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Open Access Publications from the University of California

Scholarly Works (2 results)

  • Thesis
  • Peer Reviewed
UC Irvine Electronic Theses and Dissertations (2019)

Extreme weather events are inherent in climate variability and they can cause ecosystem alterations, infrastructure damages, suspension of food supply chains, and loss of lives. Today's highly populated and urbanized society is more vulnerable than ever to natural hazards and their disruptive consequences. Projected population growth and changes in climate variability are expected to exacerbate the societal and economic impact of climatic extremes. The scientific community, global organizations, and other stakeholders have all recognized the urgency of improving our understanding of both natural and human-induced climate variability.

The overarching goal of this thesis is to advance the current methods for nonstationary analysis of climatic extremes and their attributions. Here we propose a methodological framework for investigating hydroclimatic extremes over time and in response to a physical driver/covariate. The Process-based Nonstationary Extreme Value Analysis (ProNEVA) framework is unique in that it allows for incorporating a physical component into traditional frequency analysis techniques to account for observed or process-based changes in the variable of interest. The model can be used for both stationary and nonstationary analyses of extremes and includes a Graphical User Interface (GUI) for easier implementation.

We then shed light on the uncertainty inherent in the estimation of climatic extremes. We propose a generalized approach for including uncertainty information in the recurrence interval of extremes. The approach offers insights on how information about extremes should be interpreted by planners and decision-makers under conditions of uncertainty.

Using the method developed in this thesis, we show how extreme precipitation is expected to change in the future. We also highlight the importance of merging information from observations and climate model simulations for risk assessment purposes.

Finally, we outline a methodological framework for attribution of changes in multiple extremes or multiple features of an extreme event. We show the potential of copula functions for attribution of changes in both the magnitude and the dependence structure between characteristics of a natural phenomenon or, more generally, between two dependent variables.

    Cover page: Advancing Process-Based Nonstationary Analysis of Climate Extremes: Modeling, Uncertainty Assessment and Multivariate Attribution
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2017)
    Rising global temperatures are causing increases in the frequency and severity of extreme climatic events, such as floods, droughts, and heat waves. We analyze changes in summer temperatures, the frequency, severity, and duration of heat waves, and heat-related mortality in India between 1960 and 2009 using data from the India Meteorological Department. Mean temperatures across India have risen by more than 0.5°C over this period, with statistically significant increases in heat waves. Using a novel probabilistic model, we further show that the increase in summer mean temperatures in India over this period corresponds to a 146% increase in the probability of heat-related mortality events of more than 100 people. In turn, our results suggest that future climate warming will lead to substantial increases in heat-related mortality, particularly in developing low-latitude countries, such as India, where heat waves will become more frequent and populations are especially vulnerable to these extreme temperatures. Our findings indicate that even moderate increases in mean temperatures may cause great increases in heat-related mortality and support the efforts of governments and international organizations to build up the resilience of these vulnerable regions to more severe heat waves.
      Cover page: Increasing probability of mortality during Indian heat wavesCreative Commons 'BY' version 4.0 license
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