, Thomas, Manu A., Tsigaridis, Kostas, Tsyro, Svetlana, Turnock, Steven T., Wang, Minqi, and Winter, Barbara
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- 2022
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5. Scientific data from precipitation driver response model intercomparison project
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Myhre, Gunnar, Samset, Bjørn, Forster, Piers M., Hodnebrog, Øivind, Sandstad, Marit, Mohr, Christian W., Sillmann, Jana, Stjern, Camilla W., Andrews, Timothy, Boucher, Olivier, Faluvegi, Gregory, Iversen, Trond, Lamarque, Jean-Francois, Kasoar, Matthew, Kirkevåg, Alf, Kramer, Ryan, Liu, Longbo, Mülmenstädt, Johannes, Olivié, Dirk, Quaas, Johannes, Richardson, Thomas B., Shawki, Dilshad, Shindell, Drew, Smith, Chris, Stier, Philip, Tang, Tao, Takemura, Toshihiko, Voulgarakis, Apostolos, and Watson-Parris, Duncan
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- 2022
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6. Shutdown of Southern Ocean convection controls long-term greenhouse gas-induced warming
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Gjermundsen, Ada, Nummelin, Aleksi, Olivié, Dirk, Bentsen, Mats, Seland, Øyvind, and Schulz, Michael
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- 2021
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7. Multi-model simulations of aerosol and ozone radiative forcing due to anthropogenic emission changes during the period 1990–2015
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Myhre, Gunnar, Aas, Wenche, Cherian, Ribu, Collins, William, Faluvegi, Greg, Flanner, Mark, Forster, Piers, Hodnebrog, Øivind, Klimont, Zbigniew, Lund, Marianne T, Mülmenstädt, Johannes, Myhre, Cathrine Lund, Olivié, Dirk, Prather, Michael, Quaas, Johannes, Samset, Bjørn H, Schnell, Jordan L, Schulz, Michael, Shindell, Drew, Skeie, Ragnhild B, Takemura, Toshihiko, and Tsyro, Svetlana
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Climate Action ,Astronomical and Space Sciences ,Atmospheric Sciences ,Meteorology & Atmospheric Sciences - Abstract
Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990-2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g.-1 to-3%yr-1 in aerosols over the USA and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990-2015 period increased by +0.17±0.08Wm-2, with approximately one-third due to ozone. This increase is more strongly positive than that reported in IPCC AR5. The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions.
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- 2017
8. Natural marine bromoform emissions in the fully coupled ocean–atmosphere model NorESM2
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Booge, Dennis, Tjiputra, Jerry F., Olivié, Dirk J. L., Quack, Birgit, Krüger, Kirstin, Booge, Dennis, Tjiputra, Jerry F., Olivié, Dirk J. L., Quack, Birgit, and Krüger, Kirstin
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- 2024
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9. Natural marine bromoform emissions in the fully coupled ocean-atmosphere-model NorESM2
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Booge, Dennis, primary, Tjiputra, Jerry F., additional, Olivié, Dirk J. L., additional, Quack, Birgit, additional, and Krüger, Kirstin, additional
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- 2024
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10. Supplementary material to "Natural marine bromoform emissions in the fully coupled ocean-atmosphere-model NorESM2"
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Booge, Dennis, primary, Tjiputra, Jerry F., additional, Olivié, Dirk J. L., additional, Quack, Birgit, additional, and Krüger, Kirstin, additional
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- 2024
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11. Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models.
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Kalisoras, Alkiviadis, Georgoulias, Aristeidis K., Akritidis, Dimitris, Allen, Robert J., Naik, Vaishali, Kuo, Chaincy, Szopa, Sophie, Nabat, Pierre, Olivié, Dirk, van Noije, Twan, Le Sager, Philippe, Neubauer, David, Oshima, Naga, Mulcahy, Jane, Horowitz, Larry W., and Zanis, Prodromos
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RADIATIVE forcing ,AEROSOLS ,CARBONACEOUS aerosols ,EARTH (Planet) ,CARBON-black - Abstract
Anthropogenic aerosols play a major role in the Earth–atmosphere system by influencing the Earth's radiative budget and precipitation and consequently the climate. The perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF). In this work, the present-day shortwave (SW), longwave (LW), and total (i.e., SW plus LW) ERF of anthropogenic aerosols is quantified using two different sets of experiments with prescribed sea surface temperatures (SSTs) from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6): (a) time-slice pre-industrial perturbation simulations with fixed SSTs (piClim) and (b) transient historical simulations with time-evolving SSTs (histSST) over the historical period (1850–2014). ERF is decomposed into three components for both piClim and histSST experiments: (a) ERFARI , representing aerosol–radiation interactions; (b) ERFACI , accounting for aerosol–cloud interactions (including the semi-direct effect); and (c) ERFALB , which is due to temperature, humidity, and surface albedo changes caused by anthropogenic aerosols. We present spatial patterns at the top-of-atmosphere (TOA) and global weighted field means along with inter-model variability (1 standard deviation) for all SW, LW, and total ERF components (ERFARI , ERFACI , and ERFALB) and for every experiment used in this study. Moreover, the inter-model agreement and the robustness of our results are assessed using a comprehensive method as utilized in the IPCC Sixth Assessment Report. Based on piClim experiments, the total present-day (2014) ERF from anthropogenic aerosol and precursor emissions is estimated to be - 1.11 ± 0.26 Wm-2 , mostly due to the large contribution of ERFACI to the global mean and to the inter-model variability. Based on the histSST experiments for the present-day period (1995–2014), similar results are derived, with a global mean total aerosol ERF of - 1.28 ± 0.37 Wm-2 and dominating contributions from ERFACI. The spatial patterns for total ERF and its components are similar in both the piClim and histSST experiments. Furthermore, implementing a novel approach to determine geographically the driving factor of ERF, we show that ERFACI dominates over the largest part of the Earth and that ERFALB dominates mainly over the poles, while ERFARI dominates over certain reflective surfaces. Analysis of the inter-model variability in total aerosol ERF shows that SW ERFACI is the main source of uncertainty predominantly over land regions with significant changes in aerosol optical depth (AOD), with eastern Asia contributing mostly to the inter-model spread of both ERFARI and ERFACI. The global spatial patterns of total ERF and its components from individual aerosol species, such as sulfates, organic carbon (OC), and black carbon (BC), are also calculated based on piClim experiments. The total ERF caused by sulfates (piClim- SO2) is estimated at - 1.11 ± 0.31 Wm-2 , and the OC ERF (piClim-OC) is - 0.35 ± 0.21 Wm-2 , while the ERF due to BC (piClim-BC) is 0.19 ± 0.18 Wm-2. For sulfates and OC perturbation experiments, ERFACI dominates over the globe, whereas for BC perturbation experiments ERFARI dominates over land in the Northern Hemisphere and especially in the Arctic. Generally, sulfates dominate ERF spatial patterns, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere (NH), such as North America, Europe, and eastern and southern Asia. Our analysis of the temporal evolution of ERF over the historical period (1850–2014) reveals that ERFACI clearly dominates over ERFARI and ERFALB for driving the total ERF temporal evolution. Moreover, since the mid-1980s, total ERF has become less negative over eastern North America and western and central Europe, while over eastern and southern Asia there is a steady increase in ERF magnitude towards more negative values until 2014. [ABSTRACT FROM AUTHOR]
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- 2024
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12. The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics
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Ahsan, Hamza, primary, Wang, Hailong, additional, Wu, Jingbo, additional, Wu, Mingxuan, additional, Smith, Steven J., additional, Bauer, Susanne, additional, Suchyta, Harrison, additional, Olivié, Dirk, additional, Myhre, Gunnar, additional, Matsui, Hitoshi, additional, Bian, Huisheng, additional, Lamarque, Jean-François, additional, Carslaw, Ken, additional, Horowitz, Larry, additional, Regayre, Leighton, additional, Chin, Mian, additional, Schulz, Michael, additional, Skeie, Ragnhild Bieltvedt, additional, Takemura, Toshihiko, additional, and Naik, Vaishali, additional
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- 2023
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13. The Time Scales of Climate Responses to Carbon Dioxide and Aerosols
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Stjern, Camilla W., Forster, Piers M., Jia, Hailing, Jouan, Caroline, Kasoar, Matthew R., Myhre, Gunnar, Olivié, Dirk, Quaas, Johannes, Samset, BjØrn H., Sand, Maria, Takemura, Toshihiro, Voulgarakis, Apostolos, and Wells, Christopher D.
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Atmospheric Science - Abstract
The climate system responds to changes in the amount of atmospheric greenhouse gases or aerosols through rapid processes, triggered within hours and days, and through slower processes, where the full response may only be seen after centuries. In this paper, we aim to elucidate the mechanisms operating on time scales of hours to years to better understand the response of key climate quantities such as energy fluxes, temperature, and precipitation after a sudden increase in either carbon dioxide (CO2), black carbon (BC), or sulfate (SO4) aerosols. The results are based on idealized simulations from six global climate models. We find that the effect of changing ocean temperatures kicks in after a couple of months. Rapid precipitation reductions start occurring instantly and are established after just a few days. For BC, they constitute most of the equilibrium response. For CO2 and SO4, the magnitude of the precipitation response gradually increases as surface warming/cooling evolves, and for CO2, the sign of the response changes from negative to positive after 2 years. Rapid cloud adjustments are typically established within the first 24 h, and while the magnitude of cloud feedbacks for CO2 and SO4 increases over time, the geographical pattern of the equilibrium cloud change is present already after the first year. While there are model differences, our work underscores the overall similarity of the major time-varying processes and responses simulated by current global models and hence the robustness of key features of simulated responses to historical and future anthropogenic forcing. Significance Statement How does the climate system respond to a change in the amount of atmospheric greenhouse gases or aerosols? Some processes are rapid, responding within hours and days. Others are slow, and the full response to a forcing of the climate may only be seen after centuries. In this paper, we use six global climate models to investigate the time scales of climate responses to carbon dioxide, black carbon, and sulfate, focusing on key climate quantities, such as temperature, precipitation, and clouds. While there are ample model differences, our work underscores the overall similarity of the major time-varying processes and responses simulated by current global models and hence the robustness of key features of simulated responses to historical and future anthropogenic forcing.
