Yann Quilcaille

Last Name

Quilcaille

First Name

Yann

ORCID

0000-0002-1474-0144

Organisational unit

03778 - Seneviratne, Sonia / Seneviratne, Sonia

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Publications 1 - 10 of 15

Extending MESMER-X: a spatially resolved Earth system model emulator for fire weather and soil moisture
Quilcaille, Yann; Gudmundsson, Lukas; Seneviratne, Sonia I. (2023)
Earth System Dynamics
Climate emulators are models calibrated on Earth system models (ESMs) to replicate their behavior. Thanks to their low computational cost, these tools are becoming increasingly important to accelerate the exploration of emission scenarios and the coupling of climate information to other models. However, the emulation of regional climate extremes and water cycle variables has remained challenging. The MESMER emulator was recently expanded to represent regional temperature extremes in the new "MESMER-X"version, which is targeted at impact-related variables, including extremes. This paper presents a further expansion of MESMER-X to represent indices related to fire weather and soil moisture. Given a trajectory of global mean temperature, the extended emulator generates spatially resolved realizations for the seasonal average of the Canadian Fire Weather Index (FWI), the number of days with extreme fire weather, the annual average of the soil moisture, and the annual minimum of the monthly average soil moisture. For each ESM, the emulations mimic the statistical distributions and the spatial patterns of these indicators. For each of the four variables considered, we evaluate the performances of the emulations by calculating how much their quantiles deviate from those of the ESMs. Given how it performs over a large range of annual indicators, we argue that this framework can be expanded to further variables. Overall, the now expanded MESMER-X emulator can emulate several climate variables, including climate extremes and soil moisture availability, and is a useful tool for the exploration of regional climate changes and their impacts.
Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100
Quilcaille, Yann; Batibeniz, Fulden; Ribeiro, Andreia F.S.; et al. (2023)
Earth System Science Data
Human-induced climate change is increasing the incidence of fire events and associated impacts on livelihood, biodiversity, and nature across the world. Understanding current and projected fire activity together with its impacts on ecosystems is crucial for evaluating future risks and taking actions to prevent such devastating events. Here we focus on fire weather as a key driver of fire activity. Fire weather products that have a global homogenous distribution in time and space provide many advantages to advance fire science and evaluate future risks. Therefore, in this study we calculate and provide for the first time the Canadian Fire Weather Index (FWI) with all available simulations of the 6th phase of the Coupled Model Intercomparison Project (CMIP6). Furthermore, we expand its regional applicability by combining improvements to the original algorithm for the FWI from several packages. A sensitivity analysis of the default version versus our improved version shows significant differences in the final FWI. With the improved version, we calculate the FWI using average relative humidity in one case and minimum relative humidity in another case. We provide the data for both cases while recommending the one with minimum relative humidity for studies focused on actual FWI values and the one with average relative humidity for studies requiring larger ensembles. The following four annual indicators, (i) maximum value of the FWI (fwixx), (ii) number of days with extreme fire weather (fwixd), (iii) length of the fire season (fwils), and (iv) seasonal average of the FWI (fwisa), are made available and are illustrated here. We find that, at a global warming level of 3 degrees C, the mean fire weather would increase on average by at least 66% in duration and frequency, while associated 1-in-10-year events would approximately triple in duration and increase by at least 31% in intensity. Ultimately, this new fire weather dataset provides a large ensemble of simulations to understand the potential impacts of climate change spanning a range of shared socioeconomic narratives with their radiative forcing trajectories over 1850-2100 at annual and 2.5 degrees x 2.5 degrees resolutions. The produced full global dataset is a freely available resource at https://doi.org/10.3929/ethz-b-000583391 (Quilcaille and Batibeniz, 2022) for fire danger studies and beyond, which highlights the need to reduce greenhouse gas emissions for reducing fire impacts.
Systematic attribution of heatwaves to the emissions of carbon majors
Quilcaille, Yann; Gudmundsson, Lukas; Schumacher, Dominik; et al. (2025)
Nature
Extreme event attribution assesses how climate change affected climate extremes, but typically focuses on single events. Furthermore, these attributions rarely quantify the extent to which anthropogenic actors have contributed to these events. Here we show that climate change made 213 historical heatwaves reported over 2000–2023 more likely and more intense, to which each of the 180 carbon majors (fossil fuel and cement producers) substantially contributed. This work relies on the expansion of a well-established event-based framework. Owing to global warming since 1850–1900, the median of the heatwaves during 2000–2009 became about 20 times more likely, and about 200 times more likely during 2010–2019. Overall, one-quarter of these events were virtually impossible without climate change. The emissions of the carbon majors contribute to half the increase in heatwave intensity since 1850–1900. Depending on the carbon major, their individual contribution is high enough to enable the occurrence of 16–53 heatwaves that would have been virtually impossible in a preindustrial climate. We, therefore, establish that the influence of climate change on heatwaves has increased, and that all carbon majors, even the smaller ones, contributed substantially to the occurrence of heatwaves. Our results contribute to filling the evidentiary gap to establish accountability of historical climate extremes.
Showcasing MESMER-X: Spatially Resolved Emulation of Annual Maximum Temperatures of Earth System Models
