About

Dr. Noah Diffenbaugh is the William Wrigley Professor and Kimmelman Family Senior Fellow in Stanford's Doerr School of Sustainability, as well as the Olivier Nomellini Family University Fellow in Undergraduate Education. His research focuses on understanding the aspects of the climate system that most directly and acutely impact people and ecosystems. He has served as a Lead Author for the Intergovernmental Panel on Climate Change (IPCC) and as Editor-in-Chief of the peer-reviewed journals Geophysical Research Letters and Environmental Research: Climate. Dr. Diffenbaugh has provided scientific expertise and testimony to Federal, State, and local officials. He holds a Ph.D. in Earth Sciences from the University of California, Santa Cruz, and both a B.S. and M.S. in Earth Systems from Stanford University. His professional achievements include being an elected Fellow of the American Geophysical Union (AGU), receiving the James R. Holton Award and William Kaula Award from the AGU, and being recognized as a Kavli Fellow by the U.S. National Academy of Sciences.

Research topics

• Geography
• Climatology
• Geology
• Oceanography
• Environmental science
• Ecology
• Environmental planning
• Environmental resource management
• Meteorology
• Development economics
• Atmospheric sciences
• Physical geography
• Economics
• Business
• Natural resource economics
• Economic growth
• Biology

Selected publications

• Extreme precipitation, exacerbated by anthropogenic climate change, drove Peru’s record-breaking 2023 dengue outbreak

  One Earth · 2026-03-17

  articleOpen access
  PublisherDOI

• Extreme climate events and transboundary effects of global crop trade

  Environmental Research Climate · 2026-01-15

  articleOpen accessSenior author

  Abstract Global warming is likely to increase the frequency of extreme climate events, triggering cascading effects in crop trade across country borders. When extreme events affect multiple trading partners simultaneously, the resulting exposure may aggregate through trade dependencies in ways that are not captured by single-location analyses. To address this gap, we develop a new metric that quantifies countries’ exposure as a trade-weighted fractional change in projected future climate extremes in trade partner countries. Our results show that, in a Mid-term period (2041–2060) exposure to hot events that occur abroad would increase nearly three times for 10% of countries via import of staple crops. Top sources of this imported exposure to remote extreme events are often major breadbaskets—including Australia and Russia—across hot, wet and dry events. Even in a Near-term period (2021–2040), twice as much exposure may be exported from these countries. Our findings show that extremes and trade can reinforce each other in a way that will substantially heighten exposure, and underscore the urgency of enhanced preparedness for interconnected climate risks.

  PublisherDOI

• Replication materials for "Valuing wildfire smoke-related mortality benefits from climate mitigation"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-01-01

  articleOpen access

  This repository is to support the peer-review process of the manuscript entitled “Valuing wildfire smoke related mortality benefits from climate mitigation”. The repo contains three R codes and can be used to reproduce the two main text figures. Data contained in this repo: final_GMST_combined_20yrmean.rds: calculated global mean surface temperature (GMST) for GCMs and scenarios used in our analysis. smoke_county_20yrmean_dynamic.rds: county-level projected smoke PM2.5 annual concentrations of future climate scenarios (fire-fuel feedback incorporated). historical_death_gmst_2011_2020_mean_lag1.xlsx: estimated deaths due to smoke PM2.5 during the historical period (2011-2020). summ_death_20years_2020_2099_2part_CRF_dynamic_lag1.rds: estimated deaths due to fire smoke PM2.5 under future climate scenarios (population pattern fixed at 2019, fire-fuel feedback incorporated). SC-CO2_2025pulse_2partcrf_2poly_dynamic_lag1.parquet: estimated social cost of carbon from wildfire smoke PM2.5 and other sectors originally considered in GIVE. The pulse emission year is 2025. GIVE_Smoke_Module_Final.zip: contains our modifications to the GIVE model with a newly developed module for estimating wildfire smoke damage.

