Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4): Part II. Parametric and Structural Uncertainty Estimations

• Published in: Journal of climate 2015-02, Vol.28 (3), p.931-951
• Main Authors: Liu, Wei, Huang, Boyin, Thorne, Peter W., Banzon, Viva F., Zhang, Huai-Min, Freeman, Eric, Lawrimore, Jay, Peterson, Thomas C., Smith, Thomas M., Woodruff, Scott D.
• Format: Article
• Language: English
• Subjects: Algorithms; Analytical estimating; Climate; Climate change; Critical values; Data smoothing; Datasets; Estimates; Global climate models; Nonlinearity; Polar regions; Sea surface; Sea surface temperature; Statistical methods; Surface temperature; Temperature; Term weighting; Time; Tropical environments; Uncertainty
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/jcli-d-14-00007.1

Described herein is the parametric and structural uncertainty quantification for the monthly Extended Reconstructed Sea Surface Temperature (ERSST) version 4 (v4). A Monte Carlo ensemble approach was adopted to characterize parametric uncertainty, because initial experiments indicate the existence of significant nonlinear interactions. Globally, the resulting ensemble exhibits a wider uncertainty range before 1900, as well as an uncertainty maximum around World War II. Changes at smaller spatial scales in many regions, or for important features such as Niño-3.4 variability, are found to be dominated by particular parameter choices. Substantial differences in parametric uncertainty estimates are found between ERSST.v4 and the independently derived Hadley Centre SST version 3 (HadSST3) product. The largest uncertainties are over the mid and high latitudes in ERSST.v4 but in the tropics in HadSST3. Overall, in comparison with HadSST3, ERSST.v4 has larger parametric uncertainties at smaller spatial and shorter time scales and smaller parametric uncertainties at longer time scales, which likely reflects the different sources of uncertainty quantified in the respective parametric analyses. ERSST.v4 exhibits a stronger globally averaged warming trend than HadSST3 during the period of 1910–2012, but with a smaller parametric uncertainty. These global-mean trend estimates and their uncertainties marginally overlap. Several additional SST datasets are used to infer the structural uncertainty inherent in SST estimates. For the global mean, the structural uncertainty, estimated as the spread between available SST products, is more often than not larger than the parametric uncertainty in ERSST.v4. Neither parametric nor structural uncertainties call into question that on the global-mean level and centennial time scale, SSTs have warmed notably.