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- 2023
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14. Point Splitting and U(1) Gauge Invariance
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Olivie, Dirk
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High Energy Physics - Theory - Abstract
A gauge transformation in quantum electrodynamics involves the product of field operators at the same space-time point and hence does not have a well-defined meaning. One way to avoid this difficulty is to generalize the gauge transformation by using different space-time points in the spirit of Dirac's point splitting. Such a generalization indeed exists and the resulting infinitesimal gauge transformation takes the form of an infinite series in the coupling constant. In this text I will present two examples of generalized gauge transformations., Comment: 6 pages, 0 figures, to be published in the proceedings of the NATO ASI Summer School held in Cargese, July 26 - August 7, 1999 : Particle Physics, Ideas and Recent Developments
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- 1999
15. Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models
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Kalisoras, Alkiviadis, primary, Georgoulias, Aristeidis K., additional, Akritidis, Dimitris, additional, Allen, Robert J., additional, Naik, Vaishali, additional, Kuo, Chaincy, additional, Szopa, Sophie, additional, Nabat, Pierre, additional, Olivié, Dirk, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Neubauer, David, additional, Oshima, Naga, additional, Mulcahy, Jane, additional, Horowitz, Larry W., additional, and Zanis, Prodromos, additional
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- 2023
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16. Supplementary material to "Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models"
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Kalisoras, Alkiviadis, primary, Georgoulias, Aristeidis K., additional, Akritidis, Dimitris, additional, Allen, Robert J., additional, Naik, Vaishali, additional, Kuo, Chaincy, additional, Szopa, Sophie, additional, Nabat, Pierre, additional, Olivié, Dirk, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Neubauer, David, additional, Oshima, Naga, additional, Mulcahy, Jane, additional, Horowitz, Larry W., additional, and Zanis, Prodromos, additional
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- 2023
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17. Historical total ozone radiative forcing derived from CMIP6 simulations
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Skeie, Ragnhild Bieltvedt, Myhre, Gunnar, Hodnebrog, Øivind, Cameron-Smith, Philip J., Deushi, Makoto, Hegglin, Michaela I., Horowitz, Larry W., Kramer, Ryan J., Michou, Martine, Mills, Michael J., Olivié, Dirk J. L., Connor, Fiona M. O’, Paynter, David, Samset, Bjørn H., Sellar, Alistair, Shindell, Drew, Takemura, Toshihiko, Tilmes, Simone, and Wu, Tongwen
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- 2020
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18. The effect of rapid adjustments to halocarbons and N2O on radiative forcing
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Hodnebrog, Øivind, Myhre, Gunnar, Kramer, Ryan J., Shine, Keith P., Andrews, Timothy, Faluvegi, Gregory, Kasoar, Matthew, Kirkevåg, Alf, Lamarque, Jean-François, Mülmenstädt, Johannes, Olivié, Dirk, Samset, Bjørn H., Shindell, Drew, Smith, Christopher J., Takemura, Toshihiko, and Voulgarakis, Apostolos
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- 2020
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19. Author Correction: Global and regional trends of atmospheric sulfur
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Aas, Wenche, Mortier, Augustin, Bowersox, Van, Cherian, Ribu, Faluvegi, Greg, Fagerli, Hilde, Hand, Jenny, Klimont, Zbigniew, Galy-Lacaux, Corinne, Lehmann, Christopher M. B., Myhre, Cathrine Lund, Myhre, Gunnar, Olivié, Dirk, Sato, Keiichi, Quaas, Johannes, Rao, P. S. P., Schulz, Michael, Shindell, Drew, Skeie, Ragnhild B., Stein, Ariel, Takemura, Toshihiko, Tsyro, Svetlana, Vet, Robert, and Xu, Xiaobin
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- 2020
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20. Historical Changes and Reasons for Model Differences in Anthropogenic Aerosol Forcing in CMIP6
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Fiedler, Stephanie, primary, van Noije, Twan, additional, Smith, Christopher J., additional, Boucher, Olivier, additional, Dufresne, Jean‐Louis, additional, Kirkevåg, Alf, additional, Olivié, Dirk, additional, Pinto, Rovina, additional, Reerink, Thomas, additional, Sima, Adriana, additional, and Schulz, Michael, additional
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- 2023
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21. Extreme wet and dry conditions affected differently by greenhouse gases and aerosols
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Sillmann, Jana, Stjern, Camilla W., Myhre, Gunnar, Samset, Bjørn H., Hodnebrog, Øivind, Andrews, Timothy, Boucher, Olivier, Faluvegi, Gregory, Forster, Piers, Kasoar, Matthew R., Kharin, Viatcheslav V., Kirkevåg, Alf, Lamarque, Jean-Francois, Olivié, Dirk J. L., Richardson, Thomas B., Shindell, Drew, Takemura, Toshihiko, Voulgarakis, Apostolos, and Zwiers, Francis W.
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- 2019
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22. Historical Changes and Reasons for Model Differences in Anthropogenic Aerosol Forcing in CMIP6
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Fiedler, Stephanie, van Noije, Twan, Smith, Christopher J., Boucher, Olivier, Dufresne, Jean‐Louis, Kirkevåg, Alf, Olivié, Dirk, Pinto, Rovina, Reerink, Thomas, Sima, Adriana, Schulz, Michael, Fiedler, Stephanie, van Noije, Twan, Smith, Christopher J., Boucher, Olivier, Dufresne, Jean‐Louis, Kirkevåg, Alf, Olivié, Dirk, Pinto, Rovina, Reerink, Thomas, Sima, Adriana, and Schulz, Michael
- Abstract
The Radiative Forcing Model Intercomparison Project (RFMIP) allows estimates of effective radiative forcing (ERF) in the Coupled Model Intercomparison Project phase six (CMIP6). We analyze the RFMIP output, including the new experiments from models that use the same parameterization for anthropogenic aerosols (RFMIP-SpAer), to characterize and better understand model differences in aerosol ERF. We find little changes in the aerosol ERF for 1970–2014 in the CMIP6 multi-model mean, which implies greenhouse gases primarily explain the positive trend in the total anthropogenic ERF. Cloud-mediated effects dominate the present-day aerosol ERF in most models. The results highlight a regional increase in marine cloudiness due to aerosols, despite suppressed cloud lifetime effects in that RFMIP-SpAer experiment. Negative cloud-mediated effects mask positive direct effects in many models, which arise from strong anthropogenic aerosol absorption. The findings suggest opportunities to better constrain simulated ERF by revisiting the optical properties and long-range transport of aerosols. Key Points: - Coupled Model Intercomparison Project phase six (CMIP6) averaged trend in aerosol effective radiative forcing (ERF) is small for 1970–2014 and weakly positive for 2000–2014 - Positive direct aerosol radiative effects in CMIP6 models are associated with strong aerosol absorption - Diverse and often strong cloud-mediated effects primarily determine the magnitude of aerosol ERF in CMIP6
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- 2023
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23. Investigating the role of stratospheric ozone as a driver of inter-model spread in CO2 effective radiative forcing.
