Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

International audience 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 er...

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Published in:Geophysical Research Letters
Main Authors: Wang, Rong, Andrews, Elisabeth, Balkanski, Yves, Boucher, Olivier, Myhre, Gunnar, Samset, Bjørn Hallvard, Schulz, Michael, Schuster, Gregory, Valari, Myrto, Tao, Shu
Other Authors: Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), 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)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-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)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), 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), Center for International Climate and Environmental Research Oslo (CICERO), University of Oslo (UiO), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University Beijing
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2018
Subjects:
Online Access:https://hal.science/hal-01806880
https://hal.science/hal-01806880/document
https://hal.science/hal-01806880/file/2017GL076817.pdf
https://doi.org/10.1002/2017GL076817
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collection École des Ponts ParisTech: HAL
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language English
topic [SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces
environment
spellingShingle [SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces
environment
Wang, Rong
Andrews, Elisabeth
Balkanski, Yves
Boucher, Olivier
Myhre, Gunnar
Samset, Bjørn Hallvard
Schulz, Michael
Schuster, Gregory
Valari, Myrto
Tao, Shu
Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption
topic_facet [SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces
environment
description International audience 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. Plain Language Summary When comparing the black carbon model at a resolution of 2°× 2°with local measurements, the global representativeness error is 30% for AErosol RObotic NETwork sites, compared to 7% for Global Atmosphere Watch sites. It demonstrates that, in absence of high-resolution models, the current top-down estimate of black carbon direct radiative forcing is overestimated by 30%.
author2 Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE)
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)-Direction de Recherche Fondamentale (CEA) (DRF (CEA))
Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID)
Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-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)-Direction de Recherche Fondamentale (CEA) (DRF (CEA))
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)
Center for International Climate and Environmental Research Oslo (CICERO)
University of Oslo (UiO)
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences
Peking University Beijing
format Article in Journal/Newspaper
author Wang, Rong
Andrews, Elisabeth
Balkanski, Yves
Boucher, Olivier
Myhre, Gunnar
Samset, Bjørn Hallvard
Schulz, Michael
Schuster, Gregory
Valari, Myrto
Tao, Shu
author_facet Wang, Rong
Andrews, Elisabeth
Balkanski, Yves
Boucher, Olivier
Myhre, Gunnar
Samset, Bjørn Hallvard
Schulz, Michael
Schuster, Gregory
Valari, Myrto
Tao, Shu
author_sort Wang, Rong
title Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption
title_short Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption
title_full Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption
title_fullStr Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption
title_full_unstemmed Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption
title_sort spatial representativeness error in the ground-level observation networks for black carbon radiation absorption
publisher HAL CCSD
publishDate 2018
url https://hal.science/hal-01806880
https://hal.science/hal-01806880/document
https://hal.science/hal-01806880/file/2017GL076817.pdf
https://doi.org/10.1002/2017GL076817
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source ISSN: 0094-8276
EISSN: 1944-8007
Geophysical Research Letters
https://hal.science/hal-01806880
Geophysical Research Letters, 2018, 45 (4), pp.2106 - 2114. ⟨10.1002/2017GL076817⟩
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op_doi https://doi.org/10.1002/2017GL076817
container_title Geophysical Research Letters
container_volume 45
container_issue 4
container_start_page 2106
op_container_end_page 2114
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spelling ftecoleponts:oai:HAL:hal-01806880v1 2024-06-09T07:37:53+00:00 Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption Wang, Rong Andrews, Elisabeth Balkanski, Yves Boucher, Olivier Myhre, Gunnar Samset, Bjørn Hallvard Schulz, Michael Schuster, Gregory Valari, Myrto Tao, Shu Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) 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)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-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)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) 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) Center for International Climate and Environmental Research Oslo (CICERO) University of Oslo (UiO) Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences Peking University Beijing 2018-02-28 https://hal.science/hal-01806880 https://hal.science/hal-01806880/document https://hal.science/hal-01806880/file/2017GL076817.pdf https://doi.org/10.1002/2017GL076817 en eng HAL CCSD American Geophysical Union info:eu-repo/semantics/altIdentifier/doi/10.1002/2017GL076817 hal-01806880 https://hal.science/hal-01806880 https://hal.science/hal-01806880/document https://hal.science/hal-01806880/file/2017GL076817.pdf doi:10.1002/2017GL076817 info:eu-repo/semantics/OpenAccess ISSN: 0094-8276 EISSN: 1944-8007 Geophysical Research Letters https://hal.science/hal-01806880 Geophysical Research Letters, 2018, 45 (4), pp.2106 - 2114. ⟨10.1002/2017GL076817⟩ [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment info:eu-repo/semantics/article Journal articles 2018 ftecoleponts https://doi.org/10.1002/2017GL076817 2024-05-16T13:00:32Z International audience 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. Plain Language Summary When comparing the black carbon model at a resolution of 2°× 2°with local measurements, the global representativeness error is 30% for AErosol RObotic NETwork sites, compared to 7% for Global Atmosphere Watch sites. It demonstrates that, in absence of high-resolution models, the current top-down estimate of black carbon direct radiative forcing is overestimated by 30%. Article in Journal/Newspaper Aerosol Robotic Network École des Ponts ParisTech: HAL Geophysical Research Letters 45 4 2106 2114