Quilcaille, Yann; Gudmundsson, Lukas; Beusch, Lea; et al. (2022)
Geophysical Research Letters
Emulators of Earth System Models (ESMs) are complementary to ESMs by providing climate information at lower computational costs. Thus far, the emulation of spatially resolved climate extremes has only received limited attention, even though extreme events are one of the most impactful aspects of climate change. Here, we propose a method for the emulation of local annual maximum temperatures, with a focus on reproducing essential statistical properties such as correlations in space and time. We test different emulator configurations and find that driving the emulations with global mean surface temperature offers an optimal compromise between model complexity and performance. We show that the emulations can mimic the temporal evolution and spatial patterns of the underlying climate model simulations and are able to reproduce their natural variability. The general design and the good performance for annual maximum temperatures suggest that the proposed methodology can be applied to other climate extremes.
Representing natural climate variability in an event attribution context: Indo-Pakistani heatwave of 2022
Nath, Shruti; Hauser, Mathias; Schumacher, Dominik L.; et al. (2024)
Weather and Climate Extremes
Attribution of extreme climate events to global climate change as a result of anthropogenic greenhouse gas emissions has become increasingly important. Extreme climate events arise at the intersection of natural climate variability and a forced response of the Earth system to anthropogenic greenhouse gas emissions, which may alter the frequency and severity of such events. Accounting for the effects of both natural climate variability and the forced response to anthropogenic climate change is thus central for the attribution. Here, we investigate the reproducibility of probabilistic extreme event attribution results under more explicit representations of natural climate variability. We employ well-established methodologies deployed in statistical Earth System Model emulators to represent natural climate variability as informed from its spatio-temporal covariance structures. Two approaches towards representing natural climate variability are investigated: (1) where natural climate variability is treated as a single component; and (2) where natural climate variability is disentangled into its annual and seasonal components. We showcase our approaches by attributing the 2022 Indo-Pakistani heatwave to human-induced climate change. We find that explicit representation of annual and seasonal natural climate variability increases the overall uncertainty in attribution results considerably compared to established approaches such as the World Weather Attribution Initiative. The increase in likelihood of such an event occurring as a result of global warming differs slightly between the approaches, mainly due to different assessments of the pre-industrial return periods. Our approach that explicitly resolves annual and seasonal natural climate variability indicates a median increase in likelihood by a factor of 41 (95% range: 6-603). We find a robust signal of increased likelihood and intensification of the event with increasing global warming levels across all approaches. Compared to its present likelihood, under 1.5 °C (2 °C) of global near-surface air temperature increase relative to pre-industrial temperatures, the likelihood of the event would be between 2.2 to 2.5 times (8 to 9 times) higher. We note that regardless of the different statistical approaches to represent natural variability, the outcomes on the conducted event attribution are similar, with minor differences mainly in the uncertainty ranges. Possible reasons for differences are evaluated, including limitations of the proposed approach for this type of application, as well as the specific aspects in which it can provide complementary information to established approaches.
Overconfidence in climate overshoot
Schleussner, Carl-Friedrich; Ganti, Gaurav; Lejeune, Quentin; et al. (2024)
Nature
Global emission reduction efforts continue to be insufficient to meet the temperature goal of the Paris Agreement. This makes the systematic exploration of so-called overshoot pathways that temporarily exceed a targeted global warming limit before drawing temperatures back down to safer levels a priority for science and policy. Here we show that global and regional climate change and associated risks after an overshoot are different from a world that avoids it. We find that achieving declining global temperatures can limit long-term climate risks compared with a mere stabilization of global warming, including for sea-level rise and cryosphere changes. However, the possibility that global warming could be reversed many decades into the future might be of limited relevance for adaptation planning today. Temperature reversal could be undercut by strong Earth-system feedbacks resulting in high near-term and continuous long-term warming. To hedge and protect against high-risk outcomes, we identify the geophysical need for a preventive carbon dioxide removal capacity of several hundred gigatonnes. Yet, technical, economic and sustainability considerations may limit the realization of carbon dioxide removal deployment at such scales. Therefore, we cannot be confident that temperature decline after overshoot is achievable within the timescales expected today. Only rapid near-term emission reductions are effective in reducing climate risks.
Reversal of the impact chain for actionable climate information
Pfleiderer, Peter; Frölicher, Thomas L.; Kropf, Chahan M.; et al. (2025)
Nature Geoscience
Escalating impacts of climate change underscore the risks posed by crossing potentially irreversible Earth and socioecological system thresholds and adaptation limits. However, limitations in the provision of actionable climate information may hinder an anticipatory response. Here we suggest a reversal of the traditional impact chain methodology as an end-user focused approach linking specific climate risk thresholds, including at the local level, to emissions pathways. We outline the socioeconomic and value judgement dimensions that can inform the identification of such risk thresholds. The applicability of the approach is highlighted by three examples that estimate the required CO2 emissions constraints to avoid critical levels of health-related heat risks in Berlin, fire weather in Portugal and glacier mass loss in High Mountain Asia. We argue that linking risk threshold exceedance directly to global emissions benchmarks can aid the understanding of the benefits of stringent emissions reductions for societies and local decision-makers.
