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1. The AeroCom evaluation and intercomparison of organic aerosol in global models

Author: Tsigaridis, K, Daskalakis, N, Kanakidou, M, Adams, PJ, Artaxo, P, Bahadur, R, Balkanski, Y, Bauer, SE, Bellouin, N, Benedetti, A, Bergman, T, Berntsen, TK, Beukes, JP, Bian, H, Carslaw, KS, Chin, M, Curci, G, Diehl, T, Easter, RC, Ghan, SJ, Gong, SL, Hodzic, A, Hoyle, CR, Iversen, T, Jathar, S, Jimenez, JL, Kaiser, JW, Kirkevåg, A, Koch, D, Kokkola, H, Lee, YH, Lin, G, Liu, X, Luo, G, Ma, X, Mann, GW, Mihalopoulos, N, Morcrette, J-J, Müller, J-F, Myhre, G, Myriokefalitakis, S, Ng, NL, O'Donnell, D, Penner, JE, Pozzoli, L, Pringle, KJ, Russell, LM, Schulz, M, Sciare, J, Seland, Ø, Shindell, DT, Sillman, S, Skeie, RB, Spracklen, D, Stavrakou, T, Steenrod, SD, Takemura, T, Tiitta, P, Tilmes, S, Tost, H, van Noije, T, van Zyl, PG, von Salzen, K, Yu, F, Wang, Z, Zaveri, RA, Zhang, H, Zhang, K, Zhang, Q, and Zhang, X
Subjects: Aging, Climate Action, Astronomical and Space Sciences, Atmospheric Sciences, Meteorology & Atmospheric Sciences
Abstract: This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a-1 (range 34-144 Tg a-1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a-1 (range 13-121 Tg a-1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a-1 (range 16-121 Tg a-1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a-1; range 13-20 Tg a-1, with one model at 37 Tg a-1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6-2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8-9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a-1 (range 28-209 Tg a-1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model-observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model-measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to -0.62 (-0.51) based on the comparison against OC (OA) urban data of all models at the surface, -0.15 (+0.51) when compared with remote measurements, and -0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.
Published: 2014

2. Bounding the role of black carbon in the climate system: A scientific assessment

Author: Bond, T. C, Doherty, S. J, Fahey, D. W, Forster, P. M, Berntsen, T., DeAngelo, B. J, Flanner, M. G, Ghan, S., KÃ¤rcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K, Sarofim, M. C, Schultz, M. G, Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K, Hopke, P. K, Jacobson, M. Z, Kaiser, J. W, Klimont, Z., Lohmann, U., Schwarz, J. P, Shindell, D., Storelvmo, T., Warren, S. G, and Zender, C. S
Subjects: black carbon, climate forcing, aerosol
Abstract: Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr(-1) in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m(-2) with 90% uncertainty bounds of (+0.08, +1.27) W m(-2). Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m(-2). Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m(-2) with 90% uncertainty bounds of +0.17 to +2.1 W m(-2). Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m(-2), is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (-0.50 to +1.08) W m(-2) during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (-0.06 W m(-2) with 90% uncertainty bounds of -1.45 to +1.29 W m(-2)).The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.
Published: 2013

3. Global Carbon Budget 2023

Author: Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.
Published: 2023

4. Tuning of a new parameterization of ice supersaturation in LMDZ

Author: Sanogo, S., Boucher, O., Borella, A., Hourdin, F., Bellouin, N., Vignon, E., Musat, I., and Coulon-Decorzens, M.
Abstract: Ice supersaturation is a feature of the upper troposphere and is a necessary condition for cirrus cloud formation. Aircraft flying in these ice-supersaturated regions (ISSR) can produce contrails that can persist and grow for several hours, with important radiative effects. These radiative effects have an uncertain magnitude both in observations and in climate models and represent a significant fraction of the non-CO2 effects of aviation’s impact on climate.A parameterization of ISSR has been implemented in the atmospheric component (LMDZ) of the IPSL climate model known as IPSL-CM. Its main shortcoming is an underestimation of ISSR in the northern hemisphere, limiting its use to study the formation mechanisms of contrails and their radiative effects. These deficiencies come partly from an insufficient calibration.In this study, we have applied statistical methods based on Gaussian process and history matching to tune 16 free parameters of the ISSR, large-scale condensation and convection parameterizations in LMDZ. It allowed us to efficiently explore the space of these 16 parameters to identify LMDZ configurations satisfactorily matching global (top-of-atmosphere radiative budget) and regional (ISSR frequency of occurrence, cloud fraction and the ice water path) constraints, thus presenting smaller biases on the clouds and contrails radiative effects.These tuned configurations will be used in our future work to study the mechanisms of contrail and induced cirrus formation and to investigate their radiative effects while better characterizing the parametric uncertainties attached to these effects. Our tuning method could be applied to other climate models., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)
Published: 2023
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5. Global Carbon Budget 2022

Author: Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-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), 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, College of Life and Environmental Sciences [Exeter], University of Exeter, Rice University [Houston], Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Meteorology and Air Quality Department [Wageningen] (MAQ), Ludwig-Maximilians-Universität München (LMU), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), 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), Stanford Woods Institute for the Environment, Stanford University, European Commission - Joint Research Centre [Ispra] (JRC), Karlsruhe Institute of Technology (KIT), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Earth Sciences, Amsterdam Sustainability Institute, and Isotope Research
Subjects: WIMEK, [SDE.MCG]Environmental Sciences/Global Changes, SDG 13 - Climate Action, Life Science, General Earth and Planetary Sciences, Luchtkwaliteit, Air Quality
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).
Published: 2022

6. Microplastic Compendium

Author: Hildebrandt, L., El Gareb, F., Hansen, J., Takyar, H., Lange, M., Zimmermann, T., Jahnke, A., Bergmann, Melanie, Peeken, Ilka, Tekman, Mine Banu, Gerdts, Gunnar, Bellouin, N., Pohl, F., Baldewein, L., Pröfrock, D., Ebinghaus, R., Hildebrandt, L., El Gareb, F., Hansen, J., Takyar, H., Lange, M., Zimmermann, T., Jahnke, A., Bergmann, Melanie, Peeken, Ilka, Tekman, Mine Banu, Gerdts, Gunnar, Bellouin, N., Pohl, F., Baldewein, L., Pröfrock, D., and Ebinghaus, R.
Abstract: The Microplastic Compendium (MPC) serves as digital source of information and platform on different aspects of microplastic pollution. It targets various interest groups, both interested readers without scientific background and people with relevant scientific questions. Most importantly, users can find aggregated information on various aspects of this highly relevant environmental problem. Extensive information was gathered on the scope and consequences of microplastic pollution, as well as possible measures and solutions tackling the issue from a policy- and industry perspective. For early starts in the scientific field, the most relevant reviews are linked. Additionally, recommendations for suitable chemical-analytical workflows are included. The MPC does not claim to be complete. Content selection of reviews and recommendations are based on authors’ point of view on personal expert knowledge. The contents are therefore subjective. They are largely extracted from the theses by Fadi El Gareb, Jeannette Hansen and Lars Hildebrandt. Experts from Hereon, the Helmholtz Centre for Environmental Research (UFZ), the Alfred Wegener Institute (AWI) and the University of Plymouth have kindly contributed special articles. Special thanks to Hatef Takyar for the development and maintenance of the portal. The MPC has been developed in the context and is part of the Coastal Pollution Toolbox (URL: www.coastalpollutiontoolbox.org), a knowledge hub and digital working environment and tool set to study contaminant, nutrient and carbon dynamics in temperate and polar coastal zones. URL: www.microplastic-compendium.eu
Published: 2022

7. Global Carbon Budget 2022

Author: Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.
Published: 2022

8. Robust evidence for reversal in the aerosol effective climate forcing trend

Author: Quaas, J., Jia, H., Smith, C., Albright, A.L., Aas, W., Bellouin, N., Boucher, O., Doutriaux-Boucher, M., Forster, P.M., Grosvenor, D., Jenkins, S., Klimont, Z., Loeb, N.G., Ma, X., Naik, V., Paulot, F., Stier, P., Wild, M., Myhre, G., Schulz, M., Quaas, J., Jia, H., Smith, C., Albright, A.L., Aas, W., Bellouin, N., Boucher, O., Doutriaux-Boucher, M., Forster, P.M., Grosvenor, D., Jenkins, S., Klimont, Z., Loeb, N.G., Ma, X., Naik, V., Paulot, F., Stier, P., Wild, M., Myhre, G., and Schulz, M.
Abstract: Anthropogenic aerosols exert a cooling inﬂuence that offsets part of the greenhouse gas warming. Due to their short tropospheric lifetime of only up to several days, the aerosol forcing responds quickly to emissions. Here we present and discuss the evolution of the aerosol forcing since 2000. There are multiple lines of evidence that allow to robustly conclude that the anthropogenic aerosol effective radiative forcing – both aerosol-radiation and aerosol-cloud interactions – has become globally less negative, i.e. that the trend in aerosol effective radiative forcing changed sign from negative to positive. Bottom-up inventories show that anthropogenic primary aerosol and aerosol precursor emissions declined in most regions of the world; observations related to aerosol burden show declining trends, in particular of the ﬁne-mode particles that make up most of the anthropogenic aerosols; satellite retrievals of cloud droplet numbers show trends consistent in sign, as do observations of top-of-atmosphere radiation. Climate model results, including a revised set that is constrained by observations of the ocean heat content evolution show a consistent sign and magnitude for a positive forcing relative to 2000 due to reduced aerosol effects. This reduction leads to an acceleration of the forcing of climate change, i.e. an increase in forcing by 0.1 to 0.3 W m-2, up to 12 % of the total climate forcing in 2019 compared to 1750 according to IPCC.
Published: 2022

9. Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century

Author: Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E., Österle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.
Published: 2011

10. Highly contrasting effects of different climate forcing agents on terrestrial ecosystem services

Author: Huntingford, C., Cox, P. M., Mercado, L. M., Sitch, S., Bellouin, N., Boucher, O., and Gedney, N.
Published: 2011

11. AEROSOLS | Climatology of Tropospheric Aerosols

Author: Bellouin, N., primary and Haywood, J., additional
Published: 2015
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12. AEROSOLS | Role in Climate Change

Author: Bellouin, N., primary
Published: 2015
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13. Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity

Author: Smith, C. J., primary, Harris, G. R., additional, Palmer, M. D., additional, Bellouin, N., additional, Collins, W., additional, Myhre, G., additional, Schulz, M., additional, Golaz, J.‐C., additional, Ringer, M., additional, Storelvmo, T., additional, and Forster, P. M., additional
Published: 2021
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14. Human Influence on the Climate System (Chapter 3)

Author: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M.I, Huang, M., Leitzell, K., Lonnoy, E., Matthews, J.B.R., Maycock, T.K., Waterfield, T., Yelekçi, K., Yu, R., Zhu, B., Eyring, V., Gillett, N.P., Achuta Rao, K.M., Barimalala, R., Barreiro Parrillo, M., Bellouin, N., Cassou, C., Durack, P.J., Kosaka, Y., McGregor, S., Min, S., Morgenstern, O., Sun, Y., Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M.I, Huang, M., Leitzell, K., Lonnoy, E., Matthews, J.B.R., Maycock, T.K., Waterfield, T., Yelekçi, K., Yu, R., Zhu, B., Eyring, V., Gillett, N.P., Achuta Rao, K.M., Barimalala, R., Barreiro Parrillo, M., Bellouin, N., Cassou, C., Durack, P.J., Kosaka, Y., McGregor, S., Min, S., Morgenstern, O., and Sun, Y.
Abstract: The AR5 concluded that human influence on the climate system is clear, evident from increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and physical understanding of the climate system. This chapter updates the assessment of human influence on the climate system for large-scale indicators of climate change, synthesizing information from paleo records, observations and climate models. It also provides the primary evaluation of large-scale indicators of climate change in this Report, complemented by fitness-for-purpose evaluation in subsequent chapters.
Published: 2021

15. Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity

Author: Smith, C., Harris, G. R., Palmer, M. D., Bellouin, N., Collins, W., Myhre, G., Schulz, M., Golaz, J.‐C., Ringer, M., Storelvmo, T., Forster, P. M., Smith, C., Harris, G. R., Palmer, M. D., Bellouin, N., Collins, W., Myhre, G., Schulz, M., Golaz, J.‐C., Ringer, M., Storelvmo, T., and Forster, P. M.
Abstract: An observationally constrained time series of historical aerosol effective radiative forcing (ERF) from 1750 to 2019 is developed in this study. We find that the time history of aerosol ERFs diagnosed in CMIP6 models exhibits considerable variation and explore how the time history of aerosol forcing influences the probability distributions of present-day aerosol forcing and emergent metrics such as climate sensitivity. Using a simple energy balance model, trained on CMIP6 climate models and constrained by observed near-surface warming and ocean heat uptake, we derive estimates for the historical aerosol forcing. We find 2005–2014 mean aerosol ERF to be −1.1 (−1.8 to −0.5) W m−2 relative to 1750. Assuming recently published historical emissions from fossil fuel and industrial sectors and biomass burning emissions from SSP2-4.5, aerosol ERF in 2019 is −0.9 (−1.5 to −0.4) W m−2. There is a modest recovery in aerosol forcing (+0.025 W m−2 decade−1) between 1980 and 2014. This analysis also gives a 5%–95% range of equilibrium climate sensitivity of 1.8°C –5.1°C (best estimate 3.1°C) with a transient climate response of 1.2°C –2.6°C (best estimate 1.8°C).
Published: 2021

16. Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity

Author: Mann, G. W, Carslaw, K. S, Reddington, C. L, Pringle, K. J, Schulz, M, Asmi, A, Spracklen, D. V, Ridley, D. A, Woodhouse, M. T, Lee, L. A, Zhang, K, Ghan, S. J, Easter, R. C, Liu, X, Stier, P, Lee, Y. H, Adams, P. J, Tost, H, Lelieveld, J, Bauer, S. E, Tsigaridis, K, van Noije, T. P. C, Strunk, A, Vignati, E, and Bellouin, N
Subjects: Geophysics, Meteorology And Climatology
Abstract: Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multimodel- mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation an growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
Published: 2014
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17. An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

Author: Jiao, C, Flanner, M. G, Balkanski, Y, Bauer, S. E, Bellouin, N, Bernsten, T. K, Bian, H, Carslaw, K. S, Chin, M, DeLuca, N, Diehl, T, Ghan, S. J, Iversen, T, Kirkevag, A, Koch, D, Liu, X, Mann, G. W, Penner, J. E, Pitari, G, Schulz, M, Seland, O, Skeie, R. B, Steenrod, S. D, Stier, P, and Tkemura, T
Subjects: Meteorology And Climatology
Abstract: Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W/sq m and 0.18 (0.06-0.28) W/sq m in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W/sq m for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.
Published: 2014
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18. Bounding Global Aerosol Radiative Forcing of Climate Change

Author: Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A. -L., Dufresne, J. -L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, Thorsten, McCoy, D. T., Myhre, G., Muelmenstaedt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., Stevens, B., Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A. -L., Dufresne, J. -L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, Thorsten, McCoy, D. T., Myhre, G., Muelmenstaedt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.
Abstract: Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol-radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of -1.6 to -0.6Wm(-2), or -2.0 to -0.4Wm(-2) with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial-era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds. Plain Language Summary Human activities emit into the atmosphere small liquid and solid particles called aerosols. Those aerosols change the energy budget of the Earth and trigger climate changes, by scattering and absorbing solar and terrestrial radiation and playing important roles in the forma
Published: 2020
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19. Black Carbon Vertical Profiles Strongly Affect Its Radiative Forcing Uncertainty

Author: Samset, B. H, Myhre, G, Schulz, M, Balkanski, Y, Bauer, S, Berntsen, T. K, Bian, H, Bellouin, N, Diehl, T, Easter, R. C, Ghan, S. J, Iversen, T, Kinne, S, Kirkevag, A, Lamarque, J.-F, Lin, G, Liu, X, Penner, J. E, Seland, O, Skeie, R. B, Stier, P, Takemura, T, Tsigaridis, K, and Zhang, K
Subjects: Meteorology And Climatology
Abstract: The impact of black carbon (BC) aerosols on the global radiation balance is not well constrained. Here twelve global aerosol models are used to show that at least 20% of the present uncertainty in modeled BC direct radiative forcing (RF) is due to diversity in the simulated vertical profile of BC mass. Results are from phases 1 and 2 of the global aerosol model intercomparison project (AeroCom). Additionally, a significant fraction of the variability is shown to come from high altitudes, as, globally, more than 40% of the total BC RF is exerted above 5 km. BC emission regions and areas with transported BC are found to have differing characteristics. These insights into the importance of the vertical profile of BC lead us to suggest that observational studies are needed to better characterize the global distribution of BC, including in the upper troposphere.
Published: 2013
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20. Radiative Forcing of the Direct Aerosol Effect from AeroCom Phase II Simulations

Author: Myhre, G, Samset, B. H, Schulz, M, Balkanski, Y, Bauer, S, Berntsen, T. K, Bian, H, Bellouin, N, Chin, M, Diehl, T, Easter, R. C, Feichter, J, Ghan, S. J, Hauglustaine, D, Iversen, T, Kinne, S, Kirkevag, A, Lamarque, J.-F, Lin, G, Liu, X, Lund, M. T, Luo, G, Ma, X, vanNoije, T, Penner, J. E, Rasch, P. J, Ruiz, A, Seland, O, Skeie, R. B, Stier, P, Takemura, T, Tsigaridis, K, Wang, P, Wang, Z, Xu, L, Yu, H, Yu, F, Yoon, J. -H, Zhang, K, Zhang, H, and Zhou, C
Subjects: Meteorology And Climatology
Abstract: We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02 W m(sup−2), with a mean of −0.27 W m(sup−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35 W m(sup−2). Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study.We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results
Published: 2013
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21. Quantifying Progress Across Different CMIP Phases With the ESMValTool

Author: Bock, L., primary, Lauer, A., additional, Schlund, M., additional, Barreiro, M., additional, Bellouin, N., additional, Jones, C., additional, Meehl, G. A., additional, Predoi, V., additional, Roberts, M. J., additional, and Eyring, V., additional
Published: 2020
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22. Constraining Uncertainty in Aerosol Direct Forcing

Author: Watson‐Parris, D., primary, Bellouin, N., additional, Deaconu, L. T., additional, Schutgens, N. A. J., additional, Yoshioka, M., additional, Regayre, L. A., additional, Pringle, K. J., additional, Johnson, J. S., additional, Smith, C. J., additional, Carslaw, K. S., additional, and Stier, P., additional
Published: 2020
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23. Bounding Global Aerosol Radiative Forcing of Climate Change

Author: Bellouin, N., primary, Quaas, J., additional, Gryspeerdt, E., additional, Kinne, S., additional, Stier, P., additional, Watson‐Parris, D., additional, Boucher, O., additional, Carslaw, K. S., additional, Christensen, M., additional, Daniau, A.‐L., additional, Dufresne, J.‐L., additional, Feingold, G., additional, Fiedler, S., additional, Forster, P., additional, Gettelman, A., additional, Haywood, J. M., additional, Lohmann, U., additional, Malavelle, F., additional, Mauritsen, T., additional, McCoy, D. T., additional, Myhre, G., additional, Mülmenstädt, J., additional, Neubauer, D., additional, Possner, A., additional, Rugenstein, M., additional, Sato, Y., additional, Schulz, M., additional, Schwartz, S. E., additional, Sourdeval, O., additional, Storelvmo, T., additional, Toll, V., additional, Winker, D., additional, and Stevens, B., additional
Published: 2020
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24. State of the Climate in 2018

