Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO 2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.
A mesoscale convective system (MCS) is organized thunderstorms with connected anvils, which has a significant impact on the global climate. By focusing on MCSs over the Maritime Continent of Indonesia, this study aims to gain a better understanding on the properties of the MCSs over the study area. The "Grab 'em Tag 'em Graph 'em" (GTG) tracking algorithm is applied to hourly Multi-functional Transport Satellite-1R data for two years to observe the distribution of MCSs and the evolution of MCSs along their lifetime. The results of MCS identification by using GTG are combined with CloudSat data products to study the vertical structure of the MCSs at various MCS life stages: developing, mature, and dissipating.The distribution of MCSs over Indonesia has a seasonal variation and distinct diurnal cycle. The life stages of the observed MCSs are characterized by distinct cloud microphysics at each stage. In the developing stage, the upper level of the MCS raining region shows the presence of precipitating ice particles. As the MCS progresses to the mature stage, the proportion of the raining area becomes small and the intensity of rain is reduced, accompanied by increasing occurrence of small-sized ice particles at the upper level. In the dissipating stage, large hydrometeors no longer exist at the upper part of the raining region. Within the MCS anvils, the dissipating stage shows a more uniform distribution of ice-particle effective radius compared to that shown by the developing and mature stages.MCS characteristics over the land and ocean differ on the basis of the minimum brightness temperature, the equivalent radius, the maximum rain rate, and the rain fraction that varies along the MCS evolution.
27Two case studies of Mesoscale Convective System (MCS) in Indonesian region were 28 conducted by applying an improved GTG tracking algorithm and ICAS algorithm to Himawari-8 29 AHI infrared data. The first case over Java Island showed a land-originating MCS in the boreal 30 winter, which coincided with a wet phase of Madden-Julian Oscillation (MJO) over the Maritime 31Continent. The second case showed the evolution of MCS under the influence of a strong vertical 32 wind shear during the boreal summer. The cloud top height (CTH) of deep convective part in the 33 first case was larger than that in the second case, while the temporal evolution of CTH was similar 34 between two cases. For the anvil part, the median CTH of the second case was relatively stable at 35 around 13 km, while that of the first case showed a considerable temporal variation ranging from 14 36 to 16 km. The cloud-particle effective radius (CER) of anvil increased after the period of maximum 37 deep convective CTH in both cases, although the CER was slightly larger in the second case than in 38 the first case. These differences in cloud properties between two cases were attributable to the 39 background wind profiles.
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