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AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations
Atmospheric Chemistry and Physics, Volume: 21, Issue: 1, Pages: 87 - 128
Swansea University Author: Peter North
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DOI (Published version): 10.5194/acp-21-87-2021
Abstract
Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Ear...
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<?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>54247</id><entry>2020-03-18</entry><title>AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations</title><swanseaauthors><author><sid>fc45a0cb36c24d6cf35313a8c808652f</sid><ORCID>0000-0001-9933-6935</ORCID><firstname>Peter</firstname><surname>North</surname><name>Peter North</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2020-03-18</date><deptcode>SGE</deptcode><abstract>Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes.Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1.Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc.Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment.Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models.Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions.Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.</abstract><type>Journal Article</type><journal>Atmospheric Chemistry and Physics</journal><volume>21</volume><journalNumber>1</journalNumber><paginationStart>87</paginationStart><paginationEnd>128</paginationEnd><publisher>Copernicus GmbH</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>1680-7324</issnElectronic><keywords/><publishedDay>6</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-01-06</publishedDate><doi>10.5194/acp-21-87-2021</doi><url>http://dx.doi.org/10.5194/acp-21-87-2021</url><notes/><college>COLLEGE NANME</college><department>Geography</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SGE</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2023-12-21T11:29:11.6842379</lastEdited><Created>2020-03-18T00:00:00.0000000</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Biosciences, Geography and Physics - Geography</level></path><authors><author><firstname>Jonas</firstname><surname>Gliß</surname><orcid>0000-0003-1147-4482</orcid><order>1</order></author><author><firstname>Augustin</firstname><surname>Mortier</surname><orcid>0000-0002-7724-3583</orcid><order>2</order></author><author><firstname>Michael</firstname><surname>Schulz</surname><orcid>0000-0003-4493-4158</orcid><order>3</order></author><author><firstname>Elisabeth</firstname><surname>Andrews</surname><orcid>0000-0002-9394-024x</orcid><order>4</order></author><author><firstname>Yves</firstname><surname>Balkanski</surname><orcid>0000-0001-8241-2858</orcid><order>5</order></author><author><firstname>Susanne E.</firstname><surname>Bauer</surname><orcid>0000-0001-7823-8690</orcid><order>6</order></author><author><firstname>Anna M. K.</firstname><surname>Benedictow</surname><order>7</order></author><author><firstname>Huisheng</firstname><surname>Bian</surname><order>8</order></author><author><firstname>Ramiro</firstname><surname>Checa-Garcia</surname><orcid>0000-0001-7653-3653</orcid><order>9</order></author><author><firstname>Mian</firstname><surname>Chin</surname><order>10</order></author><author><firstname>Paul</firstname><surname>Ginoux</surname><orcid>0000-0003-3642-2988</orcid><order>11</order></author><author><firstname>Jan J.</firstname><surname>Griesfeller</surname><order>12</order></author><author><firstname>Andreas</firstname><surname>Heckel</surname><order>13</order></author><author><firstname>Zak</firstname><surname>Kipling</surname><orcid>0000-0003-4039-000x</orcid><order>14</order></author><author><firstname>Alf</firstname><surname>Kirkevåg</surname><orcid>0000-0002-3691-554x</orcid><order>15</order></author><author><firstname>Harri</firstname><surname>Kokkola</surname><orcid>0000-0002-1404-6670</orcid><order>16</order></author><author><firstname>Paolo</firstname><surname>Laj</surname><order>17</order></author><author><firstname>Philippe Le</firstname><surname>Sager</surname><order>18</order></author><author><firstname>Marianne Tronstad</firstname><surname>Lund</surname><orcid>0000-0001-9911-4160</orcid><order>19</order></author><author><firstname>Cathrine Lund</firstname><surname>Myhre</surname><orcid>0000-0003-3587-5926</orcid><order>20</order></author><author><firstname>Hitoshi</firstname><surname>Matsui</surname><orcid>0000-0002-0376-0879</orcid><order>21</order></author><author><firstname>Gunnar</firstname><surname>Myhre</surname><orcid>0000-0002-4309-476x</orcid><order>22</order></author><author><firstname>David</firstname><surname>Neubauer</surname><orcid>0000-0002-9869-3946</orcid><order>23</order></author><author><firstname>Twan van</firstname><surname>Noije</surname><orcid>0000-0002-5148-5867</orcid><order>24</order></author><author><firstname>Peter</firstname><surname>North</surname><order>25</order></author><author><firstname>Dirk J. L.</firstname><surname>Olivié</surname><order>26</order></author><author><firstname>Samuel</firstname><surname>Rémy</surname><order>27</order></author><author><firstname>Larisa</firstname><surname>Sogacheva</surname><order>28</order></author><author><firstname>Toshihiko</firstname><surname>Takemura</surname><orcid>0000-0002-2859-6067</orcid><order>29</order></author><author><firstname>Kostas</firstname><surname>Tsigaridis</surname><orcid>0000-0001-5328-819x</orcid><order>30</order></author><author><firstname>Svetlana G.</firstname><surname>Tsyro</surname><order>31</order></author><author><firstname>Peter</firstname><surname>North</surname><orcid>0000-0001-9933-6935</orcid><order>32</order></author></authors><documents><document><filename>54247__18984__b20a959f348d4a2cb1b6634ecac06a20.pdf</filename><originalFilename>54247.pdf</originalFilename><uploaded>2021-01-06T15:11:58.4104632</uploaded><type>Output</type><contentLength>8693710</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This work is distributed under the Creative Commons Attribution 4.0 License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