Author: Arndt, D. S., Blunden, J., Dunn, R. J. H., Stanitski, D. M., Gobron, N., Willett, K. M., Sanchez-lugo, A., Berrisford, P., Morice, C., Nicolas, Jp, Carrea, L., Woolway, R. I., Merchant, C. J., Dokulil, M. T., De Eyto, E., Degasperi, C. L., Korhonen, J., Marszelewski, W., May, L., Paterson, A. M., Rusak, J. A., Schladow, S. G., Schmid, M., Verburg, P., Watanabe, S., Weyhenmeyer, G. A., King, A. D., Donat, M. G., Christy, J. R., Po-chedley, S., Mears, C. R., Haimberger, L., Covey, C., Randel, W., Noetzli, J., Biskaborn, B. K., Christiansen, H. H., Isaksen, K., Schoeneich, P., Smith, S., Vieira, G., Zhao, L., Streletskiy, D. A., Robinson, D. A., Pelto, M., Berry, D. I., Bosilovich, M. G., Simmons, A. J., Mears, C., Ho, S. P., Bock, O., Zhou, X., Nicolas, J, Vose, R. S., Adler, R., Gu, G., Becker, A., Yin, X, Tye, M. R., Blenkinsop, S., Durre, I., Ziese, M., Collow, A. B. Marquardt, Rustemeier, E., Foster, M. J., Di Girolamo, L., Frey, R. A., Heidinger, A. K., Sun-mack, S., Phillips, C., Menzel, W. P., Stengel, M., Zhao, G., Kim, H., Rodell, M., Li, B., Famiglietti, J. S., Scanlon, T., Van Der Schalie, R., Preimesberger, W., Reimer, C., Hahn, S., Gruber, A., Kidd, R., De Jeu, R. A. M., Dorigo, W. A., Barichivich, J., Osborn, T. J., Harris, I., Van Der Schrier, G., Jones, P. D., Miralles, D. G., Martens, B., Beck, H. E., Dolman, A. J., Jimenez, C., Mccabe, M. F., Wood, E. F., Allan, R., Azorin-molina, C., Mears, C. A., Mcvicar, T. R., Mayer, M., Schenzinger, V., Hersbach, H., Stackhouse, P. W., Jr., Wong, T., Kratz, D. P., Sawaengphokhai, P., Wilber, A. C., Gupta, S. K., Loeb, N. G., Dlugokencky, E. J., Hall, B. D., Montzka, S. A., Dutton, G., Muhle, J., Elkins, J. W., Miller, Br, Remy, S., Bellouin, N., Kipling, Z., Ades, M., Benedetti, A., Boucher, O., Weber, M., Steinbrecht, W., Arosio, C., Van Der A, R., Frith, S. M., Anderson, J., Coldewey-egbers, M., Davis, S., Degenstein, D., Fioletov, V. E., Froidevaux, L., Hubert, D., Long, C. S., Loyola, D., Rozanov, A., Roth, C., Sofieva, V., Tourpali, K., Wang, R., Wild, J. D., Davis, S. M., Rosenlof, K. H., Hurst, D. F., Selkirk, H. B., Vomel, H., Ziemke, J. R., Cooper, O. R., Flemming, J., Inness, A., Pinty, B., Kaiser, J. W., Van Der Werf, G. R., Hemming, D. L., Garforth, J., Park, T., Richardson, A. D., Rutishauser, T., Sparks, T. H., Thackeray, S. J., Myneni, R., Lumpkin, R., Huang, B., Kennedy, J., Xue, Y., Zhang, H. -m., Hu, C., Wang, M., Johnson, G. C., Lyman, J. M., Boyer, T., Cheng, L., Domingues, C. M., Gilson, J., Ishii, M., Killick, R. E., Monselesan, D., Purkey, S. G., Wijffels, S. E., Locarnini, R., Yu, L., Jin, X., Stackhouse, P. W., Kato, S., Weller, R. A., Thompson, P. R., Widlansky, M. J., Leuliette, E., Sweet, W., Chambers, D. P., Hamlington, B. D., Jevrejeva, S., Marra, J. J., Merrifield, M. A., Mitchum, G. T., Nerem, R. S., Kelble, C., Karnauskas, M., Hubbard, K., Goni, G., Streeter, C., Dohan, K., Franz, B. A., Cetinic, I., Karakoylu, E. M., Siegel, D. A., Westberry, T. K., Feely, R. A., Wanninkhof, R., Carter, B. R., Landschutzer, P., Sutton, A. J., Cosca, C., Trinanes, J. A., Baxter, S., Schreck, C., Bell, G. D., Mullan, A. B., Pezza, A. B., Coelho, C. A. S., Wang, B., He, Q., Diamond, H. J., Schreck, C. J., Blake, E. S., Landsea, C. W., Wang, H., Goldenberg, S. B., Pasch, R. J., Klotzbach, P. J., Kruk, M. C., Camargo, S. J., Trewin, B. C., Pearce, P. R., Lorrey, A. M., Domingues, R., Goni, G. J., Knaff, J. A., Lin, I. -i., Bringas, F., Richter-menge, J., Osborne, E., Druckenmiller, M., Jeffries, M. O., Overland, J. E., Hanna, E., Hanssen-bauer, I., Kim, S. -j., Walsh, J. E., Bhatt, U. S., Timmermans, M. -l., Ladd, C., Perovich, D., Meier, W., Tschudi, M., Farrell, S., Hendricks, S., Gerland, S., Haas, C., Krumpen, T., Polashenski, C., Ricker, R, Webster, M., Stabeno, P. J., Tedesco, M., Box, J. E., Cappelen, J., Fausto, R. S., Fettweis, X., Andersen, J. K., Mote, T., Smeets, C. J. P. P., Van As, D., Van De Wal, R. S. W., Romanovsky, V. E., Smith, S. L., Shiklomanov, N. I., Kholodov, A. L., Drozdov, D. S., Malkova, G. V., Marchenko, S. S., Jella, K. B., Mudryk, L., Brown, R., Derksen, C., Luojus, K., Decharme, B., Holmes, R. M., Shiklomanov, A. I., Suslova, A., Tretiakov, M., Mcclelland, J. W., Spencer, R. G. M., Tank, S. E., Epstein, H., Bhatt, U., Raynolds, M., Walker, D., Forbes, B., Phoenix, G., Bjerke, J., Tommervik, H., Karlsen, S. -r., Goetz, S., Jia, G., Bernhard, G. H., Grooss, J. -u., Ialongo, I., Johnsen, B., Lakkala, K., Manney, G. L., Mueller, R., Scambos, T., Stammerjohn, S., Clem, K. R., Barreira, S., Fogt, R. L., Colwell, S., Keller, L. M., Lazzara, M. A., Reid, P., Massom, R. A., Lieser, J. L., Meijers, A., Sallee, J. -b., Grey, A., Johnson, K., Arrigo, K., Swart, S., King, B., Meredith, M., Mazloff, M., Scardilli, A., Claus, F., Shuman, C. A., Kramarova, N., Newman, P. A., Nash, E. R., Strahan, S. E., Johnson, B., Pitts, M., Santee, M. L., Petropavlovskikh, I., Braathen, G. O., Coy, L., De Laat, J., Bissolli, P., Ganter, C., Li, T., Mekonnen, A., Gleason, K., Smith, A., Fenimore, C., Heim, R. R., Jr., Nauslar, N. J., Brown, T. J., Mcevoy, D. J., Lareau, N. P., Amador, J. A., Hidalgo, H. G., Alfaro, E. J., Calderon, B., Mora, N., Stephenson, T. S., Taylor, M. A., Trotman, A. R., Van Meerbeeck, C. J., Campbell, J. D., Brown, A., Spence, J., Martinez, R., Diaz, E., Marin, D., Hernandez, R., Caceres, L., Zambrano, E., Nieto, J., Marengo, J. A., Espinoza, J. C., Alves, L. M., Ronchail, J., Lavado-casimiro, J. W., Ramos, I., Davila, C., Ramos, A. M., Diniz, F. A., Aliaga-nestares, V., Castro, A. Y., Stella, J. L., Aldeco, L. S., Diaz, D. A. Campos, Misevicius, N., Kabidi, K., Sayouri, A., Elkharrim, M., Mostafa, A. E., Hagos, S., Feng, Z., Ijampy, J. A., Sima, F., Francis, S. D., Tsidu, G. Mengistu, Kruger, A. C., Mcbride, C., Jumaux, G., Dhurmea, K. R., Belmont, M., Rakotoarimalala, C. L., Labbe, L., Rosner, B., Benedict, I., Van Heerwaarden, C., Weerts, A., Hazeleger, W., Trachte, K., Zhu, Z., Zhang, P., Lee, T. C., Ripaldi, A., Mochizuki, Y., Lim, J. -y, Oyunjargal, L., Timbal, B., Srivastava, A. K., Revadekar, J. V., Rajeevan, M., Shimpo, A., Khoshkam, M., Kazemi, A. Fazl, Zeyaeyan, S., Lander, M. A., Mcgree, S., Tobin, S., Bettio, L., Arndt, D. S., Blunden, J., Dunn, R. J. H., Stanitski, D. M., Gobron, N., Willett, K. M., Sanchez-lugo, A., Berrisford, P., Morice, C., Nicolas, Jp, Carrea, L., Woolway, R. I., Merchant, C. J., Dokulil, M. T., De Eyto, E., Degasperi, C. L., Korhonen, J., Marszelewski, W., May, L., Paterson, A. M., Rusak, J. A., Schladow, S. G., Schmid, M., Verburg, P., Watanabe, S., Weyhenmeyer, G. A., King, A. D., Donat, M. G., Christy, J. R., Po-chedley, S., Mears, C. R., Haimberger, L., Covey, C., Randel, W., Noetzli, J., Biskaborn, B. K., Christiansen, H. H., Isaksen, K., Schoeneich, P., Smith, S., Vieira, G., Zhao, L., Streletskiy, D. A., Robinson, D. A., Pelto, M., Berry, D. I., Bosilovich, M. G., Simmons, A. J., Mears, C., Ho, S. P., Bock, O., Zhou, X., Nicolas, J, Vose, R. S., Adler, R., Gu, G., Becker, A., Yin, X, Tye, M. R., Blenkinsop, S., Durre, I., Ziese, M., Collow, A. B. Marquardt, Rustemeier, E., Foster, M. J., Di Girolamo, L., Frey, R. A., Heidinger, A. K., Sun-mack, S., Phillips, C., Menzel, W. P., Stengel, M., Zhao, G., Kim, H., Rodell, M., Li, B., Famiglietti, J. S., Scanlon, T., Van Der Schalie, R., Preimesberger, W., Reimer, C., Hahn, S., Gruber, A., Kidd, R., De Jeu, R. A. M., Dorigo, W. A., Barichivich, J., Osborn, T. J., Harris, I., Van Der Schrier, G., Jones, P. D., Miralles, D. G., Martens, B., Beck, H. E., Dolman, A. J., Jimenez, C., Mccabe, M. F., Wood, E. F., Allan, R., Azorin-molina, C., Mears, C. A., Mcvicar, T. R., Mayer, M., Schenzinger, V., Hersbach, H., Stackhouse, P. W., Jr., Wong, T., Kratz, D. P., Sawaengphokhai, P., Wilber, A. C., Gupta, S. K., Loeb, N. G., Dlugokencky, E. J., Hall, B. D., Montzka, S. A., Dutton, G., Muhle, J., Elkins, J. W., Miller, Br, Remy, S., Bellouin, N., Kipling, Z., Ades, M., Benedetti, A., Boucher, O., Weber, M., Steinbrecht, W., Arosio, C., Van Der A, R., Frith, S. M., Anderson, J., Coldewey-egbers, M., Davis, S., Degenstein, D., Fioletov, V. E., Froidevaux, L., Hubert, D., Long, C. S., Loyola, D., Rozanov, A., Roth, C., Sofieva, V., Tourpali, K., Wang, R., Wild, J. D., Davis, S. M., Rosenlof, K. H., Hurst, D. F., Selkirk, H. B., Vomel, H., Ziemke, J. R., Cooper, O. R., Flemming, J., Inness, A., Pinty, B., Kaiser, J. W., Van Der Werf, G. R., Hemming, D. L., Garforth, J., Park, T., Richardson, A. D., Rutishauser, T., Sparks, T. H., Thackeray, S. J., Myneni, R., Lumpkin, R., Huang, B., Kennedy, J., Xue, Y., Zhang, H. -m., Hu, C., Wang, M., Johnson, G. C., Lyman, J. M., Boyer, T., Cheng, L., Domingues, C. M., Gilson, J., Ishii, M., Killick, R. E., Monselesan, D., Purkey, S. G., Wijffels, S. E., Locarnini, R., Yu, L., Jin, X., Stackhouse, P. W., Kato, S., Weller, R. A., Thompson, P. R., Widlansky, M. J., Leuliette, E., Sweet, W., Chambers, D. P., Hamlington, B. D., Jevrejeva, S., Marra, J. J., Merrifield, M. A., Mitchum, G. T., Nerem, R. S., Kelble, C., Karnauskas, M., Hubbard, K., Goni, G., Streeter, C., Dohan, K., Franz, B. A., Cetinic, I., Karakoylu, E. M., Siegel, D. A., Westberry, T. K., Feely, R. A., Wanninkhof, R., Carter, B. R., Landschutzer, P., Sutton, A. J., Cosca, C., Trinanes, J. A., Baxter, S., Schreck, C., Bell, G. D., Mullan, A. B., Pezza, A. B., Coelho, C. A. S., Wang, B., He, Q., Diamond, H. J., Schreck, C. J., Blake, E. S., Landsea, C. W., Wang, H., Goldenberg, S. B., Pasch, R. J., Klotzbach, P. J., Kruk, M. C., Camargo, S. J., Trewin, B. C., Pearce, P. R., Lorrey, A. M., Domingues, R., Goni, G. J., Knaff, J. A., Lin, I. -i., Bringas, F., Richter-menge, J., Osborne, E., Druckenmiller, M., Jeffries, M. O., Overland, J. E., Hanna, E., Hanssen-bauer, I., Kim, S. -j., Walsh, J. E., Bhatt, U. S., Timmermans, M. -l., Ladd, C., Perovich, D., Meier, W., Tschudi, M., Farrell, S., Hendricks, S., Gerland, S., Haas, C., Krumpen, T., Polashenski, C., Ricker, R, Webster, M., Stabeno, P. J., Tedesco, M., Box, J. E., Cappelen, J., Fausto, R. S., Fettweis, X., Andersen, J. K., Mote, T., Smeets, C. J. P. P., Van As, D., Van De Wal, R. S. W., Romanovsky, V. E., Smith, S. L., Shiklomanov, N. I., Kholodov, A. L., Drozdov, D. S., Malkova, G. V., Marchenko, S. S., Jella, K. B., Mudryk, L., Brown, R., Derksen, C., Luojus, K., Decharme, B., Holmes, R. M., Shiklomanov, A. I., Suslova, A., Tretiakov, M., Mcclelland, J. W., Spencer, R. G. M., Tank, S. E., Epstein, H., Bhatt, U., Raynolds, M., Walker, D., Forbes, B., Phoenix, G., Bjerke, J., Tommervik, H., Karlsen, S. -r., Goetz, S., Jia, G., Bernhard, G. H., Grooss, J. -u., Ialongo, I., Johnsen, B., Lakkala, K., Manney, G. L., Mueller, R., Scambos, T., Stammerjohn, S., Clem, K. R., Barreira, S., Fogt, R. L., Colwell, S., Keller, L. M., Lazzara, M. A., Reid, P., Massom, R. A., Lieser, J. L., Meijers, A., Sallee, J. -b., Grey, A., Johnson, K., Arrigo, K., Swart, S., King, B., Meredith, M., Mazloff, M., Scardilli, A., Claus, F., Shuman, C. A., Kramarova, N., Newman, P. A., Nash, E. R., Strahan, S. E., Johnson, B., Pitts, M., Santee, M. L., Petropavlovskikh, I., Braathen, G. O., Coy, L., De Laat, J., Bissolli, P., Ganter, C., Li, T., Mekonnen, A., Gleason, K., Smith, A., Fenimore, C., Heim, R. R., Jr., Nauslar, N. J., Brown, T. J., Mcevoy, D. J., Lareau, N. P., Amador, J. A., Hidalgo, H. G., Alfaro, E. J., Calderon, B., Mora, N., Stephenson, T. S., Taylor, M. A., Trotman, A. R., Van Meerbeeck, C. J., Campbell, J. D., Brown, A., Spence, J., Martinez, R., Diaz, E., Marin, D., Hernandez, R., Caceres, L., Zambrano, E., Nieto, J., Marengo, J. A., Espinoza, J. C., Alves, L. M., Ronchail, J., Lavado-casimiro, J. W., Ramos, I., Davila, C., Ramos, A. M., Diniz, F. A., Aliaga-nestares, V., Castro, A. Y., Stella, J. L., Aldeco, L. S., Diaz, D. A. Campos, Misevicius, N., Kabidi, K., Sayouri, A., Elkharrim, M., Mostafa, A. E., Hagos, S., Feng, Z., Ijampy, J. A., Sima, F., Francis, S. D., Tsidu, G. Mengistu, Kruger, A. C., Mcbride, C., Jumaux, G., Dhurmea, K. R., Belmont, M., Rakotoarimalala, C. L., Labbe, L., Rosner, B., Benedict, I., Van Heerwaarden, C., Weerts, A., Hazeleger, W., Trachte, K., Zhu, Z., Zhang, P., Lee, T. C., Ripaldi, A., Mochizuki, Y., Lim, J. -y, Oyunjargal, L., Timbal, B., Srivastava, A. K., Revadekar, J. V., Rajeevan, M., Shimpo, A., Khoshkam, M., Kazemi, A. Fazl, Zeyaeyan, S., Lander, M. A., Mcgree, S., Tobin, S., and Bettio, L.
Published: 2019

