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1. A review of coarse mineral dust in the Earth system

Author

Adebiyi, Adeyemi, Kok, Jasper F, Murray, Benjamin J, Ryder, Claire L, Stuut, Jan-Berend W, Kahn, Ralph A, Knippertz, Peter, Formenti, Paola, Mahowald, Natalie M, García-Pando, Carlos Pérez, Klose, Martina, Ansmann, Albert, Samset, Bjørn H, Ito, Akinori, Balkanski, Yves, Di Biagio, Claudia, Romanias, Manolis N, Huang, Yue, and Meng, Jun

Subjects
Earth Sciences, Atmospheric Sciences, Climate Action, Mineral dust, Coarse dust, Size distribution, Climate, Earth system, Environmental Sciences, Earth sciences, Environmental sciences
Published
2023

3. Contribution of the world's main dust source regions to the global cycle of desert dust

Author

Kok, Jasper F, Adebiyi, Adeyemi A, Albani, Samuel, Balkanski, Yves, Checa-Garcia, Ramiro, Chin, Mian, Colarco, Peter R, Hamilton, Douglas S, Huang, Yue, Ito, Akinori, Klose, Martina, Li, Longlei, Mahowald, Natalie M, Miller, Ron L, Obiso, Vincenzo, García-Pando, Carlos Pérez, Rocha-Lima, Adriana, and Wan, Jessica S

Subjects
Earth Sciences, Atmospheric Sciences, Life Below Water, Climate Action
Abstract

Abstract. Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, the relative contributions of the world’s major dust source regions to the global dust cycle remain poorly constrained. This problem hinders accounting for the potentially large impact of regional differences in dust properties on clouds, the Earth's energy balance, and terrestrial and marine biogeochemical cycles. Here, we constrain the contribution of each of the world’s main dust source regions to the global dust cycle. We use an analytical framework that integrates an ensemble of global model simulations with observationally informed constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We obtain a data set that constrains the relative contribution of each of nine major source regions to size-resolved dust emission, atmospheric loading, optical depth, concentration, and deposition flux. We find that the 22–29 Tg (one standard error range) global loading of dust with geometric diameter up to 20 μm is partitioned as follows: North African source regions contribute ~50 % (11–15 Tg), Asian source regions contribute ~40 % (8–13 Tg), and North American and Southern Hemisphere regions contribute ~10 % (1.8–3.2 Tg). Current models might on average be overestimating the contribution of North African sources to atmospheric dust loading at ~65 %, while underestimating the contribution of Asian dust at ~30 %. However, both our results and current models could be affected by unquantified biases, such as due to errors in separating dust aerosol optical depth from that produced by other aerosol species in remote sensing retrievals in poorly observed desert regions. Our results further show that each source region's dust loading peaks in local spring and summer, which is partially driven by increased dust lifetime in those seasons. We also quantify the dust deposition flux to the Amazon rainforest to be ~10 Tg/year, which is a factor of 2–3 less than inferred from satellite data by previous work that likely overestimated dust deposition by underestimating the dust mass extinction efficiency. The data obtained in this paper can be used to obtain improved constraints on dust impacts on clouds, climate, biogeochemical cycles, and other parts of the Earth system.

Published
2021

4. Improved representation of the global dust cycle using observational constraints on dust properties and abundance

Author

Kok, Jasper F, Adebiyi, Adeyemi A, Albani, Samuel, Balkanski, Yves, Checa-Garcia, Ramiro, Chin, Mian, Colarco, Peter R, Hamilton, Douglas S, Huang, Yue, Ito, Akinori, Klose, Martina, Leung, Danny M, Li, Longlei, Mahowald, Natalie M, Miller, Ron L, Obiso, Vincenzo, García-Pando, Carlos Pérez, Rocha-Lima, Adriana, Wan, Jessica S, and Whicker, Chloe A

Subjects
Earth Sciences, Atmospheric Sciences, Climate Action, Astronomical and Space Sciences, Meteorology & Atmospheric Sciences, Atmospheric sciences, Climate change science
Abstract

