1. Introduction

The extreme weather events cause a large damage to life and ecosystem. Since the last few decades, there has been an increase in extreme weather events in South Asia. Despite large efforts, prediction errors in extreme precipitation events have not reduced (Zhang et al. 2023). It is known that stratospheric processes affect tropospheric processes; for example, QBO and ENSO modulate tropical cyclones (Doane-Solomon et al. 2024; Huangfu et al. 2021; Fadnavis et al. 2014). Gray (1984) identified the QBO signal as one of the important predictors in tropical cyclone seasonal forecasts. The upper-tropospheric Rossby wave breaking events are associated with these extreme precipitation events (Tamarin-Brodsky and Harnik 2024). Therefore, it is important to assess the impacts of stratosphere–troposphere interactions on extreme weather events. It is the right time to evaluate if the extension of the top of prediction model above the stratosphere, into the mesosphere improves the prediction of extreme precipitation events and thereby, develops pathways for improving the accuracy of prediction of extreme weather events in a changing climate. This is important in the global context as the extreme events over South Asia especially can trigger a chain of extreme weather events elsewhere in the Northern Hemisphere via the waveguide teleconnection patterns.

Keeping in view the influence of cross tropopause processes on extreme weather that may affect the forecast of extreme weather events, an international workshop on “Stratosphere–Troposphere Interactions and Prediction of Monsoon Weather Extremes (STIPMEX)” was organized during 2–7 June 2024 at the Indian Institute of Tropical Meteorology, Pune, India (Fig. 1).

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Attendees of the international workshop on STIPMEX.

Citation: Bulletin of the American Meteorological Society 105, 11; 10.1175/BAMS-D-24-0210.1

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2. Recap of the STIPMEX training and workshop sessions

A capacity building component was included in the STIPMEX workshop through dedicated training sessions. The workshop began on 2 June with two separate training sessions for early career scientists (ECSs) on stratosphere–troposphere processes and monsoon weather extremes, respectively. A hands-on training for 120 ECSs was given on preparation and launching of instruments on the balloon sonde flight such as 1) RS41 for met parameters, 2) ozonesondes for atmospheric ozone, 3) cryogenic frost point hygrometer (CFH) for atmospheric water vapor, and 4) Compact Optical Backscatter Aerosol Detector (COBALD). The training session also included 1) simulations and analysis of chemistry climate model and reanalysis datasets data for understanding the stratosphere–troposphere interaction process understanding, 2) highly specialized talks from international experts on scientific challenges required for improving the skill of weather forecasts, and 3) a hands-on experience with online ECMWF products.

The STIPMEX workshop during 3–7 June included 34 invited and lead oral talks covering different aspects of stratospheric–tropospheric processes and their linkages with extreme weather over South Asia and challenges in subseasonal to seasonal, short-range weather forecasts. The details of the talks are mentioned in Table 1. The workshop sessions during 3–7 June were attended by ∼310 participants, 25 from different countries, viz., Asia, Europe, America, and Africa along with ∼500 online participants (Fig. 2). The workshop also featured two public talks by 1) Prof. Timothy Palmer, University of Oxford, United Kingdom, on “Ensemble Weather and Climate Prediction: From Origins to AI,” delivered online on 3 June 2024, and 2) Dr. V Ramaswamy, GFDL NOAA, United States, on “Twenty-First Century Earth Energy Imbalance and Climate Change.”

Table 1.

Invited and lead talks in STIPMEX workshop.

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Attendees of the training sessions of international workshop STIPMEX.

Citation: Bulletin of the American Meteorological Society 105, 11; 10.1175/BAMS-D-24-0210.1

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The presentations made by the speakers are available online (https://sparc-extreme.tropmet.res.in/workshop-posters). Additionally, the video recordings of all the talks are available in the IITM YouTube Channel (https://www.youtube.com/playlist?list=PLgQCKqNw6z_Bxja5SfYawCBasTl9fXCGc).

