Manajit Sengupta received his B.Sc. with Honors in Physics from Calcutta University and his Ph.D. in Meteorology (2002) from The Pennsylvania State University. He is interested in understanding the transfer of radiation in clouds using both satellite and ground based remote sensing. He is also interested in 4-dimensional variational (4d-Var) data assimilation and works on assimilation of satellite radiances in cloudy atmospheres to improve prediction of clouds in the mesoscale. Additionally Dr. Sengupta is interested in developing techniques to create synthetic imagery of severe weather events and fires that are used to develop remote sensing algorithms for future satellites. Dr. Sengupta worked at the US DOE Pacific Northwest National Laboratory before joining CIRA as a Research Scientist in 2003. His work involved understanding the radiative properties of stratus clouds and how they influence solar radiation reaching the surface. He also resolved a decades old problem involving anomalous absorption in clouds. Since 2003 he has worked on directly assimilating GOES satellite radiances in cloudy atmospheres using the Regional Atmospheric Modeling Data Assimilation System (RAMDAS) to improve cloud prediction in the mesoscale. He has also worked on creating high quality synthetic imagery for hurricanes, thunderstorms and fires for the GOES-R Advanced Baseline Instrument (GOES-R ABI). The synthetic imagery is used by NOAA’s GOES-R Algorithm Working Group (AWG) for creating new algorithms to be used when GOES-R ABI launches in 2014. Dr. Sengupta is a member of the GOES-R AWG.

Grasso, L., M. Sengupta, J. F. Dostalek, R. Brummer and M. DeMaria, 2008: Synthetic satellite imagery for current and future environmental satellites. Int. J. Remote Sensing accepted for publication.