Measurement-based climatology of aerosol direct radiative effect, its sensitivities, and uncertainties from a background southeast US site

Abstract

Abstract. Aerosol optical properties measured at Appalachian State University's co-located NASA AERONET and NOAA ESRL aerosol network monitoring sites over a nearly four-year period (June 2012–Feb 2016) are used, along with satellite-based surface reflectance measurements, to study the seasonal variability of diurnally averaged clear sky aerosol direct radiative effect (DRE) and radiative efficiency (RE) at the top-of-atmosphere (TOA) and at the surface. Aerosol chemistry and loading at the Appalachian State site are likely representative of the background southeast US (SE US), home to high summertime aerosol loading and one of only a few regions not to have warmed during the 20th century. This study is the first multi-year ground truth DRE study in the SE US, using aerosol network data products that are often used to validate satellite-based aerosol retrievals. The study is also the first in the SE US to quantify DRE uncertainties and sensitivities to aerosol optical properties and surface reflectance, including their seasonal dependence.Median DRE for the study period is −2.9 W m−2 at the TOA and −6.1 W m−2 at the surface. Monthly median and monthly mean DRE at the TOA (surface) are −1 to −2 W m−2 (−2 to −3 W m−2) during winter months and −5 to −6 W m−2 (−10 W m−2) during summer months. The DRE cycles follow the annual cycle of aerosol optical depth (AOD), which is 9 to 10 times larger in summer than in winter. Aerosol RE is anti-correlated with DRE, with winter values 1.5 to 2 times more negative than summer values. Due to the large seasonal dependence of aerosol DRE and RE, we quantify the sensitivity of DRE to aerosol optical properties and surface reflectance, using a calendar day representative of each season (21 December for winter; 21 March for spring, 21 June for summer, and 21 September for fall). We use these sensitivities along with measurement uncertainties of aerosol optical properties and surface reflectance to calculate DRE uncertainties. We also estimate uncertainty in calculated diurnally-averaged DRE due to diurnal aerosol variability. Aerosol DRE at both the TOA and surface is most sensitive to changes in AOD, followed by single-scattering albedo (ω0). One exception is under the high summertime aerosol loading conditions (AOD ≥ 0.15 at 550 nm), when sensitivity of TOA DRE to ω0 is comparable to that of AOD. Aerosol DRE is less sensitive to changes in scattering asymmetry parameter (g) and surface reflectance (R). While DRE sensitivity to AOD varies by only ∼ 25 to 30 % with season, DRE sensitivity to ω0, g, and R largely follow the annual AOD cycle at APP, varying by factors of 8 to 15 with season. Since the measurement uncertainties of AOD, ω0, g, and R are comparable at Appalachian State, their relative contributions to DRE uncertainty are largely influenced by their (seasonally dependent) DRE sensitivity values, which suggests that the seasonal dependence of DRE uncertainty must be accounted for. Clear sky aerosol DRE uncertainty at the TOA (surface) due to measurement uncertainties ranges from 0.45 (0.75 W m−2) for December to 1.1 (1.6 W m−2) for June. Expressed as a fraction of DRE computed using monthly median aerosol optical properties and surface reflectance, the DRE uncertainties at TOA (surface) are 20 to 24 % (15 to 22 %) for March, June, and September and 49 (50 %) for DEC. The relatively low DRE uncertainties are largely due to the low uncertainty in AOD measured by AERONET. Use of satellite-based AOD measurements by MODIS in the DRE calculations increases DRE uncertainties by a factor of 2 to 5 and DRE uncertainties are dominated by AOD uncertainty for all seasons. Diurnal variability in AOD (and to a lesser extent g) contributes to uncertainties in DRE calculated using daily-averaged aerosol optical properties that are slightly larger (by ∼ 20 to 30 %) than DRE uncertainties due to measurement uncertainties during summer and fall, with comparable uncertainties during winter and spring.