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

Published
2021

5. Quantifying the range of the dust direct radiative effect due to source mineralogy uncertainty

Author

Li, Longlei, Mahowald, Natalie M, Miller, Ron L, García-Pando, Carlos Pérez, Klose, Martina, Hamilton, Douglas S, Ageitos, Maria Gonçalves, Ginoux, Paul, Balkanski, Yves, Green, Robert O, Kalashnikova, Olga, Kok, Jasper F, Obiso, Vincenzo, Paynter, David, and Thompson, David R

Subjects
Climate Action, Astronomical and Space Sciences, Atmospheric Sciences, Meteorology & Atmospheric Sciences
Abstract

Abstract. The large uncertainty in the mineral dust direct radiative effect (DRE) hinders projections of future climate change due to anthropogenic activity. Resolving modeled dust mineral speciation allows for spatially and temporally varying refractive indices consistent with dust aerosol composition. Here, for the first time, we quantify the range in dust DRE at the top of the atmosphere (TOA) due to current uncertainties in the surface soil mineralogical content using a dust mineral-resolving climate model. We propagate observed uncertainties in soil mineral abundances from two soil mineralogy atlases along with the optical properties of each mineral into the DRE and compare the resultant range with other sources of uncertainty across six climate models. The shortwave DRE responds region-specifically to the dust burden depending on the mineral speciation and underlying shortwave surface albedo: positively when the regionally averaged annual surface albedo is larger than 0.28 and negatively otherwise. Among all minerals examined, the shortwave TOA DRE and single scattering albedo at the 0.44–0.63 µm band are most sensitive to the fractional contribution of iron oxides to the total dust composition. The global net (shortwave plus longwave) TOA DRE is estimated to be within −0.23 to +0.35 W m−2. Approximately 97 % of this range relates to uncertainty in the soil abundance of iron oxides. Representing iron oxide with solely hematite optical properties leads to an overestimation of shortwave DRE by +0.10 W m−2 at the TOA, as goethite is not as absorbing as hematite in the shortwave spectrum range. Our study highlights the importance of iron oxides to the shortwave DRE: they have a disproportionally large impact on climate considering their small atmospheric mineral mass fractional burden (∼2 %). An improved description of iron oxides, such as those planned in the Earth Surface Mineral Dust Source Investigation (EMIT), is thus essential for more accurate estimates of the dust DRE.

Published
2021

6. Satellites reveal Earth's seasonally shifting dust emission sources

Author

Chappell, Adrian, Webb, Nicholas P., Hennen, Mark, Schepanski, Kerstin, Ciais, Philippe, Balkanski, Yves, Zender, Charles S., Tegen, Ina, Zeng, Zhenzhong, Tong, Daniel, Baker, Barry, Ekström, Marie, Baddock, Matthew, Eckardt, Frank D., Kandakji, Tarek, Lee, Jeffrey A., Nobakht, Mohamad, von Holdt, Johanna, and Leys, John F.

Published
2023
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8. Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations

Author

Xing, Xiaofan, Xiong, Yuankang, Yang, Ruipu, Wang, Rong, Wang, Weibing, Kan, Haidong, Lu, Tun, Li, Dongsheng, Cao, Junji, Peñuelas, Josep, Ciais, Philippe, Bauer, Nico, Boucher, Olivier, Balkanski, Yves, Hauglustaine, Didier, Brasseur, Guy, Morawska, Lidia, Janssens, Ivan A., Wang, Xiangrong, Sardans, Jordi, Wang, Yijing, Deng, Yifei, Wang, Lin, Chen, Jianmin, Tang, Xu, and Zhang(张人禾), Renhe

