Webinar on 

"S2S forecast and its applications in South Asia”

Indian Institute of Tropical Meteorology (IITM), Pune, India

1100-1300 UTC, 28 July 2021

Please join us at :https://youtu.be/-A15D1pl0BY



The South Asia region experiences various hydro-meteorological hazards including cyclones, depressions, heavy rainfall, floods, droughts, heat and cold waves. The forecast and early warning is the key to the management of these hazards. The rainfall variability in this region strongly impacts local societies, especially through the annual rhythm of the monsoons with distinct wet and dry seasons and pronounced interannual and intraseasonal variability. To address this forecast need, WMO has initiated the S2S project which focuses on improving the forecast skill and understanding of the sub-seasonal to seasonal timescales with special emphasis on high-impact weather events. Forecast on these timescales is not only useful to predict the magnitude, location, and timing of potentially damaging hydro-meteorological hazards but also helps in planning various agricultural activities, e.g., crop sowing, application of pesticide, and planning of irrigation, and also dam water management, generating health emergency warning associated with the heat waves and cold waves, vector-borne diseases and several other applications.  

WMO S2S Working Group along with the International CLIVAR Monsoon Project Office (ICMPO) is organising a one-day webinar on “S2S forecast and its applications in South Asia” on 28 July 2021 from 1100-1300 UTC (1630-1830 IST) with the active support from the Indian Institute of Tropical Meteorology (IITM), Pune, India.  The webinar will have four talks from leading scientists and users who are at the forefront of S2S prediction and application areas.


1100–1110 UTC

Introduction and Welcoming the dignitaries by Dr AK Sahai, SSC Member, WWRP


1110–1130 UTC

Prof Subimal Ghosh 

: Agricultural Water Management with Extended Range Forecasts and Water Savings

1135–1155 UTC

Dr Giriraj Amarnath

: Subseasonal weather forecasts in managing floods and droughts

1200–1220 UTC

Dr Nachiketa Acharya

: Sub-seasonal to seasonal prediction of the southwest monsoon rainfall: A Research-to-Operation approach

1225–1245 UTC

Dr Susmitha Joseph

: Towards the development of an efficient extended range prediction system for societal applications over South Asia

1250–1300 UTC

Discussions and Concluding Remarks by S2S Project Leads – Dr Andrew Robertson and Dr Frederic Vitart

How to Join the Webinar:

Please join us at :




1. Prof Subimal Ghosh, IIT Bombay, India

About the speaker: Prof Subimal Ghosh is currently serving as the Convener of Interdisciplinary Program in Climate Studies and the Institute Chair Professor in the Department of Civil Engineering, IIT Bombay. His research interest includes hydro-climatology, regional climate modelling, understanding of Indian Monsoon and its variability, mesoscale hydrological modelling, water resources systems and simulating land surface feedbacks to climate.

He has around 110 journal publications, including Nature Climate Change, Nature Communications, Science Advances, Geophysical Research Letters, Water Resources Research etc. He is the conferred fellow of the American Geophysical Union and the recipient of the AGU D L Memorial Medal, Shanti Swarup Bhatnagar Prize, Swarnajayanti Fellowship, PRL Award, Dr. A P J Abdul Kalam Cray HPC Award, and many more. He is also the lead author of IPCC, Assessment Report-6, Working Group 1.

Title of the talk: Agricultural Water Management with Extended Range Forecasts and Water Savings

Abstract: There has been a significant improvement in numerical weather prediction and extended range prediction over the last decade. Despite these improvements, the majority of the farmers in India do not use the weather or extended range products. Here we co-developed an irrigation optimization tool with the farmers of Maharashtra for irrigation water management for their grape farms and show 10-30% of water can be saved through soil moisture monitoring and weather forecasts. The methodology involves the development of a chance constraint optimization model considering information from the hindcast and ecohydrological modelling with Monte-Carlo Simulations. We extended the framework for extended range prediction with the use of the hidden Markov model. We showed that it is possible to make early water arrangements for irrigation to be applied to the farm without waste in water and losing yield. Our results showed that the only way to make the climate services usable through co-developing tools with the stakeholders.

