Education

• Postdoctoral Research Associate, University of Oklahoma, USA (2011 – 2014)
• Ph.D. in Atmospheric Science, IIT Kharagpur (2006- 2010)
• M.Sc. in Meteorology, Cochin University of Science and Technology (2003-2005)

Course Offered

• Atmospheric Thermodynamics
• Planetary Atmospheres
• Boundary Layer Meteorology

Research Work / Area

• Atmospheric Modelling
• Data Assimilation 
• Predictability of Weather 
• Ensemble methods 

Area of Interest

Improving the understanding of the predictability of extreme weather events  through data assimilation and ensemble approaches

Recent Publications

• George, B., Babu, F., & Kutty, G. (2025). Identifying optimal observation locations for improved Indian summer monsoon forecasts using ensemble sensitivity analysis. Meteorology and Atmospheric Physics, 137(4), 1-11.https://doi.org/10.1007/s00703-025-01083-x
• Rath, S., Kesarkar, A., Patnaik, Bhate.J & Kutty G.  (2025). Infrared heating/cooling-induced perturbation in vertical velocity inside stratiform clouds. J Earth Syst Sci 134, 29 . https://doi.org/10.1007/s12040-024-02486-x
• Gogoi, D., Rao, T. N., Satheeshkumar, S., & Kutty, G. (2025). Impact of improved air quality during complete and partial lockdowns on surface energetics and atmospheric boundary layer. Science of The Total Environment, 973, 179078.
• Amal, K. K., Viswanadhapalli, Y., Meka, R., & Kutty, G. (2024). Long-term climate characteristics of sea breeze phenomena over Sriharikota using met-tower observations and ERA-5 reanalysis dataset. Theoretical and Applied Climatology, 1-19. https://doi.org/10.1007/s00704-024-05211-2
• Hari, M., Kutty, G., & Tyagi, B. (2024). Integrating multi-source datasets in exploring the covariation of gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) at an Indian tropical forest flux site. Environmental Earth Sciences, 83(8), 232.
• Pushpalatha, R., Roshni, T., Gangadharan, B., & Kutty, G. (2024). Computer-Aided Crop Yield Forecasting Techniques-Systematic Review Highlighting the Application of AI. Environmental Modeling & Assessment, 1-16.
• Munsi, A., Kesarkar, A.P., Bhate, J.N., Kutty, G. et al., (2023) Atmosphere-upper-ocean interactions during three rare cases of rapidly intensified tropical cyclones over North Indian Oceans. J Oceanogr. https://doi.org/10.1007/s10872-022-00664-3
• Munsi, A., Kesarkar, A. P., Bhate, J. N., VPM, V. R., & Kutty, G. (2023). Helicity evolution during the life cycle of tropical cyclones formed over the north Indian ocean. Advances in Space Research:https://doi.org/10.1016/j.asr.2022.10.004
• Chawang, N., and Kutty, G. (2022). Ensemble-based forecast sensitivity approach to estimate the impact of satellite-derived atmospheric motion vectors in a limited area model.  J Earth Syst Sci 131, (254). https://doi.org/10.1007/s12040-022-02000-1
• Munsi, A., Kesarkar, A., Bhate, J., Singh, K., Panchal, A., Kutty, G., & Giri, R. (2022). Simulated dynamics and thermodynamics processes leading to the rapid intensification of rare tropical cyclones over the North Indian Oceans. Journal of Earth System Science, 131(4), 1-26.
• George, B., & Kutty, G. (2022). Sensitivity analysis applied to two extreme rainfall events over Kerala using TIGGE ensembles. Meteorology and Atmospheric Physics, 134(2), 1-14.
• George, B., & Kutty, G. (2022). Multivariate ensemble sensitivity analysis applied for an extreme rainfall over Indian subcontinent. Atmospheric Research, 106324.
• Rakesh S and Kutty G., (2021) Intercomparison of the Performance of Four Data Assimilation Schemes in a Limited-Area Model on Forecasts of an Extreme Rainfall Event over the Uttarakhand in the Himalayas, Earth and Space Science, AGU  https://doi.org/10.1029/2020EA001461
• Munsi, A., Kesarkar, A., Bhate, J., Panchal, A., Singh, K., Kutty, G., & Giri, R. (2021). Rapidly intensified, long duration North Indian Ocean tropical cyclones: Mesoscale downscaling and validation. Atmospheric Research, 259, 105678.
• Gogoi, R. B., Kutty, G., & Boroghain, A. (2021). Intercomparison of the impact of INSAT-3D atmospheric motion vectors in 3DVAR and hybrid ensemble-3DVAR data assimilation systems during Indian summer monsoon. Theoretical and Applied Climatology, 1-12.
• Gogoi, R. B., Kutty, G., & Borgohain, A. (2021). Impact of INSAT-3D satellite-derived wind in 3DVAR and hybrid ensemble-3DVAR data assimilation systems in the simulation of tropical cyclones over the Bay of Bengal. Modeling Earth Systems and Environment, 1-11.
• Pushpalatha, R., Shiny, R., Kutty, G. et al. (2021) Testing of Cassava (Manihot esculenta) Varieties for Climate Resilience Under Kerala (India) Conditions.  Agricultural Research https://doi.org/10.1007/s40003-021-00547-x
• Bhate, J., Munsi, A., Kesarkar, A., Kutty, G., & Deb, S. K. (2021) Impact of assimilation of satellite retrieved ocean surface winds on the tropical cyclone simulations over the north Indian Ocean. Earth and Space Science, e2020EA001517.https://doi.org/10.1029/2020EA001517
• George, B., & Kutty, G. (2021). Ensemble Sensitivity Analysis of an Extreme Rainfall Event over the Himalayas in June 2013. Dynamics of Atmospheres and Oceans, 101202.
• Kutty, G., Gogoi, R., Rakesh, V., & Pateria, M. (2020). Comparison of the performance of HYBRID ETKF-3DVAR and 3DVAR data assimilation scheme on the forecast of tropical cyclones formed over the Bay of Bengal. Journal of Earth System Science, 129(1), 1-14.
• Gogoi, R. B., Kutty, G., Rakesh, V., & Borogain, A. (2020). Comparison of the Performance of Hybrid ETKF-3DVAR and 3DVAR Data Assimilation Systems on Short-Range Forecasts during Indian Summer Monsoon Season in a Limited-Area Model. Pure and Applied Geophysics, 1-20.
• KU, J., Kutty, G., & George, B. On the Predictability and Dynamics of Tropical Cyclone: Nargis (2020). Journal of Geophysical Research: Atmospheres, e2019JD032040.
• Mounika, K., Kutty, G., & Gorthi, S. S. R. (2018). Consistent Robust and Recursive Estimation of Atmospheric Motion Vectors From Satellite Images. IEEE Transactions on Geoscience and Remote Sensing, 57(3), 1538-1544.
• Kutty, G., Muraleedharan, R., & Kesarkar, A. P. (2018). Impact of Representing Model Error in a Hybrid Ensemble-Variational Data Assimilation System for Track Forecast of Tropical Cyclones over the Bay of Bengal. Pure and Applied Geophysics, 175(3), 1155-1167.
• Kutty, G., Sandeep, S., & Nhaloor, S. (2018). Sensitivity of convective precipitation to soil moisture and vegetation during break spell of Indian summer monsoon. Theoretical and Applied Climatology, 133(3-4), 957-972
• Kutty, G., & Gohil, K. (2017). The role of mid-level vortex in the intensification and weakening of tropical cyclones. Journal of Earth System Science, 126(7), 94.
• Kutty, G., & Wang, X. (2015). A comparison of the impacts of radiosonde and AMSU radiance observations in GSI based 3DEnsVar and 3DVar data assimilation systems for NCEP GFS. Advances in Meteorology, 2015.
• Kutty G & Chandrasekar, A. (2011). Impact of assimilation of ATOVS temperature and humidity and SSM/I total precipitable water on the simulation of a monsoon depression. Natural hazards, 59(3), 1647-1669
• Kutty. G, Chandrasekar, A., & Pradhan, D. (2010). Impact of 3DVAR assimilation of Doppler Weather Radar wind data and IMD observation for the prediction of a tropical cyclone. International Journal of Remote Sensing, 31(24), 6327-6345.
• Kutty. G., & Chandrasekar, A. (2010). Effect of 3DVAR assimilation of MODIS temperature and humidity profiles on the dynamic and thermodynamic features of three monsoon depressions over the Bay of Bengal. Meteorology and Atmospheric Physics, 107(1-2), 65-79.