Published
2021

13. Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China

Author

Xing, Xiaofan, Wang, Rong, Bauer, Nico, Ciais, Philippe, Cao, Junji, Chen, Jianmin, Tang, Xu, Wang, Lin, Yang, Xin, Boucher, Olivier, Goll, Daniel, Peñuelas, Josep, Janssens, Ivan A., Balkanski, Yves, Clark, James, Ma, Jianmin, Pan, Bo, Zhang, Shicheng, Ye, Xingnan, Wang, Yutao, Li, Qing, Luo, Gang, Shen, Guofeng, Li, Wei, Yang, Yechen, and Xu, Siqing

Published
2021
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14. Letter to the Editor regarding Chappell et al., 2023, “Satellites reveal Earth's seasonally shifting dust emission sources”

Author

Mahowald, Natalie, Ginoux, Paul, Okin, Gregory S., Kok, Jasper, Albani, Samuel, Balkanski, Yves, Chin, Mian, Bergametti, Gilles, Eck, Thomas F., Pérez García-Pando, Carlos, Gkikas, Antonis, Gonçalves Ageitos, María, Kim, Dongchul, Klose, Martina, LeGrand, Sandra, Li, Longlei, Marticorena, Beatrice, Miller, Ronald, Ryder, Claire, Zender, Charles, and Yu, Yan

Published
2024
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17. Elucidating Hidden and Enduring Weaknesses in Dust Emission Modeling

Author

Chappell, Adrian, primary, Webb, Nicholas P., additional, Hennen, Mark, additional, Zender, Charles S., additional, Ciais, Philippe, additional, Schepanski, Kerstin, additional, Edwards, Brandon L., additional, Ziegler, Nancy P., additional, Balkanski, Yves, additional, Tong, Daniel, additional, Leys, John F., additional, Heidenreich, Stephan, additional, Hynes, Robert, additional, Fuchs, David, additional, Zeng, Zhenzhong, additional, Baddock, Matthew C., additional, Lee, Jeffrey A., additional, and Kandakji, Tarek, additional

Published
2023
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18. Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Author

Gonçalves Ageitos, María, primary, Obiso, Vincenzo, additional, Miller, Ron L., additional, Jorba, Oriol, additional, Klose, Martina, additional, Dawson, Matt, additional, Balkanski, Yves, additional, Perlwitz, Jan, additional, Basart, Sara, additional, Di Tomaso, Enza, additional, Escribano, Jerónimo, additional, Macchia, Francesca, additional, Montané, Gilbert, additional, Mahowald, Natalie M., additional, Green, Robert O., additional, Thompson, David R., additional, and Pérez García-Pando, Carlos, additional

Published
2023
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21. Evaluation and intercomparison of global atmospheric transport models using 222 Rn and other short-lived tracers

Author

Jacob, Daniel J, Prather, Michael J, Rasch, Philip J, Shia, Run-Lie, Balkanski, Yves J, Beagley, Stephen R, Bergmann, Daniel J, Blackshear, W. T, Brown, Margaret, Chiba, Masaru, Chipperfield, Martyn P, de Grandpra, J., Dignon, Jane E, Feichter, Johann, Genthon, Christophe, Grose, W. L, Kasibhatla, Prasad S, Kahler, Ines, Kritz, Mark A, Law, Kathy, Penner, Joyce E, Ramonet, Michel, Reeves, Claire E, Rotman, Douglas A, Stockwell, Deianeira Z, Van Velthoven, Peter F. J, Verver, G, Wild, Oliver, Yang, Hu, and Zimmermann, Peter

Subjects
general-circulation model, zonally averaged circulation, two-dimensional model, tropospheric ozone, odd nitrogen, 3-dimensional simulation, nongeostrophic theory, seasonal-variation, middle atmosphere, climate model
Abstract

