Direct aerosol forcing: Calculation from observables and sensitivities to inputs

Abstract

[1] Understanding sources of uncertainty in aerosol direct radiative forcing (DRF), the difference in a given radiative flux component with and without aerosol, is essential to quantifying changes in Earth's radiation budget. We examine the uncertainty in DRF owing to measurement uncertainty in the quantities on which it depends: aerosol optical depth, single scattering albedo, asymmetry parameter, solar geometry, and surface albedo. Direct radiative forcing at the top of the atmosphere and at the surface is calculated at three locations representing distinct aerosol types and radiative environments. Sensitivities, the changes in DRF in response to unit changes in individual aerosol or surface properties, are also calculated for these conditions. The uncertainty in DRF associated with a given property is computed as the product of the sensitivity and typical measurement uncertainty in the respective property. Sensitivity and uncertainty values permit estimation of total uncertainty in calculated DRF and identification of properties that most limit accuracy in estimating forcing. Absolute total uncertainties in modeled local diurnally averaged forcing range from 0.2 to 3.1 W m À2 for the ranges of properties examined here. Relative total uncertainties range from $20 to 80% with larger values at higher latitudes, where fluxes are low. The largest contributor to total uncertainty in DRF is single scattering albedo; however, decreasing measurement uncertainties for any property would increase accuracy in DRF. Comparison of two radiative transfer models suggests the contribution of modeling error is small compared to the total uncertainty although comparable to uncertainty arising from some individual properties.

Urban impacts on regional carbonaceous aerosols: Case study in central Texas

“…Absorption due to carbonaceous aerosols, both the organic and elemental fractions, is currently one of the greatest sources of uncertainty in the global radiative budget (Anderson et al, 2003;McComiskey et al, 2008;Chen and Bond, 2010). Absorption coefficient for WSOC absorption (b abs ) and mass absorption cross-section measurements for the United States have been made in the Southeast and on the West Coast, including Atlanta, GA (b abs ¼ 0.61 AE 0.38 Mm À1 ), and Pasadena, CA (b abs ¼ 0.88 AE 0.71 Mm À1 ), but are needed for the central United States, particularly for BrC (Hecobian et al, 2010;.…”

Contrasting aerosol characteristics and radiative forcing over Hyderabad, India due to seasonal mesoscale and synoptic‐scale processes

“…The estimation of ARF by means of a radiative transfer model depends on aerosol properties used as model inputs; the most significant contributors to total uncertainty in ARF are the AOD and SSA (McComiskey et al, 2008). However, the satisfactory simulation of the measured AODs with those calculated from OPAC ( Figure 10) reduces the uncertainties in SSA to lower than 10%, while in some months of excellent agreement (e.g.…”

“…The aerosol optical properties and ARF depend on size, shape and composition of the particles, as well as on ambient relative humidity (RH) that determines the growth rate of aerosols; the measured monthly mean values of RH were used for the ARF calculation. The uncertainty in the ARF computation using this method is about 10% (Bellouin et al, 2004) as ARF depends also on the surface reflectance, which is one of the major contributors to the ARF uncertainties (McComiskey et al, 2008). In order to eliminate such errors, the 8-day (L3 Global 500 m) surface reflectance values over Hyderabad were taken from MODIS at seven wavelengths from visible to infrared.…”

Failure and Redemption of Multifilter Rotating Shadowband Radiometer (MFRSR)/Normal Incidence Multifilter Radiometer (NIMFR) Cloud Screening: Contrasting Algorithm Performance at Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) and Southern Great Plains (SGP) Sites

“…Aerosol optical depth (AOD) is an important parameter required for resolving aerosol radiative effects and their climate impacts [10]. AOD is representative of the total aerosol burden in the atmosphere, and its spectral dependence, typically described by the Angstrom exponent (AE), indicates particle size [11].…”