A5045362718- Climate variability and models
- Meteorological Phenomena and Simulations
- Climate Change and Health Impacts
- Soil Moisture and Remote Sensing
- Viral Infections and Vectors
- Climate change and permafrost
- Air Quality and Health Impacts
- Plant Water Relations and Carbon Dynamics
- Tree-ring climate responses
- Hydrology and Drought Analysis
- Climate change impacts on agriculture
- Mosquito-borne diseases and control
- Zoonotic diseases and public health
Stanford University
2022-2024
The observed increase in extreme weather has prompted recent methodological advances event attribution. We propose a machine learning–based approach that uses convolutional neural networks to create dynamically consistent counterfactual versions of historical events under different levels global mean temperature (GMT). apply this technique one heat (southcentral North America 2023) and several have been previously analyzed using established attribution methods. estimate temperatures during...
The potential death toll of worst-case extreme heat events is crucial for climate risk analysis and adaptation planning. We estimate this quantity Europe using machine learning to calculate the intensity historical waves if they occur at present or future global temperatures, combined with empirical exposure-response functions quantify resulting mortality. Each event projected generate tens thousands excess deaths. For example, July 1994 August 2003 meteorological conditions recur current...
Understanding the mortality effects of most extreme heat events is central to climate change risk analysis and adaptation decision-making. Accurate representation these impacts requires accounting for prolonged sequences hot days on mortality, in that due anthropogenic forcing, potential compensating heat. Here, we revisit August 2003 wave France, a canonical event region with rich data, understand influences. We find standard exposure-response functions underpredict excess deaths by 60%,...
Abstract Soil moisture (SM) influences near‐surface air temperature by partitioning downwelling radiation into latent and sensible heat fluxes, through which dry soils generally lead to higher temperatures. The strength of this coupled soil moisture‐temperature (SM‐T) relationship is not spatially uniform, numerous methods have been developed assess SM‐T coupling across the globe. These tend involve either idealized climate‐model experiments or linear statistical cannot fully capture...
Anthropogenic forcing is increasing the likelihood and severity of certain extreme weather events, which may catalyze outbreaks climate-sensitive infectious diseases. Extreme precipitation events can promote spread mosquito-borne illnesses by creating vector habitat, destroying infrastructure, impeding control. Here, we focus on Cyclone Yaku, caused heavy rainfall in northwestern Peru from March 7th - 20th, 2023 was followed worst dengue outbreak Peru's history. We apply generalized...
Abstract Independently, both droughts and heatwaves can induce severe impacts on human natural systems. However, when these two climate extremes occur concurrently in a given region, their compound are often more pronounced. With the improvement spatiotemporal resolution representation of complex processes global models (GCMs), they increasingly used to study future changes associated regional impacts. GCM selection for such impact assessments is generally based historical performance and/or...
Soil moisture influences near-surface air temperature by partitioning downwelling radiation into latent and sensible heat fluxes, through which dry soils generally lead to higher temperatures. The strength of this coupled soil moisture-temperature (SM-T) relationship is not spatially uniform, numerous methods have been developed assess SM-T coupling across the globe. These tend involve either idealized climate-model experiments or linear statistical cannot fully capture nonlinear coupling....
Soil moisture influences near-surface air temperature by partitioning downwelling radiation into latent and sensible heat fluxes, through which dry soils generally lead to higher temperatures.The strength of this coupled soil moisture-temperature (SM-T) relationship is not spatially uniform, numerous methods have been developed assess SM-T coupling across the globe.These tend involve either idealized climate-model experiments or linear statistical cannot fully capture nonlinear coupling.In...