Surface radiative fluxes are a key driver of the terrestrial energy budget; among these the fluxes, the downward longwave radiative fluxes (DLF) are an important component of estimating the Earth's greenhouse effect and therefore the climate variability. Meanwhile direct observations of surface irradiances are limited of a ground sites over the land, accurate satellite-based estimations help us to understanding flux variability at larger spatial scales. To date most satellite based longwave flux algorithms make assumptions regarding the vertical profiles of clouds (Zhang et al., 2004, Gupta et al., 1992, Stackhouse et al., 2011). New methods, using CALIPSO and CloudSat now specify cloud vertical profiles explicitly (Kato et al, 2011), but are limited in time and space.

During an overlapping period of two years (2006/2007), this study assesses the LRFs estimated by two different projects SRB (Surface Radiative Budget) and CCCM (CALIPSO-CloudSat-CERES-MODIS). Based on an achieved fluxes on a 1° x 1° global grid, the agreement between NASA/GEWEX Surface Radiation Budget (SRB) and CCCM LW data sets is quantified assuming different spatial (land/ocean) and temporal scales (day/night). The agreement between both datasets is related in some initial assumptions in each dataset such as input cloud properties and cloud bases and overlap compared to the explicit vertical profiles.