A5037262007- Air Quality and Health Impacts
- Climate variability and models
- Meteorological Phenomena and Simulations
- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
- Hydrology and Drought Analysis
- Air Quality Monitoring and Forecasting
- Ecology and Vegetation Dynamics Studies
- Bayesian Methods and Mixture Models
- Climate Change and Health Impacts
- Soil Geostatistics and Mapping
- Forest ecology and management
- Markov Chains and Monte Carlo Methods
- Economic and Environmental Valuation
- Gaussian Processes and Bayesian Inference
- Tree-ring climate responses
- Atmospheric and Environmental Gas Dynamics
- Geology and Paleoclimatology Research
- Urban Transport and Accessibility
- Spatial and Panel Data Analysis
- Vehicle emissions and performance
- Atmospheric chemistry and aerosols
- Energy and Environment Impacts
- Tropical and Extratropical Cyclones Research
- Financial Risk and Volatility Modeling
University of California, Berkeley
2015-2024
Planetary Science Institute
2023
Lawrence Berkeley National Laboratory
2015-2020
Berkeley College
2020
University of Wisconsin System
2020
University of Mississippi
2019
Georgia Institute of Technology
2015
University of California System
2014
Harvard University
2004-2012
Brigham and Women's Hospital
2006-2012
The state of knowledge regarding trends and an understanding their causes is presented for a specific subset extreme weather climate types. For severe convective storms (tornadoes, hailstorms, thunderstorms), differences in time space practices collecting reports events make using the reporting database to detect extremely difficult. Overall, changes frequency environments favorable thunderstorms have not been statistically significant. precipitation, there strong evidence nationally...
Abstract We introduce a new class of nonstationary covariance functions for spatial modelling. Nonstationary allow the model to adapt surfaces whose variability changes with location. The includes version Matérn stationary covariance, in which differentiability surface is controlled by parameter, freeing one from fixing advance. allows knit together local parameters into valid global regardless how structure estimated. employ this fully Bayesian unknown process has Gaussian (GP) prior...
Weather and climate extremes have been varying changing on many different time scales. In recent decades, heat waves generally become more frequent across the United States, while cold decreasing. While this is in keeping with expectations a warming climate, it turns out that decadal variations number of U.S. do not correlate well observed during last century. Annual peak flow data reveal river flooding trends century scale show uniform changes country. flood magnitudes Southwest decreasing,...
BackgroundStudies of chronic health effects due to exposures particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) are often limited by sparse measurements. Satellite aerosol remote sensing data may be used extend PM2.5 ground networks cover a much larger area.ObjectivesIn this study we examined the benefits using optical depth (AOD) retrieved Geostationary Operational Environmental (GOES) in conjunction land use and meteorologic information estimate ground-level...
The relationship of fine particulate matter < 2.5 microm in diameter (PM(2.5)) air pollution with mortality and cardiovascular disease is well established, more recent long-term studies reporting larger effect sizes than earlier studies. Some have suggested the coarse fraction, particles between 10 (PM(10-2.5)), may also be important. With respect to events, questions remain regarding relative strength for chronic exposure particles.We examined PM(2.5) PM(10-2.5) exposures all-cause fatal...
We describe NIMBLE, a system for programming statistical algorithms general model structures within R. NIMBLE is designed to meet three challenges: flexible specification, language that can use different models, and balance between high-level programmability execution efficiency. For extends the BUGS creates objects, which manipulate variables, calculate log probability values, generate simulations, query relationships among variables. algorithm programming, provides functions operate with...
Abstract We present an analysis of version 5.1 the Community Atmospheric Model (CAM5.1) at a high horizontal resolution. Intercomparison this global model approximately 0.25°, 1°, and 2° is presented for extreme daily precipitation as well suite seasonal mean fields. In general, amounts are larger in resolution than lower‐resolution configurations. many but not all locations and/or seasons, rates high‐resolution configuration higher more realistic. The produces tropical cyclones up to...
Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it difficult quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated effects as compared nearest monitor or county-specific ambient concentrations. We developed generalized additive mixed models that...
Abstract The analysis of climatological data often involves statistical significance testing at many locations. While the field approach determines if a as whole is significant, multiple procedure which particular tests are significant. Many such procedures available, most control, for every test, probability detecting that does not really exist. aim this paper to introduce novel “false discovery rate” approach, controls false rejections in more meaningful way. Specifically, it priori...
In many environmental epidemiology studies, the locations and/or times of exposure measurements and health assessments do not match. such settings, effects analyses often use predictions from an model as a covariate in regression model. Such contain some measurement error predicted values equal true exposures. We provide framework for spatial modeling, showing that smoothing induces Berkson-type with nondiagonal structure. From this viewpoint, we review existing approaches to estimation...
