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Subimal Ghosh
 
Publications
 

Patents

 

  1. Ghosh, S and Roy A (2019), Method and electronic device for irrigation water management [Indian Patent Filed, Application no: E-137/5285/2019/MUM]

  2. Ghosh, S, Tripathy, S and Karmakar S (2020), Method for real time forecasting of Flood Risk considering Hazard, Exposure and Vulnerability [Indian Patent Filed, Application no: 202021000003]

  3. Unnithan, K, Biswal, B, Rudiger C and Ghosh S (2023), Method and System for Generating Flood Inundation Forecasts for Large Geographical Areas [Indian Patent Filed, Application no.: 202321007807]

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Edited Volume

  1. Climate Change Signals and Response: A Strategic Knowledge Compendium for India (2018), Ed by Venkataran, C., Mishra, T, Ghosh, S and Karmakar, S. (Pub: Springer, In Press)

 

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Book Chapters:

  1. Pathak, A, Paul, S, and Ghosh S (2018), Land-Surface Feedback and Impacts of Land-Use Change to Indian Monsoon Rainfall. In Climate Change Signals and Response: A Strategic Knowledge Compendium for India, Springer.

  2. Shastri H and Ghosh, S (2018), Urbanization and Surface Heat island Intensity, In Climate Change Signals and Response: A Strategic Knowledge Compendium for India, Springer.

  3. Murari K and Ghosh S (2018), Future Heat Wave Projections and Impacts. In Climate Change Signals and Response: A Strategic Knowledge Compendium for India, Springer.

  4. Niyogi, D., Subramanian, S., Mohanty, U.C., Kishtawal, C.M., Ghosh, S., Nair, U.S., Ek, M. and Rajeevan, M. (2018) The Impact of Land Cover and Land Use Change on the Indian Monsoon Region Hydroclimate. In Land-Atmospheric Research Applications in South and Southeast Asia (pp. 553-575). Springer.

  5. Saha, A., Shashikanth, K and Ghosh S (2018), Changing Monsoon Behaviour with the Evaluation of CMIP5 Climate Models, Sustainable Holistic Water Resources Management in a Changing Climate (Pub: Jain Brothers)

  6. Mujumdar, P., P., and S. Ghosh (2008), Fuzzy Logic Based Approaches in Water Resources Systems Modeling, Practical Hydroinformatics, (Eds) R.J. Abrahart, Linda See and D. P. Solomatine, Water Science and Technology Library (Pub : Springer) ISBN : 978-3-540-79980-4, pp. 165-176.

  7. Raje, D., Ghosh, S. and Mujumdar, P. P. (2012) Hydrologic impacts of climate change: Quantification of Uncertainties, Climate Change Modeling Mitigation and Adaptation,  (Eds)  Rao  Y.  Surampalli,  Tian  C.  Zhang,  C.  S.   P.   Ojha,   B. Gurjar, R.D.Tyagi and C.M.Kao, (Pub : American Soc. Civil Engrs (ASCE)) (http://ascelibrary.org/doi/abs/10.1061/9780784412718)

 

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Journals:

  1. Ghosh, M., Ghosh, S. and Karmakar, S., 2024. Assessment of socio-economic strategies for managing regional flood risk in an urban coastal catchment. Urban Climate, 58, p.102142. https://doi.org/10.1016/j.uclim.2024.102142 

  2. Verma, A. and Ghosh, S., 2024. Unveiling the role of past vapor pressure deficit through soil moisture in driving tropical vegetation productivity. Environmental Research Letters, 19(10), p.104040.

  3. Jha, R., Mondal, A., Ghosh, S., & Murtugudde, R. (2024). Northward shift of pre-monsoon zonal winds exacerbating heatwaves over India. Geophysical Research Letters, 51, e2024GL110486. https://doi.org/10.1029/2024GL110486

  4. Verma A, and Ghosh, S (2024), Improved Water Use Efficiency of Vegetation due to Carbon Fertilization Not Translating to Increased Soil Moisture in India, Journal of Hydrology, doi:  10.1016/j.jhydrol.2024.131890.

  5. Chandel, V.S., Bhatia, U., Ganguly, A.R. and Ghosh, S., 2024. State-of-the-art bias correction of climate models misrepresent climate science and misinform adaptation. Environmental Research Letters, https://doi.org/10.1088/1748-9326/ad6d82

  6. Goswami, S., Ternikar, C.R., Kandala, R., Pillai, N.S., Yadav, V.K., Joseph, J., Ghosh, S. and Vishwakarma, B.D., 2024. Water budget-based evapotranspiration product captures natural and human-caused variability. Environmental Research Letters, 19(9), p.094034.

  7. Ghosh, M., Ghosh, S. and Karmakar, S., 2024. Assessment of flood risk in a coastal city considering multiple socio-economic vulnerability scenarios. Proceedings of IAHS, 386, pp.299-306.

  8. Gupta, M., Murtugudde, R. and Ghosh, S., 2024. Simulating urban surface energy balance of an academic campus and surroundings in Mumbai, India. Urban Climate, 56, p.102044.

  9. Shilin, A., Ghosh, S. and Karmakar, S., 2024. Flipping of temperature and precipitation trends over the Indian subcontinent due to diametrically opposing influence of GHGs and aerosols. Environmental Research Letters, 19(6), p.064045.

  10. Anoop S, Ramana, MV, Karmakar S, and Ghosh, S (2024), Evaluating Pulse-reserve Characteristics of Soil-plant Continuum in India using Remote Sensing, Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2024.130913.

  11. Tripathy, S.S., Chaudhuri, S., Murtugudde, R., Mhatre, V., Parmar, D., Pinto, M., Zope, P.E., Dixit, V., Karmakar, S. and Ghosh, S., 2024. Analysis of Mumbai floods in recent years with crowdsourced data. Urban Climate, 53, p.101815.

  12. Varghese, S. J., Surendran, S., Rajendran, K., Ghosh, S., Kitoh, A., & Ashok, K. (2024). Precipitation scaling in extreme rainfall events and the implications for future Indian monsoon: Analysis of high-resolution global climate model simulations. Geophysical Research Letters, 51, e2023GL105680. https://doi.org/10.1029/2023GL105680

  13. Tantary, D., Tangirala, A.K., Murthugudde, R., Ghosh, S., Kumar, R. and Bhatia, U., (2023) Geographical trapping of synchronous extremes amidst increasing variability of Indian Summer Monsoon Rainfall. Geophysical Research Letters, 50(22), p.e2023GL104788. https://doi.org/10.1029/2023GL104788

  14. Chauhan, T., Chandel, V. and Ghosh, S., (2024), Global land drought hubs confounded by teleconnection hotspots in equatorial oceans. npj Climate and Atmospheric Science, 7(1), p.15.

  15. Das, R., Chaturvedi, R.K., Roy, A., Karmakar, S. and Ghosh, S., (2023). Warming inhibits increases in vegetation net primary productivity despite greening in India. Scientific Reports, 13(1), p.21309., https://doi.org/10.1038/s41598-023-48614-3

  16. Khadke, L., Mukherjee, S., Kumar, K. and Ghosh, S., (2023). Hydrometeorological factors affecting the carbon exchange of the Himalayan pine-dominated ecosystem. Ecological Informatics, https://doi.org/10.1016/j.ecoinf.2023.102446

  17. Ghosh, M., Shastri, H., Ghosh, S., & Karmakar, S. (2023). A novel response priority framework for an urban coastal catchment using global weather forecasts-based improved flood risk estimates. Journal of Geophysical Research: Atmospheres, 128, e2023JD038876. https://doi.org/10.1029/2023JD038876

  18. Chauhan, T, Devanand, A, Roxy, M K., Karumuri, A and Ghosh, S (2023), River interlinking alters land-atmosphere feedback and changes the Indian summer monsoon, Nature Communications, DOI : 10.1038/s41467-023-41668-x

  19. Chakraborti, R, Davis, K F., DeFries R, Rao, N D, Joseph, J and Ghosh, S (2023), Crop switching for water sustainability in India’s food bowl yields co-benefits for food security, and farmers’ profits, Nature Water, , DOI : 10.1038/s44221-023-00135-z  .

