Satellite monitoring of the first indirect aerosol effect: Retrieval of the droplet concentration of water clouds

Abstract

[1] A model for the vertical variation of microphysical and optical properties of single-layer water clouds is used to design a procedure to obtain cloud droplet concentration from satellite cloud optical thickness/effective radius retrievals. The model allows for smooth vertical variations in microphysical variables including droplet concentration and liquid water content. The procedure is applied to data from the MODIS instrument aboard the EOS-TERRA satellite platform over a region near Cape Grim, Tasmania, over the Southern Ocean. At this unpolluted location, there are seasonally repeated well-described variations in cloud condensation nucleus concentration. The satellite observations show that there is a factor 2.5 difference in retrieved droplet concentration between the summer and winter seasons as measured over the 4 year period (July 2000 to July 2004). Comparison of these results with cloud condensation nuclei concentrations observed at Cape Grim showed good agreement. Furthermore, for a fixed solar zenith angle cos (45°) cloud albedo varied between 0.45 and 0.55 and exhibited a clear correlation with the retrieved droplet concentration (correlation coefficient R = 0.80). Such correlation was absent between albedo and the second retrieval product, namely the cloud depth.

Estimating seasonal variations in cloud droplet number concentration over the boreal forest from satellite observations

“…Opposite to our results, Boers et al (2006) found a clear relation between N CD and N CCN . They, however, studied clouds over the ocean, which do not experience the strong diurnal cycle in atmospheric boundary layer as over land.…”

“…A way to circumvent this problem is to estimate the cloud droplet number concentration (N CD ), since it directly links cloud optical and microphysical properties to the aerosol concentration at cloud base. Several methods have been developed for this purpose, each one requiring different assumptions about the sub-adiabatic character of and the mixing that occurs inside clouds (Bennartz, 2007;Boers et al, 2006;Szczodrak et al, 2001).…”

“…The method developed by Boers et al (2006) (hereinafter referred to as B06), was validated by Roebeling et al (2008), combining ground-based observations of cloud depth (h) and LWP with calculations of the cloud model using data from the SEVIRI-instrument onboard METEOSAT as input. This showed very good agreement for strictly selected cases over the Netherlands.…”

Ice crystal number concentration estimates from lidar-radar satellite remote sensing. Part 1: Method and evaluation

“…Moreover, N i appears as a particularly useful metric to quantify aerosol-cloud interactions due its potentially close link with the aerosol concentration (Kärcher and Ström, 2003;Kay and Wood, 2008;Hendricks et al, 2011). Consequently, while numerous studies have for these reasons used satellite estimates of the cloud droplet number 20 concentration (N d ) to evaluate the indirect aerosol radiative forcing (Boers et al, 2006;Quaas et al, 2006Quaas et al, , 2008Gryspeerdt et al, 2016), the contribution of ice clouds to this effect remains largely unknown (Heyn et al, 2017).…”

Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations

“…Zhang et al, 2012;He et al, 2015;Wang et al, 2015;Ban-Weiss et al, 2014). A variety of observational case studies and process studies were also published using similar approaches for deriving CDNC (Boers et al, 2006;George and Wood, 2010;Painemal and Zuidema, 2010;Rausch et al, 2010;. Various authors have addressed shortcomings and issues related to CDNC climatologies (Merk et al, 2016;Grosvenor and Wood, 2014) as well as issues related to the cloud retrievals underlying the CDNC climatologies (Zhang and Platnick, 2011;Nakajima et al, 2010;Maddux et al, 2010;Horvath et al, 2014).…”