25. State of the climate in 2018

Author: Ades, M., Adler, R., Aldeco, L.S., Alejandra, G., Alfaro, E.J., Aliaga-Nestares, V., Allan, R.P., Allan, R., Alves, L.M., Amador, J.A., Andersen, J.K., Anderson, J., Arndt, D.S., Arosio, C., Arrigo, K., Azorin-Molina, C., Bardin, M.Y., Barichivich, J., Barreira, S., Baxter, S., Beck, H.E., Becker, A., Bell, G.D., Bellouin, N., Belmont, M., Benedetti, A., Benedict, I., Bernhard, G.H., Berrisford, P., Berry, D.I., Bettio, L., Bhatt, U.S., Biskaborn, B.K., Bissolli, P., Bjella, K.L., Bjerke, J.K., Blake, E.S., Blenkinsop, S., Blunden, J., Bock, O., Bosilovich, M.G., Boucher, O., Box, J.E., Boyer, T., Braathen, G., Bringas, F.G., Bromwich, D.H., Brown, A., Brown, R., Brown, T.J., Buehler, S.A., CÃ¡ceres, L., CalderÃ³n, B., Camargo, S.J., Campbell, J.D., Campos Diaz, D.A., Cappelen, J., Carrea, L., Carrier, S.B., Carter, B.R., Castro, A.Y., Cetinic, I., Chambers, D.P., Chen, L., Cheng, L., Cheng, V.Y.S., Christiansen, H.H., Christy, J.R., Chung, E.-S., Claus, F., Clem, K.R., Coelho, C.A.S., Coldewey-Egbers, M., Colwell, S., Cooper, O.R., Cosca, C., Covey, C., Coy, L., DÃ¡vila, C.P., Davis, S.M., de Eyto, E., de Jeu, R.A.M., De Laat, J., Decharme, B., Degasperi, C.L., Degenstein, D., Demircan, M., Derksen, C., Dhurmea, K.R., Di Girolamo, L., Diamond, H.J., Diaz, E., Diniz, F.A., Dlugokencky, E.J., Dohan, K., Dokulil, M.T., Dolman, A.J., Domingues, C.M., Domingues, R., Donat, M.G., Dorigo, W.A., Drozdov, D.S., Druckenmiller, M.L., Dunn, R.J.H., Durre, I., Dutton, G.S., Elkharrim, M., Elkins, J.W., Epstein, H.E., Espinoza, J.C., Famiglietti, J.S., Farrell, S.L., Fausto, R.S., Feely, R.A., Feng, Z., Fenimore, C., Fettweis, X., Fioletov, V.E., Flemming, J., Fogt, R.L., Forbes, B.C., Foster, M.J., Francis, S.D., Franz, B.A., Frey, R.A., Frith, S.M., Froidevaux, L., Ganter, C., Garforth, J., Gerland, S., Gilson, J., Gleason, K., Gobron, N., Goetz, S., Goldenberg, S.B., Goni, G., Gray, A., Groo, J.-U., Gruber, A., Gu, G., Guard, C.C.P., Gupta, S.K., GutiÃ©rrez, D., Haas, Christian, Hagos, S., Hahn, S., Haimberger, L., Hall, B.D., Halpert, M.S., Hamlington, B.D., Hanna, E., Hanssen-Bauer, I., Harris, I., Hazeleger, W., He, Q., Heidinger, A.K., Heim, Jr., Hemming, D.L., Hendricks, Stefan, HernÃ¡ndez, R., Hersbach, H.E., Hidalgo, H.G., Ho, S.-P.B., Holmes, R.M., Hu, C., Huang, B., Hubbard, K., Hubert, D., Hurst, D.F., Ialongo, I., Ijampy, J.A., Inness, A., Isaac, V., Isaksen, K., Ishii, M., Jeffries, M.O., Jevrejeva, S., Jia, G., JimÃ©nez, C., Jin, X., John, V., Johnsen, B., Johnson, G.C., Johnson, K.S., Johnson, B., Jones, P.D., Jumaux, G., Kabidi, K., Kaiser, J.W., KarakÃ¶ylÃ¼, E.M., Karlsen, S.-R., Karnauskas, M., Kato, S., Kazemi, A.F., Kelble, C., Keller, L.M., Kennedy, J., Kholodov, A.L., Khoshkam, M., Kidd, R., Killick, R., Kim, H., Kim, S.-J., King, A.D., King, B.A., Kipling, Z., Klotzbach, P.J., Knaff, J.A., Korhonen, J., Korshunova, N.N., Kramarova, N.A., Kratz, D.P., Kruger, A., Kruk, M.C., Krumpen, Thomas, LabbÃ©, L., Ladd, C., Lakatos, M., Lakkala, K., Lander, M.A., LandschÃ¼tzer, P., Landsea, C.W., Lareau, N.P., Lavado-Casimiro, W., Lazzara, M.A., Lee, T.C., Leuliette, E., Lâ��heureux, M., Li, B., Li, T., Lieser, J.L., Lim, J.-Y., Lin, I.-I., Liu, H., Locarnini, R., Loeb, N.G., Long, C.S., LÃ³pez, L.A., Lorrey, A.M., Loyola, D., Lumpkin, R., Luo, J.-J., Luojus, K., Lyman, J.M., Malkova, G.V., Manney, G.L., Marchenko, S.S., Marengo, J.A., Marin, D., Marquardt Collow, A.B., Marra, J.J., Marszelewski, W., Martens, B., MartÃnez-GÃ¼ingla, R., Massom, R.A., May, L., Mayer, M., Mazloff, M., McBride, C., McCabe, M., McClelland, J.W., McEvoy, D.J., McGree, S., McVicar, T.R., Mears, C.A., Meier, W., Meijers, A., Mekonnen, A., Mengistu Tsidu, G., Menzel, W.P., Merchant, C.J., Meredith, M.P., Merrifield, M.A., Miller, B., Miralles, D.G., Misevicius, N., Mitchum, G.T., Mochizuki, Y., Monselesan, D., Montzka, S.A., Mora, N., Morice, C., Mosquera-VÃ¡squez, K., Mostafa, A.E., Mote, T., Mudryk, L., MÃ¼hle, J., Mullan, A.B., MÃ¼ller, R., Myneni, R., Nash, E.R., Nauslar, N.J., Nerem, R.S., Newman, P.A., Nicolas, J.P., Nieto, J.J., Noetzli, J., Osborn, T.J., Osborne, E., Overland, J., Oyunjargal, L., Park, T., Pasch, R.J., Pascual RamÃrez, R., Pastor Saavedra, M.A., Paterson, A.M., Pearce, P.R., Pelto, M.S., Perovich, D., Petropavlovskikh, I., Pezza, A.B., Phillips, C., Phillips, D., Phoenix, G., Pinty, B., Pitts, M., Po-Chedley, S., Polashenski, C., Preimesberger, W., Purkey, S.G., Quispe, N., Rajeevan, M., Rakotoarimalala, C.L., Ramos, A.M., Ramos, I., Randel, W., Raynolds, M.K., Reagan, J., Reid, P., Reimer, C., RÃ©my, S., Revadekar, J.V., Richardson, A.D., Richter-Menge, J., Ricker, Robert, Ripaldi, A., Robinson, D.A., Rodell, M., Rodriguez Camino, E., Romanovsky, V.E., Ronchail, J., Rosenlof, K.H., RÃ¶sner, B., Roth, C., Rozanov, A., Rusak, J.A., Rustemeier, E., RutishÃ¤user, T., SallÃ©e, J.-B., SÃ¡nchez-Lugo, A., Santee, M.L., Sawaengphokhai, P., Sayouri, A., Scambos, T.A., Scanlon, T., Scardilli, A.S., Schenzinger, V., Schladow, S.G., Schmid, C., Schmid, M., Schoeneich, P., Schreck, III, Selkirk, H.B., Sensoy, S., Shi, L., Shiklomanov, A.I., Shiklomanov, N.I., Shimpo, A., Shuman, C.A., Siegel, D.A., Sima, F., Simmons, A.J., Smeets, C.J.P.P., Smith, A., Smith, S.L., Soden, B., Sofieva, V., Sparks, T.H., Spence, J., Spencer, R.G.M., Spillane, S., Srivastava, A.K., Stabeno, P.J., Stackhouse, Jr., Stammerjohn, S., Stanitski, D.M., Steinbrecht, W., Stella, J.L., Stengel, M., Stephenson, T.S., Strahan, S.E., Streeter, C., Streletskiy, D.A., Sun-Mack, S., Suslova, A., Sutton, A.J., Swart, S., Sweet, W., Takahashi, K.S., Tank, S.E., Taylor, M.A., Tedesco, M., Thackeray, S.J., Thompson, P.R., Timbal, B., Timmermans, M.-L., Tobin, S., TÃ¸mmervik, H., Tourpali, K., Trachte, K., Tretiakov, M., Trewin, B.C., TriÃ±anes, J.A., Trotman, A.R., Tschudi, M., Tye, M.R., van As, D., van de Wal, R.S.W., van der A, R.J., van der Schalie, R., van der Schrier, G., van der Werf, G.R., van Heerwaarden, C., Van Meerbeeck, C.J., Verburg, P., Vieira, G., Vincent, L.A., VÃ¶mel, H., Vose, R.S., Walker, D.A., Walsh, J.E., Wang, B., Wang, H., Wang, L., Wang, M., Wang, R., Wang, S.-H., Wanninkhof, R., Watanabe, S., Weber, M., Webster, M., Weerts, A., Weller, R.A., Westberry, T.K., Weyhenmeyer, G.A., Widlansky, M.J., Wijffels, S.E., Wilber, A.C., Wild, J.D., Willett, K.M., Wong, T., Wood, E.F., Woolway, R.I., Xue, Y., Yin, X., Yu, L., Zambrano, E., Zeyaeyan, S., Zhang, H.