  20. Gupta M, Wild, M, and Ghosh, S (2023), Analytical framework based on thermodynamics to estimate spatially distributed surface energy fluxes from remotely sensed radiations, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2023.113659

  21. Dubey, N. and Ghosh, S. (2023), CO2 fertilization enhances vegetation productivity and reduces ecological drought in India, Environmental Research Letters, 18, 064025, DOI 10.1088/1748-9326/acd5e7

  22. Dubey, N. and Ghosh, S. (2023), The relative role of soil moisture and vapor pressure deficit in affecting the Indian vegetation productivity, Environmental Research Letters, https://doi.org/10.1088/1748-9326/acd2ef

  23. Ashfaq, M., Johnson, N., Kucharski, F., Diffenbaugh, N.S., Abid, M.A., Horan, M.F., Singh, D., Mahajan, S., Ghosh, S., Ganguly, A.R. and Evans, K.J., (2023) The influence of natural variability on extreme monsoons in Pakistan, npj Climate and Atmospheric Science (In Press).

  24. DeFries, R., Liang, S., Chhatre, A., Davis, K, F, Ghosh, S, Rao, D, N, and Singh, D(2023) Climate resilience of dry season cereals in India. Sci Rep 13, 9960 (2023). https://doi.org/10.1038/s41598-023-37109-w

  25. Srivastava, A., Rao, S. A., & Ghosh, S. (2023). Improving the subseasonal variability of the Indian summer monsoon in a climate model. International Journal of Climatology, https://doi.org/10.1002/joc.8142

  26. Sahastrabuddhe, R., Ghausi, S A, Joseph J and Ghosh S (2023), Indian Summer Monsoon Rainfall in a changing climate: a review, Journal of Water and Climate Change,   14(4), 1061, doi:10.2166/wcc.2023.127

  27. Battula S B, Siems, S., Mondal, A and Ghosh, S (2023), Aerosol-heavy precipitation relationship within monsoonal regimes in the Western Himalayas, Atmospheric Research, Volume 288, 106728, ISSN 0169-8095, https://doi.org/10.1016/j.atmosres.2023.106728

  28. Roy, A., Murtugudde, R., Sahai, A.K., Narvekar, P., and Ghosh, S., (2023) Remote sensing and climate services improve irrigation water management at farm scale in Western-Central India, Science of The Total Environment, 163003, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2023.163003

  29. Sebastian, D.E., Murtugudde, R. & Ghosh, S. (2023) Soil–vegetation moisture capacitor maintains dry season vegetation productivity over India. Sci Rep 13, 888. https://doi.org/10.1038/s41598-022-27277-6  

  30. Joseph, J., & Ghosh, S. (2023). Representing Indian agricultural practices and paddy cultivation in the Variable Infiltration Capacity model. Water Resources Research, 59, e2022WR033612. https://doi.org/10.1029/2022WR033612  

  31. Joseph, J., Scheidegger, J.M., Jackson, C.R., Barik, B. and Ghosh, S., (2022) Is flood to drip irrigation a solution to groundwater depletion in the Indo-Gangetic plain?. Environmental Research Letters, 17(10), p.104002.

  32. Vittal H., Ghosh S., Zhang, W and Kumar, R, (2022). Strong influence of north Pacific Ocean variability on Indian summer heatwaves Nature communications, 13, 5349 (2022). https://doi.org/10.1038/s41467-022-32942-5

  33. Deroliya, P., Ghosh, M., Mohanty, M.P., Ghosh, S., Rao, K.D. and Karmakar, S., (2022). A novel flood risk mapping approach with machine learning considering geomorphic and socio-economic vulnerability dimensions. Science of The Total Environment, p.158002.

  34. Ghausi, S.A., Ghosh, S. and Kleidon, A., (2022). Break in precipitation–temperature scaling over India predominantly explained by cloud-driven cooling. Hydrology and Earth System Sciences, 26, 4431–4446, https://doi.org/10.5194/hess-26-4431-2022

  35. Roy, A., Murtugudde, R., Sahai, A.K., Narvekar, P., Shinde, V. and Ghosh, S., (2022). Water Savings with Irrigation Water Management at Multi-week Lead Time Using Extended Range Predictions. Climate Services, 27, p.100320.

  36. Jha, R., Mondal, A., Devanand, A., Roxy, M.K. and Ghosh, S. (2022), Limited influence of irrigation on pre-monsoon heat stress in the Indo-Gangetic Plain. Nature communications, 13(1), pp.1-10.

  37. Verma, A., Chandel, V. and Ghosh, S. (2022), Climate drivers of the variations of vegetation productivity in India. Environmental Research Letters, 17(8), p.084023.

  38. Ashfaq, M., Mehmood, S., Kapnick, S., Ghosh, S., Adnan Abid,M, Kucharski, F., Batibeniz, F., Saha, A., Evans, K. and Huang-Hsiung H. (2022), Dominant controls of cold-season precipitation variability over the high mountains of Asia, npj Climate and Atmospheric Science 5, 65 (2022). https://doi.org/10.1038/s41612-022-00282-2

  39. Srivastava, A., Anguluri, S.R. and Ghosh, S. (2022), Impact of riverine freshwater on Indian Summer Monsoon: Coupling a runoff routing model to a global seasonal forecast model. Frontiers in Climate,  https://doi.org/10.3389/fclim.2022.902586

  40. Nair, A.S., Verma, K., Karmakar, S., Ghosh, S. and Indu, J.  (2021) Exploring the potential of SWOT mission for reservoir monitoring in Mahanadi basin. Advances in Space Research. https://doi.org/10.1016/j.asr.2021.11.019

  41. Tripathy, S.S., Karmakar, S. and Ghosh, S., (2021) Hazard at weather scale for extreme rainfall forecast reduces uncertainty. Water Security, 14, p.100106.

  42. Singh, J., Ghosh, S., Simonovic, S. P., & Karmakar, S. (2021). Identification of flood seasonality and drivers across Canada. Hydrological Processes, 35( 10), e14398. https://doi.org/10.1002/hyp.14398

  43. Sahastrabuddhe, R. and Ghosh, S., 2021. Does statistical model perform at par with computationally expensive General Circulation Model for decadal prediction?. Environmental Research Letters.,  16 064028, https://doi.org/10.1088/1748-9326/abfeed

  44. Budakoti, S., Chauhan, T., Murtugudde, R., Karmakar, S., & Ghosh, S. (2021). Feedback from Vegetation to Interannual variations of Indian Summer Monsoon Rainfall. Water Resources Research, 57,  e2020WR028750.  https://doi.org/10.1029/2020WR028750

  45. Roy,  A.,  Narvekrar, P., Murtugudde R, Shindhe, V and Ghosh S (2021), Short and Medium Range Irrigation Scheduling using Stochastic Simulation-Optimization Framework with farm-scale Ecohydrological Model and Weather Forecasts, Water Resources Research, 57, e2020WR029004. https://doi.org/10.1029/2020WR029004

  46. Thuruvengadam, P,  Indu, J and Ghosh S (2021),  Radar reflectivity and radial velocity assimilation in a Hybrid ETKF-3DVAR System for Prediction of a Heavy Convective Rainfall, Quarterly Journal of Royal Meteorological Society, https://doi.org/10.1002/qj.4021.

