Is a decline of AMOC causing the warming hole above the North Atlantic in observed and modeled warming patterns?

Sybren Drijfhout, Geert Jan van Oldenborgh, Andrea Cimatoribus

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The pattern of global mean temperature (GMT) change is calculated by regressing local surface air temperature (SAT) to GMT for an ensemble of CMIP5 models and for observations over the last 132 years. Calculations are based on the historical period and climate change scenarios. As in the observations the warming pattern contains a warming hole over the subpolar North Atlantic. Using a bivariate regression of SAT to GMT and an index of the Atlantic meridional overturning circulation (AMOC), the warming pattern is decomposed in a radiatively forced part and an AMOC fingerprint. The North Atlantic warming hole is associated with a decline of the AMOC. The AMOC fingerprint resembles Atlantic multidecadal variability (AMV), but details of the pattern change when theAMOCdecline increases, underscoring the nonlinearity in the response. The warming hole is situated south of deep convection sites, indicating that it involves an adjustment of the gyre circulation, although it should be noted that some models feature deep convection in the middle of the subpolar gyre. The warming hole is already prominent in historical runs, where the response of the AMOCto GMT is weak, which suggests that it is involved in an ocean adjustment that precedes the AMOC decline. In the more strongly forced scenario runs, the warming hole over the subpolar gyre becomes weaker, while cooling over the Nordic seas increases, consistent with previous findings that deep convection in the Labrador and Irminger Seas is more vulnerable to changes in external forcing than convection in the Nordic seas, which only reacts after a threshold is passed. © 2012 American Meteorological Society.
Original languageEnglish
Pages (from-to)8373-8379
Number of pages7
JournalJournal of Climate
Volume25
Issue number24
DOIs
Publication statusPublished - 2012

Keywords

  • Climate variability
  • Ensembles
  • Model evaluation/performance
  • Pattern detection
  • Regression analysis
  • Trends

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