Uncertainty quantification in climate modeling and projection

Yun Qian; Charles Jackson; Filippo Giorgi; Ben Booth; Qingyun Duan; Chris Forest; Dave Higdon; Z. Jason Hou; Gabriel Huerta

doi:10.1175/BAMS-D-15-00297.1

Uncertainty quantification in climate modeling and projection

Yun Qian
, Charles Jackson
, Filippo Giorgi
, Ben Booth
, Qingyun Duan
, Chris Forest
, Dave Higdon
, Z. Jason Hou
, Gabriel Huerta

Meteorology and Atmospheric Science

Research output: Contribution to journal › Article › peer-review

64 Scopus citations

Abstract

The projection of future climate is one of the most complex problems undertaken by the scientific community. With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in vulnerability, impact, and adaptation (VIA) studies should be provided with both well-characterized and well quantified uncertainty.

Original language	English (US)
Pages (from-to)	821-824
Number of pages	4
Journal	Bulletin of the American Meteorological Society
Volume	97
Issue number	5
DOIs	https://doi.org/10.1175/BAMS-D-15-00297.1
State	Published - May 2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

All Science Journal Classification (ASJC) codes

Atmospheric Science

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10.1175/BAMS-D-15-00297.1

Cite this

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AU - Giorgi, Filippo

AU - Booth, Ben

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AU - Forest, Chris

AU - Higdon, Dave

AU - Hou, Z. Jason

AU - Huerta, Gabriel

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AB - The projection of future climate is one of the most complex problems undertaken by the scientific community. With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in vulnerability, impact, and adaptation (VIA) studies should be provided with both well-characterized and well quantified uncertainty.

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ER -

Uncertainty quantification in climate modeling and projection

Abstract

UN SDGs

All Science Journal Classification (ASJC) codes

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