CMIP6 simulations with the compact Earth system model OSCAR v3.1
Quilcaille, Yann; Gasser, Thomas; Ciais, Philippe; et al. (2023)
Geoscientific Model Development
Reduced-complexity models, also called simple climate models or compact models, provide an alternative to Earth system models (ESMs) with lower computational costs, although at the expense of spatial and temporal information. It remains important to evaluate and validate these reduced-complexity models. Here, we evaluate a recent version (v3.1) of the OSCAR model using observations and results from ESMs from the current Coupled Model Intercomparison Project 6 (CMIP6). The results follow the same post-processing used for the contribution of OSCAR to the Reduced Complexity Model Intercomparison Project (RCMIP) Phase 2 regarding the identification of stable configurations and the use of observational constraints. These constraints succeed in decreasing the overestimation of global surface air temperature over 2000-2019 with reference to 1961-1900 from 0.60±0.11 to 0.55±0.04gK (the constraint being 0.54±0.05gK). The equilibrium climate sensitivity (ECS) of the unconstrained OSCAR is 3.17±0.63gK, while CMIP5 and CMIP6 models have ECSs of 3.2±0.7 and 3.7±1.1gK, respectively. Applying observational constraints to OSCAR reduces the ECS to 2.78±0.47gK. Overall, the model qualitatively reproduces the responses of complex ESMs, although some differences remain due to the impact of observational constraints on the weighting of parametrizations. Specific features of OSCAR also contribute to these differences, such as its fully interactive atmospheric chemistry and endogenous calculations of biomass burning, wetlands CH4 and permafrost CH4 and CO2 emissions. Identified main points of needed improvements of the OSCAR model include a low sensitivity of the land carbon cycle to climate change, an instability of the ocean carbon cycle, the climate module that is seemingly too simple, and the climate feedback involving short-lived species that is too strong. Beyond providing a key diagnosis of the OSCAR model in the context of the reduced-complexity models, this work is also meant to help with the upcoming calibration of OSCAR on CMIP6 results and to provide a large group of CMIP6 simulations run consistently within a probabilistic framework.
Fire weather compromises forestation-reliant climate mitigation pathways
Jäger, Felix; Schwaab, Jonas; Quilcaille, Yann; et al. (2024)
Earth System Dynamics
Forestation can contribute to climate change mitigation. However, increasing frequency and intensity of climate extremes are posed to have profound impact on forests and consequently on the mitigation potential of forestation efforts. In this perspective, we critically assess forestation-reliant climate mitigation scenarios from five different integrated assessment models (IAMs) by showcasing the spatially explicit exposure of forests to fire weather and the simulated increase in global annual burned area. We provide a detailed description of the feedback from climate change to forest carbon uptake in IAMs. Few IAMs are currently accounting for feedback mechanisms like loss from fire disturbance. Consequently, many forestation areas proposed by IAM scenarios will be exposed to fire-promoting weather conditions and without costly prevention measures might be object to frequent burning. We conclude that the actual climate mitigation portfolio in IAM scenarios is subject to substantial uncertainty and that the risk of overly optimistic estimates of negative emission potential of forestation should be avoided. As a way forward we propose how to integrate more detailed climate information when modeling climate mitigation pathways heavily relying on forestation.
Increasing Fire Weather Season Overlap Between North America and Australia Challenges Firefighting Cooperation
Richardson, Doug; Ribeiro, Andreia F.S.; Batibeniz, Fulden; et al. (2025)
Earth's Future
The USA, Canada and Australia are members of an international partnership that shares firefighting resources, including equipment and personnel. This partnership is effective because fire risk between Australia and North America is historically asynchronous. However, climate change is causing longer fire seasons in both regions, increasing the likelihood of simultaneous fire risk and threatening the partnership's viability. We focus on spatially compounding fire weather as the annual number of days on which the fire seasons in Australia and North America overlap, investigating historical and future projections of fire weather season lengths. We use the Canadian Fire Weather Index and compute season length statistics using ERA5 reanalysis data together with historical and future projections from four CMIP6 single model initial-condition large ensembles. Our analysis shows that the length of fire weather season overlap between eastern Australia and western North America has increased by approximately one day per year since 1979. The interannual variability of overlap is driven primarily by the variability in Australia, with correlations between that region's fire weather season length and the degree of overlap exceeding 0.9. Composites of ERA5 and CMIP6 sea surface temperatures suggest a link between the interannual variability of overlap and the El Ni & ntilde;o-Southern Oscillation, despite this climate mode's opposing relationship with fire weather in the two regions. Finally, we find that the overlap is projected to increase by similar to ${\sim} $4 to similar to ${\sim} $29 days annually by 2050. We conclude that an increasing overlap of fire seasons is expected to constrain current resource-sharing agreements and shorten preparedness windows.

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Yann Quilcaille

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