  47. Tripathi S, Bhatia U, Mohanty M, Karmakar S and Ghosh S (2021), Flood evacuation during pandemic: a multi-objective framework to handle compound hazard. Environmental Research Letters,  https://doi.org/10.1088/1748-9326/abda70

  48. Chandel, V. S., & Ghosh, S. (2021) Components of Himalayan River Flows in a Changing Climate. Water Resources Research, 57, e2020WR027589. https://doi.org/10.1029/2020WR027589

  49. Gupta, M., Chauhan, T., Murtugudde, R., and Ghosh, S. (2020). Pollutants control the process networks of urban environmental-meteorology. Environ. Res. Lett. Available at: http://iopscience.iop.org/article/10.1088/1748-9326/abce28

  50. Gusain, A., Ghosh, S. and Karmakar, S., 2020. Added value of CMIP6 over CMIP5 models in simulating Indian summer monsoon rainfall. Atmospheric Research, 232, p.104680.

  51. Tripathy, S.S., Vittal, H., Karmakar, S. and Ghosh, S., 2020. Flood risk forecasting at weather to medium range incorporating weather model, topography, socio-economic information and land use exposure. Advances in Water Resources, 146, p.103785.

  52. Mohanty, M.P., Nithya, S., Nair, A.S., Indu, J., Ghosh, S., Bhatt, C.M., Rao, G.S. and Karmakar, S., 2020. Sensitivity of various topographic data in flood management: Implications on inundation mapping over large data-scarce regions. Journal of Hydrology, p.125523.

  53. Raghav, P., Borkotoky, S.S., Joseph, J., Chattopadhyay, R., Sahai, A.K. and Ghosh, S., 2020. Revamping extended range forecast of Indian summer monsoon. Climate Dynamics, https://doi.org/10.1007/s00382-020-05454-5

  54. Chauhan, T. and Ghosh, S 2020, Partitioning of Memory and Real-time Connections between Variables in Himalayan Ecohydrological Process Networks, Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2020.125434

  55. Ghausi, S. A., & Ghosh, S. (2020). Diametrically Opposite Scaling of Extreme Precipitation and Streamflow to Temperature in South and Central Asia. Geophysical Research Letters, 47, e2020GL089386. https://doi.org/10.1029/2020GL089386

  56. Singh, R., Mishra, V., Narasimhan, B., Ghosh, S., Sharma, A., Dutta, S. and Mujumdar, P., 2020, March. Hydrological Modeling in India. In Proc Indian Natn Sci Acad (Vol. 86, No. 1, pp. 479-494).

  57. Rehana, S., Rajulapati, C.R., Ghosh, S., Karmakar, S. and Mujumdar, P., 2020. Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India. Water, 12(6), p.1793.

  58. Sinha, R.K., Eldho, T.I. and Subimal, G., 2020. Assessing the impacts of land cover and climate on runoff and sediment yield of a river basin. Hydrological Sciences Journal, https://doi.org/10.1080/02626667.2020.1791336

  59. Chug, D., Pathak, A., Indu, J., Jain, S.K., Jain, S.K., Dimri, A.P., Niyogi, D. and Ghosh, S., Observed Evidence for Steep Rise in the Extreme Flow of Western Himalayan Rivers. Geophysical Research Letters, p.e2020GL087815.

  60. Thiruvengadam, P., Indu, J. and Ghosh, S., 2020. Significance of 4DVAR Radar Data Assimilation in Weather Research and Forecast Model‐Based Nowcasting System. Journal of Geophysical Research: Atmospheres, 125(11), p.e2019JD031369.

  61. Saha, A., Joseph, J. and Ghosh, S., 2020. Climate controls on the terrestrial water balance: Influence of aridity on the basin characteristics parameter in the Budyko framework. Science of The Total Environment, p.139863.

  62. Zachariah, M., Mondal, A., Das, M., AchutaRao, K.M. and Ghosh, S., 2020. On the role of rainfall deficits and cropping choices in loss of agricultural yield in Marathwada, India. Environmental Research Letters, https://doi.org/10.1088/1748-9326/ab93fc

  63. Saha, A. and Ghosh, S., 2020. Relative Impacts of Projected Climate and Land Use Changes on Terrestrial Water Balance: A Case Study on Ganga River Basin. Frontiers in Water, 2, p.12.

  64. Thiruvengadam, P., Indu, J. and Ghosh, S., 2020. Improving Convective Precipitation Forecasts Using Ensemble‐Based Background Error Covariance in 3DVAR Radar Assimilation System. Earth and Space Science, 7(4), p.e2019EA000667.

  65. Singh, J, Karmakar, S,  Paimazumder, D, Ghosh, S and  Niyogi, D, 2020, Urbanization alters rainfall extremes over the contiguous United States, Environmental Research Letters, https://doi.org/10.1088/1748-9326/ab8980

  66. Gusain, A., Mohanty, M.P., Ghosh, S., Chatterjee, C. and Karmakar, S., 2020. Capturing transformation of flood hazard over a large River Basin under changing climate using a top-down approach. Science of The Total Environment, 726, 138600. https://doi.org/10.1016/j.scitotenv.2020.138600

  67. Mohanty, M.P., Sherly, M.A., Ghosh, S. and Karmakar, S., 2020. Tide-Rainfall Flood Quotient: An incisive measure of comprehending a region’s response to storm- tide          and pluvial     flooding. Environmental          Research        Letters, https://doi.org/10.1088/1748-9326/ab8092.

  68. Patel, P., Karmakar, S., Ghosh, S. and Niyogi, D., 2020. Improved simulation of very heavy rainfall events by incorporating WUDAPT urban land use/land cover in WRF. Urban Climate, 32, p.100616.

  69. Chun K P, He Q, Fok, H S, Ghosh, S, Yetemen, O, Chen, Q, Mijic, A (2020), Gravimetry-based water storage shifting over the China-India border area controlled by regional climate variability, Science of Total Environment, 714, 136360, https://doi.org/10.1016/j.scitotenv.2019.136360

  70. Ghosh, S. et al., (2019). Development of India’s first integrated expert urban flood forecasting system for Chennai. Current Science, 117(5), pp.741-745.

  71. Sharma T, Vittal, H, Karmkar S and Ghosh S (2019), Increasing agricultural risk to      hydro-climatic      extremes      in      India,       Environmental       Research Letters,    https://doi.org/10.1088/1748-9326/ab63e1

  72. Vittal H, Karmakar S, Ghosh, S and Murtugudde R (2019), A comprehensive India-wide social vulnerability analysis: highlighting its influence on hydro-climatic risk, Environmental Research Letters, https://doi.org/10.1088/1748-9326/ab6499

  73. Sebastian, D.E., Ganguly, S., Krishnaswamy, J., Duffy, K., Nemani, R.  and Ghosh, S., 2019. Multi-Scale Association between Vegetation Growth and Climate in India: A Wavelet Analysis Approach. Remote Sensing, 11(22), p.2703.

  74. Mohanty, M.P., Vittal, H., Yadav, V., Ghosh, S., Rao, G.S. and Karmakar, S., 2020. A new bivariate risk classifier for flood management considering hazard and socio-economic dimensions. Journal of Environmental Management, 255, p.109733.

  75. Salvi, K. and Ghosh, S., (2019). A kaleidoscopic research memoir on Indian summer monsoon rainfall. MAUSAM, 70(2), pp.293-298.

  76. Saha, A. and Ghosh, S., (2019). Can the weakening of Indian Monsoon be attributed to anthropogenic aerosols?. Environmental Research Communications, 1(6), p.061006.

  77. Patel, P., Ghosh, S., Kaginalkar, A., Islam, S. and Karmakar, S., (2019). Performance evaluation of WRF for extreme flood forecasts in a coastal urban environment. Atmospheric Research, 223, pp.39-48.