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Byrom, Rachael, Myhre, Gunnar, Olivié, Dirk, and Schulz, Michael
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RADIATIVE forcing ,OZONE layer ,CLIMATE sensitivity ,RADIATIVE transfer ,CARBON dioxide ,CLIMATOLOGY - Abstract
Addressing the cause of inter-model spread in carbon dioxide (CO
2 ) radiative forcing is essential for reducing uncertainty in estimates of climate sensitivity. Recent studies demonstrate that a large proportion of this spread arises from variance in model base state climatology, particularly the specification of stratospheric temperature, which itself plays a dominant role in determining the magnitude of CO2 forcing. Here we investigate stratospheric ozone (O3 ) as a cause of inter-model differences in stratospheric temperature, and hence its role as a contributing factor to spread in CO2 radiative forcing. We use the Norwegian Earth System Model 2 (NorESM2) to analyse the impact of systematic increases/decreases in stratospheric O3 on the magnitude of 4xCO2 effective radiative forcing (ERF) and its components. Firstly, we demonstrate that accurate estimation of instantaneous radiative forcing requires the use of host-model radiative transfer calculations. Secondly, we show that a 50 % increase and decrease in stratospheric O3 concentration leads to significant differences in base state stratospheric temperature, ranging from +6 K to -9 K, respectively. However, this does not result in a correspondingly large spread in CO2 ERF due to the impact of base-state stratospheric temperature on the emission of outgoing longwave radiation and the spectral overlap of CO2 and O3 . We conclude that inter-model differences in stratospheric O3 concentration are therefore not predominantly responsible for inter-model spread in CO2 ERF. [ABSTRACT FROM AUTHOR]- Published
- 2024
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24. Supplementary material to "The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics"
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Ahsan, Hamza, primary, Wang, Hailong, additional, Wu, Jingbo, additional, Wu, Mingxuan, additional, Smith, Steven J., additional, Bauer, Susanne, additional, Suchyta, Harrison, additional, Olivié, Dirk, additional, Myhre, Gunnar, additional, Matsui, Hitoshi, additional, Bian, Huisheng, additional, Lamarque, Jean-François, additional, Carslaw, Ken, additional, Horowitz, Larry, additional, Regayre, Leighton, additional, Chin, Mian, additional, Schulz, Michael, additional, Skeie, Ragnhild Bieltvedt, additional, Takemura, Toshihiko, additional, and Naik, Vaishali, additional
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- 2023
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25. Global and regional marine bromoform emissions in a fully coupled ocean-atmosphere-model
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Booge, Dennis, primary, Tjiputra, Jerry, additional, Olivié, Dirk, additional, Quack, Birgit, additional, Schulz, Michael, additional, and Krüger, Kirstin, additional
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- 2023
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26. Global and regional trends of atmospheric sulfur
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Aas, Wenche, Mortier, Augustin, Bowersox, Van, Cherian, Ribu, Faluvegi, Greg, Fagerli, Hilde, Hand, Jenny, Klimont, Zbigniew, Galy-Lacaux, Corinne, Lehmann, Christopher M. B., Myhre, Cathrine Lund, Myhre, Gunnar, Olivié, Dirk, Sato, Keiichi, Quaas, Johannes, Rao, P. S. P., Schulz, Michael, Shindell, Drew, Skeie, Ragnhild B., Stein, Ariel, Takemura, Toshihiko, Tsyro, Svetlana, Vet, Robert, and Xu, Xiaobin
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- 2019
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27. Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models.
- Author
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Kalisoras, Alkiviadis, Georgoulias, Aristeidis K., Akritidis, Dimitris, Allen, Robert J., Naik, Vaishali, Kuo, Chaincy, Szopa, Sophie, Nabat, Pierre, Olivié, Dirk, van Noije, Twan, Le Sager, Philippe, Neubauer, David, Naga Oshima, Mulcahy, Jane, Horowitz, Larry W., and Zanis, Prodromos
- Abstract
Anthropogenic aerosols play a major role for the Earth-Atmosphere system by influencing the Earth’s radiative budget and climate. The effect of the perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF) which is the recommended metric for perturbations affecting the Earth’s top-of-atmosphere energy budget since it is a better way to link this perturbation to subsequent global mean surface temperature change. In this work, the present-day ERF of anthropogenic aerosols is quantified using simulations from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ERFs of individual aerosol species, such as sulphates, organic carbon (OC), and black carbon (BC) are calculated along with the ERF due to all anthropogenic aerosols and the transient ERF over the historical period (1850–2014). Additionally, ERF is analyzed into three components: (a) ERF
ARI , representing aerosol-radiation interactions, (b) ERFACI , accounting for aerosol-cloud interactions, and (c) ERFALB , which is mainly due to the contribution of surface albedo changes caused by anthropogenic aerosols. Here, the total anthropogenic aerosol ERF (calculated using the piClim-aer experiment) is estimated to be -1.11 ± 0.26 W m-2 , mostly due to the large contribution of ERFACI (-1.14 ± 0.33 W m-2 ), compared to ERFARI (-0.02 ± 0.20 W m-2 ) and ERFALB (0.05 ± 0.07 W m-2 ). The total ERF caused by sulphates (piClim-SO2 ) is estimated at -1.11 ± 0.31 W m-2 , the OC ERF (piClim-OC) is -0.35 ± 0.21 W m-2 , whereas the ERF exerted by BC (piClim-BC) is 0.19 ± 0.18 W m-2 . On top of that, our analysis reveals that ERFACI clearly prevails over the largest part of the Earth except for the BC experiment where ERFARI prevails over land. By the end of the historical period (1995–2014), the global mean total aerosol ERF is estimated at -1.28 ± 0.37 W m-2 (calculated using the histSST experiment). We find that sulphates dominate both present-day and transient ERF spatial patterns at the top of the atmosphere, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere, such as North America, Europe, East and South Asia. Since the mid-1980s ERF has become less negative over Eastern North America and Western and Central Europe, while over East and South Asia there is a steady increase in ERF magnitude towards more negative values until 2014. [ABSTRACT FROM AUTHOR]- Published
- 2023
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28. Using Ice Cores to Evaluate CMIP6 Aerosol Concentrations Over the Historical Era
