The Clouds and the Earth's Radiant Energy System Synoptic (SYN1deg), edition 3, product provides climate-quality global 3-hourly 18 3 18gridded top of atmosphere, in-atmosphere, and surface radiant fluxes. The in-atmosphere surface fluxes are computed hourly using a radiative transfer code based upon inputs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), 3-hourly geostationary (GEO) data, and meteorological assimilation data from the Goddard Earth Observing System. The GEO visible and infrared imager calibration is tied to MODIS to ensure uniform MODIS-like cloud properties across all satellite cloud datasets. Computed surface radiant fluxes are compared to surface observations at 85 globally distributed land (37) and ocean buoy (48) sites as well as several other publicly available global surface radiant flux data products. Computed monthly mean downward fluxes from SYN1deg have a bias (standard deviation) of 3.0 W m 22 (5.7%) for shortwave and 24.0 W m 22 (2.9%) for longwave compared to surface observations. The standard deviation between surface downward shortwave flux calculations and observations at the 3-hourly time scale is reduced when the diurnal cycle of cloud changes is explicitly accounted for. The improvement is smaller for surface downward longwave flux owing to an additional sensitivity to boundary layer temperature/humidity, which has a weaker diurnal cycle compared to clouds.

The Clouds and the Earth’s Radiant Energy System (CERES) project has provided the climate community 15 years of globally observed top-of-the-atmosphere fluxes critical for climate and cloud feedback studies. To accurately monitor the earth’s radiation budget, the CERES instrument footprint fluxes must be spatially and temporally averaged properly. The CERES synoptic 1° (SYN1deg) product incorporates derived fluxes from the geostationary satellites (GEOs) to account for the regional diurnal flux variations in between Terra and Aqua CERES measurements. The Edition 4 CERES reprocessing effort has provided the opportunity to reevaluate the derivation of longwave (LW) fluxes from GEO narrowband radiances by examining the improvements from incorporating 1-hourly versus 3-hourly GEO data, additional GEO infrared (IR) channels, and multichannel GEO cloud properties. The resultant GEO LW fluxes need to be consistent across the 16-satellite climate data record. To that end, the addition of the water vapor channel, available on all GEOs, was more effective than using a reanalysis dataset’s column-weighted relative humidity combined with the window channel radiance. The benefit of the CERES LW angular directional model to derive fluxes was limited by the inconsistency of the GEO cloud retrievals. Greater success was found in the direct conversion of window and water vapor channel radiances into fluxes. Incorporating 1-hourly GEO fluxes had the greatest impact on improving the accuracy of high-temporal-resolution fluxes, and normalizing the GEO LW fluxes with CERES greatly reduced the monthly regional LW flux bias.