In the workshop, experts deliberated on the role of stratospheric processes on monsoon extremes, the importance of observations of chemical species in the troposphere and stratosphere over the Asian region for model improvement, and the latest forecast and AI/ML techniques. There is a need of climate intervention modelling experiments for extreme weather metigations. There was a brainstorming discussion of the model parameterizations and linkages of influence of cross-tropopause processes on monsoon extremes. Experts also mentioned the gray areas, e.g., insufficient observations over the Asian region, convective parameterization in the models, and representation of stratospheric processes in the forecasting model.

3. Key takeaways: Feedback and recommendations

• For extreme weather prediction, the use of models which have tops in the mesosphere or above along with the full stratospheric processes is recommended.

• The role of high-resolution modeling, quantum computing, along with hybrid AI/ML and physics-based models to tackle challenges faced by the global modeling community for extreme weather prediction. Physics-based approaches must go hand-in-hand with AI/ML-based approaches to tackle scientific problems.

• It is recommended to celebrate 50 years monsoon experiment (MONEX-1979), with a major observational field campaign program “MONEX-2” involving all the regional monsoons of the world.

• Modeling experiments on climate interventions for mitigating the effects of climate change to be conducted.

• Importance of observations ground-based and upper air, including soundings and aircraft over the Asian region and process level understanding, was highlighted.

• The Earth system modeling framework including studies on the impact of chemical and climate change on monsoons and the aerosol–cloud interaction is needed.

• Need to enhance research on the internal and external drivers of extremes and role of stratospheric dynamic in collaborations with the stakeholders.

• Downscaling the NWP prediction with high-quality datasets and bias correction is the solution which may lead to better prediction of rainfall amounts.

• Observation protocols should be decided considering modeling needs that will help in bias correction. The role of local low-cost sensors for weather parameters, flood, air quality, GHG monitoring, etc. to fill up the data gaps and reach of such local data to the researchers/organizations.

• Improving extreme forecasts with longer lead times helps in adaptation and translating scientific knowledge into user-friendly products to the community is essential. There is a need for sustainability and adaptation to mitigate the adverse effects of climate change.

• Frequent international conferences, brainstorming sessions, and collaborative efforts of the observational and modeling community are conducted for improvement in extreme weather predictions and to formulate mitigation policies.

• Atmosphere–ocean coupling seems an important mechanism for the effects of stratosphere–troposphere interactions during the NH winter and spring to linger and influence summertime heat and precipitation extremes; it would be good to understand the extent and mechanisms of variability in the capacitor beyond the ENSO pacemaker paradigm.

4. Organizations represented at the workshop

The organizations represented at the workshop are as follows: European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), the Met Office (UKMO), National Centre for Medium Range Weather Forecasting (NCMRWF), and India Meteorological Department (IMD) and also from research institutes/universities such as the Forschungszentrum Jülich; Massachusetts Institute of Technology; National Center for Atmospheric Research; National Oceanic and Atmospheric Administration; Jet Propulsion Laboratory; Karlsruhe Institute of Technology (KIT), Germany; TROPOS Leipzig, Germany; Seoul National University, South Korea; the University of Iowa, United States; National Institute of Aerospace, United States; NASA, LaRC, United States; University of Oxford, United Kingdom; University of Reading, United Kingdom; University College London; Columbia University, United States; University of Texas, Austin, United States; Chiba University, Japan; MRI, JMA, Japan; Cornell University, United States; Environment and Climate Change Canada; IZMIRAN; Russian Academy of Sciences, Russia; Tsinghua University, China; National Central University, Taiwan; Goethe University Frankfurt, Germany; INPE, Brazil; University of Arizona, United States; Kagawa University, Japan; ARIES, Nainital, India; Indian Institute of Science, India; MoES, Delhi, India; IIT Delhi, India; IIT Kharagpur, India; IIT Bhubaneswar, India; IIIT West Bengal, India; IIT Indore, India; IIT Gandhinagar, India; IISER Bhopal, India; NARL, Gadanki, India; SRM Chennai; CUSAT, Kerala, India; University of Petroleum and Energy Studies, Dehradun, India; Space Application Centre, Ahmedabad, India; Indian Space Research Organization; Indian National Centre for Ocean Information Services (INCOIS); Krea University, Andhra Pradesh, India; WRLDC, Mumbai, India; and Indian Institute of Tropical Meteorology (IITM).