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Moseid, Kine Onsum, primary, Schulz, Michael, additional, Eichler, Anja, additional, Schwikowski, Margit, additional, McConnell, Joseph R., additional, Olivié, Dirk, additional, Criscitiello, Alison S., additional, Kreutz, Karl J., additional, and Legrand, Michel, additional
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- 2022
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29. Point Splitting and U(1) Gauge Invariance
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Olivie, Dirk, Aubert, J.-J., editor, Gastmans, R., editor, and Gérard, J.-M., editor
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- 2000
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30. Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study
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Whaley, Cynthia H., primary, Mahmood, Rashed, additional, von Salzen, Knut, additional, Winter, Barbara, additional, Eckhardt, Sabine, additional, Arnold, Stephen, additional, Beagley, Stephen, additional, Becagli, Silvia, additional, Chien, Rong-You, additional, Christensen, Jesper, additional, Damani, Sujay Manish, additional, Dong, Xinyi, additional, Eleftheriadis, Konstantinos, additional, Evangeliou, Nikolaos, additional, Faluvegi, Gregory, additional, Flanner, Mark, additional, Fu, Joshua S., additional, Gauss, Michael, additional, Giardi, Fabio, additional, Gong, Wanmin, additional, Hjorth, Jens Liengaard, additional, Huang, Lin, additional, Im, Ulas, additional, Kanaya, Yugo, additional, Krishnan, Srinath, additional, Klimont, Zbigniew, additional, Kühn, Thomas, additional, Langner, Joakim, additional, Law, Kathy S., additional, Marelle, Louis, additional, Massling, Andreas, additional, Olivié, Dirk, additional, Onishi, Tatsuo, additional, Oshima, Naga, additional, Peng, Yiran, additional, Plummer, David A., additional, Popovicheva, Olga, additional, Pozzoli, Luca, additional, Raut, Jean-Christophe, additional, Sand, Maria, additional, Saunders, Laura N., additional, Schmale, Julia, additional, Sharma, Sangeeta, additional, Skeie, Ragnhild Bieltvedt, additional, Skov, Henrik, additional, Taketani, Fumikazu, additional, Thomas, Manu A., additional, Traversi, Rita, additional, Tsigaridis, Kostas, additional, Tsyro, Svetlana, additional, Turnock, Steven, additional, Vitale, Vito, additional, Walker, Kaley A., additional, Wang, Minqi, additional, Watson-Parris, Duncan, additional, and Weiss-Gibbons, Tahya, additional
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- 2022
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31. Effects of increased aerosol emissions over Asia on global sea-surface temperatures
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Pietschnig, Marianne, primary, Olivié, Dirk, additional, Moseid, Kine Onsum, additional, Hofer, Stefan, additional, Madan, Gaurav, additional, Lacasce, Joseph Henry, additional, and Storelvmo, Trude, additional
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- 2022
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32. Decomposing the direct and indirect radiative effects by mineral dust aerosols in CMIP6
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Haugvaldstad, Ove, primary, Olivié, Dirk, additional, Schulz, Michael, additional, and Storelvmo, Trude, additional
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- 2022
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33. ClimateBench: A benchmark for data-driven climate projections
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Watson-Parris, Duncan, primary, Rao, Yuhan, additional, Olivié, Dirk, additional, Seland, Øyvind, additional, Nowack, Peer, additional, Camps-Valls, Gustau, additional, Stier, Philip, additional, Bouabid, Shahine, additional, Dewey, Maura, additional, Fons, Emilie, additional, Gonzalez, Jessenia, additional, Harder, Paula, additional, Jeggle, Kai, additional, Lenhardt, Julien, additional, Manshausen, Peter, additional, Novitasari, Maria, additional, Ricard, Lucile, additional, and Roesch, Carla, additional
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- 2022
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34. The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics.
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Ahsan, Hamza, Wang, Hailong, Wu, Jingbo, Wu, Mingxuan, Smith, Steven J., Bauer, Susanne, Suchyta, Harrison, Olivié, Dirk, Myhre, Gunnar, Matsui, Hitoshi, Bian, Huisheng, Lamarque, Jean-François, Carslaw, Ken, Horowitz, Larry, Regayre, Leighton, Chin, Mian, Schulz, Michael, Skeie, Ragnhild Bieltvedt, Takemura, Toshihiko, and Naik, Vaishali
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ATMOSPHERIC chemistry ,ATMOSPHERIC models ,CHEMICAL models ,ATMOSPHERIC transport ,HUMAN ecology ,TROPOSPHERIC aerosols ,CARBONACEOUS aerosols - Abstract
Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth-atmosphere system, alter the formation of clouds and precipitation, and have substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO
2 injection, seasonality of SO2 and BC emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as SO4 in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find a large variation in atmospheric lifetime across models for SO2 , SO4 , and BC, with a particularly large relative variation for SO2 , which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of -0.35 W m-2 ), SO2 lifetime over northern hemisphere land (maximum difference of 0.8 days), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to assure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models. [ABSTRACT FROM AUTHOR]- Published
- 2023
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35. ClimateBench: A benchmark dataset for data-driven climate projections
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Watson-Parris, Duncan, primary, Rao, Yuhan, additional, Olivié, Dirk, additional, Seland, Øyvind, additional, Nowack, Peer J, additional, Camps-Valls, Gustau, additional, Stier, Philip, additional, Bouabid, Shahine, additional, Dewey, Maura, additional, Fons, Emilie, additional, Gonzalez, Jessenia, additional, Harder, Paula, additional, Jeggle, Kai, additional, Lenhardt, Julien, additional, Manshausen, Peter, additional, Novitasari, Maria, additional, Ricard, Lucile, additional, and Roesch, Carla, additional
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- 2022
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36. ClimateBench: A benchmark dataset for data-driven climate projections
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Watson-Parris, Duncan, primary, Rao, Yuhan, additional, Olivié, Dirk, additional, Seland, Øyvind, additional, Nowack, Peer J, additional, Camps-Valls, Gustau, additional, Stier, Philip, additional, Bouabid, Shahine, additional, Dewey, Maura, additional, Fons, Emilie, additional, Gonzalez, Jessenia Margarita Marina, additional, Harder, Paula, additional, Jeggle, Kai, additional, Lenhardt, Julien, additional, Manshausen, Peter, additional, Novitasari, Maria, additional, Ricard, Lucile, additional, and Roesch, Carla, additional
