Large-scale features and evaluation of the PMIP4-CMIP6 &amp;lt;i&amp;gt;midHolocene&amp;lt;/i&amp;gt; simulations

Brierley, Chris; Zhao, Anni; Harrison, Sandy P.; Braconnot, Pascale; Williams, Charles; Thornalley, David; Shi, Xiaoxu; Peterschmitt, Jean-Yves; Ohgaito, Rumi; Kaufman, Darrell S.; Kageyama, Masa; Hargreaves, J. C.; Erb, Michael P.; Emile‐Geay, Julien; D’Agostino, Roberta; Chandan, Deepak; Carré, Matthieu; Bartlein, Patrick J.; Zheng, Weipeng; Zhang, Zhongshi; Zhang, Qiong; Yang, Hu; Volodin, E. M.; Tomas, Robert A.; Routson, Cody; Peltier, W. Richard; Otto‐Bliesner, Bette L.; Morozova, Polina; McKay, Nicholas P.; Lohmann, Gerrit; LeGrande, Allegra N.; Guo, Chuncheng; Cao, Jian; Brady, Esther C.; Abe‐Ouchi, Ayako

doi:10.5194/cp-2019-168

Cited by 15 publications

(31 citation statements)

References 74 publications

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“…6c, d), consis-1 Further analysis and description of the results of these PMIP4 experiments can be found in other articles in this special issuee.g. Brierley et al (2020) for midHolocene and Otto-Bliesner et al (2020) for lig127k. tent with previous modelling studies and proxy reconstructions (Ballantyne et al, 2005;MARGO Project Members et al, 2009;Masson-Delmotte et al, 2014;Otto-Bliesner et al, 2009).…”

Section: Mean State Changesmentioning

confidence: 94%

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Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

Brown

Brierley

et al. 2020

Clim. Past

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Abstract. El Niño–Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.

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Section: Mean State Changesmentioning

confidence: 94%

“…Mechanisms and drivers for precipitation changes over the tropics in last interglacial climates are still unclear and represent an active area of research (see, e.g. Scussolini et al, 2019;Otto-Bliesner et al, 2020).…”

Section: Mean State Changesmentioning

confidence: 99%

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

Brown

Brierley

et al. 2020

Clim. Past

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“…At each site, the 6 ka anomaly (corresponding to the 5.5-6.5 ka average value) is given relative to the present day, and in the case where modern values could not be directly inferred from the record, modern climatology values were extracted from the Climate Research Unit historical climatology dataset (New et al, 2002). Further proxy data for the MH, such as SST reconstructions, are not included here, as an extensive model-data comparison is presented in a companion paper (Brierley et al, 2020).…”

Section: Datamentioning

confidence: 99%

“…the SST value at 127 ka was taken on the provided mean 0.1 kyr interpolated SST curve for each core location. Data syntheses from both Capron et al (2014Capron et al ( , 2017 and Hoffman et al 2017are associated with quantitative uncertainties accounting for relative dating and surface temperature reconstruction methods. Here, the two datasets are treated as independent data benchmarks, as they use different reference chronologies and methodologies to infer temporal surface temperature changes, and therefore they should not be combined.…”

Section: Datamentioning

confidence: 99%

“…Drake et al, 2011;Lézine et al, 2011). Recent palaeodata compilations involving either air temperatures or sea surface temperature (SST) (Capron et al, 2014;Hoffman et al, 2017) reveal that the maximum temperatures were reached asynchronously in the LIG between the Northern Hemisphere and Southern Hemisphere. Concerning precipitation, historically this has been lacking relative to temperature or SST reconstructions.…”

Section: Introductionmentioning

confidence: 99%

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CMIP6/PMIP4 simulations of the mid-Holocene and Last Interglacial using HadGEM3: comparison to the pre-industrial era, previous model versions and proxy data

et al. 2020

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Abstract. Palaeoclimate model simulations are an important tool to improve our understanding of the mechanisms of climate change. These simulations also provide tests of the ability of models to simulate climates very different to today. Here we present the results from two brand-new simulations using the latest version of the UK's physical climate model, HadGEM3-GC3.1; they are the mid-Holocene (∼6 ka) and Last Interglacial (∼127 ka) simulations, both conducted under the auspices of CMIP6/PMIP4. This is the first time this version of the UK model has been used to conduct palaeoclimate simulations. These periods are of particular interest to PMIP4 because they represent the two most recent warm periods in Earth history, where atmospheric concentration of greenhouse gases and continental configuration are similar to the pre-industrial period but where there were significant changes to the Earth's orbital configuration, resulting in a very different seasonal cycle of radiative forcing. Results for these simulations are assessed firstly against the same model's pre-industrial control simulation (a simulation comparison, to describe and understand the differences between the pre-industrial – PI – and the two palaeo simulations) and secondly against previous versions of the same model relative to newly available proxy data (a model–data comparison, to compare all available simulations from the same model with proxy data to assess any improvements due to model advances). The introduction of this newly available proxy data adds further novelty to this study. Globally, for metrics such as 1.5 m temperature and surface rainfall, whilst both the recent palaeoclimate simulations are mostly capturing the expected sign and, in some places, magnitude of change relative to the pre-industrial, this is geographically and seasonally dependent. Compared to newly available proxy data (including sea surface temperature – SST – and rainfall) and also incorporating data from previous versions of the model shows that the relative accuracy of the simulations appears to vary according to metric, proxy reconstruction used for comparison and geographical location. In some instances, such as mean rainfall in the mid-Holocene, there is a clear and linear improvement, relative to proxy data, from the oldest to the newest generation of the model. When zooming into northern Africa, a region known to be problematic for models in terms of rainfall enhancement, the behaviour of the West African monsoon in both recent palaeoclimate simulations is consistent with current understanding, suggesting a wetter monsoon during the mid-Holocene and (more so) the Last Interglacial, relative to the pre-industrial era. However, regarding the well-documented “Saharan greening” during the mid-Holocene, results here suggest that the most recent version of the UK's physical model is still unable to reproduce the increases suggested by proxy data, consistent with all other previous models to date.

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Eurasian Holocene climate trends in transient coupled climate simulations and stable oxygen isotope records

Danek

Gierz

Kostrova

et al. 2021

J Quaternary Science

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Transient simulations of the global fully coupled climate model COSMOS under realistic varying orbital and greenhouse gas forcings are systematically compared to diatom oxygen isotope ( δ 18 O 0.1em diatom0.1em) records from Russian lakes with focus on Eurasian Holocene climate trends. The measured δ 18 O 0.1em diatom0.1em decrease and other temperature proxies are interpreted as large‐scale cooling throughout the Holocene while the model simulations are biased too warm, likely through missing radiative forcings. This large‐scale warm bias also dictates the modeled δ 18 O 0.1em precipitation. Hence, at locations where the signs of model and proxy temperature/precipitation trends agree, measured δ 18 O 0.1em diatom0.1em and modeled δ 18 O 0.1em precipitation0.1em trends show notable accordance. An increased temporal variability of modeled δ 18 O 0.1em precipitation0.1em is linked to persistent atmospheric circulation patterns. Applying the transient forcings in an accelerated way (every 10th year only) yields a similar, yet weaker or delayed model response, especially in the ocean.

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Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations

Cited by 15 publications

References 74 publications

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

CMIP6/PMIP4 simulations of the mid-Holocene and Last Interglacial using HadGEM3: comparison to the pre-industrial era, previous model versions and proxy data

Eurasian Holocene climate trends in transient coupled climate simulations and stable oxygen isotope records

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