Studying the cloud radiative effect using a new, 35yr spanning dataset of cloud properties and radiative fluxes inferred from global satellite observations Benjamin Würzler & Martin Stengel Within the Cloud_cci project (Hollmann et al., 2013 ; Stengel et al., 2017) satellite-based, long-term cloud data records have been generated that (1) meet the challenging requirements of the Global Climate Observing System, and (2) also include mathematically consistent uncertainty information following the optimal estimation (OE) retrieval theory. The project will soon release version 3.0 of the datasets which will be introduced in this presentation by summarizing dataset features, key strengths as well as the cloud properties and the new radiation fluxes included. We present climatological maps of selected cloud properties and radiation fluxes and demonstrate how they can be used to calculate the cloud radiative effect (shortwave, longwave and net). The new datasets present an excellent tool for studying the dependence of the cloud radiative effect on cloud properties. 1 Features & Key strengths Cloud_cci v3.0 datasets contain multi-decadal, global datasets of cloud properties and radiation fluxes including uncertainty characterizations based on inter-calibrated radiances from AVHRR and ATSR2/AATSR Retrival algorithms applied are CC4CL (Sus et al., 2017; McGarragh et al., 2017) for cloud properties and BUGSrad for radiation fluxes (Stephens et al., 2001) Spectral consistency among the derived cloud properties is achieved fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the thermal infrared using optimal estimation techniques. Cloud & Radiation Products (AVHRR-PM v3.0) a) b) Variable Abb. Definition Cloud mask / Cloud fraction CMA CFC A binary cloud mask per pixel and therefrom derived monthly total cloud fractional coverage and separation into 3 vertical classes (high, mid- level, low clouds) (Fig. 2-a). Cloud phase CPH The thermodynamic phase of the retrieved cloud and the therefrom derived monthly liquid cloud fraction (Fig. 2-b). Cloud optical thickness COT The line integral of the absorption coefficient and the scattering coefficient along the vertical in cloudy pixels (Fig. 2-c). Cloud effective radius CER The area weighted radius of the cloud drop and crystal particles, respectively (Fig. 2-d). Cloud top pressure/height/ temperature CTP CTH CTT The air pressure [hPa] /height [m] /temperature [K] of the uppermost cloud layer that could be identified by the retrieval system. Liquid water path Ice water path LWP IWP The vertical integrated liquid/ice water content of existing cloud layers; derived from CER and COT (Fig. 2-e & Fig. 2-f). Joint cloud property histogram JCH Spatially resolved two-dimensional histogram of combinations of COT and CTP for each spatial grid box. Spectral cloud albedo CLA The black-sky cloud albedo derived at 0.67 and 0.87 µm. (experimental product) c) d) e) f) Figure 2 Climatological maps of Cloud fraction (a), Cloud phase (b), Cloud optical thickness (c), Cloud effective radius (d), Liquid water path (e) and Ice water path (f), all based on 35 years of AVHRR observations (Cloud_cci AVHRR-PM v3.0 dataset). Figure 1 Time periods and local observation times (equator crossing times) of each satellite sensor considered in Cloud_cci v3.0. Variable Abb. Definition Top of the atmosphere fluxes TOA_SWUP TOA_SWUP_CLR Reflected solar radiation at the top of the atmosphere (all-sky/clear-sky) (Fig. 3-a &Fig. 3-b). TOA_LWUP TOA_LWUP_CLR Outgoing longwave radiation at the top of the atmosphere (all-sky/clear-sky) (Fig. 3-c & Fig. 3-d). Bottom of the atmosphere (surface) fluxes BOA_SWDN BOA_SWDN_CLR Incoming solar radiation at the surface (all-sky/clear-sky) BOA_LWDN BOA_LWDN_CLR Downward longwave radiation at the surface (all-sky/clear-sky) BOA_SWUP Reflected solar radiation at the surface BOA_LWUP Outgoing longwave radiation at the surface Photosynthetically active radiation PAR Photosynthetically active radiation downward at the surface a) b) Results a) c) d) Figure 3 Climatological maps of the all-sky (a) and clear-sky (b) reflected solar and all-sky (c) and clear-sky (d) outgoing longwave radiation at the top of the atmosphere, all based on 35 years of AVHRR observations (Cloud_cci AVHRR-PM v3.0 dataset). Validation b) c) a) b) c) d) Figure 5 Top: Time series of monthly mean (60S-60N) cloud radiative effects (a) based on Cloud_cci AVHRR-PM v3.0 and CERES EBAF Edition 4.0 TOA Fluxes (Wielicki et. al., 1996). Right: Scatterplots comparing the shortwave (b), longwave (c) and net cloud radiative effects (d) from Cloud_cci AVHRR-PM v3.0 and CERES EBAF Edition 4.0 TOA Fluxes in relation to the correlation (R), bias, mean absolute bias (MAB) and root mean square error (RMSE) for the period from 2003 to 2016. Project consortium References: Hollmann, R. et al.: The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables, BAMS, 94, 1541–1552, 2013. McGarragh, G. R.: The Community Cloud retrieval for Climate (CC4CL). Part II: The optimal estimation approach, Atmospheric Measurement Techniques Discussions, 2017, 1-55, https://doi.org/10.5194/amt-2017-333, https://www.atmos-meas-tech-discuss.net/amt-2017-333/, 2017. Stengel, M. et al.: Cloud property datasets retrieved from AVHRR, MODIS, AATSR, and MERIS in the framework of the Cloud_cci project, Earth System Science Data, 9, https://doi.org/10.5194/essd-9-881-2017, https://www.earth-syst-sci-data.net/9/881/2017/, 2017. Stephens, G. L. et al.: Parameterization of Atmospheric Radiative Transfer. Part I: Validity of Simple Models. Journal of the Atmospheric Sciences, 58(22):3391-3409, 2001. Sus, O. et al.: The Community Cloud retrieval for Climate (CC4CL). Part I: A framework applied to multiple satellite imaging sensors, Atmospheric Measurement Techniques Discussions, 2017, 1–42, https://doi.org/10.5194/amt-2017-334, https://www.atmos-meas-tech-discuss.net/amt-2017-334/, 2017. Wielicki, B. A. et al.: Clouds and the Earth‘s Radiant Energy System (CERES): An Earth Observing System Experiment, BAMS, 77, 853-868, 1996. Acknowledgement: This work was supported by the European Space Agency (ESA) through the Cloud_cci project (contract No.: 4000109870/13/I15NB).