Why it is important to study the liquid and solid water content of cloud?
Clouds have been of interest to many for a long time because of their wide variety of shapes, sizes, and colors, and for their unpredictable and complex nature. The primary constituent of clouds is a conglomeration of water and/or ice growing on small particles called condensation nuclei.
Clouds, the most prominent aspect of the sky play an important role in maintaining the radiation budget of the atmosphere by preventing the incoming shortwave solar radiation from reaching the earth and outgoing longwave thermal radiation from escaping into the outer atmosphere. Clouds thus cool or warm the earth, depending on their optical properties and spatial distribution. This radiation feedback mechanism due to clouds and most significantly water vapour, the chief greenhouse gas in the thermal longwave infrared spectral region, is believed to be responsible for altering or maintaining the global climate. Thus, understanding the interaction between clouds and atmospheric radiation is essential for building a good climate model.
Apart from providing the information necessary for climate studies, measurements of cloud statistics or cloud cover fraction can provide link availability statistics for optical ground-space or space-ground communication and thus help in designing a network of telescopes/instruments on selected sites for uninterrupted data transmission.
Thus to describe variability in solar transmission in numerical weather prediction and climate models in an accurate way , it is extremely important to develop instruments retrieval algorithms which can observe cloud water. For evalution of model predicted cloud parameter long term time series need to be compared. Principally profiles of vertical cloud liquid water content are needed for this purpose. Besides sporadic and expensive in-situ measurements from research aircraft ,LWC can be derived from reflectivity factor (Z) profiles measured by a cloud radar. However due to the fact that LWC is proportional to the total volume of all cloud drops and Z is proportional to the cloud drop radius to the order of six, the conversion of Z to LWC can have an error. More than one order of magnitude. However ground based passive remote sensing is by far the most method to derive the vertical integral of LWC .
The cloud ice total content has been identified as the most relevant climatic parameter for ice cloud depolarization. This parameter can be derived from vertical profiles of meteorological data.