A new statistical approach to improve the satellite-based estimation of the radiative forcing by aerosol–cloud interactions

Abstract

Abstract. In a previous study of Quaas et al. (2008) the radiative forcing by anthropogenic aerosol due to aerosol–cloud interactions, RFaci, was obtained by a statistical analysis of satellite retrievals using a multilinear regression. Here we employ a new statistical approach to obtain the fitting parameters, determined using a nonlinear least square statistical approach for the relationship between planetary albedo and cloud properties and, further, for the relationship between cloud properties and aerosol optical depth. In order to verify the performance, the results from both statistical approaches (previous and present) were compared to the results from radiative transfer simulations over three regions for different seasons. We find that the results of the new statistical approach agree well with the simulated results both over land and ocean. The new statistical approach increases the correlation by 21–23 % and reduces the error compared to the previous approach.

Author response to reviewer comments

“…Based on this relationship, a first indirect radiative forcing of −0.97 Wm −2 was derived. The forcing found in McCoy et al (2017a) based on the stratocumulus regions and confirmed globally by this study is stronger than found in previous empirical remote-sensing studies (Bellouin et al, 2013;Quaas et al, 2008), but not out of line with climate model studies forced to be consistent with in situ relationships between sulfate and CDNC (Storelvmo et al, 2009). Therefore remotely sensed CCN proxies that are not speciated are not as skillful a predictor of true CCN variability as sulfate mass and will underestimate the radiative forcing due to aerosol-cloud interactions.…”

“…Aerosol indirect effects can be grouped into two categories: the first indirect effect, or Twomey effect (Twomey, 1977), by which enhanced concentrations of cloud condensation nuclei (CCN) enhance CDNC (for a fixed liquid water content), leading to an increase in cloud albedo; and the lifetime, or Albrecht effect (Albrecht, 1989), by which enhanced CDNC suppresses precipitation and leads to thicker or more persistent clouds and higher cloud albedo. The first indirect effect has been supported by numerous empirical studies relating remotely sensed aerosol properties to remotely sensed CDNC (Bellouin et al, 2013;Gryspeerdt et al, 2016;Patel et al, 2017;Quaas et al, 2008Quaas et al, , 2009Matsui et al, 2006;Nakajima et al, 2001;Sekiguchi et al, 2003), although whether aerosol affects cloud lifetime is still debated (McCoy et al, 2017b;Malavelle et al, 2017;Gryspeerdt et al, 2016;Mace and Avey, 2016). Studies have utilized the natural laboratory provided by transient degassing volcanoes to study cloud responses to changes in aerosol (Mace and Abernathy, 2016;Gassó, 2008;Yuan et al, 2011;Malavelle et al, 2017;Mc-D. T. McCoy et al: Predicting decadal trends Coy and Hartmann, 2015).…”

Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data

“…Aerosol indirect effects can be grouped into two categories: the first indirect effect, or Twomey effect (Twomey, 1977), by which enhanced concentrations of cloud condensation nuclei (CCN) enhance CDNC (for a fixed liquid water content), leading to an increase in cloud albedo; and the lifetime, or Albrecht effect (Albrecht, 1989), by which enhanced CDNC suppresses precipitation and leads to thicker or more persistent clouds and higher cloud albedo. The first indirect effect has been supported by numerous empirical studies relating remotely-sensed aerosol properties to remotely-30 sensed CDNC Gryspeerdt et al, 2016;Patel et al, 2017;Quaas et al, 2008;Quaas et al, 2009;Matsui et Atmos. Chem.…”

Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data

“…Aerosol indirect effects can be grouped into two categories: the first indirect effect, or Twomey effect (Twomey, 1977), by which enhanced concentrations of cloud condensation nuclei (CCN) enhance CDNC (for a fixed liquid water content), leading to an increase in cloud albedo; and the lifetime, or Albrecht effect (Albrecht, 1989), by which enhanced CDNC suppresses precipitation and leads to thicker or more persistent clouds and higher cloud albedo. The first indirect effect has been supported by numerous empirical studies relating remotely sensed aerosol properties to remotely sensed CDNC Gryspeerdt et al, 2016;Patel et al, 2017;Quaas et al, 2008Quaas et al, , 2009Matsui et al, 2006;Nakajima et al, 2001;Sekiguchi et al, 2003), although whether aerosol affects cloud lifetime is still debated (McCoy et al, 2017b;Malavelle et al, 2017;Gryspeerdt et al, 2016;Mace and Avey, 2016). Studies have utilized the natural laboratory provided by transient degassing volcanoes to study cloud responses to changes in aerosol (Mace and Abernathy, 2016;Gassó, 2008;Yuan et al, 2011;Malavelle et al, 2017; Mc-…”