The THERMA Lab studies human populations and ecological health systems facing unprecedented thermal extremes. Our goal is to understand the physical and physiological processes that shape risk, quantify mortality attribution, and build proactive resilience for a warming world.
Excess Thermal Mortality Attribution
Attributable to anthropogenic warming in urban micro-climates during peak heat events.
1.5B+
Hourly Reanalysis Points
42 Cities
Vulnerability Registry
We value robust epidemiological designs, high-resolution reanalysis datasets, and careful non-linear statistical inquiry to develop a deep, actionable understanding of the climate-health systems we study.
We use downscaled climate models, wearable biomonitoring sensors, health registry datasets, and distributed lag non-linear models (DLNM) to test hypotheses about how populations respond to shifting temperature extremes.
We are motivated by health justice in frontline communities. We prioritize open-source epidemiological tools, respectful community partnerships, and diverse perspectives that reflect the vulnerabilities of those most exposed.
We are driven when our models reveal counter-intuitive thresholds, compound multi-stressors (like wildfire smoke + extreme heat), or unexpected adaptations. Non-linear findings motivate our most transformative scientific discoveries.
Our lab introduces a novel probabilistic attribution pipeline linking regional climate reanalysis with hospital cardiovascular emergency admissions.
Joining us from Oxford's Environmental Change Institute, Dr. Chen brings world-class expertise in compound heat-humidity indices and thermal resilience modeling.
An open-source interactive mapping toolkit designed for municipal health departments to pinpoint hyper-local microclimates and prioritize cooling centers.
Populations worldwide are confronting unprecedented extremes in their thermal environments, and their physiological and infrastructural capacities will dictate the future burden of preventable mortality.
We study if, when, and where communities mitigate, adapt to, or succumb to shifting temperature distributions to better understand who is most vulnerable to climate-mediated shocks. While our models evaluate fine-scale metropolitan and rural cohorts, our attribution framework yields general insights that broadly inform national health adaptation plans.
“The best dispositions for understanding, believing, and persuading … are curiosity, open-mindedness, and empirical rigor.”
We aim to understand the mechanisms that shape how human populations tolerate extreme thermal stress and adapt to accelerating climate disruption using spatial statistics, counterfactual climate simulations, and health registry datasets.
We combine short-term acute exposure models, multi-decadal epidemiological cohorts, earth system models, and computational attribution algorithms to address core questions about public health resilience.
How much of an observed heatwave's excess health burden can be formally attributed to human-induced climate change? We couple counterfactual climate model ensembles (World Weather Attribution pipelines) with non-linear distributed lag health models to calculate attributable fractions for emergency visits and cause-specific mortality.
Simulating factual vs. non-warming counterfactual worlds across 500+ global administrative districts.
Temperature is not distributed equally within cities. Historic redlining, lack of canopy cover, and impermeable surfaces create micro-heat islands with 10°F to 15°F differentials. We fuse high-resolution ECOSTRESS satellite land surface temperatures with socioeconomic deprivation indices to highlight equity gaps in heat exposure.
Meter-scale thermal vulnerability atlases delivered directly to urban planners and municipal cooling centers.
Extreme temperatures rarely occur in isolation. When heat domes trap particulate matter (PM2.5) or coincide with dangerous wet-bulb temperatures, physiological thresholds collapse much faster. Our group models synergisms between air stagnation, wildfires, and heatwaves.
Multi-hazard vulnerability curves to protect outdoor workers and sensitive populations.
High-resolution reanalyses
Parallel Bayesian pipelines
Global epidemiology cohorts
FAIR data and open code
We are motivated by a genuine curiosity about climate dynamics and human wellbeing, and prioritize responsible, careful, and respectful science. We embrace different perspectives and value the unique strengths that each person brings to our lab.
(she/her)
Director & Associate Professor
My research focuses on understanding the multi-scale processes that govern how extreme weather and thermal anomalies affect public health. Before establishing the THERMA Lab, I was an environmental health fellow at Harvard and a climate modeling research scientist at NCAR.
“Outside the lab, I love trail running at sunrise, hand-pour coffee, reading speculative fiction, and restoring native prairie grasses.”
Postdoctoral fellows, doctoral candidates, and research data specialists.
NSF Postdoctoral Fellow
(she/her)
I am an atmospheric scientist and epidemiologist. My research focuses on how adaptations to microclimates influence larger-scale heat vulnerability trends in metropolitan areas.
Free time: cycling mountain passes, ceramic pottery, and espresso brewing.
PhD Candidate & Fellow
(he/him)
I study spatiotemporal mortality patterns during compounding events (heatwaves + wildfires). I leverage high-performance computing and Bayesian hierarchical modeling.