Simulations of 222Rn and other short-lived tracers are used to evaluate and intercompare the representations of convective and synoptic processes in 20 global atmospheric transport models. Results show that most established three-dimensional models simulate vertical mixing in the troposphere to within the constraints offered by the observed mean 222Rn concentrations and that subgrid parameterization of convection is essential for this purpose. However, none of the models captures the observed variability of 222Rn concentrations in the upper troposphere, and none reproduces the high 222Rn concentrations measured at 200 hPa over Hawaii. The established three-dimensional models reproduce the frequency and magnitude of high-222Rn episodes observed at Crozet Island in the Indian Ocean, demonstrating that they can resolve the synoptic-scale transport of continental plumes with no significant numerical diffusion. Large differences between models are found in the rates of meridional transport in the upper troposphere (interhemispheric exchange, exchange between tropics and high latitudes). The four two-dimensional models which participated in the intercomparison tend to underestimate the rate of vertical transport from the lower to the upper troposphere but show concentrations of 222Rn in the lower troposphere that are comparable to the zonal mean values in the three-dimensional models.

Published
1997

22. Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Author

Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, Gonçalves Ageitos, María, Obiso, Vincenzo, Miller, Ron L., Jorba Casellas, Oriol, Klose, Martina, Dawson, Matthew, Balkanski, Yves, Perlwitz, Jan, Basart Alpuente, Sara, di Tomaso, Enza, Escribano Alisio, Jeronimo, Macchia, Francesca, Montané Pinto, Gilbert, Mahowald, Natalie, Green, Robert, Thompson, David R., Pérez García-Pando, Carlos, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, Gonçalves Ageitos, María, Obiso, Vincenzo, Miller, Ron L., Jorba Casellas, Oriol, Klose, Martina, Dawson, Matthew, Balkanski, Yves, Perlwitz, Jan, Basart Alpuente, Sara, di Tomaso, Enza, Escribano Alisio, Jeronimo, Macchia, Francesca, Montané Pinto, Gilbert, Mahowald, Natalie, Green, Robert, Thompson, David R., and Pérez García-Pando, Carlos

Abstract

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi, This research was supported by the European Commission’s Horizon 2020 framework program (grant nos. 773051, 821205, H2020-MSCA-COFUND-2016-754433, H2020-MSCA-IF-2017-789630 and H2020-MSCA-IF-2016-747048), the National Aeronautics and Space Administration (grant nos. NNG14HH42I, 80NM0018D0004TS14, 80NSSC19K0056, 80NSSC19K0984, 80HQTR21CA005) as well as the EMIT project from the NASA Earth Venture Instrument program under the Earth Science Division of the Science Mission Directorate, the US DOE DE-SC0021302 project, the Ministerio de Economía y Competitividad of Spain (grant no. CGL2017-88911-R), the European Space Agency (grant no. ESA AO/1-10546/20/I-NB), the Department of Research and Universities of the Government of Catalonia through the Atmospheric Composition Research Group (code 2021 SGR 01550), the Helmholtz Association (grant no. VH-NG-1533), and the AXA Research Fund through the AXA Chair on Sand and Dust Storms at the Barcelona Supercomputing Center (BSC)., Peer Reviewed, Objectius de Desenvolupament Sostenible::13 - Acció per al Clima, Postprint (published version)

Published
2023

25. What are coarse dust aerosols, and how do they impact the Earth's climate system?

Author

Adebiyi, Adeyemi, primary, Kok, Jasper, additional, Murray, Benjamin, additional, Ryder, Claire, additional, Stuut, Jan-Berend, additional, Kahn, Ralph, additional, Knippertz, Peter, additional, Formenti, Paola, additional, Mahowald, Natalie, additional, Perez García-Pando, Carlos, additional, Klose, Martina, additional, Ansmann, Albert, additional, Samset, Bjørn, additional, Ito, Akinori, additional, Balkanski, Yves, additional, Di Biagio, Claudia, additional, Romanias, Manolis, additional, Huang, Yue, additional, and Meng, Jun, additional

Published
2023
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26. Supplementary material to "Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts"

