394 Pages
    by Chapman & Hall

    394 Pages
    by Chapman & Hall

    Evaluating Climate Change Impacts discusses assessing and quantifying climate change and its impacts from a multi-faceted perspective of ecosystem, social, and infrastructure resilience, given through a lens of statistics and data science. It provides a multi-disciplinary view on the implications of climate variability and shows how the new data science paradigm can help us to mitigate climate-induced risk and to enhance climate adaptation strategies.

    This book consists of chapters solicited from leading topical experts and presents their perspectives on climate change effects in two general areas: natural ecosystems and socio-economic impacts. The chapters unveil topics of atmospheric circulation, climate modeling, and long-term prediction; approach the problems of increasing frequency of extreme events, sea level rise, and forest fires, as well as economic losses, analysis of climate impacts for insurance, agriculture, fisheries, and electric and transport infrastructures. The reader will be exposed to the current research using a variety of methods from physical modeling, statistics, and machine learning, including the global circulation models (GCM) and ocean models, statistical generalized additive models (GAM) and generalized linear models (GLM), state space and graphical models, causality networks, Bayesian ensembles, a variety of index methods and statistical tests, and machine learning methods. The reader will learn about data from various sources, including GCM and ocean model outputs, satellite observations, and data collected by different agencies and research units. Many of the chapters provide references to open source software R and Python code that are available for implementing the methods.

    I Ecosystem Impacts

    1. On Evaluation of Climate Models
    2. Kaibo Gong and Snigdhansu Chatterjee


      A brief tour of climate models

      Evaluation of climate model outputs: summary measures

      Ensemble-based approaches

      Probabilistic model evaluation techniques

      Ensemble using empirical likelihood

      Conclusions and future directions

    3. A Statistical Analysis of North Atlantic Tropical Cyclone Changes
    4. Thomas J Fisher, Robert Lund, and Michael W Robbins



      Statistical methods


      Comments and conclusions

    5. Fire Weather Index and Climate Change
    6. Zuzana Hubnerova, Sylvia Esterby, and Steve Taylor


      Statistical modeling of the fire weather index monthly maxima

      Summary and discussion


    7. Probabilistic Projections of High Tide Flooding for the State of Maryland in the st Century
    8. Ming Li, Fan Zhang, Yijun Guo and Xiaohong Wang




    9. Response of Benthic Biodiversity to Climate-Sensitive Regional and Local Conditions in a Complex Estuarine System
    10. Ryan J Woodland and Jeremy M Testa






    11. Using Structural Comparisons to Measure the Behavior of Complex Systems
    12. Ryan E Langendorf



      Network alignment


      Example: the Chesapeake Bay

      Critical considerations


      Final thought

    13. Causality Analysis of Climate and Ecosystem Time Series
    14. Mohammad Gorji Sefidmazgi and Ali Gorji Sefidmazgi


      Methods of causality detection



      II Socio-economic Impacts

    15. Statistical Issues in Detection of Trends in Losses from Extreme
    16. Weather and Climate Events

      Richard W Katz


      Loss distribution

      Bias, uncertainty, and variability in losses

      Detection and attribution of trends in losses

      Summary and discussion

    17. Event Attribution: Linking Specific Extreme Events to Human-Caused Climate Change
    18. Stephanie Herring

      Why is this chapter in this book?

      Background on event attribution

      Event attribution methodologies

      Impact attribution

      FAR = or "Not possible without climate change"

      Communicating event attribution studies

    19. Financing Weather and Climate Risks in the United States
    20. Roger S Pulwarty, David R Easterling, Jeffery Adkins, and Adam B Smith

      Disasters in the US – the recent record

      Climate and extremes

      Assessing economic impacts

      Insurance and risk financing

      Data and analytical challenges

      Implementation challenges

      Financing mitigation and resilience

      Pathways and conclusion

    21. Extreme Events, Population, and Risk: an Integrated Modeling Approach
    22. Lelys Bravo de Guenni, Desireé Villalta, and Andrés Sajo-Castelli


      Conceptual framework for risk modeling

      Applications of the conceptual framework

      Discussion, conclusions, and future work

    23. Aspects of Climate-Induced Risk in Property Insurance
    24. Ola Haug


      The role of statistics in assessing insurance climate risk

      Water damage to properties in Norway

      The Gjensidige case study

      Climate change and property insurance interactions

    25. Climate Change Impacts on the Nation’s Electricity Sector
    26. Craig D Zamuda


      Climate impacts and implications for the electricity sector

      Resilience approaches and options

      Analytical approaches for assessing costs and benefits

      Gaps and opportunities for improvement in resilience planning

    27. Impacts of InclementWeather on Traffic Accidents in Mexico City
    28. Sophie Bailey, S Marcelo Olivera-Villarroel, and Vyacheslav Lyubchich


      Data description



    29. Statistical Modeling of Dynamic Greenhouse Gas Emissions
    30. Nathaniel K Newlands




      Statistical framework

      Ecosystem dynamical optimization

      Numerical results


      Appendix: model parameters and variables

    31. Agricultural Climate Risk Management and Global Food Security: Recent Progress in South-East Asia
    32. Louis Kouadio and Eric Rahn

      Climate risks management in agriculture

      Current approaches integrating SCFs and crop simulation models

      Examples of integrated SCF-crop modeling approach

      Challenges for operationalizing seasonal climate-crop modeling

      Improved climate risk management in South-East Asia

    33. Poppy Cultivation and Eradication in Mexico : the Effects of Climate

    S Marcelo Olivera-Villarroel and Maria del Pilar Fuerte Celis









    The book is an interdisciplinary initiative of statisticians, climatologists, ecologists and oceanographers whose research addresses development and implementation of analytical methodology for assessing climate change impacts. The team includes statisticians V. Lyubchich and Y. R. Gel (statistical and machine learning methods for quantification of the climate-induced risk), climatologist K. H. Kilbourne (paleoclimatology, geochemistry, assessment of the causes of climate variability), fisheries scientist T. J. Miller (effects of ocean acidification on blue crab, recruitment issues in menhaden and striped bass), disaster expert A. B. Smith (analysis of economic and societal impacts of extreme events and natural hazards), and research scientist in food-water-energy nexus N. K. Newlands (sustainability, precision agriculture and risk analysis using machine learning and integrated modeling).