Uncertainty Estimates for Sea Surface Temperature and Land Surface Air Temperature in NOAAGlobalTemp Version 5

• Published in: Journal of climate Vol. 33; no. 4; pp. 1351 - 1379
• Main Authors: Huang, Boyin, Menne, Matthew J., Boyer, Tim, Freeman, Eric, Gleason, Byron E., Lawrimore, Jay H., Liu, Chunying, Rennie, J. Jared, Schreck, Carl J., Sun, Fengying, Vose, Russell, Williams, Claude N., Yin, Xungang, Zhang, Huai-Min
• Format: Journal Article
• Language: English
• Published: Boston American Meteorological Society 15-02-2020
• Subjects: Air temperature; Bias; Climate change; Climatology; Confidence intervals; Datasets; Global temperatures; Historic temperatures; Parameter estimation; Reconstruction; Sea surface; Sea surface temperature; Simulation; Surface temperature; Surface-air temperature relationships; Trends; Uncertainty; Uncertainty analysis
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/jcli-d-19-0395.1

This analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s–1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s–2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.