Author

Gonçalves Ageitos, María, primary, Obiso, Vincenzo, additional, Miller, Ron L., additional, Jorba, Oriol, additional, Klose, Martina, additional, Dawson, Matt, additional, Balkanski, Yves, additional, Perlwitz, Jan, additional, Basart, Sara, additional, Di Tomaso, Enza, additional, Escribano, Jerónimo, additional, Macchia, Francesca, additional, Montané, Gilbert, additional, Mahowald, Natalie, additional, Green, Robert O., additional, Thompson, David R., additional, and Pérez García-Pando, Carlos, additional

Published
2023
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29. A review of coarse mineral dust in the Earth system

Author

Adebiyi, Adeyemi, primary, Kok, Jasper F., additional, Murray, Benjamin J., additional, Ryder, Claire L., additional, Stuut, Jan-Berend W., additional, Kahn, Ralph A., additional, Knippertz, Peter, additional, Formenti, Paola, additional, Mahowald, Natalie M., additional, Pérez García-Pando, Carlos, additional, Klose, Martina, additional, Ansmann, Albert, additional, Samset, Bjørn H., additional, Ito, Akinori, additional, Balkanski, Yves, additional, Di Biagio, Claudia, additional, Romanias, Manolis N., additional, Huang, Yue, additional, and Meng, Jun, additional

Published
2023
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36. Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

Author

Wang, Rong, Andrews, Elisabeth, Balkanski, Yves, Boucher, Olivier, Myhre, Gunnar, Samset, Bjørn Hallvard, Schulz, Michael, Schuster, Gregory L, Valari, Myrto, and Tao, Shu

Subjects
Earth Resources And Remote Sensing
Abstract

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

Published
2018
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37. The contribution of China's emissions to global climate forcing

Author

Li, Bengang, Gasser, Thomas, Ciais, Philippe, Piao, Shilong, Tao, Shu, Balkanski, Yves, Hauglustaine, Didier, Boisier, Juan-Pablo, Huang, Mengtian, Li, Laurent Zhaoxin, Li, Yue, Liu, Hongyan, Liu, Junfeng, Peng, Shushi, Shen, Zehao, Sun, Zhenzhong, Wang, Rong, Wang, Tao, Yin, Guodong, Yin, Yi, Zeng, Hui, Zeng, Zhenzhong, and Zhou, Feng

Subjects
China -- Environmental aspects, Global temperature changes -- Analysis, Climatic changes -- Analysis, Emissions (Pollution) -- Control -- Analysis, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on 'common but differentiated responsibilities' reached by the United [...]

Published
2016

38. A review of coarse mineral dust in the Earth system

Author

Adebiyi, Adeyemi, primary, Kok, Jasper, additional, Murray, Benjamin, additional, Ryder, Claire, additional, Stuut, Jan-Berend, additional, Kahn, Ralph, additional, Knippertz, Peter, additional, Formenti, Paola, additional, Mahowald, Natalie, additional, García-Pando, Carlos, additional, Klose, Martina, additional, Ansmann, Albert, additional, Samset, Bjørn, additional, Ito, Akinori, additional, Balkanski, Yves, additional, Di Biagio, Claudia, additional, Romanias, Manolis, additional, Huang, Yue, additional, and Meng, Jun, additional

Published
2022
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42. Aerosols at the Poles: An Aerocom Phase II Multi-Model Evaluation

Author

Sand, Maria, Bauer, Susanne E, Samset, Bjorn H, Balkanski, Yves, Bellouin, Nicolas, Berntsen, Terje K, Bian, Huisheng, Chin, Mian, Diehl, Thomas, Easter, Richard, Ghan, Steven J, Iversen, Trond, Kirkevag, Alf, Lamarque, Jean-Francois, Lin, Guangxing, Liu, Xiaohong, Luo, Gan, Myhre, Gunnar, van Noije, Twan, Penner, Joyce E, Schulz, Michael, Seland, Oyvind, Skeie, Ragnhild B, Stier, Philip, Takemura, Toshihiko, Tsigaridis, Kostas, Yu, Fangqun, Zhang, Kai, and Zhang, Hua

Subjects
Meteorology And Climatology, Earth Resources And Remote Sensing
Abstract

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 anthropogenic 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 (seasalt) 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 (defined here as north of 60 degrees N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70 degrees S) with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative 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(exp. -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 percent increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39 percent increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range.

