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

Area of Science:

• Atmospheric Science
• Climate Science
• Aerosol Science

Background:

• Black carbon (BC) aerosol significantly impacts Earth's radiative balance, but its direct radiative forcing has high uncertainty.
• Current estimates are influenced by spatial representativeness errors, particularly in comparing coarse-resolution models with observational data.

Purpose of the Study:

• To evaluate the spatial representativeness error of observational networks for black carbon aerosol.
• To assess the impact of observational network site selection on the accuracy of global BC direct radiative forcing estimates.

Main Methods:

• Downscaled a global BC aerosol absorption optical depth model to a 0.1° × 0.1° resolution.
• Compared model outputs at 2° × 2° resolution with BC aerosol absorption data from AErosol RObotic NETwork (AERONET) and Global Atmosphere Watch (GAW) sites.
• Quantified spatial representativeness error for both networks.

Main Results:

• Using AERONET sites, commonly located near emission hot spots, introduces a 30% positive bias in the top-down estimate of global BC direct radiative forcing.
• The GAW network exhibits a significantly lower global spatial representativeness error of 7%.
• GAW site distribution results in a balance of positive and negative representativeness errors, leading to a more accurate global estimate.

Conclusions:

• The spatial distribution of observational sites critically influences the accuracy of global aerosol radiative forcing estimates.
• The Global Atmosphere Watch network provides a more reliable observational basis for constraining black carbon's direct radiative forcing than AERONET.
• Improving the spatial resolution of global models and carefully selecting observational networks are crucial for reducing uncertainty in climate forcing assessments.