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- 2021
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37. Supplementary material to "Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study"
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Whaley, Cynthia H., primary, Mahmood, Rashed, additional, von Salzen, Knut, additional, Winter, Barbara, additional, Eckhardt, Sabine, additional, Arnold, Stephen, additional, Beagley, Stephen, additional, Becagli, Silvia, additional, Chien, Rong-You, additional, Christensen, Jesper, additional, Damani, Sujay M., additional, Eleftheriadis, Kostas, additional, Evangeliou, Nikolaos, additional, Faluvegi, Gregory S., additional, Flanner, Mark, additional, Fu, Joshua S., additional, Gauss, Michael, additional, Giardi, Fabio, additional, Gong, Wanmin, additional, Hjorth, Jens Liengaard, additional, Huang, Lin, additional, Im, Ulas, additional, Kanaya, Yugo, additional, Krishnan, Srinath, additional, Klimont, Zbigniew, additional, Kühn, Thomas, additional, Langner, Joakim, additional, Law, Kathy S., additional, Marelle, Louis, additional, Massling, Andreas, additional, Olivié, Dirk, additional, Onishi, Tatsuo, additional, Oshima, Naga, additional, Peng, Yiran, additional, Plummer, David A., additional, Popovicheva, Olga, additional, Pozzoli, Luca, additional, Raut, Jean-Christophe, additional, Sand, Maria, additional, Saunders, Laura N., additional, Schmale, Julia, additional, Sharma, Sangeeta, additional, Skov, Henrik, additional, Taketani, Fumikazu, additional, Thomas, Manu A., additional, Traversi, Rita, additional, Tsigaridis, Kostas, additional, Tsyro, Svetlana, additional, Turnock, Steven, additional, Vitale, Vito, additional, Walker, Kaley A., additional, Wang, Minqi, additional, Watson-Parris, Duncan, additional, and Weiss-Gibbons, Tahya, additional
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- 2021
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38. Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study
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Whaley, Cynthia H., primary, Mahmood, Rashed, additional, von Salzen, Knut, additional, Winter, Barbara, additional, Eckhardt, Sabine, additional, Arnold, Stephen, additional, Beagley, Stephen, additional, Becagli, Silvia, additional, Chien, Rong-You, additional, Christensen, Jesper, additional, Damani, Sujay M., additional, Eleftheriadis, Kostas, additional, Evangeliou, Nikolaos, additional, Faluvegi, Gregory S., additional, Flanner, Mark, additional, Fu, Joshua S., additional, Gauss, Michael, additional, Giardi, Fabio, additional, Gong, Wanmin, additional, Hjorth, Jens Liengaard, additional, Huang, Lin, additional, Im, Ulas, additional, Kanaya, Yugo, additional, Krishnan, Srinath, additional, Klimont, Zbigniew, additional, Kühn, Thomas, additional, Langner, Joakim, additional, Law, Kathy S., additional, Marelle, Louis, additional, Massling, Andreas, additional, Olivié, Dirk, additional, Onishi, Tatsuo, additional, Oshima, Naga, additional, Peng, Yiran, additional, Plummer, David A., additional, Popovicheva, Olga, additional, Pozzoli, Luca, additional, Raut, Jean-Christophe, additional, Sand, Maria, additional, Saunders, Laura N., additional, Schmale, Julia, additional, Sharma, Sangeeta, additional, Skov, Henrik, additional, Taketani, Fumikazu, additional, Thomas, Manu A., additional, Traversi, Rita, additional, Tsigaridis, Kostas, additional, Tsyro, Svetlana, additional, Turnock, Steven, additional, Vitale, Vito, additional, Walker, Kaley A., additional, Wang, Minqi, additional, Watson-Parris, Duncan, additional, and Weiss-Gibbons, Tahya, additional
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- 2021
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39. NorCPM1 and its contribution to CMIP6 DCPP
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Bethke, Ingo, primary, Wang, Yiguo, additional, Counillon, François, additional, Keenlyside, Noel, additional, Kimmritz, Madlen, additional, Fransner, Filippa, additional, Samuelsen, Annette, additional, Langehaug, Helene, additional, Svendsen, Lea, additional, Chiu, Ping-Gin, additional, Passos, Leilane, additional, Bentsen, Mats, additional, Guo, Chuncheng, additional, Gupta, Alok, additional, Tjiputra, Jerry, additional, Kirkevåg, Alf, additional, Olivié, Dirk, additional, Seland, Øyvind, additional, Solsvik Vågane, Julie, additional, Fan, Yuanchao, additional, and Eldevik, Tor, additional
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- 2021
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40. Aerosol absorption in global models from AeroCom phase III
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Sand, Maria, primary, Samset, Bjørn H., additional, Myhre, Gunnar, additional, Gliß, Jonas, additional, Bauer, Susanne E., additional, Bian, Huisheng, additional, Chin, Mian, additional, Checa-Garcia, Ramiro, additional, Ginoux, Paul, additional, Kipling, Zak, additional, Kirkevåg, Alf, additional, Kokkola, Harri, additional, Le Sager, Philippe, additional, Lund, Marianne T., additional, Matsui, Hitoshi, additional, van Noije, Twan, additional, Olivié, Dirk J. L., additional, Remy, Samuel, additional, Schulz, Michael, additional, Stier, Philip, additional, Stjern, Camilla W., additional, Takemura, Toshihiko, additional, Tsigaridis, Kostas, additional, Tsyro, Svetlana G., additional, and Watson-Parris, Duncan, additional
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- 2021
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41. Similar patterns of tropical precipitation and circulation changes under solar and greenhouse gas forcing
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Misios, Stergios, primary, Kasoar, Matthew, additional, Kasoar, Elliott, additional, Gray, Lesley, additional, Haigh, Joanna, additional, Stathopoulos, Stavros, additional, Kourtidis, Konstantinos, additional, Myhre, Gunnar, additional, Olivié, Dirk, additional, Shindell, Drew, additional, and Tang, Tao, additional
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- 2021
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42. Distinct surface response to black carbon aerosols
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Tang, Tao, primary, Shindell, Drew, additional, Zhang, Yuqiang, additional, Voulgarakis, Apostolos, additional, Lamarque, Jean-Francois, additional, Myhre, Gunnar, additional, Faluvegi, Gregory, additional, Samset, Bjørn H., additional, Andrews, Timothy, additional, Olivié, Dirk, additional, Takemura, Toshihiko, additional, and Lee, Xuhui, additional
