Regional and monthly and clear-sky aerosol direct radiative effect (and forcing) derived from the GlobAEROSOL-AATSR satellite aerosol product

Abstract

Abstract. Using the GlobAEROSOL-AATSR dataset, estimates of the instantaneous, clear-sky, direct aerosol radiative effect and radiative forcing have been produced for the year 2006. Aerosol Robotic Network sun-photometer measurements have been used to characterise the random and systematic error in the GlobAEROSOL product for 22 regions covering the globe. Representative aerosol properties for each region were derived from the results of a wide range of literature sources and, along with the de-biased GlobAEROSOL AODs, were used to drive an offline version of the Met Office unified model radiation scheme. In addition to the mean AOD, best-estimate run of the radiation scheme, a range of additional calculations were done to propagate uncertainty estimates in the AOD, optical properties, surface albedo and errors due to the temporal and spatial averaging of the AOD fields. This analysis produced monthly, regional estimates of the clear-sky aerosol radiative effect and its uncertainty, which were combined to produce annual, global mean values of (−6.7 ± 3.9) W m −2 at the top of atmosphere (TOA) and (−12 ± 6) W m −2 at the surface. These results were then used to give estimates of regional, clear-sky aerosol direct radiative forcing, using modelled pre-industrial AOD fields for the year 1750 calculated for the AEROCOM PRE experiment. However, as it was not possible to quantify the uncertainty in the pre-industrial aerosol loading, these figures can only be taken as indicative and their uncertainties as lower bounds on the likely errors. Although the uncertainty on aerosol radiative effect presented here is considerably larger than most previous estimates, the explicit inclusion of the major sources of error in the calculations suggest that they are closer to the true constraint on this figure from similar methodologies, and point to the need for more, improved estimates of both global aerosol loading and aerosol optical properties.

On the use of a satellite remote-sensing-based approach for determining aerosol direct radiative effect over land: a case study over China

“…Over heavily industrialized and populated areas, the ADRE could be more than 3 times the median values, which indicated that within the study area the anthropogenic aerosol emissions have large contribution to the cooling of the atmosphere. The obtained satellite-based ADRE estimates are in line with values found in other studies using different methods (e.g., Thomas et al, 2013). Locally some positive ADREs, especially during the summer months, were observed outside desert areas where the surface is darker, and the aerosols should have been strongly absorbing to produce a warming effect at TOA.…”

“…For example, Yu et al (2004), Bellouin et al (2005) and Yu et al (2006) showed global estimates of the aerosol radiative effect and forcing by combining remote sensing observations from MODerate Imaging Spectroradiometer (MODIS) and radiative transfer calculations, and more recently Thomas et al (2013) used the Advanced Along Track Scanning Radiometer (AATSR)-based global aerosol optical depth (AOD) data set GlobAEROSOL with a radiative transfer model. In these studies the remote sensing observations have been used as an input to the radiative transfer model to define the TOA SW fluxes with aerosols.…”

Satellite observations of cloud regime development: the role of aerosol processes

“…These are similar regimes to the ones used in this work, although there is not an exact correspondence due to differences between the instruments, retrievals and regimes determined by the clustering processes. We also use the GlobAerosol (Thomas et al, 2013) AOD retrieval from the AATSR instrument on the Envisat satellite. This is similar to Terra MODIS in that it is sun-synchronous and has an overpass time of approximately 1000 LST.…”

Retrieval of Gridded Aerosol Direct Radiative Forcing Based on Multiplatform Datasets

“…The RMSE is 7.9 W m -2 in Baoshan, 7.5 W m -2 in Fuzhou and 5.6 W m -2 in Yong'an. This discrepancy only accounts for 3-5% of the ADRF, indicating that this retrieval method has a relatively higher accuracy than those in other studies (e.g., Thomas et al, 2013;Fu et al, 2017). Additionally, all slopes are less than 1, which implies that the method has systematic biases at these sites.…”

“…Many attempts have been made to solve this key problem. For 70 instance, Thomas et al (2013) adopted prescribed aerosol properties from the literature to estimate surface ADRF. Fu et al (2017) took aerosol optical parameters from some AERONET stations as representative of the entire region to conduct gridcell ADRF simulations.…”