  78. Devanand A, Huang, M. Moetasim, A, Barik, B and Ghosh S. (2019), Choice of Irrigation Water Management Practice affects Indian Summer Monsoon Rainfall and its Extremes,           Geophysical Research                     Letters,                  46, 9126- 9135. https://doi.org/10.1029/2019GL083875

  79. Jayasankar, T., Eldho, T.I., Ghosh, S. and Murtugudde, R. (2019) Assessment of the interannual variability of local atmospheric and ITF contribution to the subsurface heat content of southern tropical Indian Ocean in GECCO2 and ORAS4 using ROMS, Global and Planetary Change, https://doi.org/10.1016/j.gloplacha.2019.05.014

  80. Patel, P, Ghosh, S., Kaginalkar, A, Islam, S. and Karmakar, S (2019) Performance evaluation of WRF for extreme flood forecasts in a coastal urban environment, Atmospheric        Research,          223,                39-48,                  ISSN           0169-8095, https://doi.org/10.1016/j.atmosres.2019.03.005.

  81. Sahana A.S., Pathak, A, Roxy, M K and Ghosh S (2019), Understanding the role of moisture transport on the dry bias in Indian monsoon simulations by CFSv2, Climate Dynamics, 52, 637-651 https://doi.org/10.1007/s00382-018-4154-y

  82. Thiruvengadam, P, Indu J and Ghosh, S, 2018. Assimilation of Doppler Weather Radar Data with a Regional WRF-3DVAR System: Impact of Control Variables on Forecasts of a Heavy Rainfall Case, Advances in Water Resources, https://doi.org/10.1016/j.advwatres.2019.02.004

  83. Singh, D, Ghosh, S, Roxy, M K, McDermid S, 2018. Indian Summer Monsoon: Extreme Events, Historical Changes and Role of Anthropogenic Forcings , WIREs Climate Change 2019;e571. https://doi.org/10.1002/wcc.571

  84. Shastri,  H.,  Ghosh,  S.,  Paul,   S., Shafizadeh-Moghadam,   H., Helbich,   M. and Karmakar, S., 2018. Future urban rainfall projections considering the impacts of climate change and urbanization with statistical-dynamical integrated approach. Climate Dynamics, https://doi.org/10.1007/s00382-018-4493-8

  85. Mohanty, M.P., Sherly, M.A., Karmakar, S. and Ghosh, S., 2018. Regionalized Design Rainfall Estimation: an Appraisal of Inundation Mapping for Flood Management Under Data-Scarce Situations. Water Resources Management, Volume 32, Issue 14, pp 4725–4746.

  86. Boyaj, A., Ashok, K., Ghosh, S., Devanand, A. and Dandu, G., 2018. The Chennai extreme rainfall event in 2015: The Bay of Bengal connection. Climate dynamics, 50(7), pp.2867-2879.

  87. Gusain, A., Vittal, H., Kulkarni, S., Ghosh, S. and Karmakar, S., 2018. Role of vertical velocity in improving finer scale statistical downscaling for projection of extreme                precipitation. Theoretical      and                                               Applied          Climatology, https://doi.org/10.1007/s00704-018-2615-1

  88. Joseph, J., Ghosh, S., Pathak, A. and Sahai, A.K., 2018. Hydrologic Impacts of Climate Change: Comparisons between Hydrological Parameter Uncertainty and Climate          Model         Uncertainty. Journal                                          of          Hydrology, DOI: 10.1016/j.jhydrol.2018.08.080 .

  89. Sahana, A. S., & Ghosh, S. (2018). An improved prediction of Indian summer monsoon onset from state-of-the-art dynamic model using physics-guided data-driven approach. Geophysical Research Letters, 45, 8510–8518. https:// doi.org/10.1029/2018GL078319

  90. Sahastrabuddhe, R, Ghosh, S and Murtugudde R (2018), A Minimalistic Seasonal Prediction Model for Indian Monsoon based on Spatial Patterns of Rainfall Anomalies, Climate Dynamics, https://doi.org/10.1007/s00382-018-4349-2 (In Press)

  91. Rastogi, D., Ashfaq, M., Leung, L. R., Ghosh, S., Saha, A., Hodges, K., & Evans, K. (2018). Characteristics of Bay of Bengal monsoon depressions in the 21st century. Geophysical Research Letters, 45. https://doi.org/10.1029/2018GL078756

  92. Patil, N., Venkataraman, C., Muduchuru, K., Ghosh, S. and Mondal, A., (2018). Disentangling sea-surface temperature and anthropogenic aerosol influences on recent trends in South Asian monsoon rainfall. Climate Dynamics, https://doi.org/10.1007/s00382-018-4251-y (In Press).

  93. Paul, S., Ghosh, S., Rajendran, K.,  & Murtugudde, R. (2018). Moisture  supply from the Western Ghats forests to water deficit East Coast of India. Geophysical Research Letters, 45, 4337–4344. https://doi.org/10.1029/2018GL078198

  94. Niroula, S, Halder S and Ghosh, S (2018), Perturbations in the Initial Soil Moisture Conditions: Impacts on Hydrologic Simulation in a Large River Basin, Journal of Hydrology, 561, pp 509-522, https://doi.org/10.1016/j.jhydrol.2018.04.029

  95. Sahana AS, Pathak, A, Roxy, M K and Ghosh S (2018), Understanding the role of moisture transport on the dry bias in Indian monsoon simulations by CFSv2, Climate Dynamics, https://doi.org/10.1007/s00382-018-4154-y (In Press).

  96. Paul, S, Ghosh, S, Mathew M, Devanand A, Karmakar S and Niyodi D (2018), Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization, Scientific Reports (Nature Publishing Group), 8, 3918, https://doi.org/10.1038/s41598-018-22322-9

  97. Devanand, A., Roxy, M. K., & Ghosh, S. (2018). Coupled land‐atmosphere regional model reduces dry bias in Indian summer monsoon rainfall simulated by CFSv2. Geophysical        Research          Letters, 45,                           2476– 2486. https://doi.org/10.1002/2018GL077218

  98. Sharma, T., Vittal, H. , Chhabra, S. , Salvi, K. , Ghosh, S. and Karmakar, S. (2018), Understanding the cascade of GCM and downscaling uncertainties in hydro‐climatic projections over India. Int. J. Climatol, 38: e178-e190. doi:10.1002/joc.5361

  99. Madhusoodhanan, C. G., Shashikanth, K. , Eldho, T. I. and Ghosh, S. (2018), Can statistical downscaling improve consensus among CMIP5 models for Indian summer monsoon rainfall projections?. Int. J. Climatol, 38: 2449-2461. doi:10.1002/joc.5352

  100. Shashikanth, K, Ghosh, S, Vittal, H and Karmakar, S (2017), Future Projections of Indian Summer Monsoon Rainfall Extremes over India with Statistical Downscaling and its Consistency with Observed Characteristics, Climate Dynamics, 51: 1. https://doi.org/10.1007/s00382-017-3604-2

  101. Pathak, A, Ghosh, S, Kumar, P and Murtugudde, R (2017), Role of Oceanic and Terrestrial Atmospheric Moisture Sources in Intraseasonal Variability of  Indian Summer Monsoon Rainfall, Scientific Reports,7, https://doi.org/10.1038/s41598-017- 13115-7

  102. Hossain, F.;  Margaret Srinivasan;  Craig Peterson;  Alice Andral; Ed Beighley; Eric Anderson; Rashied Amini; Charon Birkett; David Bjerklie; Cheryl A. Blain; Selma Cherchali; Cedric H. David; Bradley Doorn; Jorge Escurra; Lee-Lueng Fu; Christopher Frans; John Fulton; Subhrendu Gangopadhay; Subimal Ghosh; Colin Gleason; Marielle Gosset; Jessica Hausman; Gregg Jacobs; John Jones; Yasir Kaheil; Benoit Laignel;      Patrick      Le Moigne;      Li Li;      Fabien Lefevre;      Robert Mason; Amita Mehta; Abhijit Mukherjee; Anthony Nguy-Robertson; Sophie Ricci; Adrien Paris; Tamlin Pavelsky; Nicolas Picot; Guy Schumann; Sudhir Shrestha; Pierre- Yves Le Traon; Eric Trehubenko, (2017) Engaging the User Community for Advancing Societal Applications of the Surface Water Ocean Topography (SWOT) mission, Bulletin of American Meteorological Society, 98(11), pp.ES285-ES290

  103. Roxy M. K., S. Ghosh, A. Pathak, R. Athulya, M. Mujumdar, R. Murtugudde, P. Terray and M. Rajeevan, 2017: A threefold rise in widespread extreme rain events over central India. Nature Communications, 8, doi:10.1038/s41467-017-00744-9.