-M., Zhang, P., Zhao, G., Zhao, L., Zhou, X., Zhu, Z., Ziemke, J.R., Ziese, M., Andersen, A., Griffin, J., Hammer, G., Love-Brotak, S.E., Misch, D.J., Riddle, D.B., Veasey, S.W., Ades, M., Adler, R., Aldeco, L.S., Alejandra, G., Alfaro, E.J., Aliaga-Nestares, V., Allan, R.P., Allan, R., Alves, L.M., Amador, J.A., Andersen, J.K., Anderson, J., Arndt, D.S., Arosio, C., Arrigo, K., Azorin-Molina, C., Bardin, M.Y., Barichivich, J., Barreira, S., Baxter, S., Beck, H.E., Becker, A., Bell, G.D., Bellouin, N., Belmont, M., Benedetti, A., Benedict, I., Bernhard, G.H., Berrisford, P., Berry, D.I., Bettio, L., Bhatt, U.S., Biskaborn, B.K., Bissolli, P., Bjella, K.L., Bjerke, J.K., Blake, E.S., Blenkinsop, S., Blunden, J., Bock, O., Bosilovich, M.G., Boucher, O., Box, J.E., Boyer, T., Braathen, G., Bringas, F.G., Bromwich, D.H., Brown, A., Brown, R., Brown, T.J., Buehler, S.A., CÃ¡ceres, L., CalderÃ³n, B., Camargo, S.J., Campbell, J.D., Campos Diaz, D.A., Cappelen, J., Carrea, L., Carrier, S.B., Carter, B.R., Castro, A.Y., Cetinic, I., Chambers, D.P., Chen, L., Cheng, L., Cheng, V.Y.S., Christiansen, H.H., Christy, J.R., Chung, E.-S., Claus, F., Clem, K.R., Coelho, C.A.S., Coldewey-Egbers, M., Colwell, S., Cooper, O.R., Cosca, C., Covey, C., Coy, L., DÃ¡vila, C.P., Davis, S.M., de Eyto, E., de Jeu, R.A.M., De Laat, J., Decharme, B., Degasperi, C.L., Degenstein, D., Demircan, M., Derksen, C., Dhurmea, K.R., Di Girolamo, L., Diamond, H.J., Diaz, E., Diniz, F.A., Dlugokencky, E.J., Dohan, K., Dokulil, M.T., Dolman, A.J., Domingues, C.M., Domingues, R., Donat, M.G., Dorigo, W.A., Drozdov, D.S., Druckenmiller, M.L., Dunn, R.J.H., Durre, I., Dutton, G.S., Elkharrim, M., Elkins, J.W., Epstein, H.E., Espinoza, J.C., Famiglietti, J.S., Farrell, S.L., Fausto, R.S., Feely, R.A., Feng, Z., Fenimore, C., Fettweis, X., Fioletov, V.E., Flemming, J., Fogt, R.L., Forbes, B.C., Foster, M.J., Francis, S.D., Franz, B.A., Frey, R.A., Frith, S.M., Froidevaux, L., Ganter, C., Garforth, J., Gerland, S., Gilson, J., Gleason, K., Gobron, N., Goetz, S., Goldenberg, S.B., Goni, G., Gray, A., Groo, J.-U., Gruber, A., Gu, G., Guard, C.C.P., Gupta, S.K., GutiÃ©rrez, D., Haas, Christian, Hagos, S., Hahn, S., Haimberger, L., Hall, B.D., Halpert, M.S., Hamlington, B.D., Hanna, E., Hanssen-Bauer, I., Harris, I., Hazeleger, W., He, Q., Heidinger, A.K., Heim, Jr., Hemming, D.L., Hendricks, Stefan, HernÃ¡ndez, R., Hersbach, H.E., Hidalgo, H.G., Ho, S.-P.B., Holmes, R.M., Hu, C., Huang, B., Hubbard, K., Hubert, D., Hurst, D.F., Ialongo, I., Ijampy, J.A., Inness, A., Isaac, V., Isaksen, K., Ishii, M., Jeffries, M.O., Jevrejeva, S., Jia, G., JimÃ©nez, C., Jin, X., John, V., Johnsen, B., Johnson, G.C., Johnson, K.S., Johnson, B., Jones, P.D., Jumaux, G., Kabidi, K., Kaiser, J.W., KarakÃ¶ylÃ¼, E.M., Karlsen, S.-R., Karnauskas, M., Kato, S., Kazemi, A.F., Kelble, C., Keller, L.M., Kennedy, J., Kholodov, A.L., Khoshkam, M., Kidd, R., Killick, R., Kim, H., Kim, S.-J., King, A.D., King, B.A., Kipling, Z., Klotzbach, P.J., Knaff, J.A., Korhonen, J., Korshunova, N.N., Kramarova, N.A., Kratz, D.P., Kruger, A., Kruk, M.C., Krumpen, Thomas, LabbÃ©, L., Ladd, C., Lakatos, M., Lakkala, K., Lander, M.A., LandschÃ¼tzer, P., Landsea, C.W., Lareau, N.P., Lavado-Casimiro, W., Lazzara, M.A., Lee, T.C., Leuliette, E., Lâ��heureux, M., Li, B., Li, T., Lieser, J.L., Lim, J.-Y., Lin, I.-I., Liu, H., Locarnini, R., Loeb, N.G., Long, C.S., LÃ³pez, L.A., Lorrey, A.M., Loyola, D., Lumpkin, R., Luo, J.-J., Luojus, K., Lyman, J.M., Malkova, G.V., Manney, G.L., Marchenko, S.S., Marengo, J.A., Marin, D., Marquardt Collow, A.B., Marra, J.J., Marszelewski, W., Martens, B., MartÃnez-GÃ¼ingla, R., Massom, R.A., May, L., Mayer, M., Mazloff, M., McBride, C., McCabe, M., McClelland, J.W., McEvoy, D.J., McGree, S., McVicar, T.R., Mears, C.A., Meier, W., Meijers, A., Mekonnen, A., Mengistu Tsidu, G., Menzel, W.P., Merchant, C.J., Meredith, M.P., Merrifield, M.A., Miller, B., Miralles, D.G., Misevicius, N., Mitchum, G.T., Mochizuki, Y., Monselesan, D., Montzka, S.A., Mora, N., Morice, C., Mosquera-VÃ¡squez, K., Mostafa, A.E., Mote, T., Mudryk, L., MÃ¼hle, J., Mullan, A.B., MÃ¼ller, R., Myneni, R., Nash, E.R., Nauslar, N.J., Nerem, R.S., Newman, P.A., Nicolas, J.P., Nieto, J.J., Noetzli, J., Osborn, T.J., Osborne, E., Overland, J., Oyunjargal, L., Park, T., Pasch, R.J., Pascual RamÃrez, R., Pastor Saavedra, M.A., Paterson, A.M., Pearce, P.R., Pelto, M.S., Perovich, D., Petropavlovskikh, I., Pezza, A.B., Phillips, C., Phillips, D., Phoenix, G., Pinty, B., Pitts, M., Po-Chedley, S., Polashenski, C., Preimesberger, W., Purkey, S.G., Quispe, N., Rajeevan, M., Rakotoarimalala, C.L., Ramos, A.M., Ramos, I., Randel, W., Raynolds, M.K., Reagan, J., Reid, P., Reimer, C., RÃ©my, S., Revadekar, J.V., Richardson, A.D., Richter-Menge, J., Ricker, Robert, Ripaldi, A., Robinson, D.A., Rodell, M., Rodriguez Camino, E., Romanovsky, V.E., Ronchail, J., Rosenlof, K.H., RÃ¶sner, B., Roth, C., Rozanov, A., Rusak, J.A., Rustemeier, E., RutishÃ¤user, T., SallÃ©e, J.-B., SÃ¡nchez-Lugo, A., Santee, M.L., Sawaengphokhai, P., Sayouri, A., Scambos, T.A., Scanlon, T., Scardilli, A.S., Schenzinger, V., Schladow, S.G., Schmid, C., Schmid, M., Schoeneich, P., Schreck, III, Selkirk, H.B., Sensoy, S., Shi, L., Shiklomanov, A.I., Shiklomanov, N.I., Shimpo, A., Shuman, C.A., Siegel, D.A., Sima, F., Simmons, A.J., Smeets, C.J.P.P., Smith, A., Smith, S.L., Soden, B., Sofieva, V., Sparks, T.H., Spence, J., Spencer, R.G.M., Spillane, S., Srivastava, A.K., Stabeno, P.J., Stackhouse, Jr., Stammerjohn, S., Stanitski, D.M., Steinbrecht, W., Stella, J.L., Stengel, M., Stephenson, T.S., Strahan, S.E., Streeter, C., Streletskiy, D.A., Sun-Mack, S., Suslova, A., Sutton, A.J., Swart, S., Sweet, W., Takahashi, K.S., Tank, S.E., Taylor, M.A., Tedesco, M., Thackeray, S.J., Thompson, P.R., Timbal, B., Timmermans, M.-L., Tobin, S., TÃ¸mmervik, H., Tourpali, K., Trachte, K., Tretiakov, M., Trewin, B.C., TriÃ±anes, J.A., Trotman, A.R., Tschudi, M., Tye, M.R., van As, D., van de Wal, R.S.W., van der A, R.J., van der Schalie, R., van der Schrier, G., van der Werf, G.R., van Heerwaarden, C., Van Meerbeeck, C.J., Verburg, P., Vieira, G., Vincent, L.A., VÃ¶mel, H., Vose, R.S., Walker, D.A., Walsh, J.E., Wang, B., Wang, H., Wang, L., Wang, M., Wang, R., Wang, S.-H., Wanninkhof, R., Watanabe, S., Weber, M., Webster, M., Weerts, A., Weller, R.A., Westberry, T.K., Weyhenmeyer, G.A., Widlansky, M.J., Wijffels, S.E., Wilber, A.C., Wild, J.D., Willett, K.M., Wong, T., Wood, E.F., Woolway, R.I., Xue, Y., Yin, X., Yu, L., Zambrano, E., Zeyaeyan, S., Zhang, H.-M., Zhang, P., Zhao, G., Zhao, L., Zhou, X., Zhu, Z., Ziemke, J.R., Ziese, M., Andersen, A., Griffin, J., Hammer, G., Love-Brotak, S.E., Misch, D.J., Riddle, D.B., and Veasey, S.W.
Published: 2019