Published
2017
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44. Weaknesses in Dust Emission Modelling Hidden by Tuning to Dust in the Atmosphere

Author

Chappell, Adrian, primary, Webb, Nicholas, additional, Hennen, Mark, additional, Zender, Charles Sutton, additional, Ciais, Philippe, additional, Schepanski, Kerstin, additional, Edwards, Brandon L, additional, Ziegler, Nancy Parker, additional, Balkanski, Yves, additional, Tong, Daniel, additional, Leys, John F, additional, Heidenreich, Stephan, additional, Hynes, Robert, additional, Fuchs, David, additional, Zeng, Zhenzhong, additional, Baddock, Matthew C., additional, Lee, Jeff, additional, and Kandakji, Tarek, additional

Published
2022
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45. Presentation and Evaluation of the IPSL-CM6A-LR Climate Model

Author

Boucher, Olivier, Servonnat, Jérôme, Albright, Anna Lea, Aumont, Olivier, Balkanski, Yves, Bastrikov, Vladislav, Bekki, Slimane, Bonnet, Rémy, Bony, Sandrine, Bopp, Laurent, Braconnot, Pascale, Brockmann, Patrick, Cadule, Patricia, Caubel, Arnaud, Cheruy, Frédérique, Codron, Francis, Cozic, Anne, Cugnet, David, d'Andrea, Fabio, Davini, Paolo, de Lavergne, Casimir, Denvil, Sébastien, Deshayes, Julie, Devilliers, Marion, Ducharne, Agnès, Dufresne, Jean-Louis, Dupont, Eliott, Éthé, Christian, Fairhead, Laurent, Falletti, Lola, Flavoni, Simona, Foujols, Marie-Alice, Gardoll, Sébastien, Gastineau, Guillaume, Ghattas, Josefine, Grandpeix, Jean-Yves, Guenet, Bertrand, Guez, Lionel, Guilyardi, Éric, Guimberteau, Matthieu, Hauglustaine, Didier, Hourdin, Frédéric, Idelkadi, Abderrahmane, Joussaume, Sylvie, Kageyama, Masa, Khodri, Myriam, Krinner, Gerhard, Lebas, Nicolas, Levavasseur, Guillaume, Lévy, Claire, Li, Laurent, Lott, François, Lurton, Thibaut, Luyssaert, Sebastiaan, Madec, Gurvan, Madeleine, Jean-Baptiste, Maignan, Fabienne, Marchand, Marion, Marti, Olivier, Mellul, Lidia, Meurdesoif, Yann, Mignot, Juliette, Musat, Ionela, Ottle, Catherine, Peylin, Philippe, Planton, Yann, Polcher, Jan, Rio, Catherine, Rochetin, Nicolas, rousset, clement, Rousset, Clément, Sepulchre, Pierre, Sima, Adriana, Swingedouw, Didier, Thiéblemont, Rémi, Traore, Abdoul Khadre, Vancoppenolle, Martin, Vial, Jessica, Vialard, Jérôme, Viovy, Nicolas, Vuichard, Nicolas, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), 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)-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 - 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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), 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), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - 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CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), University of Amsterdam [Amsterdam] (UvA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), ANR-17-EURE-0006,IPSL-CGS,IPSL Climate graduate school(2017), ANR-15-JCLI-0004,GOTHAM,Globally Observed Teleconnections and their role and representation in Hierarchies of Atmospheric Models(2015), ANR-18-CE01-0012,ARiSE,Rôle de la non-linéarité de la réponse atmosphérique à la température de l'océan dans la physique d'ENSO (El Niño Oscillation Australe)(2018), ANR-13-MONU-0008,CONVERGENCE,Convergence en Science du Climat à l'ère du Big Data et des challenges de l'Exascale.(2013), ANR-18-MPGA-0001,ARCHANGE,Changement climatique et Arctique et circulation océanique globale(2018), European Project: 641816,H2020,H2020-SC5-2014-two-stage,CRESCENDO(2015), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-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)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Sorbonne Université (SU), École normale supérieure - Paris (ENS Paris)-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 de Paris (UP), École normale supérieure - Paris (ENS Paris), Consiglio Nazionale delle Ricerche (CNR), UMR 5805 Environnements et Paléoenvironnements Océaniques et Continentaux (EPOC), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Univers et Particules de Montpellier (LUPM), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), MOSAIC (MOSAIC), Institut FRESNEL (FRESNEL), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Grenoble Alpes (UGA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Météo France, Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), École pratique des hautes études (EPHE), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), 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)-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), 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 de Paris (UP)-École normale supérieure - Paris (ENS Paris), 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 de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-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 de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), 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 de Paris (UP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), and Systems Ecology