  104. Devanand, A., Ghosh, S., Paul, S., Karmakar, S. and Niyogi, D., 2017. Multi- ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain. Climate Dynamics, 50: 4127. https://doi.org/10.1007/s00382-017-3864-x

  105. Singh, J., Sekharan, S., Karmakar, S., Ghosh, S., Zope, P.E. and Eldho,  T.I., 2017. Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile? Journal of Earth System Science, 126(3), p.38.

  106. Barik, B., Ghosh, S., Sahana, A.S., Pathak, A. and Sekhar, M. (2017), Water food energy nexus: with changing agricultural scenarios in India during recent Decades, Hydrology and Earth System Science, 21 (6), 3041-3060, https://doi.org/ 10.5194/hess- 21-3041-2017

  107. Mazdiyasni, O., AghaKouchak, A., Davis, S.J., Madadgar, S., Mehran, A., Ragno, E., Sadegh, M., Sengupta, A., Ghosh, S., Dhanya, C.T. and Niknejad, M. (2017). Increasing probability of mortality during Indian heat waves. Science Advances, 3(6), p.e1700066.

  108. Kulkarni, S., Deo, M C and Ghosh, S. (2017), Impact of active and break wind spells on the demand supply balance in wind energy in India, Meteorology and Atmospheric Physics, 130: 81. https://doi.org/10.1007/s00703-017-0501-5

  109. Shastri, H., Ghosh, S. and Karmakar, S. (2017), Improving Global Forecast System of Extreme Precipitation Events with Regional Statistical Model: Application of Quantile based Probabilistic Forecasts, J. Geophys. Res. Atmos, 122(3), pp.1617-1634

  110. Salvi, K., Villarini, G., Vecchi, G. A., and Ghosh, S. (2017), Decadal temperature predictions over the continental United States: Analysis and Enhancement, Climate Dynamics, https://doi.org/10.1007/s00382-017-3532-1

  111. Shastri, H., Barik, B., Ghosh, S., Venkataraman, C. and Sadavarte, P., (2017), Flip flop of Day-night and Summer-Winter Surface Urban Heat Island Intensity in India. Scientific Reports (Nature Publishing Group), 7, p.40178.

  112. Pathak, A., Ghosh, S., Martinez, J. A., Dominguez, F. and Kumar, P. (2016), Role of Oceanic and Land Moisture Sources and Transport in the Seasonal and Interannual variability of Summer Monsoon in India, Journal of Climate, 30, 1839–1859 https://doi.org/10.1175/JCLI-D-16-0156.1

  113. Venkataraman, C., Ghosh, S, and Kandlikar, M (2016), Breaking out of the box: India and climate action on short-lived climate pollutants, Environmental Science and Technology, 50 (23), pp 12527–12529, DOI: 10.1021/acs.est.6b05246

  114. Singh, J., V. Hari, S. Karmakar, S. Ghosh, and D. Niyogi (2016), Urbanization causes Nonstationarity in Indian Summer Monsoon Rainfall Extremes, Geophys. Res. Lett., 43, doi:10.1002/2016GL071238.

  115. Salvi, K. and Ghosh, S. (2016), Projections of Extreme Dry and Wet Spells in the 21st Century India Using Stationary and Non-stationary Standardized Precipitation Indices, Climatic Change, 139: 667. https://doi.org/10.1007/s10584-016-1824-9

  116. Paul,   S.,   Ghosh,   S.,   Oglesby,    R.,    Pathak,    A., Chandrasekharan,    A. and Ramsankaran, R., (2016) Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover. Scientific Reports, 6, 32177.

  117. Vittal, H., Ghosh, S., Karmakar, S., Pathak, A. and Murtugudde, R., (2016) Lack of Dependence of Indian Summer Monsoon Rainfall Extremes on Temperature: An Observational          Evidence. Scientific                                                   Reports, 6,       31039, https://doi.org/10.1038/srep31039.

  118. Ghosh S, Vittal H, Sharma T, Karmakar S, Kasiviswanathan KS, Dhanesh Y, et al. (2016) Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes. PLoS ONE 11(7): e0158670. doi:10.1371/journal.pone.0158670

  119. Sebastian, D E, Pathak, A. and Ghosh S. (2016), Use of Atmospheric Budget to Reduce Uncertainty in Estimated  Water  Availability  over  South  Asia  from Different Reanalyses, Scientific Reports (Nature Publishing Group), 6, 29664; doi: 10.1038/srep29664 (2016)

  120. Murari, K. K., Sahana, A. S., Daly, E. and Ghosh, S. (2016), The influence of the El Niño Southern Oscillation on heat waves in India. Met. Apps, 23: 705-713. doi:10.1002/met.1594

  121. Singh,  S,  Ghosh  S, Sahana A   S, Vittal,   H.   and Karmakar,   S.   (2016), Do Dynamic Regional Models add Value to the Global Model Projections of Indian Monsoon?, Climate Dynamics 48: 1375. https://doi.org/10.1007/s00382-016-3147-y

  122. Salvi, K, S. Ghosh and Ganguly A R (2015), Credibility of Statistical Downscaling under Nonstationary Climate, Climate Dynamics 46: 1991. https://doi.org/10.1007/s00382-015-2688-9

  123. Sahana, A. S., Ghosh, S., Ganguly, A. and Murtugudde, R. (2015), Shift in Indian Summer Monsoon Onset during 1976/1977, Environ. Res. Lett. 10 054006 doi:10.1088/1748-9326/10/5/054006

  124. Shastri, H., S. Paul, S. Ghosh, and S. Karmakar (2015), Impacts of urbanization on Indian summer monsoon rainfall extremes, J. Geophys. Res. Atmos., 120, 495-516, doi:10.1002/2014JD022061

  125. Murari, K. M., Ghosh S., Patwardhan, A., Daly, E., and Salvi, K. (2015), Intensification of future severe heat waves in India and their effect on heat stress and mortality, Regional Environmental Change, Volume 15, Issue 4, pp 569-579

  126. Shashikanth, K, Madhusoodhanan, C. G., Ghosh  S., Eldho T  I, Rajendran K., and Murtugudde, R. (2014), Comparing Statistically Downscaled Simulations of Indian Monsoon at different spatial Resolutions, Journal of Hydrology, Volume 519, Part D, Pages 3163-3177, 10.1016/j.jhydrol.2014.10.042

  127. Saha, A., S. Ghosh, Sahana, A. S. and E. P. Rao (2014), Failure of CMIP5 climate models in simulating post-1950 decreasing trend of Indian monsoon, Geophys. Res. Lett., 41, 7323-7330, doi:10.1002/2014GL061573.

  128. Pathak, A, Ghosh , S and Kumar P (2014), Precipitation Recycling in the Indian Subcontinent during Summer Monsoon, Journal of Hydrometeorology, Vol. 15, No. 5, Page: 2050-2066

  129. Kannan S, Ghosh, S, Mishra, V and Salvi K (2014), Uncertainty Resulting from Multiple Data Usage in Statistical Downscaling, Geophys. Res. Lett., 41, 4013-4019, doi:10.1002/2014GL060089.

