Articles | Volume 17, issue 16
Research article
22 Aug 2017
Research article |  | 22 Aug 2017

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

Ralf Bennartz and John Rausch

Abstract. We present and evaluate a climatology of cloud droplet number concentration (CDNC) based on 13 years of Aqua-MODIS observations. The climatology provides monthly mean 1 × 1° CDNC values plus associated uncertainties over the global ice-free oceans. All values are in-cloud values, i.e. the reported CDNC value will be valid for the cloudy part of the grid box. Here, we provide an overview of how the climatology was generated and assess and quantify potential systematic error sources including effects of broken clouds, and remaining artefacts caused by the retrieval process or related to observation geometry. Retrievals and evaluations were performed at the scale of initial MODIS observations (in contrast to some earlier climatologies, which were created based on already gridded data). This allowed us to implement additional screening criteria, so that observations inconsistent with key assumptions made in the CDNC retrieval could be rejected. Application of these additional screening criteria led to significant changes in the annual cycle of CDNC in terms of both its phase and magnitude. After an optimal screening was established a final CDNC climatology was generated. Resulting CDNC uncertainties are reported as monthly-mean standard deviations of CDNC over each 1 × 1° grid box. These uncertainties are of the order of 30 % in the stratocumulus regions and 60 to 80 % elsewhere.

Short summary
Cloud droplet number concentration is linked to air pollution levels via indirect aerosol effects. The climatological results presented here provide constraints on cloud droplet number concentration globally, thereby helping to evaluate global climate models and study the impact of pollution regionally and globally.
Final-revised paper