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- 2021
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43. Emulating AOGCM results using simple climate models
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Olivié, Dirk and Stuber, Nicola
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- 2010
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44. Evaluating stratospheric ozone and water vapour changes in CMIP6 models from 1850 to 2100
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Keeble, James, Hassler, Birgit, Banerjee, Antara, Checa-Garcia, Ramiro, Chiodo, Gabriel, Davis, Sean, Eyring, Veronika, Griffiths, Paul T., Morgenstern, Olaf, Nowack, Peer, Zeng, Guang, Zhang, Jiankai, Bodeker, Greg, Burrows, Susannah, Cameron-Smith, Philip, Cugnet, David, Danek, Christopher, Deushi, Makoto, Horowitz, Larry W., Kubin, Anne, Li, Lijuan, Lohmann, Gerrit, Michou, Martine, Mills, Michael J., Nabat, Pierre, Olivié, Dirk, Park, Sungsu, Seland, Øyvind, Stoll, Jens, Wieners, Karl-Hermann, Wu, Tongwen, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Groupe de Météorologie de Grande Échelle et Climat (GMGEC), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
- Subjects
stratospheric ozone ,Science & Technology ,stratospheric water vapor ,[SDU]Sciences of the Universe [physics] ,Physical Sciences ,0201 Astronomical and Space Sciences ,Meteorology & Atmospheric Sciences ,Environmental Sciences & Ecology ,Erdsystemmodell -Evaluation und -Analyse ,0401 Atmospheric Sciences ,Life Sciences & Biomedicine ,CMIP6 ,Environmental Sciences - Abstract
Stratospheric ozone and water vapour are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here, we evaluate long-term changes in these species from the pre-industrial period (1850) to the end of the 21st century in Coupled Model Intercomparison Project phase 6 (CMIP6) models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations for total column ozone (TCO), although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global mean TCO has increased from ∼ 300 DU in 1850 to ∼ 305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone-depleting substances (ODSs). TCO is projected to return to 1960s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ∼ 10 DU higher than the 1960s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer–Dobson circulation under other Shared Socioeconomic Pathways (SSPs). In contrast to TCO, there is poorer agreement between the CMIP6 multi-model mean and observed lower stratospheric water vapour mixing ratios, with the CMIP6 multi-model mean underestimating observed water vapour mixing ratios by ∼ 0.5 ppmv at 70 hPa. CMIP6 multi-model mean stratospheric water vapour mixing ratios in the tropical lower stratosphere have increased by ∼ 0.5 ppmv from the pre-industrial to the present-day period and are projected to increase further by the end of the 21st century. The largest increases (∼ 2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Tropical lower stratospheric water vapour, and to a lesser extent TCO, shows large variations following explosive volcanic eruptions.
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- 2021
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45. How representative is Svalbard for future Arctic climate evolution? An Earth system modelling perspective (SvalCLIM)
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Gjermundsen, Ada, Graff, Lise Seland, Bentsen, Mats, Breivik, Lars Anders, Debernard, Jens Boldingh, Makkonen, Risto, Olivié, Dirk J L, Seland, Øyvind, Zieger, Paul, and Schulz, Michael
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Earth system modelling ,historical trends ,future projections ,Arctic amplification - Abstract
This is chapter 1 of the State of Environmental Science in Svalbard (SESS) report 2020 (https://sios-svalbard.org/SESS_Issue3). Situated in the Arctic and in a region with relatively pristine conditions, Svalbard is a very important and interdisciplinary observational supersite for the Arctic. In this SESS report, we investigate how representative Svalbard is for the Arctic region as a whole using data from numerical simulations with climate models. In our study comparing model predictions of how temperature, precipitation, and sea-ice extent develop over time, we found that the changes in Svalbard resemble those in the Arctic as a whole, both during the warming period of the past few decades and during projected future climate change. However, some important differences were found (see Highlights). Predicting and characterising climate change in Svalbard will be increasingly important in the 21st century as changes in near-surface air temperature, precipitation and sea-ice extent seem to occur at an extremely high pace in Svalbard, even higher than in the rest of the Arctic. Closer collaboration between experimentalists, observationalists, and the modelling community could help us understand the mechanisms underlying differences between observed and modelled climate changes. SIOS is in a unique position to coordinate and facilitate such collaborative research.  
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- 2021
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46. Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6
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Tebaldi, Claudia, Debeire, Kevin, Eyring, Veronika, Fischer, Erich, Fyfe, John, Friedlingstein, Pierre, Knutti, Reto, Lowe, Jason, O'Neill, Brian, Sanderson, Benjamin, Van Vuuren, Detlef, Riahi, Keywan, Meinshausen, Malte, Nicholls, Zebedee, Tokarska, Katarzyna, Hurtt, George, Kriegler, Elmar, Meehl, Gerald, Moss, Richard, Bauer, Susanne, Boucher, Olivier, Brovkin, Victor, Yhb, Yu, Dix, Martin, Gualdi, Silvio, Guo, Huan, John, Jasmin, Kharin, Slava, Kim, Young Ho, Koshiro, Tsuyoshi, Ma, Libin, Olivié, Dirk, Panickal, Swapna, Qiao, Fangli, Rong, Xinyao, Rosenbloom, Nan, Schupfner, Martin, Séférian, Roland, Sellar, Alistair, Semmler, Tido, Shi, Xiaoying, Song, Zhenya, Steger, Christian, Stouffer, Ronald, Swart, Neil, Tachiiri, Kaoru, Tang, Qi, Tatebe, Hiroaki, Voldoire, Aurore, Volodin, Evgeny, Environmental Sciences, and Sub Dynamics Meteorology
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Earth and Planetary Sciences(all) - Abstract
The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: Mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081-2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5-C) reached at the upper end of the 5 %-95% envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5-C of warming compared to the 1850-1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2-C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5-C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.
