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

• Published in: Geophysical research letters 2018-02, Vol.45 (4), p.2106-2114
• Main Authors: Wang, Rong, Andrews, Elisabeth, Balkanski, Yves, Boucher, Olivier, Myhre, Gunnar, Samset, Bjørn Hallvard, Schulz, Michael, Schuster, Gregory L., Valari, Myrto, Tao, Shu
• Format: Article
• Language: English
• Subjects: Absorption; AERONET; Aerosol absorption; Aerosol Robotic Network; Aerosols; Aerosols and Particles; Atmosphere; Atmospheric Composition and Structure; Atmospheric models; Atmospheric Processes; Atmospheric Science; Black carbon; Carbon; Clouds and Aerosols; Continental interfaces, environment; Data Assimilation; Earth Resources And Remote Sensing; Error analysis; Errors; GAW; Hydrology; Inhomogeneity; Model Calibration; model resolution; Ocean, Atmosphere; Oceanography: Biological and Chemical; Optical analysis; Paleoceanography; Pollution: Urban and Regional; Radiation absorption; Radiative forcing; representativeness error; Research Letter; Research Letters; Resolution; Robotics; Sciences of the Universe; Solar radiation; Spatial discrimination; Spatial resolution
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1002/2017GL076817

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.