Dataset Information

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

ABSTRACT: Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO₂ concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.

SUBMITTER: Dome Fuji Ice Core Project Members:

PROVIDER: S-EPMC5298857 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

Kawamura Kenji K Abe-Ouchi Ayako A Motoyama Hideaki H Ageta Yutaka Y Aoki Shuji S Azuma Nobuhiko N Fujii Yoshiyuki Y Fujita Koji K Fujita Shuji S Fukui Kotaro K Furukawa Teruo T Furusaki Atsushi A Goto-Azuma Kumiko K Greve Ralf R Hirabayashi Motohiro M Hondoh Takeo T Hori Akira A Horikawa Shinichiro S Horiuchi Kazuho K Igarashi Makoto M Iizuka Yoshinori Y Kameda Takao T Kanda Hiroshi H Kohno Mika M Kuramoto Takayuki T Matsushi Yuki Y Miyahara Morihiro M Miyake Takayuki T Miyamoto Atsushi A Nagashima Yasuo Y Nakayama Yoshiki Y Nakazawa Takakiyo T Nakazawa Fumio F Nishio Fumihiko F Obinata Ichio I Ohgaito Rumi R Oka Akira A Okuno Jun'ichi J Okuyama Junichi J Oyabu Ikumi I Parrenin Frédéric F Pattyn Frank F Saito Fuyuki F Saito Takashi T Saito Takeshi T Sakurai Toshimitsu T Sasa Kimikazu K Seddik Hakime H Shibata Yasuyuki Y Shinbori Kunio K Suzuki Keisuke K Suzuki Toshitaka T Takahashi Akiyoshi A Takahashi Kunio K Takahashi Shuhei S Takata Morimasa M Tanaka Yoichi Y Uemura Ryu R Watanabe Genta G Watanabe Okitsugu O Yamasaki Tetsuhide T Yokoyama Kotaro K Yoshimori Masakazu M Yoshimoto Takayasu T

Science advances 20170208 2

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record fro ...[more]

PMID: 28246631

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Project description:BackgroundThe lack of instrumental data before the mid-19th-century limits our understanding of present warming trends. In the absence of direct measurements, we used proxies that are natural or historical archives recording past climatic changes. A gridded reconstruction of spring-summer temperature was produced for Europe based on tree-rings, documentaries, pollen assemblages and ice cores. The majority of proxy series have an annual resolution. For a better inference of long-term climate variation, they were completed by low-resolution data (decadal or more), mostly on pollen and ice-core data.Methodology/principal findingsAn original spectral analog method was devised to deal with this heterogeneous dataset, and to preserve long-term variations and the variability of temperature series. So we can replace the recent climate changes in a broader context of the past 1400 years. This preservation is possible because the method is not based on a calibration (regression) but on similarities between assemblages of proxies. The reconstruction of the April-September temperatures was validated with a Jack-knife technique. It was also compared to other spatially gridded temperature reconstructions, literature data, and glacier advance and retreat curves. We also attempted to relate the spatial distribution of European temperature anomalies to known solar and volcanic forcings.ConclusionsWe found that our results were accurate back to 750. Cold periods prior to the 20(th) century can be explained partly by low solar activity and/or high volcanic activity. The Medieval Warm Period (MWP) could be correlated to higher solar activity. During the 20(th) century, however only anthropogenic forcing can explain the exceptionally high temperature rise. Warm periods of the Middle Age were spatially more heterogeneous than last decades, and then locally it could have been warmer. However, at the continental scale, the last decades were clearly warmer than any period of the last 1400 years. The heterogeneity of MWP versus the homogeneity of the last decades is likely an argument that different forcings could have operated. These results support the fact that we are living a climate change in Europe never seen in the past 1400 years.

Dataset Information

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

Publications

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

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