Subjects
010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, 010502 geochemistry & geophysics, climate model, IPSL‐CM6A‐LR, 01 natural sciences, Carbon cycle, lcsh:Oceanography, climate metrics, Range (statistics), SDG 13 - Climate Action, Environmental Chemistry, lcsh:GC1-1581, Precipitation, lcsh:Physical geography, ComputingMilieux_MISCELLANEOUS, CMIP6, 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, Global and Planetary Change, Coupled model intercomparison project, Intertropical Convergence Zone, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Middle latitudes, General Earth and Planetary Sciences, Environmental science, Climate sensitivity, climate sensitivity, Climate model, lcsh:GB3-5030, IPSL-CM6A-LR
Abstract

International audience This study presents the global climate model IPSL-CM6A-LR developed at Institut Pierre-Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone [ITCZ], frequency of midlatitude wintertime blockings, and El Niño–Southern Oscillation [ENSO] dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL-CM5A-LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850–2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.

Published
2020
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46. Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling.

Author

Tichý, Ondřej, Eckhardt, Sabine, Balkanski, Yves, Hauglustaine, Didier, and Evangeliou, Nikolaos

Subjects
REMOTE sensing, SOIL acidification, SWINE farms, AMMONIA, PARTICULATE matter, AGRICULTURE
Abstract

Ammonia (NH3), a significant precursor of particulate matter, is the most important alkaline gas in the atmosphere and directly affects biodiversity, ecosystems, soil acidification. It also indirectly affects climate and human health. In addition, its concentrations are constantly rising because of the increasing feeding needs of the global population accompanied by a larger use of fertilizers and animal farming. The combination of its increasing atmospheric levels with its environmental and human impact has led many countries to adopt abatement strategies in order to conform with respective regulations. While the significance of ammonia is pronounced, its emissions are often associated with large uncertainties, while its atmospheric abundance is difficult to measure. However, during the last decade, several satellite products have been developed that measure ammonia very effectively, with low uncertainty, and most importantly, with a global coverage. Here, we use satellite observations of column ammonia in combination with an inversion algorithm to derive ammonia emissions with a high resolution over Europe for the period 2013–2020. Ammonia emissions peak in Northern Europe due to agricultural application and livestock management and the local maxima are found over Western Europe (industrial activity) and over Spain (pig farming). Our calculations show that these emissions have decreased by −26 % since 2013 (from 5431 Gg in 2013 to 3994 Gg in 2020) showing that the abatement strategies adopted by the European Union have been very efficient. The slight increase (+4.4 %) reported in 2015 is also reproduced here and is attributed to some European countries exceeding annual emission targets. Ammonia emissions are low in winter (286 Gg) and peak in summer (563 Gg) and are dominated by the temperature dependent volatilization of ammonia from the soil. The largest emission decreases were observed in Central and Eastern Europe (−38 %) and in Western Europe (−37 %), while smaller decreases were recorded in Northern (−17 %) and Southern Europe (−7.6 %). Our results are associated with relatively low uncertainties reaching a maximum of 42 %; when complemented against independent ground-based observations, modelled concentrations using the posterior emissions showed improved statistics, also following the observed seasonal trends. The posterior emissions presented here also agree well with respective estimates reported in the literature and inferred from different methodologies. These results indicate that the posterior emissions of ammonia calculated with satellite measurements and combined with our adapted inverse modelling framework constitute a robust basis for European NH3 estimates and show the de facto evolution of ammonia emissions since 2013. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Atmospheric phosphorus deposition amplifies carbon sinks in simulations of a tropical forest in Central Africa.

