Chahan Michael Kropf

Last Name

Kropf

First Name

Chahan Michael

ORCID

0000-0002-3761-2292

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09576 - Bresch, David Niklaus / Bresch, David Niklaus

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Publications1 - 10 of 23

Climate overshoot implications for local adaptation planning
Theokritoff, Emily; Lejeune, Quentin; Costa, Hugo P.; et al. (2025)
Climate Policy
As global warming increases, the topic of overshoot, understood as the temporary exceedance of the 1.5℃ limit of the Paris Agreement, is gaining prominence both in scientific and political spheres. However, overshoot and its implications for adaptation in the short - and long-term remain unexplored. In this Perspective, we reflect on the current use of global climate scenarios and local impact projections in science-based adaptation planning. The risks arising from overshoot scenarios in relation to the transgression of limits to adaptation and impact irreversibility are highlighted. We find that the prospects of potential long-term impact reversibility may have limited relevance in most adaptation decision-making contexts, indicating that it might be peak warming, rather than a long-term outcome, that determines adaptation needs and costs. While overshoot may not be relevant for short-term planning, it should be considered for long-term plans and policies, for example for infrastructure-based measures and for irreversible impacts such as sea-level rise. Key insights from adaptation practitioners in four diverse urban vulnerability contexts (Bod & oslash;, Lisbon, Nassau, Islamabad) are presented on how these risks are perceived and integrated (or not) into local planning and policy-making. We find that current adaptation planning must be extensively evaluated against a wider set of future global climate outcomes to incorporate risks of transgression of local limits to adaptation and overshoot. To this end, data gaps on adaptation limits and impact reversibility need to be filled and capacity building needs on climate scenarios, overshoot and related concepts for local adaptation practitioners should be addressed.
Uncertainty and sensitivity analysis for probabilistic, global modelling of future tropical cyclone risk
Meiler, Simona; Ciullo, Alessio; Bresch, David N.; et al. (2023)
14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)
Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, growing economies, evolving societies, and declining ecosystems. Here we apply a new feature of the CLIMADA climate risk modelling platform, which allows carrying out global uncertainty and sensitivity analysis. We showcase the comprehensive treatment of uncertainty and sensitivity of CLIMADAﾒs outputs for the assessment of future global tropical cyclone (TC) risk. Our results show that socio-economic development contributes more strongly to TC risk increase in the future and is a more uncertain risk driver than climate change. Besides, we find that exposure scaling based on the Shared Socioeconomic Pathways (SSP) is the input variable with the most significant impact on TC risk change calculations. In conclusion, we argue that a thorough and systematic assessment of future global TC risk will help focus forthcoming research efforts and enable better-informed adaptation decisions and mitigation strategies.
Climate-resilient strategy planning using the SWOT methodology: A case study of the Japanese wind energy sector
Bachmann, Lisa; Lex, Ricarda; Regli, Florian; et al. (2024)
Climate Risk Management
As climate change leads to more frequent and intense extreme weather events, industry stakeholders and policymakers must assess their business strategies, practices, and entire sector policies under these uncertain conditions. Much recent research has integrated quantitative climate risk modeling into frameworks to engage policymakers and inform adaptation decisions in a general way, but relatively little attention has been devoted to extending this to strategic business and investment decisions. This falls short of identifying economic opportunities and threats in a wider socio-economic context, such as the development of new technologies or evolving political and regulatory environments. Here, a methodology is developed to integrate quantitative climate risk modeling with SWOT analysis (strengths, weaknesses, opportunities, and threats) which is commonly used in business and investment strategic planning. This moves the focus from avoidance of negative outcomes to prospective planning in an evolving environment. This methodology is illustrated with a case study of the Japanese wind energy sector, using open-access data and the open-source climate risk-assessment platform CLIMADA. This Climate risk assessment indicates threats from increasing damages to the wind energy infrastructure, as well as the profitability of typhoon-resistant wind turbines under present and future climate. Expert interviews and extensive literature research on opportunities and threats, however, also show that the transition towards renewable energies faces restrictive market dynamics, political and social hurdles, which set external conditions surpassing physically-informed dimensions. Beyond this illustrative case study, the methodology developed here bridges established concepts in climate risk modeling and strategic management and thus can be used to identify industry-centric ways forward for climate-resilient planning across a wide range of economic sectors.
Navigating and attributing uncertainty in future tropical cyclone risk estimates
Meiler, Simona; Kropf, Chahan Michael; McCaughey, Jamie W; et al. (2025)