  PublisherDOI

• Antarctic Ozone Loss Shapes Surface Cooling Pattern and Climate Sensitivity

  Research Square · 2026-01-13

  preprintOpen accessSenior author
  PublisherOA PDFDOI

• Acceleration

  Climate Change · 2026-04-15

  book-chapter1st authorCorresponding

  Climate change is accelerating, bringing with it more frequent and overlapping weather extremes such as heat waves, droughts, floods, wildfires, and storms. These events are already stretching the existing disaster response systems beyond their limits. In light of this reality, this chapter offers a sober, evidence-based description of what changes are necessary for humanity to adapt to a changing climate. Paradoxically, the fact that adaptation is already falling short is a sign that we’re going to need to rely on adaptation even more in the future. This is especially the case for marginalized communities that still lack access to the fundamental resources that ensure human well-being. We can respond by investing more in these communities, just as we also possess the scientific knowledge and technical capacities needed to keep pace with escalating climate risks and to accelerate both mitigation and adaptation. However, the chapter stresses that these efforts must unfold alongside the equally urgent tasks of expanding energy access and decarbonizing the global energy system, which is why we haven’t been able to overcome the climate challenge yet.

  PublisherDOI

• Quantifying climate loss and damage consistent with a social cost of carbon

  Nature · 2026-03-25

  articleOpen access

  Climate change is causing measurable harm globally1,2. Political and legal efforts seek to link these damages with specific emissions, including in discussions of loss and damage (L&D)3,4; however, no quantitative definition of L&D exists5,6, nor is there a framework to link past and future emissions from specific sources to monetized, location-specific damages. Here we develop such a framework, which is integrated with recent efforts to estimate the social cost of carbon7. Using empirical estimates of the non-linear relationship between temperature and aggregate economic output, we show that future damages from past emissions—one component of L&D—are at least an order of magnitude larger than historical damages from the same emissions. For instance, one tonne of CO2 emitted in 1990 caused US$180 in discounted global damages by 2020 ($40–530) and will cause an additional $1,840 through 2100 ($500–5,700). Thus, settling debts for past damages will not settle debts for past emissions. In other illustrative estimates, a single long-haul flight per year over the past decade leads to about $25k ($6,000–77,000) in future damages by 2100, and US emissions since 1990 caused $500 billion ($180–1,300 billion) of damage in India and $330 billion ($110–820 billion) in Brazil. Carbon removal offers an alternative to transfer payments for settling L&D, but is increasingly ineffective in limiting damages as the delay between emission and recapture increases. A new framework links specific emissions to monetized, location-specific climate damages, showing that future harms from past CO2 emissions far exceed historical damages and that delayed carbon removal cannot fully offset these losses.

  PublisherOA PDFDOI

• Replication materials for "Valuing wildfire smoke-related mortality benefits from climate mitigation"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-01-01

  articleOpen access

  This repository is to support the peer-review process of the manuscript entitled “Valuing wildfire smoke related mortality benefits from climate mitigation”. The repo contains three R codes and can be used to reproduce the two main text figures. Data contained in this repo: final_GMST_combined_20yrmean.rds: calculated global mean surface temperature (GMST) for GCMs and scenarios used in our analysis. smoke_county_20yrmean_dynamic.rds: county-level projected smoke PM2.5 annual concentrations of future climate scenarios (fire-fuel feedback incorporated). historical_death_gmst_2011_2020_mean_lag1.xlsx: estimated deaths due to smoke PM2.5 during the historical period (2011-2020). summ_death_20years_2020_2099_2part_CRF_dynamic_lag1.rds: estimated deaths due to fire smoke PM2.5 under future climate scenarios (population pattern fixed at 2019, fire-fuel feedback incorporated). SC-CO2_2025pulse_2partcrf_2poly_dynamic_lag1.parquet: estimated social cost of carbon from wildfire smoke PM2.5 and other sectors originally considered in GIVE. The pulse emission year is 2025. GIVE_Smoke_Module_Final.zip: contains our modifications to the GIVE model with a newly developed module for estimating wildfire smoke damage.

  PublisherDOI

• Stress testing insurance market stability under climate risk

  2026-04-01

  articleOpen access

  Extreme weather events exert increasing pressure on communities in hazard-prone areas and on the systems designed to protect them. Insurance serves as a risk-transfer mechanism, providing financial security for homeowners and supporting community resilience. Yet, behind this first layer of protection lies a complex web of reinsurers, capital markets, and public institutions that absorb and redistribute disaster risk. Intensifying climate hazards, continued coastal development, and evolving market dynamics threaten the stability of this network. Here, we develop a risk-propagation model to assess whether single or sequential tropical cyclones striking Florida could generate systemic financial stress across the property-insurance system. The model links physics-based, probabilistic simulations of tropical cyclone wind and flood losses with data on the Florida residential insurance market, its backstop mechanisms, and regulatory frameworks. By tracing how losses cascade as capital constraints and contractual thresholds bind, we evaluate systemic risk under present-day conditions, future climate scenarios, and alternative market and adaptation configurations within the same quantitative architecture. We estimate an annual 4\% probability that total public burden exceeds 1\% of Florida’s GDP, indicating that extreme tropical cyclone seasons can overwhelm private market capacity and shift costs to public institutions. Vulnerabilities differ across institutional layers, with post-insolvency mechanisms, residual markets, and the NFIP exhibiting greater sensitivity to extreme and sequential events than formal reinsurance limits. Although we focus on Florida in this proof-of-concept study, this approach provides a transferable template for quantitatively stress-testing insurance systems and evaluating how climate change, market dynamics, and adaptation strategies reshape systemic disaster risk.

