Analysing the PMIP4-CMIP6 collection: a workflow and tool (pmip_p2fvar_analyzer v1)

Zhao, Anni; Brierley, Chris; Jiang, Zhiyi; Eyles, Rachel; Oyarzún, Damián; Gómez-Dans, José

doi:10.5194/gmd-15-2475-2022

Cited by 5 publications

(8 citation statements)

References 41 publications

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“…The AMOC intensity is computed using a modified version of the Climate Variability Diagnostic Package (CVDP; Phillips et al, 2014;Danabasoglu et al, 2012). Rather than using principal component analysis to define the AMOC (Danabasoglu et al, 2012), the maximum overturning streamfunction at 30 • N is used (Zhao et al, 2022). Patterns of surface climate anomalies associated with AMOC variations are computed by the CVDP via linear regression (more details below), with the ability to determine precipitation patterns added by Zhao et al (2022).…”

Section: Modelmentioning

confidence: 99%

No changes in overall AMOC strength in interglacial PMIP4 time slices

et al. 2023

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Abstract. The Atlantic Meridional Overturning Circulation (AMOC) is a key mechanism of poleward heat transport and an important part of the global climate system. How it responded to past changes in forcing, such as those experienced during Quaternary interglacials, is an intriguing and open question. Previous modelling studies suggest an enhanced AMOC in the mid-Holocene compared to the preindustrial period. In earlier simulations from the Palaeoclimate Modelling Intercomparison Project (PMIP), this arose from feedbacks between sea ice and AMOC changes, which were dependent on resolution. Here we present an initial analysis of recently available PMIP4 simulations for three experiments representing different interglacial conditions – one 127 000 years ago within the Last Interglacial (127 ka, called lig127k), one in the middle of the Holocene (midHolocene, 6 ka), and a preindustrial control simulation (piControl, 1850 CE). Both lig127k and midHolocene have altered orbital configurations compared to piControl. The ensemble mean of the PMIP4 models shows the strength of the AMOC does not markedly change between the midHolocene and piControl experiments or between the lig127k and piControl experiments. Therefore, it appears orbital forcing itself does not alter the overall AMOC. We further investigate the coherency of the forced response in AMOC across the two interglacials, along with the strength of the signal, using eight PMIP4 models which performed both interglacial experiments. Only two models show a stronger change with the stronger forcing, but those models disagree on the direction of the change. We propose that the strong signals in these two models are caused by a combination of forcing and the internal variability. After investigating the AMOC changes in the interglacials, we further explored the impact of AMOC on the climate system, especially on the changes in the simulated surface temperature and precipitation. After identifying the AMOC's fingerprint on the surface temperature and rainfall, we demonstrate that only a small percentage of the simulated surface climate changes could be attributed to the AMOC. Proxy records of sedimentary Pa/Th ratio during the two interglacial periods both show a similar AMOC strength compared to the preindustrial, which fits nicely with the simulated results. Although the overall AMOC strength shows minimal changes, future work is required to explore whether this occurs through compensating variations in the different components of AMOC (such as Iceland–Scotland overflow water). This line of evidence cautions against interpreting reconstructions of past interglacial climate as being driven by AMOC, outside of abrupt events.

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Section: Modelmentioning

confidence: 99%

No changes in overall AMOC strength in interglacial PMIP4 time slices

et al. 2023

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“…Outputs from PMIP3 and PMIP4 have curated and processed following the workflow outlined by Zhao et al (2022), and available from them.…”

Section: Discussionmentioning

confidence: 99%

“…The analysis undertaken in this research follows the workflow described by Zhao et al (2022). This involves the creation of a curated replica of the relevant simulation output available on the Earth System Grid Federation (ESGF).…”

Section: Analysis and Definitionsmentioning

confidence: 99%

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Indian Ocean variability changes in the Palaeoclimate Model Intercomparison Project

