## 2 Clouds Properties from Infrared and Microwave Satellite Observations
### Infrared Observations Only

Table 1: _Cont._Very-High-Resolution Radiometer (AVHRR) observations over the ocean (channels at 0.64, 3.75, and 11.0 \(\upmu\)m) was studied by [42], finding good agreement between satellite and in situ products. The cloud retrieval schemes described in [40; 42] have also been widely adopted in the simultaneous estimation of cloud optical thickness and effective cloud particle radius and in the generation of operational JAXA and NASA satellite products [43; 44]. Another method based on a radiative transfer model to retrieve the radii of cloud particles in liquid-water clouds using AVHRR data is described in [45]. This method shows significant seasonal and diurnal variations in the effective radii of droplets, particularly at lower latitudes. An approach based on AVHRR observations at 0.63 and 1.6 \(\upmu\)m for CLWP retrievals is reported by [46]. A cloud analysis through the phase classification of cloud particles and estimation of optical thickness and effective radius is described. The validation of the retrieved CLWP is carried out against ground-based observations retrieved from microwave radiometers during the campaigns of the Cloud Liquid Water Network project (CLIWA-NET). It is important to remember that many aspects of atmospheric conditions (such as, for example, the wind speed at cloud height and the structure of the cloud field) influence the relationship between satellite observations and ground-based measurements, causing a spatial and temporal discrepancy between the two observing strategies. On average, CLWP derived from satellite and ground observations correlates with a 0.88 correlation coefficient with the slope of the linear regression close to 1 and the intercept smaller than 10 gm\({}^{2}\). No systematic bias was found even though the CLWP from a satellite is generally higher than that measured through a ground-based approach. The authors conclude that this is an effect of the satellite effective radius, used to link optical thickness to CLWP, which is representative of larger particles at the cloud-top. This may cause a CLWP overestimation because of the particle-size overestimation [47]. Refs. [48; 49] propose to partially solve this problem by making the parameterization of the vertical droplet size distribution in radiative transfer calculations more realistic. Ref. [50] shows that airborne multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) data over the Arctic with the 1.62 \(\upmu\)m and 2.13 \(\upmu\)m algorithm make the determination of the effective radius and the optical thickness of water clouds more reliable over snow and sea ice surfaces. The explanation for this behavior lies in the very low surface reflectance of snow and sea ice at these wavelengths. For these reasons, the reflectance contrast of the liquid-water clouds compared to the underlying dark surface is relatively strong. However, this algorithm is less reliable due to the ice particles' strong absorption in both bands for ice clouds. Based on the work of [42], ref. [51] used cloud-reflected solar radiances for both visible and near-infrared wavelengths to develop a retrieval algorithm capable of analyzing cloud microphysical parameters on a global scale, with good agreement between the results and in situ measurements. The work of [52] falls under the framework of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF) and reports a comparison between the Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) and AVHRR cloud optical thickness and cloud liquid path retrievals derived from the Cloud Physical Properties (CPP) scheme. The retrieval of the physical properties of clouds is based on the principle that the clouds' reflectance at a non-absorbing wavelength in the visible region (0.6 or 0.8 \(\upmu\)m) is strongly related to the optical thickness, while it does not depend on the particle size.