  130. Kulkarni S, Deo M C, Ghosh S, (2014). Changes in the design and operational wind due to climate change at the Indian offshore sites, Marine Structures (2014), 37, July 2014, Pages 33-53 http://dx.doi.org/10.1016/j.marstruc.2014.02.005

  131. Ganguly, A.R. Kodra, E.A., Banerjee, A., Boriah, S., Chatterjee, S., Chatterjee, S., Choudhary, A., Das, D., Faghmous, J., Ganguli, P., Ghosh, S., Hayhoe, K., Hays, C., Hendrix, W., Fu, Q., Kawale, J., Kumar, D., Kumar, V., Liess, S., Mawalagedara, R.,Mithal, V., Oglesby, R., Salvi, K., Snyder, P.K., Steinhaeuser, K., Wang, D., and D. Wuebbles (2014): Toward enhanced understanding and prediction of climate extremes using physics-guided data mining techniques, Nonlin. Processes Geophys., 21, 777-795, 2014.

  132. Ashfaq, M., S. Ghosh, S.‐C. Kao, L. C. Bowling, P. Mote, D. Touma, S. A. Rauscher, and N. S. Diffenbaugh (2013), Near‐term acceleration of hydroclimatic change  in  the  western  U.S., J.  Geophys.   Res.   Atmos., 118,   10,676–10,693, doi: 10.1002/jgrd.50816.

  133. Shashikanth, K. , Salvi, K. , Ghosh, S. and Rajendran, K. (2014), Do CMIP5 simulations of Indian summer monsoon rainfall differ from those of CMIP3?. Atmos. Sci. Lett., 15: 79-85. doi:10.1002/asl2.466

  134. Vittal, H., S. Karmakar, and S. Ghosh (2013), Diametric changes in trends and patterns    of    extreme    rainfall    over    India    from    pre-1950     to     post- 1950, Geophys.Res. Lett., 40, 3253-3258, doi:10.1002/ grl. 50631.

  135. Patil K, Deo M C, Ghosh, S and Ravichandran M (2013), Predicting Sea Surface Temperatures in the North Indian Ocean with Nonlinear Autoregressive Neural Networks, International Journal of Oceanography, Article ID 302479, http://dx.doi.org/10.1155/2013/302479

  136. Nayak, M A and Ghosh, S (2013), Prediction of extreme rainfall event using weather pattern recognition and support vector machine classifier, Theoretical and Applied Climatology, doi: 10.1007/s00704-013-0867-3

  137. Salvi, K., S. Kannan, and S. Ghosh (2013), High-resolution multisite daily rainfall projections in India with statistical downscaling for climate  change  impacts assessment, J. Geophys. Res. Atmos.,118, 3557-3578, doi:10.1002/jgrd.50280.

  138. Kannan, S., and S. Ghosh (2013), A nonparametric kernel regression model for downscaling multisite daily precipitation in the  Mahanadi  basin, Water Resour. Res., 49, 1360-1385, doi:10.1002/wrcr.20118.

  139. Ghosh, S and Katkar, S (2012), Modeling Uncertainty Resulting from Multiple Downscaling Methods in Assessing Hydrological Impacts of Climate Change ,Water Resources Management, Volume 26, Issue 12, pp 3559-3579, DOI 10.1007/s11269- 012-0090-5

  140. Kodra, E, Ghosh, S and Ganguly, A. R. (2012), Evaluation of global climate models for Indian monsoon, Environmental Research Letters, 7, 014012 doi:10.1088/1748-9326/7/1/014012

  141. Ghosh, S, Das, D, Kao, S-C, Ganguly, A. R. (2012), Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes, Nature Climate Change, 2, 86-91, DOI: doi:10.1038/nclimate1327

  142. Ghosh, S (2010), SVM-PGSL coupled approach for statistical downscaling to predict rainfall from GCM output, Journal of Geophysical Research, 115, D22102, doi:10.1029/2009JD013548.

  143. Katkar, S., Gupta A., and Ghosh, S (2010), Transfer Function based Downscaling Methods for Assessing Future Rainfall using GCM Output, Hydrology Journal, Vol. 33, 9-16.

  144. Kashid S, Ghosh, S and Maity R. (2010),Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection,, Journal Of Hydrology, 395, pp 23- 38, doi:10.1016/j.jhydrol.2010.10.004

  145. Ghosh, S and Misra C (2010),Assessing Hydrological Impacts of  Climate Change: Modeling Techniques and Challenges,, Open Hydrology Journal, 4, 115-121

  146. Ghosh, S (2010),Modelling bivariate rainfall distribution and generating bivariate correlated rainfall data in neighbouring meteorological subdivisions using copula,, Hydrological Processes, 24, 3558-3567

  147. Kannan, S. and Ghosh, S (2010),Prediction of daily rainfall state in a river basin using statistical downscaling from GCM output,, Stochastic Environmental Research and Risk Assessment, Springer.

  148. Ghosh, S, Raje D. and P. P. Mujumdar (2010),Mahanadi Streamflow: Climate Change Impact Assessment and Adaptive Strategies,, Current Science, 98(8), pp 1084- 1091.

  149. Ghosh, S and P. P. Mujumdar (2010): Fuzzy Waste Load Allocation Model: A Multiobjective Approach, Journal of Hydroinformatics, 12.1, 96-109.

  150. Ghosh, S, Luniya, V. and Gupta, A. (2009),Trend Analysis of Indian Summer Monsoon Rainfall at Different Spatial Scales,, Atmospheric Sciences Letter, Royal Meteorological Society, 10(4), pp. 285-290

  151. Musti, S., Ghosh, S and Mujumdar, P. P. (2009), Imprecise Probability for Modeling Partial Ignorance: Application to Waste Load Allocation in a River System, ISH Journal of Hydraulic Engineering, 15 (SP1), pp. 258-271

  152. Ghosh, S and P. P. Mujumdar (2009), Climate Change Impact Assessment- Uncertainty Modeling with Imprecise Probability, Journal of Geophysical Research- Atmosphere (AGU), 114, D18113, doi:10.1029/2008JD011648

  153. Mujumdar P. P. and Ghosh, S (2008), Climate Change Impact on Hydrology and Water Resources, ISH Journal of Hydraulic Engineering, 14(3), 1-17.

  154. Mujumdar, P. P., and S. Ghosh (2008), Modeling GCM and scenario uncertainty using a possibilistic approach: Application to the Mahanadi River, India, Water Resources Research, 44, W06407, doi:10.1029/2007WR006137

  155. Ghosh, S and P. P. Mujumdar (2008): Statistical Downscaling of GCM Simulations to Streamflow Ghosh,Susing Relevance Vector  Machine. Advances in Water Resources. (Pub: Elsevier, Netherlands), 31(1), pp. 132-146

  156. Ghosh,S and P. P. Mujumdar, (2007), “Nonparametric Methods for Modeling GCM and Scenario Uncertainty in Drought Assessment”, Water Resources Research, AGU, 43, W07405, doi:10.1029/2006WR005351.

  157. Ghosh,S and P. P. Mujumdar, (2006), “Future Rainfall Scenario over Orissa with GCM Projections by Statistical Downscaling”, Current Science (Indian Academy of Sciences), 90(3), pp. 396-404.

  158. Ghosh,S, and P. P. Mujumdar, (2006), “Risk Minimization in Water Quality Control Problems of a River System”, Advances in Water Resources, Elsevier, 29, pp. 458-470.

  159. V. V. R. Subbarao, P. P. Mujumdar, and Ghosh,S (2004),“Risk Evaluation in Water Quality Management of a River System”, Journal of Water Resour. Plng and Mgmt., ASCE, 130(5), pp 413-423.

 

Conference Proceedings/ Abstracts/ Extended Abstracts (Published)

​

  1. Dubey, N. and Ghosh, S., 2023. Changes in Indian vegetation productivity under increasing CO2 concentration (No. EGU23-14235). Copernicus Meetings.

  2. Chauhan, T. and Ghosh, S., 2023. Dynamics of Sundarbans mangroves under climate extremes and changing soil nutrient composition (No. EGU23-13968). Copernicus Meetings.