26. State of the climate in 2017

Author: Abernethy, R, Ackerman, SA, Adler, R, Albanil Encarnación, A, Aldeco, LS, Alfaro, EJ, Aliaga-Nestares, V, Allan, RP, Allan, R, Alves, LM, Amador, JA, Anderson, J, Andreassen, LM, Argüez, A, Armitage, C, Arndt, DS, Avalos, G, Azorin-Molina, C, Báez, J, Bardin, MY, Barichivich, J, Baringer, MO, Barreira, S, Baxter, S, Beck, HE, Becker, A, Bedka, KM, Behe, C, Bell, GD, Bellouin, N, Belmont, M, Benedetti, A, Bernhard, GH, Berrisford, P, Berry, DI, Bhatt, US, Bissolli, P, Bjerke, J, Blake, ES, Blenkinsop, S, Blunden, J, Bolmgren, K, Bosilovich, MG, Boucher, O, Bouchon, M, Box, JE, Boyer, T, Braathen, GO, Bromwich, DH, Brown, R, Buehler, S, Bulygina, ON, Burgess, D, Calderón, B, Camargo, SJ, Campbell, EC, Campbell, JD, Cappelen, J, Carrea, L, Carter, BR, Castro, A, Chambers, DP, Cheng, L, Christiansen, HH, Christy, JR, Chung, ES, Clem, KR, Coelho, CAS, Coldewey-Egbers, M, Colwell, S, Cooper, OR, Copland, L, Costanza, C, Covey, C, Coy, L, Cronin, T, Crouch, J, Cruzado, L, Daniel, R, Davis, SM, Davletshin, SG, De Eyto, E, De Jeu, RAM, De La Cour, JL, De Laat, J, De Gasperi, CL, Degenstein, D, Deline, P, Demircan, M, Derksen, C, Dewitte, B, Dhurmea, R, Di Girolamo, L, Diamond, HJ, Dickerson, C, Dlugokencky, EJ, Dohan, K, Dokulil, MT, Dolman, AJ, and Domingues, CM
Abstract: In 2017, the dominant greenhouse gases released into Earth's atmosphere-carbon dioxide, methane, and nitrous oxide-reached new record highs. The annual global average carbon dioxide concentration at Earth's surface for 2017 was 405.0 ± 0.1 ppm, 2.2 ppm greater than for 2016 and the highest in the modern atmospheric measurement record and in ice core records dating back as far as 800 000 years. The global growth rate of CO2 has nearly quadrupled since the early 1960s. With ENSO-neutral conditions present in the central and eastern equatorial Pacific Ocean during most of the year and weak La Niña conditions notable at the start and end, the global temperature across land and ocean surfaces ranked as the second or third highest, depending on the dataset, since records began in the mid-to-late 1800s. Notably, it was the warmest non-El Niño year in the instrumental record. Above Earth's surface, the annual lower tropospheric temperature was also either second or third highest according to all datasets analyzed. The lower stratospheric temperature was about 0.2°C higher than the record cold temperature of 2016 according to most of the in situ and satellite datasets. Several countries, including Argentina, Uruguay, Spain, and Bulgaria, reported record high annual temperatures. Mexico broke its annual record for the fourth consecutive year. On 27 January, the temperature reached 43.4°C at Puerto Madryn, Argentina-the highest temperature recorded so far south (43°S) anywhere in the world. On 28 May in Turbat, western Pakistan, the high of 53.5°C tied Pakistan's all-time highest temperature and became the world-record highest temperature for May. In the Arctic, the 2017 land surface temperature was 1.6°C above the 1981-2010 average, the second highest since the record began in 1900, behind only 2016. The five highest annual Arctic temperatures have all occurred since 2007. Exceptionally high temperatures were observed in the permafrost across the Arctic, with record values reported in much of Alaska and northwestern Canada. In August, high sea surface temperature (SST) records were broken for the Chukchi Sea, with some regions as warm as +11°C, or 3° to 4°C warmer than the longterm mean (1982-present). According to paleoclimate studies, today's abnormally warm Arctic air and SSTs have not been observed in the last 2000 years. The increasing temperatures have led to decreasing Arctic sea ice extent and thickness. On 7 March, sea ice extent at the end of the growth season saw its lowest maximum in the 37-year satellite record, covering 8% less area than the 1981-2010 average. The Arctic sea ice minimum on 13 September was the eighth lowest on record and covered 25% less area than the long-term mean. Preliminary data indicate that glaciers across the world lost mass for the 38th consecutive year on record; the declines are remarkably consistent from region to region. Cumulatively since 1980, this loss is equivalent to slicing 22 meters off the top of the average glacier. Antarctic sea ice extent remained below average for all of 2017, with record lows during the first four months. Over the continent, the austral summer seasonal melt extent and melt index were the second highest since 2005, mostly due to strong positive anomalies of air temperature over most of the West Antarctic coast. In contrast, the East Antarctic Plateau saw record low mean temperatures in March. The year was also distinguished by the second smallest Antarctic ozone hole observed since 1988. Across the global oceans, the overall long-term SST warming trend remained strong. Although SST cooled slightly from 2016 to 2017, the last three years produced the three highest annual values observed; these high anomalies have been associated with widespread coral bleaching. The most recent global coral bleaching lasted three full years, June 2014 to May 2017, and was the longest, most widespread, and almost certainly most destructive such event on record. Global integrals of 0-700-m and 0-2000-m ocean heat content reached record highs in 2017, and global mean sea level during the year became the highest annual average in the 25-year satellite altimetry record, rising to 77 mm above the 1993 average. In the tropics, 2017 saw 85 named tropical storms, slightly above the 1981-2010 average of 82. The North Atlantic basin was the only basin that featured an above-normal season, its seventh most active in the 164-year record. Three hurricanes in the basin were especially notable. Harvey produced record rainfall totals in areas of Texas and Louisiana, including a storm total of 1538.7 mm near Beaumont, Texas, which far exceeds the previous known U.S. tropical cyclone record of 1320.8 mm. Irma was the strongest tropical cyclone globally in 2017 and the strongest Atlantic hurricane outside of the Gulf of Mexico and Caribbean on record with maximum winds of 295 km h-1. Maria caused catastrophic destruction across the Caribbean Islands, including devastating wind damage and flooding across Puerto Rico. Elsewhere, the western North Pacific, South Indian, and Australian basins were all particularly quiet. Precipitation over global land areas in 2017 was clearly above the long-term average. Among noteworthy regional precipitation records in 2017, Russia reported its second wettest year on record (after 2013) and Norway experienced its sixth wettest year since records began in 1900. Across India, heavy rain and flood-related incidents during the monsoon season claimed around 800 lives. In August and September, above-normal precipitation triggered the most devastating floods in more than a decade in the Venezuelan states of Bolívar and Delta Amacuro. In Nigeria, heavy rain during August and September caused the Niger and Benue Rivers to overflow, bringing floods that displaced more than 100 000 people. Global fire activity was the lowest since at least 2003; however, high activity occurred in parts of North America, South America, and Europe, with an unusually long season in Spain and Portugal, which had their second and third driest years on record, respectively. Devastating fires impacted British Columbia, destroying 1.2 million hectares of timber, bush, and grassland, due in part to the region's driest summer on record. In the United States, an extreme western wildfire season burned over 4 million hectares; the total costs of $18 billion tripled the previous U.S. annual wildfire cost record set in 1991. ispartof: Bulletin of the American Meteorological Society vol:99 issue:8 pages:Si-S310 status: published
Published: 2018

27. Ensembles of Global Climate Model Variants Designed for the Quantification and Constraint of Uncertainty in Aerosols and Their Radiative Forcing

Author: Yoshioka, M., primary, Regayre, L. A., additional, Pringle, K. J., additional, Johnson, J. S., additional, Mann, G. W., additional, Partridge, D. G., additional, Sexton, D. M. H., additional, Lister, G. M. S., additional, Schutgens, N., additional, Stier, P., additional, Kipling, Z., additional, Bellouin, N., additional, Browse, J., additional, Booth, B. B. B., additional, Johnson, C. E., additional, Johnson, B., additional, Mollard, J. D. P., additional, Lee, L., additional, and Carslaw, K. S., additional
Published: 2019
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28. Strong constraints on aerosol–cloud interactions from volcanic eruptions

Author: Malavelle, FF, Haywood, JM, Jones, A, Gettelman, A, Clarisse, L, Bauduin, S, Allan, RP, Karset, IHH, Kristjánsson, JE, Oreopoulos, L, Cho, N, Lee, D, Bellouin, N, Boucher, O, Grosvenor, DP, Carslaw, KS, Dhomse, S, Mann, GW, Schmidt, A, Coe, H, Hartley, ME, Dalvi, M, Hill, AA, Johnson, BT, Johnson, CE, Knight, JR, O’Connor, FM, Partridge, DG, Stier, P, Myhre, G, Platnick, S, Stephens, GL, Takahashi, H, and Thordarson, T
Abstract: Aerosols have a potentially large effect on climate, particularly through their interactions with clouds, but the magnitude of this effect is highly uncertain. Large volcanic eruptions produce sulfur dioxide, which in turn produces aerosols; these eruptions thus represent a natural experiment through which to quantify aerosol–cloud interactions. Here we show that the massive 2014–2015 fissure eruption in Holuhraun, Iceland, reduced the size of liquid cloud droplets—consistent with expectations—but had no discernible effect on other cloud properties. The reduction in droplet size led to cloud brightening and global-mean radiative forcing of around −0.2 watts per square metre for September to October 2014. Changes in cloud amount or cloud liquid water path, however, were undetectable, indicating that these indirect effects, and cloud systems in general, are well buffered against aerosol changes. This result will reduce uncertainties in future climate projections, because we are now able to reject results from climate models with an excessive liquid-water-path response.
Published: 2017

29. Aerosols at the poles: an AeroCom Phase II multi-model evaluation

Author: Sand, M., Samset, B. H., Balkanski, Y., Bauer, S., Bellouin, N., Berntsen, T. K., Bian, H., Chin, M., Diehl, T., Easter, R., Ghan, S. J., Iversen, T., Kirkevåg, A., Lamarque, J.-F., Lin, G., Liu, X., Luo, G., Myhre, G., Noije, T. V., Penner, J. E., Schulz, M., Seland, Ø., Skeie, R. B., Stier, P., Takemura, T., Tsigaridis, K., Yu, F., Zhang, K., Zhang, H., Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Meteorology [Reading], University of Reading (UOR), Joint Center for Earth Systems Technology [Baltimore] (JCET), NASA Goddard Space Flight Center (GSFC)-University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System, NASA Goddard Space Flight Center (GSFC), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Pacific Northwest National Laboratory (PNNL), Atmospheric Chemistry Observations and Modeling Laboratory (ACOML), National Center for Atmospheric Research [Boulder] (NCAR), Norwegian Meteorological Institute [Oslo] (MET), Department of Physics [Oxford], University of Oxford [Oxford], Kyushu University [Fukuoka], Center for Climate Systems Research [New York] (CCSR), Columbia University [New York], Atmospheric Sciences Research Center (ASRC), University at Albany [SUNY], State University of New York (SUNY)-State University of New York (SUNY), University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System-NASA Goddard Space Flight Center (GSFC), 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), 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)-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), University of Oxford, and Kyushu University
Subjects: Earth's energy budget, Atmospheric Science, 010504 meteorology & atmospheric sciences, 010502 geochemistry & geophysics, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Latitude, lcsh:Chemistry, chemistry.chemical_compound, Sea ice, Sulfate, Optical depth, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, geography.geographical_feature_category, Radiative forcing, lcsh:QC1-999, Aerosol, lcsh:QD1-999, Arctic, chemistry, 13. Climate action, Climatology, Environmental science, lcsh:Physics
Abstract: International audience; Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar an-thropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550 nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OAs), dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs), we document the role of these aerosols at high latitudes. The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (sea-salt) and spring (dust), whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (de-fined here as north of 60 • N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70 • S) with a resulting AOD varying between 0.01 and 0.02. The Published by Copernicus Publications on behalf of the European Geosciences Union. 12198 M. Sand et al.: Aerosols at the poles: an AeroCom Phase II multi-model evaluation models have estimated the shortwave anthropogenic radia-tive forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative (−0.12 W m −2), dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in eastern Asia results in a 33 % increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39 % increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range.
Published: 2017

30. Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1

Author: Mulcahy, J. P., primary, Jones, C., additional, Sellar, A., additional, Johnson, B., additional, Boutle, I. A., additional, Jones, A., additional, Andrews, T., additional, Rumbold, S. T., additional, Mollard, J., additional, Bellouin, N., additional, Johnson, C. E., additional, Williams, K. D., additional, Grosvenor, D. P., additional, and McCoy, D. T., additional
Published: 2018
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31. Regional and global temperature response to anthropogenic SO2 emissions from China in three climate models

Author: Kasoar, M, Voulgarakis, A, Lamarque, J-F, Shindell, DT, Bellouin, N, Collins, WJ, Faluvegi, G, and Tsigaridis, K
Subjects: 0201 Astronomical And Space Sciences, Meteorology & Atmospheric Sciences, 0401 Atmospheric Sciences, complex mixtures
Abstract: We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions\ud from China. We find that the models differ by up to a factor of six in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that\ud results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a\ud near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating th at total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against observations.
Published: 2016

32. Aerosol indirect effects - General circulation model intercomparison and evaluation with satellite data

Author: Quaas, J, Ming, Y, Menon, S, Takemura, T, Wang, M, Penner, J, Gettelman, A, Lohmann, U, Bellouin, N, Boucher, O, Sayer, A, Thomas, G, McComiskey, A, Feingold, G, Hoose, C, Kristjansson, J, Liu, X, Balkanski, Y, Donner, L, Ginoux, P, Stier, P, Grandey, B, Feichter, J, Sednev, I, and Bauer, SE
Abstract: Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (andtau; a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between andtau;a and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and andtau; a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong f cldĝ€"andtau;a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between andtau;a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLRĝ€"andtau; a relationship show a strong positive correlation between andtau;a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of andtau;a, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of andminus;1.5andplusmn;0.5 Wmandminus;2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic andtau;a and satellite-retrieved Ndĝ€"andtau;a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of andminus;0.4andplusmn;0.2 Wmandminus;2 and a cloudy-sky (aerosol indirect effect) estimate of andminus;0.7andplusmn;0.5 Wmandminus;2, with a total estimate of andminus;1.2andplusmn;0. 4 Wmandminus;2.
Published: 2016

33. Constraining the aerosol influence on cloud fraction

Author: Gryspeerdt, E, Quaas, J, and Bellouin, N
Subjects: ATLANTIC, Science & Technology, causality, SATELLITE-OBSERVATIONS, SMOKE, clouds, INVIGORATION, PRODUCTS, CONVECTIVE CLOUDS, MODIS, Physical Sciences, Meteorology & Atmospheric Sciences, aerosol-cloud interactions, 0401 Atmospheric Sciences, POLLUTION AEROSOL, 0406 Physical Geography and Environmental Geoscience, OPTICAL-THICKNESS, aerosols, CONDENSATION NUCLEI CONCENTRATION
Abstract: Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.
Published: 2016

34. Contrasting fast precipitation responses to tropospheric and stratospheric ozone forcing

Author: MacIntosh, C. R., Allan, R. P., Baker, L. H., Bellouin, N., Collins, W, Mousavi, Z., and Shine, K. P.
Abstract: The precipitation response to radiative forcing (RF) can be decomposed into a fast precipitation response (FPR), which depends on the atmospheric component of RF, and a slow response, which depends on surface temperature change. We present the first detailed climate model study of the FPR due to tropospheric and stratospheric ozone changes. The FPR depends strongly on the altitude of ozone change. Increases below about 3 km cause a positive FPR; increases above cause a negative FPR. The FPR due to stratospheric ozone change is, per unit RF, about 3 times larger than that due to tropospheric ozone. As historical ozone trends in the troposphere and stratosphere are opposite in sign, so too are the FPRs. Simple climate model calculations of the time-dependent total (fast and slow) precipitation change, indicate that ozone's contribution to precipitation change in 2011, compared to 1765, could exceed 50% of that due to CO2 change.
Published: 2016

35. Southeast Atlantic Ocean aerosol direct radiative effects over clouds: Comparison of observations and simulations

Author: de Graaf, M., primary, Haywood, J., additional, Bellouin, N., additional, Tilstra, L. G., additional, and Stammes, P., additional
Published: 2017
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36. Evaluating the CLimate and Air Quality ImPacts of Short-livEd Pollutants (ECLIPSE)

Author: Stohl, A., Aamaas, B., Amann, M., Baker, L.H., Bellouin, N., Berntsen, T.K., Boucher, O., Cherian, R., Collins, W., Daskalakis, N., Dusinska, M., Eck-hardt, S., Fuglestvedt, J. S., Harju, M., Heyes, C., Hodnebrog, Ø., Hao, J., Im, Ulas, Kanakidou, M., Klimont, Z., Kupiainen, K., Law, K. S., Lund, M. T., Maas, R., MacIntosh, C. R., Myhre, G., Myriokefalitakis, S., Olivié, D., Quaas, J., Quennehen, B., Raut, J.-C., Rumbold, S. T., Samset, B.H., Schulz, M., Seland, Ø., Shine, K. P., Skeie, R. B., Wang, S., Yttri, K. E., and Zhu, T.
Published: 2015

37. Multi-model evaluation of short-lived pollutant distributions over east Asia during summer 2008

Author: Quennehen, B., Raut, J.-C., Law, K. S., Daskalakis, N., Ancellet, G., Clerbaux, C., Kim, S.-W., Lund, M. T., Myhre, G., Olivié, D. J. L., Safieddine, S., Skeie, R. B., Thomas, J. L., Tsyro, S., Bazureau, A., Bellouin, N., Hu, M., Kanakidou, M., Klimont, Z., Kupiainen, K., Myriokefalitakis, S., Quaas, J., Rumbold, S. T., Schulz, M., Cherian, R., Shimizu, A., Wang, J., Yoon, S.-C., Zhu, T., Quennehen, B., Raut, J.-C., Law, K. S., Daskalakis, N., Ancellet, G., Clerbaux, C., Kim, S.-W., Lund, M. T., Myhre, G., Olivié, D. J. L., Safieddine, S., Skeie, R. B., Thomas, J. L., Tsyro, S., Bazureau, A., Bellouin, N., Hu, M., Kanakidou, M., Klimont, Z., Kupiainen, K., Myriokefalitakis, S., Quaas, J., Rumbold, S. T., Schulz, M., Cherian, R., Shimizu, A., Wang, J., Yoon, S.-C., and Zhu, T.
Abstract: The ability of seven state-of-the-art chemistry–aerosol models to reproduce distributions of tropospheric ozone and its precursors, as well as aerosols over eastern Asia in summer 2008, is evaluated. The study focuses on the performance of models used to assess impacts of pollutants on climate and air quality as part of the EU ECLIPSE project. Models, run using the same ECLIPSE emissions, are compared over different spatial scales to in situ surface, vertical profiles and satellite data. Several rather clear biases are found between model results and observations, including overestimation of ozone at rural locations downwind of the main emission regions in China, as well as downwind over the Pacific. Several models produce too much ozone over polluted regions, which is then transported downwind. Analysis points to different factors related to the ability of models to simulate VOC-limited regimes over polluted regions and NOx limited regimes downwind. This may also be linked to biases compared to satellite NO2, indicating overestimation of NO2 over and to the north of the northern China Plain emission region. On the other hand, model NO2 is too low to the south and west of this region and over South Korea/Japan. Overestimation of ozone is linked to systematic underestimation of CO particularly at rural sites and downwind of the main Chinese emission regions. This is likely to be due to enhanced destruction of CO by OH. Overestimation of Asian ozone and its transport downwind implies that radiative forcing from this source may be overestimated. Model-observation discrepancies over Beijing do not appear to be due to emission controls linked to the Olympic Games in summer 2008. With regard to aerosols, most models reproduce the satellite-derived AOD patterns over eastern China. Our study nevertheless reveals an overestimation of ECLIPSE model mean surface BC and sulphate aerosols in urban China in summer 2008. The effect of the short-term emission mitigation in Beijing
Published: 2016

38. Aerosol direct radiative effect of smoke over clouds over the southeast Atlantic Ocean from 2006 to 2009

Author: de Graaf, M., Bellouin, N., Tilstra, L.G., Haywood, J., and Stammes, P.
Subjects: remote sensing, climate change, clouds, aerosols
Abstract: The aerosol direct radiative effect (DRE) of African smoke was analyzed in cloud scenes over the southeast Atlantic Ocean, using Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite observations and Hadley Centre Global Environmental Model version 2 (HadGEM2) climate model simulations. The observed mean DRE was about 30–35 W m−2 in August and September 2006–2009. In some years, short episodes of high-aerosol DRE can be observed, due to high-aerosol loadings, while in other years the loadings are lower but more prolonged. Climate models that use evenly distributed monthly averaged emission fields will not reproduce these high-aerosol loadings. Furthermore, the simulated monthly mean aerosol DRE in HadGEM2 is only about 6 W m−2 in August. The difference with SCIAMACHY mean observations can be partly explained by an underestimation of the aerosol absorption Ångström exponent in the ultraviolet. However, the subsequent increase of aerosol DRE simulation by about 20% is not enough to explain the observed discrepancy between simulations and observations.
Published: 2014

39. Clouds and Aerosols

Author: Boucher, O, Randall, D, Artaxo, P, Bretherton, C, Feingold, G, Forster, P, Kerminen, VM, Kondo, Y, Liao, H, Lohmann, U, Rasch, P, Satheesh, SK, Sherwood, S Stevens, B, Zhang, XY, Bala, G, Bellouin, N, Benedetti, A, Bony, S, Caldeira, K, Del Genio, A, Facchini, Maria Cristina, Flanner, M, Ghan, S, Granier, C, Hoose, C, Jones, A, Koike, M, Kravitz, B, Laken, B, Lebsock, M, Mahowald, N, Myhre, G ), O'Dowd, C, Robock, A, Samset, B, Schmidt, H, Schulz, M, Stephens, G, Stier, P, Storelvmo, T, and Winker, D Wyant, M
Subjects: GENERAL-CIRCULATION MODEL, SECONDARY ORGANIC AEROSOL, MIXED-PHASE CLOUDS, MARINE BOUNDARY-LAYER, COMMUNITY ATMOSPHERE MODEL, SHALLOW CUMULUS CONVECTION, WATER-VAPOR FEEDBACK, GLOBAL CLIMATE MODEL, HETEROGENEOUS ICE NUCLEATION, DOUBLED CARBON-DIOXIDE, Physics::Atmospheric and Oceanic Physics
Abstract: Clouds and aerosols continue to contribute the largest uncertainty to estimates and interpretations of the Earth's changing energy budget. This chapter focuses on process understanding and considers observations, theory and models to assess how clouds and aerosols contribute and respond to climate change. The following conclusions are drawn.
Published: 2014

