## 2 Input Data
### External Input Data  
Table 1 provides an overview of the external input data, that is, data not generated by the authors. From AVHRR Global Area Coverage (GAC) Level-1c data, a Fundamental Data Record (FDR) is created using the PyGAC processor tool [22], performing the calibration and homogenization of the record. It is a Python package to read, calibrate and navigate NOAA and MetOp AVHRR data. Scaled radiance (\(SR_{\lambda}\)) from shortwave channels \(1+2\), on \(0.6\,\upmu\)m and \(0.8\,\upmu\)m, are provided on their original irregular GAC orbit grid together with the necessary metadata. The time stamp, geolocation, and viewing and illumination geometry (solar zenith angle \(\theta_{0}\), viewing zenith angle \(\theta\), relative azimuth angle \(\phi\)) are also included. Channel 1 and channel 2 scaled radiances are already normalized to account for the seasonally changing Earth-Sun distance.  
The NWC SAF Polar Platform System (PPS) consists of a cloud processing software package for polar orbiting satellite data provided by the EUMETSAT NWC SAF project [23; 24]. It includes the Cloud Physical Properties (CPP) algorithm [25], which retrieves the cloud thermodynamic phase, cloud optical thickness (COT), cloud particle effective radius, and liquid/ice water path. The products used in this article are based on version PPSv2018-patch5, which will also be implemented in the CLARA-A3 products. The following PPS products are used for the TOA flux retrieval: PPS probabilistic cloud mask [26; 27], PPS classic cloud mask with snow presence flag [19; 28], and PPS-CPP cloud phase, optical thickness, and quality flag [29].  
The remaining input data consist of ERA5 reanalysis of snow depth and wind speed [7], OSI SAF sea ice concentration from products OSI-450 and OSI-430-b [30], daily Total Solar Irradiance (TSI) from the Copernicus Climate Change Service (C3S) based on Dewitte and Nevens [31] and Dewitte and Clerbaux [2], and an average annual cycle (climatology) of COT calculated from CERES EBAF Ed.4.1 [21; 32]. Static input data consist of a 30 arc-second GLCC land cover map using IGBP classification [33; 34], and a CERES low-resolution (10) land cover map [21].  
Figure 2: (**a**) Daytime Local Equatorial Crossing Time (LECT) for the different NOAA and MetOp satellites used in CLARA-A3. (**b**) Number of SW instantaneous observations contributing to daily mean of UTC day 23 July 1983 (NOAA-17 orbit).  
Finally, important static input data include the CERES shortwave Angular Distribution Models (ADMs). The models consist of radiance measurements stratified by discretized angular bins describing viewing and illumination geometry (\(\theta_{0}\), \(\theta\), \(\phi\)) resulting in three-dimensional data structures. For each solar zenith angle bin, the ADMs also provide the hemispherically integrated radiance, that is, Flux, which is also provided in terms of albedo (so-called \(\theta_{0}\)-dependent \"albedo model\"). Together these data make up the ADM, which describes the radiance's anisotropy. Models are constructed for a variety of land surface types and cloud properties, together constituting so-called \"scene types\". The TRMM Shortwave Ed.2B ADMs [35] are derived from 8 months of observations from the CERES instrument in Rotating Azimuth Plane Scan (RAPS) mode on board the Tropical Rainfall Measurement Mission (TRMM) satellite. Since this satellite was flying on a sun precessing orbit, these ADM models span the entire \(\theta_{0}\) range, which makes it well suited to generating ADMs. On the other hand, as the inclination of the TRMM orbit was only 35\({}^{\circ}\) above the equatorial plane, the mid- and high-latitude regions have not been sampled, which means that snow and ice are not taken into account: for these scene types, the Terra Shortwave Ed.2B ADMs [36] are used, derived from the polar-orbiting Terra satellite.