On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature

Hsi Yen Ma, A. Cheska Siongco, Stephen A. Klein, Shaocheng Xie, Alicia R. Karspeck, Kevin Raeder, Jeffrey L. Anderson, Jiwoo Lee, Ben P. Kirtman, William J. Merryfield, Hiroyuki Murakami, Joseph J. Tribbia

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multimodel Ensemble, and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and subtropics than over the extratropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with time scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean-atmosphere models.

Original languageEnglish (US)
Pages (from-to)427-446
Number of pages20
JournalJournal of Climate
Issue number1
StatePublished - Jan 1 2021


  • Bias
  • Climate models
  • General circulation models
  • Hindcasts
  • Model errors
  • Sea surface temperature

ASJC Scopus subject areas

  • Atmospheric Science


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