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

• 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), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), 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 Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), 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: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces; environment; Aerosol Robotic Network
• Online Access: https://hal.archives-ouvertes.fr/hal-01806880; https://hal.archives-ouvertes.fr/hal-01806880/document; https://hal.archives-ouvertes.fr/hal-01806880/file/2017GL076817.pdf; https://doi.org/10.1002/2017GL076817

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%.