Brierley

Thirumalai²,

Grindrod³

et al. 2022

Preprint

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Abstract. The Indian Ocean exhibits multiple modes of interannual climate variability, whose future behaviour is uncertain. Recent analysis of glacial climates has uncovered an additional El Niño-like equatorial mode in the Indian Ocean, which could also emerge in future warm states. Here we explore changes in the tropical Indian Ocean simulated by the Palaeoclimate Model Intercomparison Project (PMIP4). These simulations are performed by an ensemble of models contributing to the Coupled Model Intercomparison Project 6, and over four coordinated experiments: three past periods - the mid-Holocene (6000 years5 ago), the last glacial maximum (21,000 years ago), the last interglacial (127,000 years ago) - and an idealised forcing scenario to examine the impact of greenhouse forcing. The two interglacial experiments are used to characterise the role of orbital variations on the seasonal cycle, whilst the other pair focus on responses to large changes in global temperature. The Indian Ocean Basin Mode (IOBM) is damped in both the mid-Holocene and last interglacial, with the amount related to the damping of the El Niño-Southern Oscillation in the Pacific. No coherent changes in the strength of the IOBM are seen10 with global temperature changes; neither are changes in the Indian Ocean Dipole (IOD) nor the Niño-like mode. Under orbital forcing, the IOD robustly weakens during the mid-Holocene experiment, with only minor reductions in amplitude during the last interglacial. Orbital changes do impact the SST pattern of the Indian Ocean Dipole, with the cold pole reaching up to the Equator and extending along it. Induced changes in the regional seasonality are hypothesised to be important control on changes in the Indian Ocean variability.

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“…The AMOC intensity is computed using a modified version of Climate Variability Diagnostic Package (Phillips et al, 2014;Danabasoglu et al, 2012). Rather than using principal component analysis to define the AMOC (Danabasoglu et al, 2012), the maximum overturning streamfunction at 30 • N is used (Zhao et al, 2022). Patterns of surface climate association with AMOC variations were computed via linear regression with the AMOC time series; precipitation regressions have been encoded to complement the existing surface temperature patterns (Zhao et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

No changes in overall AMOC strength in interglacial PMIP4 timeslices

Jiang

Brierley

Thornalley

et al. 2022

Preprint

Self Cite

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Abstract. The Atlantic Meridional Overturning Circulation (AMOC) is a key mechanism of poleward heat transport and an important part of the global climate system. How it responded to past changes in forcing, such as experienced during Quaternary interglacials, is an intriguing and open question. Previous modelling studies suggest an enhanced AMOC in the mid-Holocene compared to the pre-industrial period. In earlier simulations from the Palaeoclimate Modelling Intercomparison Project (PMIP), this arose from feedbacks between sea ice and AMOC changes, which were dependent on resolution. Here we present an initial analysis of the recently available PMIP4 simulations. The ensemble mean of the PMIP4 models shows the strength of the AMOC does not markedly change between the midHolocene and piControl experiments or between the lig127k and piControl experiments. Therefore, it appears orbital forcing itself does not alter the overall AMOC. We further investigate the coherency of the forced response in AMOC across the two interglacials, along with the strength of the signal, using eight PMIP4 models which performed both interglacial experiments. Only 2 models show a stronger change with the stronger forcing, but those models disagree on the direction of the change. We propose that the strong signals in these 2 models are caused by a combination of forcing and the internal variability. After investigating the AMOC changes in the interglacials, we further explored the impact of AMOC on the climate system, especially on the changes in the simulated surface temperature and precipitation. After identifying the AMOC’s fingerprint on the surface temperature and rainfall, we demonstrate that only a small percentage of the simulated surface climate changes can be attributed to the AMOC. Proxy records during the two interglacial periods paint a similar picture of minimal changes, which fits nicely with the simulated results. Although the overall AMOC strength shows minimal changes, future work is required to explore whether this occurs through compensating variations in the different components of AMOC (such as Iceland-Scotland overflow water). This lines of evidence caution against interpreting reconstructions of past interglacial climate as being driven by AMOC, outside of abrupt events.

show abstract

Analysing the PMIP4-CMIP6 collection: a workflow and tool (pmip_p2fvar_analyzer v1)

Cited by 5 publications

References 41 publications

No changes in overall AMOC strength in interglacial PMIP4 time slices

No changes in overall AMOC strength in interglacial PMIP4 time slices

Indian Ocean variability changes in the Palaeoclimate Model Intercomparison Project

No changes in overall AMOC strength in interglacial PMIP4 timeslices

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