  PublisherOA PDFDOI

• The debt burden of tropical cyclones and climate change

  2026-01-29

  articleOpen accessSenior author

  Addressing climate change, through both mitigation and adaptation, is anticipated to require global investments of more than $6 trillion annually by 2035. However, many countries face significant barriers to accessing the finance needed for these investments, due to low or absent credit ratings, large debt burdens, and high borrowing costs. There is concern that climate change, through its economic impacts, may amplify these barriers, potentially locking countries into a “vicious cycle” in which mounting economic losses further constrain countries' capacity to invest in adaptation and mitigation. We provide evidence that the cost and availability of capital for many countries have already been shaped by their historical exposure to tropical cyclones (TCs) and warming temperatures. Our empirically derived estimates suggest that, across all TC-exposed countries, debt-to-GDP ratios are on average 30% higher due to the cumulative effects of TCs since 1990. GDP levels are on average 10% lower due to the combined impacts of TCs and warming temperatures across all countries. We estimate that because of these impacts, hotter countries are more likely to receive credit ratings below investment grade (< BBB–), and borrowing costs are at least 1 basis point (0.01%) higher in 28 countries and 5 basis points higher in highly-exposed countries. Future increases in temperature and TC activity will likely worsen countries' credit, potentially undermining both countries' abilities to address climate change and their long-run development prospects.

  PublisherOA PDFDOI

• Machine learning predictions of summertime warming jumps on decadal timescales

  Environmental Research Climate · 2026-02-20

  articleOpen accessSenior author

  Abstract Extreme events are responsible for some of the most severe impacts of climate change, but regional extreme event prediction remains a challenge as the events contain a large amount of stochasticity. Here we demonstrate an approach for predicting future summertime temperature extremes on decadal timescales by first identifying an abrupt jump in average summertime temperature as a covariate of extreme summertime temperatures, and then showing that these jumps can be predictable. We train a convolutional neural network (CNN) on historical and future global climate simulations to predict a confidence that future 5 year mean summertime temperatures will jump above a hot threshold given maps of recent sea surface temperature (SST) variability and the global warming level. We show that in most land regions, the CNN outperforms a classifier that relies solely on the forced temperature response, implying that information about the prior 10 year SST variability improves the CNN’s prediction skill and confidence. We input the observational record into the CNN as independent unseen data and observe some skill, with investigation revealing that this skill is driven by the CNN learning conditions that best suppress summertime temperature jumps. Our study emphasizes the importance of targeted methodology for diagnosing extreme event predictability, and demonstrates that future predictions of extremes can be improved by considering the prior 10 year SST variability, rather than just the forced response to global warming.

  PublisherDOI

Recent grants

• Collaborative Research: Investigation of Holocene Seasonality and Inter-annual Variability Along the California Current System

  NSF · $149k · 2004–2008

• Collaborative Research: Water Balance of western North America:  Dynamics of the Miocene summer monsoon

  NSF · $230k · 2005–2009

• CAREER: Dynamics and Impacts of Fine-Scale Climate Change

  NSF · $444k · 2010–2016

Frequent coauthors

• Moetasim Ashfaq

  91 shared

• Daniel L. Swain

  University of California, Los Angeles

  66 shared

• Justin Mankin

  Dartmouth College

  58 shared

• Deepti Singh

  Washington State University Vancouver

  56 shared

• Daniel E. Horton

  56 shared

• Marshall Burke

  Stanford University

  42 shared

• Frances V. Davenport

  Colorado State University

  30 shared

• Danielle Touma

  The University of Texas at Austin

  29 shared

Awards & honors

• James R. Holton Award
• William Kaula Award from the AGU
• Kavli Fellow by the U.S. National Academy of Sciences