Science Advances
Future tropical cyclone risks will evolve with climate change and socioeconomic development, entailing substantial uncertainties. An uncertainty and sensitivity analysis of these risks is vital, yet the chosen model setup influences outcomes. This study investigates how much future tropical cyclone risks are driven by climate and socioeconomic changes, quantifies uncertainty from propagating alternate representations of these systems through the risk modeling chain, and evaluates how strongly each model input contributes to output uncertainty. By comparing these three elements—drivers, uncertainty, and sensitivity—across four distinct tropical cyclone models, we derive findings generalizable beyond individual model setups. We find that average tropical cyclone risk will increase 1 to 5% by 2050 globally, with maximum increases ranging from 10 to 400% by 2100, depending on tropical cyclone model choice, region, and risk model inputs, while the dominant source of uncertainty shifts with modeling choices. Last, we differentiate between aleatory, epistemic, and normative uncertainties, offering guidance to reduce them and inform better decision-making.
Impact-based forecasting of tropical cyclone-related human displacement to support anticipatory action
Kam, Pui Man; Ciccone, Fabio; Kropf, Chahan Michael; et al. (2024)
Nature Communications
Tropical cyclones (TCs) displace millions every year. While TCs pose hardships and threaten lives, their negative impacts can be reduced by anticipatory actions like evacuation and humanitarian aid coordination. In addition to weather forecasts, impact forecast enables more effective response by providing richer information on the numbers and locations of people at risk of displacement. We introduce a fully open-source implementation of a globally consistent and regionally calibrated TC-related displacement forecast at low computational costs, combining meteorological forecast with population exposure and respective vulnerability. We present a case study of TC Yasa which hit Fiji in December 2020. We emphasise the importance of considering the uncertainties associated with hazard, exposure, and vulnerability in a global uncertainty analysis, which reveals a considerable spread of possible outcomes. Additionally, we perform a sensitivity analysis on all recorded TC displacement events from 2017 to 2020 to understand how the forecast outcomes depend on these uncertain inputs. Our findings suggest that for longer forecast lead times, decision-making should focus more on meteorological uncertainty, while greater emphasis should be placed on the vulnerability of the local community shortly before TC landfall. Our open-source codes and implementations are readily transferable to other users, hazards, and impact types.
Global assessment of population exposure to multiple climate-related hazards from 2003 to 2021: a retrospective analysis
Stalhandske, Zélie; de Ruiter, Marleen C.; Chambers, Jonathan; et al. (2025)
The Lancet Planetary Health
Background: The climate crisis is increasingly recognised as a health crisis, driven in part by the growing frequency and intensity of climate-related hazards, such as heatwaves and wildfires. These hazards can coincide, potentially leading to compound impacts. However, little is known about where and how often such combinations occur globally. This study aims to map historical population exposure to multiple interacting climate-related hazards and identify regions that have been most affected. Methods: In this retrospective study, we analysed global data from the 2024 Lancet Countdown on health and climate change, International Best Track Archive for Climate Stewardship, The Inter-Sectoral Impact Model Intercomparison Project, and WorldPop from 2003 to 2021 at a 0·25° resolution to examine the population that was exposed to combinations of six climate hazards: heatwaves, droughts, wildfires (PM_(2·5)), extreme precipitation, river floods, and tropical cyclones. We identified administrative level 1 regions based on several hotspot definitions and did detailed case studies in the most exposed regions. Findings: We detail how frequently people at each grid point have been exposed to various combinations of hazards, revealing both regular patterns and rare, region-specific occurrences. Our analysis indicates an increase in per-person exposure to many hazards during the study period, with a more pronounced rise in multihazard exposure than single-hazards. Between 2003–12 and 2012–21, per-person exposure to three or more hazards increased by 69%. Heatwaves were the most common hazard and also showed the clearest trend, largely driving the observed increases in both single-hazard and multihazard exposure. Multihazard hotspots vary depending on the specific definition used. For instance, exposure to multiple hazards is explained by the seasonality of hazards, which leads them to co-occur in the same months. Additionally, incorporating specific vulnerable age groups into our analysis reveals hotspots that consider the sociodemographic characteristics of the regions. Interpretation: These findings highlight the importance of incorporating multihazards into climate and health risk assessments. Our study enables an examination of historical events to deepen our understanding of interactions between hazards. Given the rarity of many hazard combinations, traditional epidemiological methods might fall short. Thus, alternative approaches, such as storyline development, are essential to enhance our preparation for future multihazard occurrences. This work finally serves as a crucial baseline future multihazard risk assessment under different climate and socioeconomic scenarios.
