## 2 Clouds Properties from Infrared and Microwave Satellite Observations
### Infrared Observations Only
A method for deducing semitransparent ice Clouds Optical Thickness (COT \(<\) 5) using AIRS measurements is presented in [60]. In this work, the sensitivity of AIRS spectral BT and Brightness Temperature Differences (BTD) values between wavenumber pairs for COT is studied. The spectral BTs within the 1070-1135 cm\({}^{-1}\) region (atmospheric window channels) are sensitive to the ice COT and similarly for the BTD between 900.562 cm\({}^{-1}\) (atmospheric window) and 1558.692 cm\({}^{-1}\) (strong water vapor absorption band). Analogously, the BTD is sensitive to ice COT between the channels 1587.495 cm\({}^{-1}\) and 1558.692 cm\({}^{-1}\), respectively, a moderate and a strong water absorption channel. The method performance is evaluated by comparing the ice COT obtained from the AIRS observations with those estimated from MODIS (1.38 and 0.645 \(\upmu\)m bands), suitably collocated and degraded to the AIRS spatial resolution. There is substantial agreement regarding the COT for thin to moderately thick cirrus clouds (COT \(<\) 5). Instead, as COT increases, the COT retrieved via AIRS tends to be lower than MODIS. This may be due to the saturation of the BTD signal for large COT values. The methodology described in [60] and based on two or more channels in the IR window is sometimes known as the \"split-window method\". In the literature, there are many applications of this approach, which, although applicable to all clouds, is more powerful in the case of high semitransparent ice clouds [61]. Some applications can be found, for example, in [62] (for the retrieval of microphysical properties of semitransparent cirrus clouds using 11 \(\upmu\)m and 12 \(\upmu\)m AVHRR data) and in [61] (to explore its usefulness for the generation of a multidecadal climatology based on AVHRR data of cloud temperature, emissivity, and a microphysical parameter). Split-window (11\(-\)12 \(\upmu\)m) brightness temperature differences are used by [63] to identify the cloud type, while the high sensitivity to the predominance of small ice crystals of the BT difference between two bands in the atmospheric IR window is exploited by [64] to develop a technique for the unambiguous identification of thin cirrus clouds with effective radii smaller than 20 \(\upmu\)m. Split-window MODIS channels are also applied by [65] for the retrieval of the liquid-water fraction from cold clouds in the case where the liquid fraction is less than 50% of the total condensate. The theoretical basis for estimating the ice cloud microphysical properties fusing high-spectral-resolution infrared observations was reviewed by [66]. From the simulations developed in their work, it is possible to see how the slope of the IR BT spectrum between 790 and 960 cm\({}^{-1}\) is sensitive to the effective particle size; furthermore, the infrared brightness temperature appears to be highly sensitive to optical cloud thickness in the 1050-1250 cm\({}^{-1}\) region. From these spectral features' examination, the authors illustrate a method to simultaneously retrieve the visible optical thickness and effective ice cloud particle size from high spectral resolution infrared data. From the uncertainty analysis, it is concluded that the retrieved COT and effective particle size uncertainties have a small range of variation. Regarding the uncertainty of the particle size, a value lower than 15% is found in the case of a cloud temperature uncertainty of 5 K or a surface temperature uncertainty of 2.5 K. However, concerning the optical thickness, the corresponding uncertainty value is between 5% and 20%, depending on the COT value. Ref. [67] studies the advantages of a combined approach using the MODIS and AIRS products to obtain the microphysical properties of clouds during both day and night. MODIS can provide mask products (cloud mask, cloud phase detection, and cloud classification) and cloud microphysical products, while AIRS radiance measurements are useful for retrieving the COT and particle size of clouds.