Improvements in the GISTEMP Uncertainty Model. Issue 12 (24th June 2019)
- Record Type:
- Journal Article
- Title:
- Improvements in the GISTEMP Uncertainty Model. Issue 12 (24th June 2019)
- Main Title:
- Improvements in the GISTEMP Uncertainty Model
- Authors:
- Lenssen, Nathan J. L.
Schmidt, Gavin A.
Hansen, James E.
Menne, Matthew J.
Persin, Avraham
Ruedy, Reto
Zyss, Daniel - Abstract:
- Abstract: 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). Key Points: A total uncertainty analysis for GISTEMP is presented for the first time Uncertainty in global meanAbstract: 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). Key Points: A total uncertainty analysis for GISTEMP is presented for the first time Uncertainty in global mean surface temperature is roughly 0.05 degrees Celsius in recent decades increasing to 0.15 degrees Celsius in the nineteenth century Annual mean uncertainties are small relative to the long‐term trend … (more)
- Is Part Of:
- Journal of geophysical research. Volume 124:Issue 12(2019)
- Journal:
- Journal of geophysical research
- Issue:
- Volume 124:Issue 12(2019)
- Issue Display:
- Volume 124, Issue 12 (2019)
- Year:
- 2019
- Volume:
- 124
- Issue:
- 12
- Issue Sort Value:
- 2019-0124-0012-0000
- Page Start:
- 6307
- Page End:
- 6326
- Publication Date:
- 2019-06-24
- Subjects:
- Atmospheric physics -- Periodicals
Geophysics -- Periodicals
551.5 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2169-8996 ↗
http://www.agu.org/journals/jd/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2018JD029522 ↗
- Languages:
- English
- ISSNs:
- 2169-897X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4995.001000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17311.xml