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

Research Work / Area

• Data Assimilation and Predictability
• Ensemble methods
• Tropical Cyclone modelling
• Extreme Weather events modelling 
• Planetary Atmospheres

Area of Interest

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

Recent Publications

• Munsi, A., Kesarkar, A.P., Bhate, J.N., Kutty, G. et al., (2022) 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
• 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. P., Bhate, J. N., VPM, V. R., & Kutty, G. (2022). 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
• 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)

• 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)

A probabilistic method has been developed to identify regions of Initial Condition uncertainty in the NWP model

Forecast errors can be reduced if observations are assimilated in regions with the largest percentage of analysis error growth. In our recent study, the regions where additional observations will impact the forecasts over the Indian subcontinent during the summer monsoon season have been identified using the ensemble approach.

You may read the details here: https://assets.researchsquare.com/files/rs-2893417/v1/74e2a094-565d-41f1-b004-08d742468068.pdf?c=1683814947