40. Multi-model evaluation of short-lived pollutant distributions over east Asia during summer 2008

Author: Quennehen, B., primary, Raut, J.-C., additional, Law, K. S., additional, Daskalakis, N., additional, Ancellet, G., additional, Clerbaux, C., additional, Kim, S.-W., additional, Lund, M. T., additional, Myhre, G., additional, Olivié, D. J. L., additional, Safieddine, S., additional, Skeie, R. B., additional, Thomas, J. L., additional, Tsyro, S., additional, Bazureau, A., additional, Bellouin, N., additional, Hu, M., additional, Kanakidou, M., additional, Klimont, Z., additional, Kupiainen, K., additional, Myriokefalitakis, S., additional, Quaas, J., additional, Rumbold, S. T., additional, Schulz, M., additional, Cherian, R., additional, Shimizu, A., additional, Wang, J., additional, Yoon, S.-C., additional, and Zhu, T., additional
Published: 2016
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41. Evaluation of biomass burning aerosols in the HadGEM3 climate model with observations from the SAMBBA field campaign

Author: Johnson, B. T., primary, Haywood, J. M., additional, Langridge, J. M., additional, Darbyshire, E., additional, Morgan, W. T., additional, Szpek, K., additional, Brooke, J., additional, Marenco, F., additional, Coe, H., additional, Artaxo, P., additional, Longo, K. M., additional, Mulcahy, J., additional, Mann, G., additional, Dalvi, M., additional, and Bellouin, N., additional
Published: 2016
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42. Comparison of aerosol optical properties above clouds between POLDER and AeroCom models over the South East Atlantic Ocean during the fire season

Author: Peers, F., primary, Bellouin, N., additional, Waquet, F., additional, Ducos, F., additional, Goloub, P., additional, Mollard, J., additional, Myhre, G., additional, Skeie, R. B., additional, Takemura, T., additional, Tanré, D., additional, Thieuleux, F., additional, and Zhang, K., additional
Published: 2016
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43. Constraining the aerosol influence on cloud fraction

Author: Gryspeerdt, E., primary, Quaas, J., additional, and Bellouin, N., additional
Published: 2016
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44. The impact of European legislative and technology measures to reduce air pollutants on air quality, human health and climate

Author: Turnock, S T, primary, Butt, E W, additional, Richardson, T B, additional, Mann, G W, additional, Reddington, C L, additional, Forster, P M, additional, Haywood, J, additional, Crippa, M, additional, Janssens-Maenhout, G, additional, Johnson, C E, additional, Bellouin, N, additional, Carslaw, K S, additional, and Spracklen, D V, additional
Published: 2016
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45. Regional and global climate response to anthropogenic SO2 emissions from China in three climate models

Author: Kasoar, M., primary, Voulgarakis, A., additional, Lamarque, J.-F., additional, Shindell, D. T., additional, Bellouin, N., additional, Collins, W. J., additional, Faluvegi, G., additional, and Tsigaridis, K., additional
Published: 2016
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46. Supplementary material to "Regional and global climate response to anthropogenic SO2 emissions from China in three climate models"

Author: Kasoar, M., primary, Voulgarakis, A., additional, Lamarque, J.-F., additional, Shindell, D. T., additional, Bellouin, N., additional, Collins, W. J., additional, Faluvegi, G., additional, and Tsigaridis, K., additional
Published: 2016
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47. Modelled and observed changes in aerosols and surface solar radiation over Europe between 1960 and 2009

Author: Turnock, S. T., Spracklen, D. V., Carslaw, K. S., Mann, G. W., Woodhouse, M. T., Forster, P. M., Haywood, J., Johnson, C. E., Dalvi, M., Bellouin, N., Sánchez-Lorenzo, Arturo, Turnock, S. T., Spracklen, D. V., Carslaw, K. S., Mann, G. W., Woodhouse, M. T., Forster, P. M., Haywood, J., Johnson, C. E., Dalvi, M., Bellouin, N., and Sánchez-Lorenzo, Arturo
Abstract: Substantial changes in anthropogenic aerosols and precursor gas emissions have occurred over recent decades due to the implementation of air pollution control legislation and economic growth. The response of atmospheric aerosols to these changes and the impact on climate are poorly constrained, particularly in studies using detailed aerosol chemistry climate models. Here we compare the HadGEM3-UKCA coupled chemistry-climate model for the period 1960 to 2009 against extensive ground based observations of sulfate aerosol mass (1978–2009), total suspended particle matter (SPM, 1978–1998), PM10 (1997–2009), aerosol optical depth (AOD, 2000–2009) and surface solar radiation (SSR, 1960–2009) over Europe. The model underestimates observed sulfate aerosol mass (normalised mean bias factor (NMBF) = −0.4), SPM (NMBF = −0.9), PM10 (NMBF = −0.2) and aerosol optical depth (AOD, NMBF = −0.01) but slightly overpredicts SSR (NMBF = 0.02). Trends in aerosol over the observational period are well simulated by the model, with observed (simulated) changes in sulfate of −68% (−78%), SPM of −42% (−20%), PM10 of −9% (−8%) and AOD of −11% (−14%). Discrepancies in the magnitude of simulated aerosol mass do not affect the ability of the model to reproduce the observed SSR trends. The positive change in observed European SSR (5%) during 1990–2009 (>brightening>) is better reproduced by the model when aerosol radiative effects (ARE) are included (3%), compared to simulations where ARE are excluded (0.2%). The simulated top-of-the-atmosphere aerosol radiative forcing over Europe under all-sky conditions increased by 3 W m−2 during the period 1970–2009 in response to changes in anthropogenic emissions and aerosol concentrations. © Author(s) 2015.
Published: 2015

48. Southeast Atlantic Ocean Aerosol Direct Radiative Effects Over Clouds: Comparison Of Observations And Simulations.

Author: de Graaf, M., Haywood, J., Bellouin, N., Tilstra, L. G., and Stammes, P.
Subjects: RADIOACTIVE aerosols, RADIATION absorption, GENERAL circulation model, MICROPHYSICS, ATMOSPHERIC radiation
Abstract: Absorbing aerosols exert a warming or a cooling effect on the Earth's system, depending on the circumstances. The direct radiative effect (DRE) of absorbing aerosols is negative (cooling) at the top-of-the-atmosphere (TOA) over a dark surface like the ocean, as the aerosols increase the planetary albedo, but it is positive (warming) over bright backgrounds like clouds. Furthermore, radiation absorption by aerosols heat the atmosphere locally, and, through rapid adjustments of the atmospheric column and cloud dynamics, the net effect can be amplified considerably. We developed a technique to study the absorption of radiation of smoke over low lying clouds using satellite spectrometry. The TOA DRE of smoke over clouds is large and positive over the southeast Atlantic Ocean off the west coast of Africa, which can be explained by the large decrease of reflected radiation by a polluted cloud, especially in the UV. However, general circulation models (GCMs) fail to reproduce these strong positive DRE, and in general GCMs disagree on the magnitude and even sign of the aerosol DRE in the southeast Atlantic region. Our satellite-derived DRE measurements show clear seasonal and inter-annual variations, consistent with other satellite measurements, which are not reproduced by GCMs. A comparison with model results showed discrepancies with the Ångström exponent of the smoke aerosols, which is larger than assumed in simulations, and a sensitivity to emission scenarios. However, this was not enough to explain the discrepancies, and we suspect that the modeling of cloud distributions and microphysics will have the necessary larger impact on DRE that will explain the differences between observations and modeling. [ABSTRACT FROM AUTHOR]
Published: 2017
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49. Bounding the role of black carbon in the climate system: A scientific assessment

Author: Bond, T., Doherty, S.D., Fahey, D.W., Forster, P.M. de, Berntsen, T.K., DeAngelo, B.J., Flanner, M.G., Ghan, S.J., Kärcher, Bernd, Koch, D., Kinne, S., Kondo, Y., Quinn, P.K., Lohmann, Ulrike, Sarofim, M.C., Schulz, M., Schultz, M., Venkatamaran, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S., Hopke, P.K., Jacobson, M.Z., Kaiser, J.W., Klimont, Z., Schwarz, J.P., Shindell, D., Storelvmo, T., Warren, S.G., and Zender, C.S.
Subjects: ddc:550, Physical Sciences and Mathematics, black carbon, climate forcing, aerosol, Schwarzer Kohlenstoff
Abstract: Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr(-1) in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m(-2) with 90% uncertainty bounds of (+0.08, +1.27) W m(-2). Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m(-2). Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m(-2) with 90% uncertainty bounds of +0.17 to +2.1 W m(-2). Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m(-2), is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (-0.50 to +1.08) W m(-2) during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (-0.06 W m(-2) with 90% uncertainty bounds of -1.45 to +1.29 W m(-2)). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.
Published: 2013

50. The HadGEM2 family of Met Office Unified Model climate configurations

Author: Martin, Gm, Bellouin, N., Collins, Wj, Culverwell, Id, Halloran, Pr, Hardiman, Sc, Hinton, Tj, Jones, Cd, Mcdonald, Re, Mclaren, Aj, O Connor, Fm, Roberts, Mj, Rodriguez, Jm, Woodward, S., Best, Mj, Brooks, Me, Brown, Ar, Butchart, N., Dearden, C., Derbyshire, Sh, Imtiaz Dharssi, Doutriaux-Boucher, M., Edwards, Jm, Falloon, Pd, Gedney, N., Gray, Lj, Hewitt, Ht, Hobson, M., Huddleston, MR, Hughes, J., Ineson, S., Ingram, Wj, James, Pm, Johns, Tc, Johnson, Ce, Jones, A., Jones, Cp, Joshi, Mm, Keen, Ab, Liddicoat, S., Lock, Ap, Maidens, Av, Manners, Jc, Milton, Sf, Rae, Jgl, Ridley, Jk, Sellar, A., Senior, Ca, Totterdell, Ij, Verhoef, A., Vidale, Pl, Wiltshire, A., and Team, Hd
Subjects: Set (abstract data type), lcsh:Geology, Sea surface temperature, Meteorology, Climatology, Component (UML), lcsh:QE1-996.5, Range (statistics), Northern Hemisphere, HadGEM1, Unified Model, Stratosphere
Abstract: We describe the HadGEM2 family of climate configurations of the Met Office Unified Model, MetUM. The concept of a model "family" comprises a range of specific model configurations incorporating different levels of complexity but with a common physical framework. The HadGEM2 family of configurations includes atmosphere and ocean components, with and without a vertical extension to include a well-resolved stratosphere, and an Earth-System (ES) component which includes dynamic vegetation, ocean biology and atmospheric chemistry. The HadGEM2 physical model includes improvements designed to address specific systematic errors encountered in the previous climate configuration, HadGEM1, namely Northern Hemisphere continental temperature biases and tropical sea surface temperature biases and poor variability. Targeting these biases was crucial in order that the ES configuration could represent important biogeochemical climate feedbacks. Detailed descriptions and evaluations of particular HadGEM2 family members are included in a number of other publications, and the discussion here is limited to a summary of the overall performance using a set of model metrics which compare the way in which the various configurations simulate present-day climate and its variability.
Published: 2011

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