the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The hydrological cycle and ocean circulation of the Maritime Continent in the mid-Pliocene: results from PlioMIP2
- 1School of Geographical Sciences, University of Bristol, Bristol, UK
- 2Institute for Marine and Atmospheric research Utrecht (IMAU), Department of Physics, Utrecht University, Utrecht, the Netherlands
- 3Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan
- 4Climate and Global Change Dynamics lab, National Center for Atmospheric research, USA
- 5NCAS, Department of Meteorology, University of Reading, Reading, UK
- 6Alfred-Wegener-Institut – Helmholtz-Zentrum für Polar and Meeresforschung (AWI), Bremerhaven, Germany
- 7NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
- 8Department of Physics, University of Toronto, Toronto, Canada
- 9School of Earth and Environment, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire, UK
- 10Center for Climate Systems Research at Columbia University, New York, NY, USA
- 11NASA Goddard Institute for Space Studies, New York, NY, USA
- 12LSCE/IPSL – Laboratoire des Sciences du Climat et de l’Environnement, UMR8212, CEA-CNRS-UVSQ – CE Saclay, L’Orme des Merisiers, Gif-sur-Yvette Cedex, France
- 13Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China
- 14Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- 15Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
- 16Department of Earth Sciences, College of Liberal Arts and Sciences, University of Connecticut, Storrs, USA
- 17Centre for Severe Weather and Climate and Hydro-geological HazardsWuhan, China
- 18Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan, China
- 19Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
- 20Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
- 1School of Geographical Sciences, University of Bristol, Bristol, UK
- 2Institute for Marine and Atmospheric research Utrecht (IMAU), Department of Physics, Utrecht University, Utrecht, the Netherlands
- 3Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan
- 4Climate and Global Change Dynamics lab, National Center for Atmospheric research, USA
- 5NCAS, Department of Meteorology, University of Reading, Reading, UK
- 6Alfred-Wegener-Institut – Helmholtz-Zentrum für Polar and Meeresforschung (AWI), Bremerhaven, Germany
- 7NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
- 8Department of Physics, University of Toronto, Toronto, Canada
- 9School of Earth and Environment, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire, UK
- 10Center for Climate Systems Research at Columbia University, New York, NY, USA
- 11NASA Goddard Institute for Space Studies, New York, NY, USA
- 12LSCE/IPSL – Laboratoire des Sciences du Climat et de l’Environnement, UMR8212, CEA-CNRS-UVSQ – CE Saclay, L’Orme des Merisiers, Gif-sur-Yvette Cedex, France
- 13Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China
- 14Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- 15Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
- 16Department of Earth Sciences, College of Liberal Arts and Sciences, University of Connecticut, Storrs, USA
- 17Centre for Severe Weather and Climate and Hydro-geological HazardsWuhan, China
- 18Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan, China
- 19Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
- 20Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
Abstract. The Maritime Continent (MC) forms the western boundary of the tropical Pacific Ocean, and relatively small changes in this region can impact the climate locally and remotely. In the mid-Pliocene (from 3.264 to 3.025 million years before present), atmospheric CO2 concentrations were ~ 400 ppm, and the subaerial Sunda and Sahul shelves made the land-sea distribution of the MC different to today. Topographic changes and elevated levels of CO2, combined with other forcings, are therefore expected to have driven a substantial climate signal in the MC region at this time. By using the results from the Pliocene Model Intercomparison Project phase 2 (PlioMIP2) we study the mean climatic features of the MC in the mid-Pliocene and changes in Indonesian Throughflow (ITF) with respect to preindustrial. Results show a warmer and wetter mid-Pliocene climate of the MC and lower sea surface salinity in the surrounding ocean compared with preindustrial. Furthermore, we quantify the volume transfer through the ITF; although the ITF may be expected to be hindered by the subaerial shelves, 10 out of 15 models show an increased volume transport compared with preindustrial.
In order to avoid undue influence from closely-related models that are present in the PlioMIP2 ensemble, we introduce a new metric – the multi-cluster mean (MCM), based on cluster analysis of the individual models. We study the effect that the choice of MCM versus the more traditional analysis of multi-model mean (MMM) and individual models has on the discrepancy between model results and reconstructed proxy data. The clusters reveal spatial signals that are not captured by the MMM, so that the MCM provides us with a new way to explore the results from model ensemble that include similar models.
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Xin Ren et al.
Status: open (until 13 Feb 2023)
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RC1: 'Comment on egusphere-2022-1281', Anonymous Referee #1, 16 Jan 2023
reply
This manuscript examines simulations of the mid-Pliocene from the PlioMIP2 models. The authors focus on the mean climate features in the maritime continent. They find a warmer and wetter mid-Pliocene climate, with a lower sea surface salinity and in general a stronger Indonesian Throughflow (ITF) in the PlioMIP2 simulations. The author also explore the use of multi-cluster mean in summarizing multiple model results and noted the advantage of this method over the traditional multiple model mean.
The manuscript is very well-written and easy to follow. The manuscript fits well with the scope of Climate of the Past. I have a few comments that need to be addressed before publication. Please see details below.
- Results on ITF are not well connected with the rest of the manuscript. In other words, why should we care about the ITF in the Pliocene simulations (considering that we do not have proxy data to provide sufficient constraints on the model results)? In the current form of the manuscript, ITF is described separately from the SST and hydroclimate variables. Although, in the introduction, the author did cite literation on how the ITF is linked to coupled ocean-atmosphere variability and how the ITF may influence the monsoons. However, the authors results on ITF do not make any of the connection or mechanistic analysis. Given this disjoint, I am wondering whether the author should consider cutting the ITF results and focus on the regional SST and hydroclimate over the Maritime Continent instead.
- In the Discussion (Section 4.3), the authors stated that “but even models of the same model family may still produce different climatic signals depending on the analysis region or the studied climate characteristic.” Can you provide explanation for this interesting result? Is it because of the potentially different model resolution, or details of the boundary condition implemented by different authors, or internal variability?
- Are there available proxies on the hydroclimate (precipitation /evaporation and sea surface salinity) and ITF in the region? If yes, please include results and discussion on these comparisons. If no, please state it explicitly in the manuscript (that there is no available proxy for benchmarking models).
- Please consider adding a summary of model-proxy comparison of SST in the abstract.
Minor comments
- Lines 23–25: Rewrite and change into “A large amount of rainfall releases large quantities of latent heat into the atmosphere, which is an important driver of global atmospheric circulation”.
- Many of the multi-panel plots are not labeled with subplot label (such as (a) and (b). Please check and make sure all the subplots are properly labeled.
- Information should be provided on how the ocean salinity was initialized in the simulations. This information is needed because the authors examined the sea-surface salinity changes in the PlioMIP simulations (e.g., Figure 5d), and it is not clear whether the ice-volume effect has been accounted for in the simulations and has an imprint in Figure 5d.
- Line 266: “the relationship is not exactly linear.”
- Figure 10: cluster 5 (GISS) looks weird. The model resolution is ~2 degree (Table 1). It is hard to believe the precipitation anomaly has such a rich fine structure. Please double check and make sure calculation has been done correctly.
Xin Ren et al.
Xin Ren et al.
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