  3. Singh, S., Salvi, K., Ghosh, S. and Karmakar, S., 2020, May. Fidelity of CORDEX Evaluation runs under Non-stationary climate. In EGU General Assembly Conference Abstracts (p. 927).

  4. Sudharsan, N., Singh, J., Ghosh, S. and Karmakar, S., 2020, May. India can't Wait to Act upon Climate Change as Heatwaves Claim Life. In EGU General Assembly Conference Abstracts (p. 1071).

  5. Gusain, A., Sudharsan, N., Karmakar, S. and Ghosh, S., 2020, May. Flood Risk Characterization of Highly Flood-prone Data Scarce Region under Changing Climate. In EGU General Assembly Conference Abstracts (p. 1078).

  6. Indu, J., Padmanabhan, T. and Ghosh, S., 2019. Inclusion of Model Error in the 3DVAR Radar Assimilation system using Ensemble based Background Error Covariance. AGUFM, 2019, pp.A31M-2875.

  7. Barik, B., Ghosh, S., Joseph, J. and Chandel, V., 2019. Understanding the Impact of Anthropogenic Factors for a Dis-balanced WEF Nexus in the Ganga Basin. AGUFM, 2019, pp.GC31J-1341.

  8. Gupta, M. and Ghosh, S., 2019. Characterization of Urban area using detection of Urban morphology and land surface parameters: Evidence from Mumbai city, India. AGUFM, 2019, pp.GC43I-1462.

  9. Ghosh, M., Shastri, H.K., Karmakar, S. and Ghosh, S., 2019. An Improved Flood Forecasting Framework with a Quantile based Probabilistic Approach for a Coastal Urban Catchment. AGUFM, 2019, pp.H13J-1816.

  10. Sahastrabuddhe, R., Saha, A., Ghosh, S., Murtugudde, R. (2018) Improvement of Seasonal Prediction for Indian Monsoon based on Spatial Patterns using Deep Learning Techniques, 2018 American Geophysical Union Fall Meeting, Washington, D.C., USA

  11. Devanand, A., Roxy, M. K., Ghosh, S. (2018). Role of land-atmospheric processes in CFSv2 monsoon rainfall dry bias over India. EGU2018-950, European Geosciences Union General Assembly, 8-13 April 2018, Vienna, Austria.

  12. Devanand, A., Huang, M., Ashfaq, M., Barik, B., Subhankar, K., Ghosh, S. (2018). Impact of irrigation and groundwater pumping over the Ganga Basin on the Indian summer monsoon. CESM land model working group session, CESM Workshop, 18-20 June 2018, NCAR - Boulder, CO, United States.

  13. Sebastian, D., Ghosh, S and Krishnaswamy, J (2018) Influence of Climate Variables on Phenology of Indian Forests. Remote sensing of interactions between vegetation and hydrology, Paper number: EGU2018-997, EGU General  Assembly 2018, Vienna, Austria.

  14. Ghosh, S., Shastri, H., Pathak, A. and Paul, S., 2017, April. Changing Pattern of Indian Monsoon Extremes: Global and Local Factors. In EGU General Assembly Conference Abstracts (Vol. 19, p. 2392).

  15. Singh, S., Ghosh, S. and Karmakar, S., 2017, April. Performance of CORDEX- Evaluation Simulations for Indian Summer Monsoon under Non-Stationary Climate. In EGU General Assembly Conference Abstracts (Vol. 19, p. 3108).

  16. Paul, S., Pathak, A. and Ghosh, S. (2016) Role of Local Characteristics On Indian Summer  Monsoon  Precipitation. Climate  Change,  Monsoon  And   Extreme Weather Events(AS02), Asia Oceania Geosciences Society (AOGS), 13th Annual Meeting, 2016, Beijing, China.

  17. Devanand, A., Paul, S., Ghosh, S. and Karmakar S. (2016) Sensitivity of Indian Summer Monsoon simulations to cumulus and microphysics parameterizations in WRF model., Poster session C: Impacts and applications, International Conference on Regional Climate - Coordinated Regional Downscaling Experiment (ICRC- CORDEX), 17-20 May, 2016, Stockholm, Sweden.

  18. Singh, S., Ghosh, S. (2016), Coupled Statistical-Dynamic Downscaling Approach for Regional Projections of Indian Summer Monsoon, Poster session C, ICRC- CORDEX 2016 Conference, Stockholm, Sweden.

  19. Sharma, T, Murari, H. V., Karmakar, S., Ghosh, S., Singh, J. (2016), Assessing the Agricultural Vulnerability for India under Changing Climate, Paper Number: EGU2016-153, EGU General Assembly 2016, Vienna, Austria.

  20. Sahana, A. S., Pathak, A., Roxy, M. K., Ghosh, S.(2016), Understanding Dry Bias in the Simulations of Indian Monsoon by CFSv2 through Analysis of Moisture Transport, EGU General Assembly 2016, Vienna, Austria.

  21. Sahana, A. S., Ghosh, S. (2015),Evaluation of CFSv2 Forecast Skill for Indian Summer Monsoon Sub-Seasonal Characteristics, 2015 American Geophysical Union Fall Meeting San Francisco.

  22. Mathew, M., Paul, S., Devanand, A., and Ghosh,S. (2015), Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model, Abstract B34C-04 presented at 2015 AGU Fall Meeting, San Francisco, USA

  23. Sharma, T, Murari, H. V., Vittal, H., Karmakar, S., Ghosh, S. and Soora N. S. (2015), Understanding the Propagation of GCM and Downscaling Uncertainty for Projecting Crop Yield: A Nationwide Analysis over India, Paper Number: GC41H-04, AGU Fall Meeting 2015, San Francisco, USA.

  24. Pathak, A., S. Ghosh, P. Kumar, & A.S. Sahana, 2015: Role of Terrestrial Moisture Source Transport on Summer Monsoon Rainfall Variability over Ganga River Basin, 2015 American Geophysical Union Fall Meeting San Francisco.

  25. Pathak A., A.S. Sahana and S. Ghosh, 2015: Impact of Atmospheric Moisture Transport on Indian Summer Monsoon Onset and Withdrawal, 2015 Dynamics of the Indian Ocean: perspective and Retrospective, NIO, Goa.

  26. Sebastian, D., A. Pathak, and S. Ghosh, 2015: Improving the Consistency in Water Availability between Different Reanalysis Data over South Asia, 2015 American Geophysical Union Fall Meeting San Francisco.

  27. Joseph, J., Pathak, A. and Ghosh, S. (2015), Uncertainty Assessment in Climate Change Simulation of Ganges Basin Uncertainty in the Identification of Indian Summer Monsoon Onset, Paper Number: H33E-1664, AGU Fall Meeting 2015, San Francisco, USA

  28. Singh, S., Ghosh, S. (2015), Evaluation of CORDEX RCMs in simulation of northward and eastward propagation of the Indian summer monsoon, Paper ID: IO50- 06-0014 , Dynamics  of          the     Indian  Ocean: perspective and Retrospective,Symposium2015, NIO, Goa, India.

  29. Sharma,  T.,   Chhabra,   S.,   Salvi,   K., Karmakar,   S.   and   Ghosh,   S. (2015), Assessing the Uncertainty in Downscaling Approaches using Hydrological Model, Paper Number: EGU2015-776, EGU General Assembly 2015, Vienna, Austria. (Poster presentation)

  30. Pathak, A., H. Shashtri, and S. Ghosh, 2015: Feedback from Urbanization and Land Surface ET to Indian Summer Monsoon Rainfall, National Climate Science Conference, Divecha Centre for Climate Change, Indian Institute of Science, Bangalore.

  31. Saha, A., Sahana, A.S., Ghosh, S. and E.P. Rao (2015). Evaluation of CMIP5 Models for post-1950 Weakening of Indian Monsoon. EGU2015-338, EGU General Assembly, 2015, Vienna, Austria.

