4.7 Article

Uncertainty in annual rankings from NOAA's global temperature time series

Journal

GEOPHYSICAL RESEARCH LETTERS
Volume 40, Issue 22, Pages 5965-5969

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2013GL057999

Keywords

temperature; global; uncertainty; Monte Carlo

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Annual rankings of global temperature are an important component of climate monitoring. However, there is some degree of uncertainty for every yearly value in the global temperature time series, which leads to uncertainty in annual rankings as well. This study applies a Monte Carlo uncertainty analysis to the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center's global land-ocean surface temperature (NOAATMP) time series. Accounting for persistence between years does not materially affect the results versus presuming statistical independence. The highest probabilities for the warmest year analysis (1880-2012) are associated with the years 2010 (similar to 36%), 2005 (similar to 28%), and 1998 (similar to 11%). The current separation among the warmest observed years is relatively small compared to the standard errors of the NOAATMP time series. However, each year between 1997 and 2012 was warmer than the vast majority of all other years since 1880 at the 95% confidence level.

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