Both grappling with an unpredictable climate crisis, India and Europe are learning to join forces, leveraging shared tools and expertise to advance science and better prepare for potential futures. An international project brings together seven EU countries and India in a spirit of equitable, multidisciplinary collaboration.
The unprecedented atmospheric levels of CO₂ and other greenhouse gases, coupled with 2024 officially becoming the hottest year on record since 1850 – recently confirmed by the Copernicus Climate Change Service – are not opening lines of a dystopian novel. When global temperatures surpassed pre-industrial levels by 1.5°C, we crossed the critical threshold established in 2015 by the Paris Accords to mitigate climate risks and impacts. The future we now face demands rewriting, aspiring toward the brighter vision we once hoped for in 2025.
Beginning anew always carries responsibility; today, we must shoulder the task of eliminating policy uncertainties and reducing scientific unknowns as much as possible. Collaboration is imperative – not only among individuals, nations, and communities but also with technology. It is justified and essential to highlight and monitor technology’s harmful impacts on climate and human rights, yet equally important is recognizing and harnessing its strengths. A compelling example, strong enough to quiet those resigned to an apocalyptic future, is the collaboration between India, Europe, and machine learning.
TAKEAWAYS
GANANA Project “forces”
The most complex and often questioned role is that of machine learning, the technology underpinning artificial intelligence. If properly utilized, machine learning can significantly enhance the alignment between complex climate models and real-world observations. It has successfully united Europe and India, merging each region’s strengths into a groundbreaking climate research project.
This collaboration is embodied in the GANANA project, aiming to minimize uncertainty and eliminate excuses for climate inaction. Recently launched, its potential global impact is immense. Funded by EuroHPC JU with a €5 million budget from the Horizon Europe program, GANANA aims to establish a foundation for sustained collaboration addressing urgent global challenges.
Climate and environmental issues top the priority list, harnessing the combined HPC computing capabilities of Europe’s leading pre-exascale supercomputers – LUMI in Finland, LEONARDO in Italy, and MareNostrum 5 in Spain. The team, coordinated by Kungliga Tekniska Högskolan (Sweden), includes five Indian universities and research institutes, along with six European centers from France, Spain, Finland, Germany, the Netherlands, and Italy (CINECA and the Euro-Mediterranean Center on Climate Change Foundation – CMCC).
Calculating potential climates
To jointly address climate emergencies daily, Europe and India facilitate exchanges of expertise and integration of research agendas, while simultaneously developing HPC software applications. This is crucial for significant advances “in studying increasing extreme events such as heatwaves, heavy rainfall, and accelerating sea-level rise along coastlines,” explains Swapna Panickal, a climate researcher at the Indian Institute of Tropical Meteorology.
“In India, uncertainties surrounding regional climate projections and monsoon behaviors under warming scenarios add complexity,” Panickal adds. Europe faces similar issues, as highlighted by Paola Mercogliano, an expert from CMCC: “We increasingly encounter phenomena previously unseen in our regions, phenomena current models cannot always adequately represent.”
Both regions, each for similar yet locally distinct reasons, identify two primary needs: a deeper understanding of climate processes and improved model representation of poorly understood phenomena.
This dual challenge, focused centrally on climate, is being tackled collaboratively, combining new HPC technologies with climate expertise. India’s regional climate knowledge and expertise in developing high-resolution models, especially concerning monsoons, complement Europe’s robust computing infrastructure essential for supporting machine learning advancements in climate modeling. Panickal emphasizes, “Today, integrating these disciplines and skills stands out as one of the most promising pathways for enhancing Earth system understanding and reducing climate projection uncertainties.”
Imagining a robust future
The strength of this partnership will soon be evident from GANANA’s initial outcomes. Expected developments include “hybrid Earth Systems Models (ESMs) integrating physical modeling, machine learning, and climate science; correcting biases in model outputs for temperature, precipitation, and winds; and downscaling global climate projections to finer spatial resolutions specific to India”, Panickal explains.
Mercogliano further elaborates on the shared ambition “to employ machine learning in detecting and attributing extreme events like sea-level rise, extreme rainfall, and Indian Ocean warming, alongside enhancing traditional modeling approaches to analyze complex, nonlinear systems, especially climate projections and ocean-climate interactions.”
Though technically complex, these efforts carry universal benefits. Improving regional climate projection robustness through innovative modeling, whether in India or Europe, facilitates more effective long-term climate adaptation policy planning. Machine learning particularly holds promise to “capture intricate relationships and enhance model interpretability, crucial for long-term climate risk assessments,” Mercogliano highlights. Both researchers have in mind frequent extreme events in previously unaffected European areas and evolving Indian climate challenges. Joint research publications and co-developed climate tools with broad global applicability are central goals.
Beyond Geographic and Gender Barriers
To increase collaborative research publications on long-term climate variability and change across South Asia and the Euro-Mediterranean region, project partners will organize joint workshops, academic exchanges, and continuous training initiatives. Panickal underscores the importance of creating a new generation of climate modelers skilled in data science and machine learning applications, a priority equally crucial for Europe. Wherever climate uncertainty persists, the need for integrated expertise will grow.
Addressing this necessity will involve interdisciplinary training programs blending machine learning with earth system science, enhanced computational resource access, and standardized workflows. More effective collaborative platforms will further facilitate peer learning and knowledge exchange, irrespective of geographic distances. Mercogliano, enthusiastically highlighting GANANA’s climate-oriented focus, also notes an additional lesson Europe, particularly Italy, could adopt from India—the pronounced gender parity in research teams: “During our visit to India earlier this year, the gender balance was strikingly evident. They explained this naturally arises from powerful female role models like Indira Gandhi and Sonia Gandhi, who continue to inspire equity today.”