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v2 54247 2020-03-18 AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations fc45a0cb36c24d6cf35313a8c808652f 0000-0001-9933-6935 Peter North Peter North true false 2020-03-18 SGE Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes.Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1.Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc.Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment.Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models.Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions.Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %. Journal Article Atmospheric Chemistry and Physics 21 1 87 128 Copernicus GmbH 1680-7324 6 1 2021 2021-01-06 10.5194/acp-21-87-2021 http://dx.doi.org/10.5194/acp-21-87-2021 COLLEGE NANME Geography COLLEGE CODE SGE Swansea University 2023-12-21T11:29:11.6842379 2020-03-18T00:00:00.0000000 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Geography Jonas Gliß 0000-0003-1147-4482 1 Augustin Mortier 0000-0002-7724-3583 2 Michael Schulz 0000-0003-4493-4158 3 Elisabeth Andrews 0000-0002-9394-024x 4 Yves Balkanski 0000-0001-8241-2858 5 Susanne E. Bauer 0000-0001-7823-8690 6 Anna M. K. Benedictow 7 Huisheng Bian 8 Ramiro Checa-Garcia 0000-0001-7653-3653 9 Mian Chin 10 Paul Ginoux 0000-0003-3642-2988 11 Jan J. Griesfeller 12 Andreas Heckel 13 Zak Kipling 0000-0003-4039-000x 14 Alf Kirkevåg 0000-0002-3691-554x 15 Harri Kokkola 0000-0002-1404-6670 16 Paolo Laj 17 Philippe Le Sager 18 Marianne Tronstad Lund 0000-0001-9911-4160 19 Cathrine Lund Myhre 0000-0003-3587-5926 20 Hitoshi Matsui 0000-0002-0376-0879 21 Gunnar Myhre 0000-0002-4309-476x 22 David Neubauer 0000-0002-9869-3946 23 Twan van Noije 0000-0002-5148-5867 24 Peter North 25 Dirk J. L. Olivié 26 Samuel Rémy 27 Larisa Sogacheva 28 Toshihiko Takemura 0000-0002-2859-6067 29 Kostas Tsigaridis 0000-0001-5328-819x 30 Svetlana G. Tsyro 31 Peter North 0000-0001-9933-6935 32 54247__18984__b20a959f348d4a2cb1b6634ecac06a20.pdf 54247.pdf 2021-01-06T15:11:58.4104632 Output 8693710 application/pdf Version of Record true This work is distributed under the Creative Commons Attribution 4.0 License. true eng https://creativecommons.org/licenses/by/4.0/ |
title |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations |
spellingShingle |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations Peter North |
title_short |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations |
title_full |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations |
title_fullStr |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations |
title_full_unstemmed |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations |
title_sort |
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations |
author_id_str_mv |
fc45a0cb36c24d6cf35313a8c808652f |
author_id_fullname_str_mv |
fc45a0cb36c24d6cf35313a8c808652f_***_Peter North |
author |
Peter North |
author2 |
Jonas Gliß Augustin Mortier Michael Schulz Elisabeth Andrews Yves Balkanski Susanne E. Bauer Anna M. K. Benedictow Huisheng Bian Ramiro Checa-Garcia Mian Chin Paul Ginoux Jan J. Griesfeller Andreas Heckel Zak Kipling Alf Kirkevåg Harri Kokkola Paolo Laj Philippe Le Sager Marianne Tronstad Lund Cathrine Lund Myhre Hitoshi Matsui Gunnar Myhre David Neubauer Twan van Noije Peter North Dirk J. L. Olivié Samuel Rémy Larisa Sogacheva Toshihiko Takemura Kostas Tsigaridis Svetlana G. Tsyro Peter North |
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Journal article |
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Atmospheric Chemistry and Physics |
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21 |
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87 |
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2021 |
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Swansea University |
issn |
1680-7324 |
doi_str_mv |
10.5194/acp-21-87-2021 |
publisher |
Copernicus GmbH |
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Faculty of Science and Engineering |
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Faculty of Science and Engineering |
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School of Biosciences, Geography and Physics - Geography{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Geography |
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http://dx.doi.org/10.5194/acp-21-87-2021 |
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description |
Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes.Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1.Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc.Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment.Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models.Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions.Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %. |
published_date |
2021-01-06T11:29:11Z |
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1785890762089562112 |
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11.03559 |