Ms. John Jinya Profile

John Jinya

at Space Applications Ctr

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Publications (2)

Proceedings Article | 9 May 2016 Paper

Remote measurement of cloud microphysics and its influence in predicting high impact weather events

Paul Bipasha, John Jinya

Proceedings Volume 9876, 98760Q (2016) https://doi.org/10.1117/12.2223373

KEYWORDS: Clouds, Particles, Sensors, Imaging systems, Climatology, LIDAR, Satellites, MODIS, Short wave infrared radiation, Inverse optics

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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.

Proceedings Article | 5 May 2016 Paper

Retrieval of cloud microphysical parameters from INSAT-3D: a feasibility study using radiative transfer simulations

John Jinya, Paul Bipasha

Proceedings Volume 9876, 98760E (2016) https://doi.org/10.1117/12.2222779

KEYWORDS: Clouds, Radiative transfer, Short wave infrared radiation, Atmospheric modeling, Imaging systems, Thermodynamics, Infrared imaging, Infrared radiation, Inverse optics, Particles, Visible radiation, Reflectivity

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