Improvements in the GISTEMP Uncertainty Model

Lenssen, Nathan J. L.; Schmidt, Gavin A.; Hansen, James E.; Menne, Matthew J.; Persin, Avraham; Ruedy, Reto; Zyss, Daniel

doi:10.1029/2018JD029522

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Improvements in the GISTEMP Uncertainty Model

2019
By Lenssen, Nathan J. L. ; Schmidt, Gavin A. ; Hansen, James E. ; ...
Source: Journal of Geophysical Research: Atmospheres, 124(12), 6307-6326

[PDF-2.12 MB]

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Journal Title:

Journal of Geophysical Research: Atmospheres
Personal Author:

Lenssen, Nathan J. L. ; Schmidt, Gavin A. ; Hansen, James E. ; Menne, Matthew J. ; Persin, Avraham ; ... More +

Lenssen, Nathan J. L. ; Schmidt, Gavin A. ; Hansen, James E. ; Menne, Matthew J. ; Persin, Avraham ; Ruedy, Reto ; Zyss, Daniel Less -
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; NCEI (National Centers for Environmental Information)

NESDIS (National Environmental Satellite, Data, and Information Service) ; NCEI (National Centers for Environmental Information) Less -
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We outline a new and improved uncertainty analysis for the Goddard Institute for Space Studies Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys, and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state-of-the-art reanalyses, and incorporate independently derived estimates for ocean data processing, station homogenization, and other structural biases. The resulting 95% uncertainties are near 0.05 °C in the global annual mean for the last 50 years and increase going back further in time reaching 0.15 °C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date) and conclude with 87% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).
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Climatic Changes Earth Temperature Meteorological Stations Atmospheric Science Earth And Planetary Sciences (miscellaneous) Geophysics Space And Planetary Science
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Journal of Geophysical Research: Atmospheres, 124(12), 6307-6326
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https://doi.org/10.1029/2018JD029522
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Journal Article
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urn:sha256:c6d1c66106936633d363947c1c0ef96d93f8c0030d77a350a84236d6d3ed24ba
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Improvements in the GISTEMP Uncertainty Model

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