Author

Goll, Daniel S., Bauters, Marijn, Zhang, Haicheng, Ciais, Philippe, Balkanski, Yves, Wang, Rong, and Verbeeck, Hans

Subjects
ATMOSPHERIC deposition, CARBON cycle, ATMOSPHERIC nitrogen, TROPICAL forests, ATMOSPHERIC carbon dioxide, ATMOSPHERIC transport, FOREST biomass
Abstract

Summary: Spatial redistribution of nutrients by atmospheric transport and deposition could theoretically act as a continental‐scale mechanism which counteracts declines in soil fertility caused by nutrient lock‐up in accumulating biomass in tropical forests in Central Africa. However, to what extent it affects carbon sinks in forests remains elusive.Here we use a terrestrial biosphere model to quantify the impact of changes in atmospheric nitrogen and phosphorus deposition on plant nutrition and biomass carbon sink at a typical lowland forest site in Central Africa.We find that the increase in nutrient deposition since the 1980s could have contributed to the carbon sink over the past four decades up to an extent which is similar to that from the combined effects of increasing atmospheric carbon dioxide and climate change. Furthermore, we find that the modelled carbon sink responds to changes in phosphorus deposition, but less so to nitrogen deposition.The pronounced response of ecosystem productivity to changes in nutrient deposition illustrates a potential mechanism that could control carbon sinks in Central Africa. Monitoring the quantity and quality of nutrient deposition is needed in this region, given the changes in nutrient deposition due to human land use. [ABSTRACT FROM AUTHOR]

Published
2023
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48. Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts.

Author

Ageitos, María Gonçalves, Obiso, Vincenzo, Miller, Ron L., Jorba, Oriol, Klose, Martina, Dawson, Matt, Balkanski, Yves, Perlwitz, Jan, Basart, Sara, Tomaso, Enza Di, Escribano, Jerónimo, Macchia, Francesca, Montané, Gilbert, Mahowald, Natalie, Green, Robert O., Thompson, David R., and García-Pando, Carlos Pérez

Subjects
SOIL mineralogy, SOIL composition, MINERAL dusts, IRON ores, DUST
Abstract

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physico-chemical properties, which far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth System Models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy as invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work, we introduce an explicit mineralogy representation within the state-of-the-art atmosphere-chemistry model MONARCH. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modelling, and provide an evaluation of multi-annual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on Brittle Fragmentation Theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions, independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semiarid regions worldwide. For the least abundant or more difficult to determine minerals, such as the iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes a ∼10 % of the emitted dust mass at the global scale, and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single scattering albedo at solar wavelengths, or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high quality spaceborne hyperspectral measurements, such as those arising from the NASA EMIT mission. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Weaknesses in dust emission modelling hidden by tuning to dust in the atmosphere

Author

Chappell, Adrian, primary, Webb, Nicholas, additional, Hennen, Mark, additional, Zender, Charles, additional, Ciais, Philippe, additional, Schepanski, Kerstin, additional, Edwards, Brandon, additional, Ziegler, Nancy, additional, Jones, Sandra, additional, Balkanski, Yves, additional, Tong, Daniel, additional, Leys, John, additional, Heidenreich, Stephan, additional, Hynes, Robert, additional, Fuchs, David, additional, Zeng, Zhenzhong, additional, Ekström, Marie, additional, Baddock, Matthew, additional, Lee, Jeffrey, additional, and Kandakji, Tarek, additional

Published
2021
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