Bio

I am a weather and climate risk scientist, studying how hazard, exposure, and vulnerability interact to shape the risks and impacts of extreme weather events – both today and in a changing climate. My work combines modeling and systems thinking to explore a range of topics, including tropical cyclone risk, uncertainty and sensitivity analysis, human displacement, post-disaster recovery, and systemic risk. My approach is inherently interdisciplinary, with the goal of translating model insights into real-world applications that support climate-resilient decision-making.

I am currently a postdoctoral researcher at Stanford University, supported by an SNSF Postdoc.Mobility fellowship, working with Prof. Jack W. Baker. I completed my PhD at ETH Zurich in weather and climate risk modeling, with a focus on global tropical cyclone risk and uncertainty quantification, under the supervision of Prof. David N. Bresch.

Stanford Advisors

Contact

  • Academic
    smeiler@stanford.edu
    University - Scholar Department: Civil and Environmental Engineering Position: Postdoctoral Scholar

Additional Info

  • Mail Code: 4020

Links

2024-25 Courses

All Publications

  • Global coastal wind hazard maps from the CHAZ tropical cyclone model. Scientific data Meiler, S., Lee, C., Camargo, S. J., Sobel, A. H. 2026

    Abstract

    Synthetic tropical cyclone (TC) models have become essential tools for assessing TC hazard and risk, due to both the shortness of observational records and, now, the influence of climate change. However, the direct output from these models, TC track sets, requires additional processing to become useful for impact assessments beyond traditional climate science and meteorological research. Converting TC tracks into hazard maps condenses complex information on TC intensity and frequency into widely accessible formats, facilitating diverse impact analyses. Here, we present global coastal wind risk maps generated using the Columbia TC hazard model (CHAZ) for both present-day and future climate conditions. Climate scenario-driven data are provided for a recent historical period (1995-2014) and two future periods, mid-century (2041-2060) and end-of-century (2081-2100); a reference data set downscaled from an observation-based reanalysis for 1981-2019 is also provided. These hazard maps depict TC intensity exceedance probabilities and return periods, providing valuable insights to policymakers, planners, and researchers focused on disaster preparedness.

    View details for DOI 10.1038/s41597-025-06452-0

    View details for PubMedID 41547699

  • A natural hazard risk modelling approach to human displacement - frontiers & challenges ENVIRONMENTAL RESEARCH-CLIMATE Meiler, S., Muhlhofer, E., Luthi, S., Bresch, D. N., Ottonelli, D., Ghizzoni, T., Trasforini, E., Rudari, R., Rossi, L., Kasmalkar, I., Mohammadiamanab, N., Daou, D., Nguyen, T., Gyawali, D., Peter, M., Oakes, R., Souvignet, M., Ponserre, S. 2025; 4 (4)

    View details for DOI 10.1088/2752-5295/ae014c

    View details for Web of Science ID 001577031600001

  • Beyond single company climate risk disclosure: event-based physical risk reporting ENVIRONMENTAL RESEARCH-CLIMATE Hakansson, V., Meiler, S., Hulsen, S., Villiger, L., Bossut, M., McCaughey, J. W., Kropf, C. M., Bresch, D. N. 2025; 4 (3)

    View details for DOI 10.1088/2752-5295/adf912

    View details for Web of Science ID 001555843400001

  • Extreme weather event attribution predicts climate policy support across the world NATURE CLIMATE CHANGE Cologna, V., Meiler, S., Kropf, C. M., Luethi, S., Mede, N. G., Bresch, D. N., Lecuona, O., Berger, S., Besley, J., Brick, C., Joubert, M., Maibach, E. W., Mihelj, S., Oreskes, N., Schaefer, M. S., van der Linden, S., TISP Consortium 2025; 15 (7): 725-735

    Abstract

    Extreme weather events are becoming more frequent and intense due to climate change. Yet, little is known about the relationship between exposure to extreme events, subjective attribution of these events to climate change, and climate policy support, especially in the Global South. Combining large-scale natural and social science data from 68 countries (N = 71,922), we develop a measure of exposed population to extreme weather events and investigate whether exposure to extreme weather and subjective attribution of extreme weather to climate change predict climate policy support. We find that most people support climate policies and link extreme weather events to climate change. Subjective attribution of extreme weather was positively associated with policy support for five widely discussed climate policies. However, exposure to most types of extreme weather event did not predict policy support. Overall, these results suggest that subjective attribution could facilitate climate policy support.

    View details for DOI 10.1038/s41558-025-02372-4

    View details for Web of Science ID 001520711300001

    View details for PubMedID 40641510

    View details for PubMedCentralID PMC12237696

  • Mangroves and their services are at risk from tropical cyclones and sea level rise under climate change COMMUNICATIONS EARTH & ENVIRONMENT Hulsen, S., Dee, L. E., Kropf, C. M., Meiler, S., Bresch, D. N. 2025; 6 (1)

    View details for DOI 10.1038/s43247-025-02242-z

    View details for Web of Science ID 001459313500001