2. Dr Giriraj Amarnath, IWMI, Srilanka 


About the speaker: Giriraj Amarnath is a Principal Research – Disaster Risk Management and Climate Resilience and Research Group Leader: Water Risks to Development and Resilience of the International Water Management Institute (IWMI). His role focuses on climate risk assessment, monitoring and early warning tools using earth observation data and modelling tools, and the development of disaster risk insurance solutions.

Dr Giriraj began his career as a remote sensing expert at the University of Bayreuth, Germany and was a disaster risk specialist for the International Centre for Integrated Mountain Development at Kathmandu. He recently won the World Geospatial Excellence Award and the 2020 GEO SDG Award in promoting innovative solutions in managing floods and drought using digital tools. Dr Giriraj holds a PhD in Applied remote sensing from the National Remote Sensing Centre, India, and an M.Sc. in Geoinformatics and Botany from the University of Madras.

Title of the talk: Subseasonal weather forecasts in managing floods and droughts

Abstract: Economic losses from weather-related shocks have doubled in India over the last three decades, from US$ 20 billion in 1998 to 1997 to US$ 45 billion in 2008 to 2017. As climate change continues to increase the frequency and intensity of extreme weather events, farmers need to be better prepared or risk losing their livelihoods. Weather information provided over shorter lead times provides intelligence for operational decisions regarding flood risk management, emergency response, and situational awareness of potential hazards. Sub-seasonal weather forecasts are now possible, thanks to satellite technology aiding better understanding of environmental conditions and atmospheric processes, including soil moisture, snow cover, stratospheric-tropospheric interactions, ocean-atmosphere interactions and natural climatic oscillations. In Afghanistan, ERPAS subseasonal forecast information provided by IITM has helped drought authorities for timely drought early warning and a case study in India and Sri Lanka, weekly weather maps, provided four weeks in advance, have helped guide farmers planting schedules. In the past, farmers have sometimes sown crops at the first monsoon rains, only for a dry spell to emerge and cause their plants to wither and die. Having access to sub-seasonal forecasts can help farmers understand when planting later, once the monsoon is more established, would be wiser.  

Natural disasters place a significant burden on health resources. Deaths or injuries often occur immediately when a community suffers from a shock event such as an earthquake or cyclone; they can also happen later, for example as a result of a water-borne disease emerging in the aftermath of a flood. S2S information aided with satellite technology can help to minimize loss of life and harm to health before, during and after hazard events. Locations where the risk from hazards is greatest can be overlaid with population data, as well as infrastructures such as water and sewerage facilities, to indicate where impacts from hazards are likely to be highest. In summary, emerging technologies in S2S including the use of machine learning methods can improve precipitation forecasting over weeks to months could assist stakeholders in well-informed resource management and increase lead times for responding to droughts and floods.

3. Dr Nachiketa Acharya, Pennsylvania State University, USA 

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About the speaker: Nachiketa Acharya is a statistical climatologist with specialities in statistical and machine learning modelling in climate science, especially sub-seasonal to seasonal climate forecasting. He is currently serving as an Assistant Research Professor at Earth System Modeling, Analysis, and Data (ESMAD) at the Department of Meteorology and Atmospheric Science, Pennsylvania State University.

His research interests include probabilistic forecasting, multi-model Ensemble, GCM diagnostics calibration and verification, stochastic weather generators, and extreme value analysis and application of Machine Learning models in climate science. He is actively engaged in several Regional Climate Outlook Fora by WMO as an expert and trainer of S2S forecast and verification in pre-COF. He is also co-leading the Building Block-3 (Prediction with a focus on the seasonal to decadal timescales) of Regional Information for Society (RifS), WWRP-WCRP. Web address: http://www.met.psu.edu/people/npa5302

Title of the talk: Sub-seasonal to seasonal prediction of the southwest monsoon rainfall: A Research-to-Operation approach

