Understanding the cloud microphysical processes and precise retrieval of parameters governing the same are crucial for weather and climate prediction. Advanced remote sensing sensors and techniques offer an opportunity for monitoring micro-level developments in cloud structure. . Using the observations from a visible and near-infrared lidar onboard CALIPSO satellite (part of A-train) , the spatial variation of cloud structure has been studied over the Tropical monsoon region . It is found that there is large variability in the cloud microphysical parameters manifesting in distinct precipitation regimes. In particular, the severe storms over this region are driven by processes which range from the synoptic to the microphysical scale. Using INSAT-3D data, retrieval of cloud microphysical parameters like effective radius (CER) and optical depth (COD) were carried out for tropical cyclone Phailine. It was observed that there is a general increase of CER in a top–down direction, characterizing the progressively increasing number and size of precipitation hydrometeors while approaching the cloud base. The distribution of CER relative to cloud top temperature for growing convective clouds has been investigated to reveal the evolution of the particles composing the clouds. It is seen that the relatively high concentration of large particles in the downdraft zone is closely related to the precipitation efficiency of the system. Similar study was also carried using MODIS observations for cyclones over Indian Ocean (2010-2013), in which we find that that the mean effective radius is 24 microns with standard deviation 4.56, mean optical depth is 21 with standard deviation 13.98, mean cloud fraction is 0.92 with standard deviation 0.13 and mainly ice phase is dominant. Thus the remote observations of microstructure of convective storms provide very crucial information about the maintenance and potential devastation likely to be associated with it. With the synergistic observations from A-Train , geostationary and futuristic imaging spectroscopic sensors, a multi-dimensional, and multi-scalar exploration of cloud systems is anticipated leading to accurate prediction of high impact weather events.
Clouds strongly modulate the Earths energy balance and its atmosphere through their interaction with the solar and terrestrial radiation. They interact with radiation in various ways like scattering, emission and absorption. By observing these changes in radiation at different wavelength, cloud properties can be estimated. Cloud properties are of utmost importance in studying different weather and climate phenomena. At present, no satellite provides cloud microphysical parameters over the Indian region with high temporal resolution. INSAT-3D imager observations in 6 spectral channels from geostationary platform offer opportunity to study continuous cloud properties over Indian region. Visible (0.65 μm) and shortwave-infrared (1.67 μm) channel radiances can be used to retrieve cloud microphysical parameters such as cloud optical thickness (COT) and cloud effective radius (CER). In this paper, we have carried out a feasibility study with the objective of cloud microphysics retrieval. For this, an inter-comparison of 15 globally available radiative transfer models (RTM) were carried out with the aim of generating a Look-up- Table (LUT). SBDART model was chosen for the simulations. The sensitivity of each spectral channel to different cloud properties was investigated. The inputs to the RT model were configured over our study region (50°S - 50°N and 20°E - 130°E) and a large number of simulations were carried out using random input vectors to generate the LUT. The determination of cloud optical thickness and cloud effective radius from spectral reflectance measurements constitutes the inverse problem and is typically solved by comparing the measured reflectances with entries in LUT and searching for the combination of COT and CER that gives the best fit. The products are available on the website www.mosdac.gov.in