  32. Sahana, A. S. and Ghosh, S. (2014), Uncertainty in the Identification of Indian Summer Monsoon Onset, Paper Number: A41C-3053, AGU Fall Meeting 2014, San Francisco, USA.

  33. Swati, S., Salvi, K., Ghosh, S. and Karmakar, S. (2014), Projections of Active and Break Spells of the Indian Summer Monsoon using Original and Statistical Downscaled CMIP5 GCMs, Paper Number: A41C-3054, AGU Fall Meeting 2014, San Francisco, USA.

  34. Agrawal, A., Salvi K., and Ghosh S (2014), Improving GEFS Weather Forecasts for Indian Monsoon with Statistical Downscaling, Geophysical Research Abstracts, Vol. 16, EGU2014-11854, 2014, EGU General Assembly 2014, Vienna, Austria

  35. Jain, A., Shashikanth K., Subimal Ghosh, Mukherjee P P (2013), Projecting Wind Energy potential Under Climate Change With Ensemble of Climate  Model Simulations, AGU Fall Meeting 2013, San Francisco, USA.

  36. Shastri, H., Ghosh. S., and Karmakar, S. (2013), Impacts of Urbanization on Indian Summer Monsoon Rainfall, AGU Fall Meeting 2013, San Francisco, USA.

  37. Pathak, A, Ghosh S. and Kumar, P (2012), Precipitation recycling in India during South West Monsoon, AGU Fall Meeting, 3-7 December, 2012

  38. Shashikanth, K., S. Ghosh and K. Rajendran (2012), Fine scale projections of Indian monsoonal rainfall using statistical models, AGU Fall Meeting, 3-7 Dec 2012, San Francisco, California, USA.

  39. Vittal Hari, Subhankar Karmakar, Subimal Ghosh (2012), "Detection of Spatio- temporal variations of rainfall and temperature extremes over India", American Geophysical Union (AGU) meet, fall 2012, San-Francisco.

  40. Salvi, K and Ghosh, S (2012), Future Patterns of Flood and Drought in India Using the Three Month Standardized Precipitation Index, HYDRO 2012, IIT Bombay, Mumbai, India

  41. Salvi K and Ghosh, S (2012), Climate Change and Simulations of Extreme Hydrologic Scenarios in India, Indo-German Conference on Modeling, Simulation and Optimization in Applications, Darmstadt, Germany.

  42. Murari, K, Daly, E. and Ghosh, S., Change in Intensity-duration Relationship of Extreme  Temperature  Episodes  in  Transient  Climate  Over  India.,  AOGS  -  AGU(WPGM) Joint Assembly, 13 to 17 August, 2012, Resorts World Convention Centre, Singapore.

  43. Salvi, K and Ghosh, S (2012), High Resolution Rainfall Projections in India for Climate Change Impact Assessment, AOGS - AGU (WPGM) Joint Assembly, 13 to 17 August, 2012, Resorts World Convention Centre, Singapore.

  44. Bhatia, U, Salvi K., and Ghosh, S (2011), Performance Comparison of quantile base correction with KNN technique of Downscaling to project future temperature, Hydro, 2011, Surat, India, 29-30 December.

  45. Salvi, K, Kannan, S. and Ghosh, S (2011), Finer Scale Temperature and Rainfall Projections for Climate Change Impacts Assessment, 4th International Conference on Environmental and Computer Science, Singapore, Sept 16-18, 2011 [Key-note]

  46. Jain,    S.,    Paliwal,     V.     and     Ghosh,S     (2010),     Selection     of Spatial   Extent   of   Predictor   Variables   in   Statistical   Downscaling,    The Ninth  International   Conference   on   Hydro-Science   and   Engineering   (ICHE 2010),  Indian  Institute  of  Technology  Madras,  Chennai,   India.   2-5   August 2010

  47. Kannan,    S.    and    Ghosh,S    (2010),    Multi-site    daily    rainfall prediction for climate change scenarios using the non-parametric k-nearest neighbours, The Ninth International  Conference  on  Hydro-Science  and Engineering  (ICHE  2010),  Indian  Institute  of  Technology   Madras,   Chennai, India. 2-5 August 2010

  48. Kannan, S. and Ghosh,S (2010), “Generation of Rainfall State in a River Basin incorporating Climate Change”, IAHR-APD 2010 Congress Auckland New Zealand, February, 2010

  49. Ghosh,S, Luniya, V. and Gupta, A. (2010), “Trend Analysis in Extreme Rainfall Events over Large Region in India: Is It Always Correct?”, 3rd developing nations conference: India 2010 - An International Perspective on Current & Future State of Water Resources & the Environment, January, 5-7, Chennai, India

  50. Ghosh,S (2009), “SVM for Statistical Downscaling with Proper Selection of Parameters”, Workshop on Advanced Soft Computing Techniques (WAST2009), 15-16 October, 2009, Kanpur, India.

  51. Mujumdar, P. P., Ghosh,S, and Raje, D. (2009), “Hydro-meteorological predictions from GCM simulations: downscaling techniques and uncertainty modelling”,IAHS Publ. 333 (Proceedings of HS.2 at the Joint IAHS & IAH Convention a symposium held in Hyderabad, India, September 2009, pp 165-175.

  52. A K Agrawal, K Sree Ram Reddy, A S Dsouza, S S More, S Shrikrishna Kolwankar, A Sirohi and Ghosh,S (2008), “Changes in Monsoon Rainfall Pattern in Indian Meteorological Subdivisions”, HYDRO 2008, Jaipur.

  53. Ghosh,S (2008), “Modeling Hydrologic Impacts of Climate Change”, National Conference on Sustainable Water Resources Development and Management, Govt. Engg. College, Aurangabad (Invited Key Note Paper), June 13-14, 2008

  54. Ghosh,S and P. P. Mujumdar (2008), “Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment”, Water Down Under 2008, Adelaide, Australia, April 14-17, 2008.

  55. Ghosh,S and P. P. Mujumdar (2007), “Modeling GCM and Scenario Uncertainty: An Imprecise Probability Approach”, 3rd Indian International Conference on Artificial Intelligence 2007 (IICAI 07), Pune, India.

  56. Ghosh,S, Sashank M, and P. P. Mujumdar (2007), “Waste Load Allocation: An Imprecise Fuzzy Risk Approach”, International Conference on Civil Engineering in the New Millennium: Opportunities and Challenges (CENeM-2007), Bengal Engineering and Science University, Shibpur, Howrah, West Bengal, India. (Invited Key  Note Paper), January 11-14, 2007.

  57. Ghosh,S and P.P. Mujumdar (2006), “Minimization of Constraint Violation in Fuzzy Multiobjective Programming”, 7th International Conference on Hydroinformatics HIC 2006, Acropolis, Nice, France, 4 - 8 September 2006.

  58. Ghosh,S, H. R. Suresh and P. P. Mujumdar (2005), “Fuzzy Water Quality Management Model: Application to a Case Study”, Proceedings of the 2nd Indian International Conference on Artificial Intelligence 2005 (IICAI 05), Pune, India, 20-22 Dec, 2005. pp. 2006-2015.

  59. Ghosh,S, and P.P. Mujumdar, (2005), “A Fuzzy Waste Load Allocation Model Integrating Skewness of Distributions”, National Conference on Advances in Water Engineering for Sustainable Development (NCAWESD-2005), Department of Civil Engineering, I.I.T. Madras, May 16 & 17, 2005.

  60. Ghosh,S, and P.P. Mujumdar, (2005), “Risk Minimization Model for River water Quality management”, Proceedings of International Conference on Hydrological Perspectives for Sustainable Development (HYPESD - 2005), 23 - 25 February 2005, Indian Institute of Technology Roorkee, India, pp. 932-940.

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