Abstract: This talk will cover the ‘Research to Operation’ aspect of the southwest monsoon on the sub-seasonal to seasonal scale. For the sub-seasonal scale, we will describe an experimental system that was developed for the state of Bihar, one of the most climate-sensitive states in India. The system is based on the rainfall forecast issued in real-time during the monsoon of 2018 in order to explore the potential value of the S2S forecasts for small-holder farmers. The real-time forecasts were generated every week using CFSvs S2S forecasts, calibrated against observed gridded rainfall from the India Meteorological Department. The forecast was able to capture the signal of the weaker monsoon including the delayed monsoon onset and break phase (in August). For the Seasonal scale, we will describe the co-design, co-development, and skill assessment of the recently developed NextGen forecast system that follows the WMOs recent seasonal forecast guidance on objective-based methods for Bangladesh. This new forecast system is based on a calibrated multi-model ensemble process using state-of-the-art coupled general circulation models from the NMME project. Since October 2019, the Bangladesh Meteorological Department has been issuing this new forecast system in real-time.

4. Dr Susmitha Joseph, IITM, Pune, India 

About the speaker: Dr Susmitha Joseph is working as the Deputy Project Director of the Extended Range Prediction Group at the Indian Institute of Tropical Meteorology (IITM), Pune, India and has more than 15 years of research experience in the field of monsoon meteorology. She obtained her M.Sc. in Meteorology from Cochin University of Science and Technology, Kerala and PhD in Atmospheric and Space Sciences from Savitribai Phule Pune University, Pune.

Dr Susmitha has expertise in the variability and predictability of the Indian monsoon. She is presently working on the development and implementation of empirical as well as dynamical ensemble prediction systems for the prediction of onset phase, active/break spells and withdrawal phase of ISM on the extended range (~15-20 days in advance). Her research also focuses on the prediction of extreme weather events such as heavy rainfall events, heat/cold waves and cyclogenesis.

Title of the talk: Towards the development of an efficient extended range prediction system for societal applications over South Asia

Abstract: Subseasonal forecast or the extended range prediction (ERP) beyond 10 days is an important component in climate forecast applications, and has numerous applications in agricultural, health, energy, hydrology and disaster management. The ERP efforts at IITM initiated in 2011 under the prestigious Monsoon Mission Project of Govt. of India. Starting from the development of an indigenous perturbation technique to generate ensemble predictions to the development of a multi-model ensemble prediction system (MMEPS), this journey spans almost a decade. Owing to the remarkable skill of the MMEPS in predicting the different phases of the Indian monsoon and extreme events like heat/cold waves, heavy rainfall events, cyclones etc., this system is operationalized by the India Meteorological Department since 2016 and is being used to generate the agricultural and health bulletins every week. Efforts are underway to develop a multiphysics multimodel ensemble prediction system (MPMME) to further improve the predictions and address the spatio-temporal errors observed at the higher lead times.


About the Chair

Dr A. K. Sahai

03. Dr A. K. Sahai, IITM Pune, India

Dr Atul Kumar Sahai is a Member of the Scientific Steering Committee of the World Weather Research Programme (WWRP) of WMO for the period 2019-2022. He retired as Scientist G from IITM in March 2021. At the time of his retirement, he was the Project Director of Monsoon Mission and the lead of the Extended Range Prediction Group at IITM.

He has expertise in climate variability and prediction, prediction of extreme weather events, operational climate services, climate change and regional climate scenario generation for impact assessment studies based on regional climate models, and utilization of Artificial Intelligence and Machine Learning in the field of climate science, as evident from more than 160 scientific research papers in peer-reviewed journals / scientific reports/ book chapters. His most notable research led to the development of a dynamical ensemble prediction system for predicting the intra-seasonal oscillations of the Indian summer monsoon season. Dr Sahai has also formulated several strategies for the application of these extended range forecasts in agriculture, hydrology, health, and disaster management.




Dr Andrew Robertson, IRI

Dr Frederic Vitart, ECMWF

Dr A K Sahai, WWRP



Prof Ravi S Nanjundiah, IITM

Dr Rupakumar Kolli, ICMPO, IITM

Dr Susmitha Joseph, IITM