NANO Alumnus Carolina Machado Lima de Camargo and colleagues published the following article in the journal JGR Oceans

Exploring Sources of Uncertainty in Steric Sea‐Level Change Estimates

Camargo et al. (2020) JGR Oceans, DOI 10.1029/2020JC016551

 

Abstract

Recent studies disagree about the contribution of variations in temperature and salinity of the oceans—steric change—to the observed sea‐level change. This article explores two sources of uncertainty to both global mean and regional steric sea‐level trends. First, we analyze the influence of different temperature and salinity data sets on the estimated steric sea‐level change. Next, we investigate the impact of different stochastic noise models on the estimation of trends and their uncertainties. By varying both the data sets and noise models, the global mean steric sea‐level trend and uncertainty can vary from 0.69 to 2.40 and 0.02 to 1.56 mm/year, respectively, for 1993–2017. This range is even larger on regional scales, reaching up to 30 mm/year. Our results show that a first‐order autoregressive model is the most appropriate choice to describe the residual behavior of the ensemble mean of all data sets for the global mean steric sea‐level change over the last 25 years, which consequently leads to the most representative uncertainty. Using the ensemble mean and the first‐order autoregressive noise model, we find a global mean steric sea‐level change of 1.36 ± 0.10 mm/year for 1993–2017 and 1.08 ± 0.07 mm/year for 2005–2015. Regionally, a combination of different noise models is the best descriptor of the steric sea‐level change and its uncertainty. The spatial coherence in the noise model preference indicates clusters that may be best suited to investigate the regional sea‐level budget.

 

Keywords

  • steric sea‐level change
  • global mean sea‐level change
  • regional sea‐level change
  • stochastic noise models
  • temperature and salinity data sets

Link for the publication here

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