Dataset Information

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

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.

SUBMITTER: Wang R

PROVIDER: S-EPMC5993241 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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

Wang Rong R Andrews Elisabeth E Balkanski Yves Y Boucher Olivier O Myhre Gunnar G Samset Bjørn Hallvard BH Schulz Michael M Schuster Gregory L GL Valari Myrto M Tao Shu S

Geophysical research letters 20180201 4

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 n ...[more]

PMID: 29937603

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Dataset Information

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

Publications

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

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