Book Chapter:

• Chandrasekar, A. and Kutty G, 2013. Studies on the impacts of 3DVAR assimilation of satellite observations on the simulation of monsoon depressions over India, Springer;ISBN 978-3-642-35087-0 ( pp 643-705)

• 2024 (Odd Semester)
• 2023 (Odd Semester)
• 2023 (Even Semester)
• 2022 (Odd Semester)
• 2022 (Even Semester)
• 2021 (Odd Semester)
• 2021 (Even Semester)
• 2020 (Odd Semester)
• 2020 (Even Semester)
• 2019 (Odd Semester)

On the Cumulative Effect of Precipitation Assimilation and Microphysics Scheme Complexity on Afternoon Convective Events 

 The study examines the impact of precipitation assimilation using the 4DVAR approach on the forecasting of convective afternoon rainfall events, with a focus on the complexity of microphysics schemes. A new criterion has been developed to address the “zero rain” issue associated with precipitation assimilation. The analysis reveals that when precipitation is assimilated, microphysics schemes incorporating graupel enhance hydrometeor activity in the upper levels, which, in turn, suppresses rainfall intensity and spatial distribution, thereby degrading the forecast accuracy for convective rain. These findings underscore the significance of employing appropriate microphysics schemes for effective precipitation assimilation.