Determining cloud forcing by cloud type from geostationary satellite data

To fully attribute differences in cloud forcing between regions, or between models and observations, requires separation of the effects of different cloud types. This can only be achieved using data which resolve both day to day and diurnal variations. Here we propose a method which takes advantage of the high temporal resolution of geostationary data to estimate the contribution of individual cloud types to the monthly mean and monthly time-step mean cloud forcing in each grid-box. Details of the method are outlined, and data from the Meteosat-8 satellite for June 2004 are used to demonstrate its benefits.