Investing in climate modeling for effective climate action

To have the tools that will make it possible to undertake measures to mitigate and adapt to climate change, a major investment is necessary in climate modeling: this is the message developed in this post by Masa Kageyama and Samuel Morin, specialists in climate science.

Climate change poses immense challenges to human societies, questioning their development, their resilience and ultimately their sustainability. As the recent reports of the Intergovernmental Panel on Climate Change (IPCC) have reminded us, the next two decades will be crucial for limiting the escalation of climate risks. However, climate action cannot be effective without insights into climate services adapted to societal needs. However, only a massive and urgent investment in climate modeling and the estimation of the impacts of climate change, mobilizing a wide range of actors and scientific disciplines, will make it possible to benefit without delay from new technological advances (calculation, artificial intelligence, …) and conceptual.

Climate services: essential tools

With the multiplication of extraordinary extreme events, climate change is now manifest. New conditions, even more extraordinary, are unfortunately to be expected in the decade to come. To deal with it, the tools to anticipate the impact of climate change and reduce its negative impacts must be developed without delay. Made public on February 28, 2022, the IPCC report on impacts, adaptation and vulnerability demonstrates the importance of tools to support political decision-making to implement climate action. As essential as the IPCC reports are as a knowledge base on which the global alert is based, they are not – and will never be – sufficient to implement, at the territorial level, the actions that calls for the urgency of the situation. Among these tools, climate services are crucial tools.

By climate services, we mean “all the information and services that make it possible to assess and qualify the past, present or future climate, to assess the vulnerability of economic activities, the environment and society to climate change, and to provide elements for undertaking mitigation and adaptation measures. They constitute in a way an operational translation (institutional or commercial) of studies on climate change and its impacts, in a highly interdisciplinary context calling for co-construction with all stakeholders.

Their emergence and their scaling up are therefore essential to allow actors from all territories and socio-economic domains to understand the consequences of climate change on all sectors, scales, and temporalities concerning them. But above all, they are essential for identifying the action levers to be implemented in the very short term to deal with them.

Develop, consolidate and amplify climate services

One example among many, the climate service ClimSnow, operated by the Dianeige study office, Météo-France and in collaboration with Inrae, makes it possible to quantify the impact of past and future climate change on the operating conditions of ski areas. Resulting from more than a decade of interdisciplinary research work, it takes into account snow management practices (grooming, snow production) in climate projections of snow cover, and thus contributes to reflections on the transitions of tourism in Mountain.

Current mapping of ClimSnow studies (climate service operated by Dianeige, Météo-France and in conjunction with the CNRS) in French winter sports resorts.

To produce relevant climate information, the cross-referencing of data characterizing the evolution of the physical climate and the evaluation of its consequences for human and natural systems is therefore essential. This must mobilize a wide range of scientific disciplines, including the humanities and social sciences, the natural sciences in all their dimensions, and high-performance scientific computing applied to climate modelling.

The emergence of regional groups of experts on climate change (Greeks) illustrates the possibility of collectively producing territorial climate information by combining complementary disciplines and expertise. Energy, agriculture, health, urban environments: other examples demonstrate, at varying degrees of maturity, such potential, in multiple sectors. However, many scientific, technical and organizational challenges limit the scaling up of such a dynamic. The implementation of effective adaptation can only be achieved at the cost of the development of these climate services, backed by climate models.

Progress in climate modelling, a crucial issue

Concentrating the highest technology available and based on decades of scientific developments in a highly collaborative framework, numerical climate models are essential tools for understanding and anticipating climate impacts and risks. Initially developed in a research framework for the needs of large-scale modeling and to improve understanding of climate change, they are our country’s key assets for implementing climate services. But in order to better use them for these new needs and feed climate action with relevant information, it is essential to continue to advance them on the scientific and technical levels.

Indeed, the current climate modeling tools do not yet allow fine characterization of the speed and scale of climate change of the most extreme phenomena operating at the local scale (heat waves, intense precipitation, combination of extremes), or the link between the water cycle, carbon and other critical elements for the habitability of environments. Physical representations of small-scale processes must also progress, as well as those of the impact of these processes on large-scale ones. The integration of new components of the climate system, such as the polar caps, must also be carried out in order to anticipate the rise in sea level and the impact of interactions with atmospheric and oceanic processes on the local sea level, for example during storms or cyclones.

Investing in climate modeling for effective climate action

Simulation of ocean, atmospheric, and land surface model grids.

Moreover, technological advances in supercomputing and the development of artificial intelligence – although there are so many opportunities to be seized to improve models and accelerate the production of knowledge – pose a risk to their sustainability. Indeed, due to their scientific and technical complexity, these numerical models, which can reach several million lines of code, cannot be adapted to these new architectures and computing paradigms without substantial dedicated resources.

The next few years will therefore be decisive for the success of the ramp-up in the production of relevant climate information, adapted to the challenges and their carriers, a key factor in being able to contribute effectively to the ecological transition, and to identify and implement the actions of most effective adaptation, in France and abroad. But this increased power in the production of climate information will only be possible by substantially strengthening the human and technical resources of the communities involved in the development, evaluation and implementation of climate models. Sustaining these tools is the condition sine qua non the development of climate services for a more ambitious and effective adaptation trajectory. It would be paradoxical if France, whose excellence in the field of climate science and climate modeling is internationally recognized, could not place itself in the capacity to produce the climate services that will allow the adaptation of its territories, for lack of means efficient calculations or human resources necessary for the implementation of emerging digital technologies, and lack of the massification of the dialogue and the interdisciplinary construction essential to the co-production of this information.

The points of view, opinions and analyzes published in this section engage only their author(s). They do not constitute any position of the CNRS.

We would love to give thanks to the author of this short article for this outstanding material

Investing in climate modeling for effective climate action

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