Transient climate response in coupled atmospheric-ocean general circulation models

Mao Chang Liang, Li Ching Lin, Ka Kit Tung, Yuk L. Yung, Shan Sun

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The equilibrium climate sensitivity (ECS) has a large uncertainty range among models participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and has recently been presented as "inherently unpredictable." One way to circumvent this problem is to consider the transient climate response (TCR). However, the TCR among AR4 models also differs by more than a factor of 2. The authors argue that the situation may not necessarily be so pessimistic, because much of the intermodel difference may be due to the fact that the models were run with their oceans at various stages of flux adjustment with their atmosphere. This is shown by comparing multimillennium-long runs of the Goddard Institute for Space Studies model, version E, coupled with the Hybrid Coordinate Ocean Model (GISS-EH) and the Community Climate System Model, version 4 (CCSM4) with what were reported to AR4. The long model runs here reveal the range of variability (~30%) in their TCR within the same model with the same ECS. The commonly adopted remedy of subtracting the "climate drift" is ineffective and adds to the variability. The culprit is the natural variability of the control runs, which exists even at quasi equilibration. Fortunately, for simulations with multidecadal time horizon, robust solutions can be obtained by branching off thousand-year-long control runs that reach "quasi equilibration" using a new protocol, which takes advantage of the fact that forced solutions to radiative forcing forget their initial condition after 30-40 yr and instead depend mostly on the trajectory of the radiative forcing.

Original languageEnglish
Pages (from-to)1291-1296
Number of pages6
JournalJournal of the Atmospheric Sciences
Volume70
Issue number4
DOIs
StatePublished - Apr 2013

Keywords

  • Climate models
  • Climate prediction
  • Climate sensitivity

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