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- 2021
47. 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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48. Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models
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Bock, Josué, primary, Michou, Martine, additional, Nabat, Pierre, additional, Abe, Manabu, additional, Mulcahy, Jane P., additional, Olivié, Dirk J. L., additional, Schwinger, Jörg, additional, Suntharalingam, Parvadha, additional, Tjiputra, Jerry, additional, van Hulten, Marco, additional, Watanabe, Michio, additional, Yool, Andrew, additional, and Séférian, Roland, additional
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- 2021
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49. Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6
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Environmental Sciences, Sub Dynamics Meteorology, Tebaldi, Claudia, Debeire, Kevin, Eyring, Veronika, Fischer, Erich, Fyfe, John, Friedlingstein, Pierre, Knutti, Reto, Lowe, Jason, O'Neill, Brian, Sanderson, Benjamin, Van Vuuren, Detlef, Riahi, Keywan, Meinshausen, Malte, Nicholls, Zebedee, Tokarska, Katarzyna, Hurtt, George, Kriegler, Elmar, Meehl, Gerald, Moss, Richard, Bauer, Susanne, Boucher, Olivier, Brovkin, Victor, Yhb, Yu, Dix, Martin, Gualdi, Silvio, Guo, Huan, John, Jasmin, Kharin, Slava, Kim, Young Ho, Koshiro, Tsuyoshi, Ma, Libin, Olivié, Dirk, Panickal, Swapna, Qiao, Fangli, Rong, Xinyao, Rosenbloom, Nan, Schupfner, Martin, Séférian, Roland, Sellar, Alistair, Semmler, Tido, Shi, Xiaoying, Song, Zhenya, Steger, Christian, Stouffer, Ronald, Swart, Neil, Tachiiri, Kaoru, Tang, Qi, Tatebe, Hiroaki, Voldoire, Aurore, Volodin, Evgeny, Environmental Sciences, Sub Dynamics Meteorology, Tebaldi, Claudia, Debeire, Kevin, Eyring, Veronika, Fischer, Erich, Fyfe, John, Friedlingstein, Pierre, Knutti, Reto, Lowe, Jason, O'Neill, Brian, Sanderson, Benjamin, Van Vuuren, Detlef, Riahi, Keywan, Meinshausen, Malte, Nicholls, Zebedee, Tokarska, Katarzyna, Hurtt, George, Kriegler, Elmar, Meehl, Gerald, Moss, Richard, Bauer, Susanne, Boucher, Olivier, Brovkin, Victor, Yhb, Yu, Dix, Martin, Gualdi, Silvio, Guo, Huan, John, Jasmin, Kharin, Slava, Kim, Young Ho, Koshiro, Tsuyoshi, Ma, Libin, Olivié, Dirk, Panickal, Swapna, Qiao, Fangli, Rong, Xinyao, Rosenbloom, Nan, Schupfner, Martin, Séférian, Roland, Sellar, Alistair, Semmler, Tido, Shi, Xiaoying, Song, Zhenya, Steger, Christian, Stouffer, Ronald, Swart, Neil, Tachiiri, Kaoru, Tang, Qi, Tatebe, Hiroaki, Voldoire, Aurore, and Volodin, Evgeny
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- 2021
50. Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models
- Author
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Bock, Josué, Michou, Martine, Nabat, Pierre, Abe, Manabu, Mulcahy, Jane P., Olivié, Dirk J. L., Schwinger, Jörg, Suntharalingam, Parvadha, Tjiputra, Jerry, van Hulten, Marco, Watanabe, Michio, Yool, Andrew, Séférian, Roland, Bock, Josué, Michou, Martine, Nabat, Pierre, Abe, Manabu, Mulcahy, Jane P., Olivié, Dirk J. L., Schwinger, Jörg, Suntharalingam, Parvadha, Tjiputra, Jerry, van Hulten, Marco, Watanabe, Michio, Yool, Andrew, and Séférian, Roland
- Abstract
Characteristics and trends of surface ocean dimethylsulfide (DMS) concentrations and fluxes into the atmosphere of four Earth system models (ESMs: CNRM-ESM2-1, MIROC-ES2L, NorESM2-LM, and UKESM1-0-LL) are analysed over the recent past (1980–2009) and into the future, using Coupled Model Intercomparison Project 6 (CMIP6) simulations. The DMS concentrations in historical simulations systematically underestimate the most widely used observed climatology but compare more favourably against two recent observation-based datasets. The models better reproduce observations in mid to high latitudes, as well as in polar and westerlies marine biomes. The resulting multi-model estimate of contemporary global ocean DMS emissions is 16–24 Tg S yr−1, which is narrower than the observational-derived range of 16 to 28 Tg S yr−1. The four models disagree on the sign of the trend of the global DMS flux from 1980 onwards, with two models showing an increase and two models a decrease. At the global scale, these trends are dominated by changes in surface DMS concentrations in all models, irrespective of the air–sea flux parameterisation used. In turn, three models consistently show that changes in DMS concentrations are correlated with changes in marine productivity; however, marine productivity is poorly constrained in the current generation of ESMs, thus limiting the predictive ability of this relationship. In contrast, a consensus is found among all models over polar latitudes where an increasing trend is predominantly driven by the retreating sea-ice extent. However, the magnitude of this trend between models differs by a factor of 3, from 2.9 to 9.2 Gg S decade−1 over the period 1980–2014, which is at the low end of a recent satellite-derived analysis. Similar increasing trends are found in climate projections over the 21st century.
- Published
- 2021
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