Open Quantum Systems’ Decay across Time
Klatt, Juliane; Kropf, Chahan Michael; Buhmann, Stefan Y. (2021)
Physical Review Letters
The description of an open quantum system’s decay almost always requires several approximations so as to remain tractable. In this Letter, we first revisit the meaning, domain, and seeming contradictions of a few of the most widely used of such approximations: (semigroup) Markovianity, linear response theory, Wigner-Weisskopf approximation, and rotating-wave approximation. Second, we derive an effective time-dependent decay theory and corresponding generalized quantum regression relations for an open quantum system linearly coupled to an environment. This theory covers all timescales and subsumes the Markovian and linear-response results as limiting cases. Finally, we apply our theory to the phenomenon of quantum friction. © 2021 American Physical Society
Uncertainty and sensitivity analysis for probabilistic weather and climate-risk modelling: an implementation in CLIMADA v.3.1.0
Kropf, Chahan Michael; Ciullo, Alessio; Otth, Laura; et al. (2022)
Geoscientific Model Development
Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, evolving societies, growing economies, and declining ecosystems. Here, we present a new feature of the climate-risk modelling platform CLIMADA (CLIMate ADAptation), which allows us to carry out global uncertainty and sensitivity analysis. CLIMADA underpins the Economics of Climate Adaptation (ECA) methodology which provides decision-makers with a fact base to understand the impact of weather and climate on their economies, communities, and ecosystems, including the appraisal of bespoke adaptation options today and in future. We apply the new feature to an ECA analysis of risk from tropical cyclone storm surge to people in Vietnam to showcase the comprehensive treatment of uncertainty and sensitivity of the model outputs, such as the spatial distribution of risk exceedance probabilities or the benefits of different adaptation options. We argue that broader application of uncertainty and sensitivity analysis will enhance transparency and intercomparison of studies among climate-risk modellers and help focus future research. For decision-makers and other users of climate-risk modelling, uncertainty and sensitivity analysis has the potential to lead to better-informed decisions on climate adaptation. Beyond provision of uncertainty quantification, the presented approach does contextualize risk assessment and options appraisal, and might be used to inform the development of storylines and climate adaptation narratives.
A generalized natural hazard risk modelling framework for infrastructure failure cascades
Mühlhofer, Evelyn; Koks, Elco E.; Kropf, Chahan Michael; et al. (2023)
Reliability Engineering & System Safety
Critical infrastructures are more exposed than ever to natural hazards in a changing climate. To understand and manage risk, failure cascades across large, real-world infrastructure networks, and their impact on people, must be captured. Bridging established methods in both infrastructure and risk modelling communities, we develop an open-source modelling framework which integrates a network-based interdependent infrastructure system model into the globally consistent and spatially explicit natural hazard risk assessment platform CLIMADA. The model captures infrastructure damages, triggers failure cascades and estimates resulting basic service disruptions for the dependent population. It flexibly operates on large areas with publicly available hazard, exposure and vulnerability information, for any set of infrastructure networks, hazards and geographies of interest. In a validated case study for 2018’s Hurricane Michael across three US states, the model reproduced important failure dynamics among six infrastructure networks, and provided a novel spatial map where people were likely to experience disruptions in access to healthcare, loss of power and other vital services. Our generalized approach allows for a view on infrastructure risks and their social impacts also in areas where detailed information and risk assessments are traditionally scarce, informing humanitarian activities through hotspot analyses and policy frameworks alike.
Mangroves and their services are at risk from tropical cyclones and sea level rise under climate change
Hülsen, Sarah; Dee, Laura E.; Kropf, Chahan Michael; et al. (2025)
Communications Earth & Environment
Climate change is expected to alter the frequency and intensity of extreme events, modifying the natural disturbance regimes to which ecosystems are adapted. Here, we present a spatially explicit risk index for mangroves and associated biodiversity and ecosystem services based on projected frequency changes of tropical cyclone wind speeds and rates of relative sea level rise under SSPs 245, 370 and 585 by 2100. Globally, approximately half of the total mangrove area (40–56% depending on the SSP) will be at high to severe levels of risk due to climate-modified tropical cyclone disturbance regimes. Further, we find mangrove areas with high levels of biodiversity and ecosystem services provision, including coastal protection for people and assets, carbon sequestration, and fishery benefits, are at proportionally higher levels of risk. Our findings emphasize the need to anticipate changes in natural disturbance regimes and adapt ecosystem management to sustain mangroves and their services in the future.

Publications1 - 10 of 23

Chahan Michael Kropf

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