Adverse health effects of exposures to acute air pollution have been well studied. Fewer studies examined chronic exposure. Previous used exposure estimates for narrow time periods and were limited by the geographic distribution monitors. This study association particulate with all-cause mortality, incident nonfatal myocardial infarction, fatal coronary heart disease (CHD) in a prospective cohort 66,250 women from Nurses' Health Study northeastern US metropolitan areas. Nonfatal outcomes...
Residuals in regression models are often spatially correlated. Prominent examples include studies environmental epidemiology to understand the chronic health effects of pollutants. I consider residual spatial structure on bias and precision coefficients, developing a simple framework which key issues derive informative analytic results. When unmeasured confounding introduces into residuals, with random closely-related such as kriging penalized splines biased, even when variance components...
We analyze the strength of association between aerosol optical depth (AOD) retrievals from GOES aerosol/smoke product (GASP) and ground-level fine particulate matter (PM2.5) to assess AOD as a proxy for PM2.5 in United States. GASP is retrieved geostationary platform, giving half-hourly observations every day, contrast once per day snapshots polar-orbiting satellites. However, based on less-sophisticated instrument retrieval algorithm. find that daily correlations over time at fixed...
Abstract Public health researchers often estimate effects of exposures (e.g., pollution, diet, and lifestyle) that cannot be directly measured for study subjects. A common strategy in environmental epidemiology is to use a first‐stage (exposure) model the exposure on basis covariates and/or spatiotemporal proximity predictions from as covariate interest second‐stage (health) model. This induces complex form measurement error. We propose an analytical framework methodology robust...
The annual “State of the Climate” report, published in Bulletin American Meteorological Society (BAMS), has included a supplement since 2011 composed brief analyses human influence on recent major extreme weather events. There are now several dozen events examined these supplements, but studies have all differed their data sources as well approaches to defining events, analyzing and consideration role anthropogenic emissions. This study reexamines most using single analytical approach set...
Event attribution in the context of climate change seeks to understand role anthropogenic greenhouse gas emissions on extreme weather events, either specific events or classes events. A common approach event uses model output under factual (real-world) and counterfactual (world that might have been without emissions) scenarios estimate probabilities interest two scenarios. is then quantified by ratio probabilities. While this has applied many times last 15 years, statistical techniques used...
Summary 1 Individuals of many woody plant species have the ability to respond damage which causes removal crown by producing new branches (sprouts) along remaining stem. Resprouting plants has received little attention in relatively undisturbed tropical forest. 2 To assess importance resprouting for forest dynamics, we estimated rates and mortality resprouted individuals as a whole individual 50‐ha permanent plot moist on Barro Colorado Island, Panama. We tested differences between asked...
The National Centers for Environmental Prediction–National Center Atmospheric Research (NCEP–NCAR) reanalysis is used to estimate time trends of, and analyze the relationships among, six indices of cyclone activity or forcing winters 1949–99, over region 20°–70°N. are Eady growth rate temperature variance, both at 500 hPa; surface meridional gradient; 95th percentile near-surface wind speed; counts cyclones intense cyclones. With multiple indices, one can examine different aspects storm...
BackgroundRecent research highlights the promise of remotely sensed aerosol optical depth (AOD) as a proxy for ground-level particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5). Particular interest lies in estimating spatial heterogeneity using AOD, important application to pollution exposure public health purposes. Given correlations reported between AOD and PM2.5, it is tempting interpret patterns reflecting PM2.5.ObjectivesWe evaluated degree which can help predict long-term...
A unique challenge in air pollution cohort studies and similar applications environmental epidemiology is that exposure not measured directly at subjects' locations. Instead, data from monitoring stations some distance the study subjects are used to predict exposures, these predicted exposures estimate health effect parameter of interest. It usually assumed minimizing error predicting true will improve estimation. We show a simulation this always case. interpret our results light recently...
The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure individuals rely on monitoring data are sparse space time, so they often assign same to participants large geographic areas across time. We estimate monthly PM during 1988–2002 a spatial domain for use studying Nurses' Health Study. develop conceptually simple spatio-temporal model uses rich set...
The relationship between traffic emissions and mobile-source air pollutant concentrations is highly variable over space time therefore difficult to model accurately, especially in urban settings with complex terrain. Regression-based approaches using continuous real-time mobile measurements may be able characterize spatiotemporal variability traffic-related but require methods incorporate temporally varying meteorology source strength a physically interpretable fashion.We developed...