Free time: backcountry climbing, analog synthesizers, and reading history.
PhD Student
(she/her)
I am interested in how social infrastructure and mutual aid networks modify heat-risk outcomes among elderly cohorts and individuals with pre-existing conditions.
Free time: sourdough baking, trail running, and tending to house plants.
Lead Scientific Programmer
(he/him)
I engineer data pipelines bridging terabytes of satellite thermal sensors and meteorological grids into clean reproducible R and Python packages for public use.
Free time: retro video gaming, cycling, and film photography.
Graduate Researcher
(she/her)
Exploring biological stress responses under acute heat waves using wearable biometric monitors and localized sensor networks in community centers.
Free time: playing the saxophone, gravel biking, and baking.
Lab Alum → Assistant Professor
(they/them)
Former THERMA postdoc, now directing their own environmental health and climate justice lab at the University of Washington. Ongoing collaborator on global heat indices.
Free time: kayaking Puget Sound and mentoring young scientists.
Our lab takes a unique, highly quantitative approach to asking urgent questions about health risk in variable environments. We are always enthusiastic about interdisciplinary partnerships.
Discover our latest peer-reviewed publications, awards, conference presentations, and team announcements.
Our comprehensive attribution study quantifies that over 37% of warm-season heat-related cardiovascular deaths in 43 countries can be traced directly to human-induced global heating.
We are thrilled to welcome Dr. Eliza Chen, who was recently awarded a highly competitive NSF Postdoctoral Research Fellowship to advance compound heatwave and wet-bulb mortality metrics.
The open-source R package and interactive web dashboard `thermaRisk` allows public health departments to compute localized temperature thresholds and estimate attributable disease burdens.
Congratulations to Marcus for securing four years of doctoral funding from the Department of Energy to run extreme weather simulations on leadership-class supercomputers!
Examining how lingering sub-lethal heat exposures compound over consecutive nights, depleting human cardiovascular reserves and driving delayed hospital admissions.
We could not be prouder to celebrate Dr. Kottler launching their independent research program in climate equity. We look forward to many years of fruitful inter-lab collaboration.
Our papers combine physical climatology, observational epidemiology, and statistical attribution. For a full repository, find us on Google Scholar.
Vance, K.C., E. Chen, M. Reed, and A. Ortiz. 2026. The Lancet Planetary Health 10(4): e214-e228.
Using extreme factual and counterfactual simulations across 43 countries, we demonstrate that anthropogenic forcing explains 37.2% of global heat-attributable excess mortality during peak warm seasons, highlighting wide regional inequities between industrialized and developing regions.
Chen, E., S. Khan, K. Bardsley, and K.C. Vance. 2025. Nature Climate Change 15: 890–901.
A multi-city longitudinal cohort study analyzing nighttime minimum temperatures and distributed lag non-linear effects over 14-day observation windows following major heat domes.
Ortiz, A., M. Reed, and K.C. Vance. 2024. Environmental Health Perspectives 132(6): 067004.
Combining ECOSTRESS thermal measurements with US census tract socioeconomic vulnerability matrices, revealing persistent 4.8°C thermal penalties in historically redlined neighborhoods.
Reed, M., D. Kottler, and K.C. Vance. 2023. Global Change Biology 29(18): 5120-5134.
A multi-risk attribution algorithm decomposing excess risk between fine particulate matter (PM2.5) inhalation and acute thermoregulatory collapse.
We use the literature to motivate our questions and hypotheses, but rely on rigorous modeling, high-frequency sensor verification, patience, and diverse perspectives to develop a deep understanding of thermal risk.
Every year our lab revisits and revises our Lab Expectations Charter to nurture a collaborative, inclusive, and mentally sustainable research culture.
Every person is safe and respected in our lab. Each perspective brings essential lived insights to our epidemiological inquiries.
We prioritize reproducible code, rigorous sensitivity tests, and open data sharing with community stakeholders.
When data confound our initial models, we lean in. Novel discoveries often spring from anomalous residuals.
Postdocs interested in co-writing proposals with Dr. Vance (e.g., NSF PRFB, NIH F32, or Marie Skłodowska-Curie) are encouraged to reach out at least 4 months prior to funding deadlines. We are especially looking for scholars with expertise in climate attribution algorithms, spatiotemporal statistics, and health economics.
Prospective PhD students can apply through the Interdisciplinary Environmental Health Sciences and Data Science graduate programs. If you love spatial modeling, R/Python programming, and planetary health, we’d love to review your introductory inquiry.
We frequently have opportunities for undergraduates to gain hands-on experience processing satellite thermal data, maintaining weather sensors, and building interactive GIS web maps.
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