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Statistical science: contributions to the Administration’s research priority on climate change

Report


Type Of Work


  • Report

Abstract


  • Data are fundamental to all of science. Data enhance scientific theories and their statistical

    analysis suggests new avenues of research and data collection. Climate science is no exception.

    Earth’s climate system is complex, involving the interaction of many different kinds of physical

    processes and many different time scales. Thus this area of science has a critical dependence on

    the examination of all relevant data and the application of statistics for its interpretation. Climate

    datasets are increasing in number, size, and complexity and challenge traditional methods of data

    analysis. Satellite remote sensing campaigns, automated weather monitoring networks, and

    climate-model experiments have contributed to a data explosion that provides a wealth of new

    information but can overwhelm standard approaches. Developing new statistical approaches is an

    essential part of understanding climate and its impact on society in the presence of uncertainty.

    Experience has shown that rapid progress can be made when “big data” is used with statistics to

    derive new technologies. Crucial to this success are new statistical methods that recognize

    uncertainties in the measurements and the scientific processes but are also tailored to the unique

    scientific questions being studied.

UOW Authors


  •   Sanso, Bruno (external author)
  •   Berliner, L M. (external author)
  •   Cooley, Daniel S. (external author)
  •   Craigmile, Peter (external author)
  •   Cressie, Noel
  •   Haran, Murali (external author)
  •   Lund, Robert B. (external author)
  •   Nychka, Douglas W. (external author)
  •   Paciorek, Chris (external author)
  •   Sain, Stephan R. (external author)
  •   Smith, Richard (external author)
  •   Stein, Michael L. (external author)

Publication Date


  • 2014

Citation


  • Sanso, B., Berliner, L. Mark., Cooley, D. S., Craigmile, P., Cressie, N. A., Haran, M., Lund, R. B., Nychka, D. W., Paciorek, C., Sain, S. R., Smith, R. & Stein, M. L. (2014). Statistical science: contributions to the Administration’s research priority on climate change. American Statistical Association. https://www.amstat.org/ASA/Science-Policy-and-Advocacy/home.aspx?hkey=b9b4cc07-1df5-4ce9-8d37-c7842ddb6383

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5964

Url


  • https://www.amstat.org/ASA/Science-Policy-and-Advocacy/home.aspx?hkey=b9b4cc07-1df5-4ce9-8d37-c7842ddb6383

Type Of Work


  • Report

Abstract


  • Data are fundamental to all of science. Data enhance scientific theories and their statistical

    analysis suggests new avenues of research and data collection. Climate science is no exception.

    Earth’s climate system is complex, involving the interaction of many different kinds of physical

    processes and many different time scales. Thus this area of science has a critical dependence on

    the examination of all relevant data and the application of statistics for its interpretation. Climate

    datasets are increasing in number, size, and complexity and challenge traditional methods of data

    analysis. Satellite remote sensing campaigns, automated weather monitoring networks, and

    climate-model experiments have contributed to a data explosion that provides a wealth of new

    information but can overwhelm standard approaches. Developing new statistical approaches is an

    essential part of understanding climate and its impact on society in the presence of uncertainty.

    Experience has shown that rapid progress can be made when “big data” is used with statistics to

    derive new technologies. Crucial to this success are new statistical methods that recognize

    uncertainties in the measurements and the scientific processes but are also tailored to the unique

    scientific questions being studied.

UOW Authors


  •   Sanso, Bruno (external author)
  •   Berliner, L M. (external author)
  •   Cooley, Daniel S. (external author)
  •   Craigmile, Peter (external author)
  •   Cressie, Noel
  •   Haran, Murali (external author)
  •   Lund, Robert B. (external author)
  •   Nychka, Douglas W. (external author)
  •   Paciorek, Chris (external author)
  •   Sain, Stephan R. (external author)
  •   Smith, Richard (external author)
  •   Stein, Michael L. (external author)

Publication Date


  • 2014

Citation


  • Sanso, B., Berliner, L. Mark., Cooley, D. S., Craigmile, P., Cressie, N. A., Haran, M., Lund, R. B., Nychka, D. W., Paciorek, C., Sain, S. R., Smith, R. & Stein, M. L. (2014). Statistical science: contributions to the Administration’s research priority on climate change. American Statistical Association. https://www.amstat.org/ASA/Science-Policy-and-Advocacy/home.aspx?hkey=b9b4cc07-1df5-4ce9-8d37-c7842ddb6383

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5964

Url


  • https://www.amstat.org/ASA/Science-Policy-and-Advocacy/home.aspx?hkey=b9b4cc07-1df5-4ce9-8d37-c7842ddb6383