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SCIENCE CHINA Earth Sciences, Volume 61 , Issue 9 : 1279-1291(2018) https://doi.org/10.1007/s11430-017-9196-4

Reconstruction of autumn sea ice extent changes since AD1289 in the Barents-Kara Sea, Arctic

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  • ReceivedNov 12, 2017
  • AcceptedApr 24, 2018
  • PublishedMay 3, 2018

Abstract


Funded by

the National Natural Science Foundation of China(Grant,No.,41425003)

the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant,No.,XDA19070103)

the Basic Research Project of Chinese Academy of Meteorological Sciences-Base Construction of Polar Atmospheric Sciences for Field Observation

and the Scientific Research Foundation of the Key Laboratory of Cryospheric Sciences(Grant,No.,SKLCS-OP-2016-03)


Acknowledgment

This research was supported by the National Natural Science Foundation of China (Grant No. 41425003), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19070103), the Basic Research Project of Chinese Academy of Meteorological Sciences-Base Construction of Polar Atmospheric Sciences for Field Observation, and the Scientific Research Foundation of the Key Laboratory of Cryospheric Sciences (Grant No. SKLCS-OP-2016-03).


References

[1] Abram N J, Wolff E W, Curran M A J. A review of sea ice proxy information from polar ice cores. Quat Sci Rev, 2013, 79: 168-183 CrossRef ADS Google Scholar

[2] Barnes E A. Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. Geophys Res Lett, 2013, 40: 4734-4739 CrossRef ADS Google Scholar

[3] Barnes E A, Screen J A. 2015. The impact of Arctic warming on the midlatitude jet-stream: Can it? Has it? Will it? WIREs Clim Change, 6: 277–286. Google Scholar

[4] Benassai S, Becagli S, Gragnani R, Magand O, Proposito M, Fattori I, Traversi R, Udisti R. Sea-spray deposition in Antarctic coastal and plateau areas from ITASE traverses. Ann Glaciol, 2005, 41: 32-40 CrossRef Google Scholar

[5] Bothe O, Evans M, Donado L F, Bustamante E G, Gergis J, Gonzalez-Rouco J F, Goosse H, Hegerl G, Hind A, Jungclaus J H, Kaufman D. 2015. Continental-scale temperature variability in PMIP3 simulations and PAGES 2k regional temperature reconstructions over the past millennium. Clim Past, 11: 1673–1699. Google Scholar

[6] Cohen J, Screen J A, Furtado J C, Barlow M, Whittleston D, Coumou D, Francis J, Dethloff K, Entekhabi D, Overland J, Jones J. Recent Arctic amplification and extreme mid-latitude weather. Nat Geosci, 2014, 7: 627-637 CrossRef ADS Google Scholar

[7] Cook E R, D’Arrigo R D, Mann M E. A well-verified, multiproxy reconstruction of the winter North Atlantic Oscillation Index since AD 1400. J Clim, 2002, 15: 1754-1764 CrossRef Google Scholar

[8] Curran M A J, van Ommen T D, Morgan V I, Phillips K L, Palmer A S. Ice core evidence for Antarctic Sea ice decline since the 1950s. Science, 2003, 302: 1203-1206 CrossRef PubMed ADS Google Scholar

[9] D’Arrigo R, Jacoby G, Wilson R, Panagiotopoulos F. A reconstructed Siberian High index since AD1599 from Eurasian and North American tree rings. Geophys Res Lett, 2005, 32: L05705 CrossRef ADS Google Scholar

[10] Fauria M M, Grinsted A, Helama S, Moore J, Timonen M, Martma T, Isaksson E, Eronen M. Unprecedented low twentieth century winter sea ice extent in the Western Nordic Seas since AD1200. Clim Dyn, 2010, 34: 781-795 CrossRef ADS Google Scholar

[11] Francis J A, Chan W, Leathers D J, Miller J R, Veron D E. Winter Northern Hemisphere weather patterns remember summer Arctic sea-ice extent. Geophys Res Lett, 2009, 36: L07503 CrossRef ADS Google Scholar

[12] Goosse H, Renssen H, Timmermann A, Bradley R S, Mann M E. Using paleoclimate proxy-data to select optimal realisations in an enSemble of simulations of the climate of the past millennium. Clim Dyn, 2006, 27: 165-184 CrossRef ADS Google Scholar

[13] IPCC. 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. In: Hartmann D L, Klein Tank A M G, Rusticucci M, Alexander L V, Brönnimann S, Charabi Y, Dentener F J, Dlugokencky E J, Easterling D R, Kaplan A, Soden B J, Thorne P W, Wild M, Zhai P M, eds. Observations: Atmosphere and Surface. Cambridge: Cambridge University Press. Google Scholar

[14] Henderson K A. 2002. An ice core paleoclimate study of Windy Dome, Franz Josef Land (Russia): Development of a recent climate history for the Barents Sea. Doctoral Dissertation. Columbus: Ohio State University. Google Scholar

[15] Helama S, Fauria M M, Mielikainen K, Timonen M, Eronen M. Sub-Milankovitch solar forcing of past climates: Mid and late Holocene perspectives. Geol Soc Am Bull, 2010, 122: 1981-1988 CrossRef ADS Google Scholar

[16] Honda M, Inoue J, Yamane S. Influence of low Arctic sea-ice minima on anomalously cold Eurasian winters. Geophys Res Lett, 2009, 36: L08707 CrossRef ADS Google Scholar

[17] Hopsch S, Cohen J, Dethloff K. Analysis of a link between fall Arctic sea ice concentration and atmospheric patterns in the following winter. Tellus Ser A-Dyn Meteorol Oceanol, 2012, 64: 18624 CrossRef Google Scholar

[18] Inoue J, Hori M E, Takaya K. The role of Barents Sea Ice in the wintertime cyclone track and emergence of a warm-Arctic cold-Siberian anomaly. J Clim, 2012, 25: 2561-2568 CrossRef ADS Google Scholar

[19] Isaksson E, Divine D, Kohler J, Martma T, Pohjola V, Motoyama H, Watanabe O. Climate oscillations as recorded in svalbard ice core δ18O records between ad 1200 and 1997. Geogr Ann Ser A-Phys Geogr, 2005a, 87: 203-214 CrossRef Google Scholar

[20] Isaksson E, Kekonen T, Moore J, Mulvaney R. The methanesulfonic acid (MSA) record in a Svalbard ice core. Ann Glaciol, 2005b, 42: 345-351 CrossRef Google Scholar

[21] Isaksson E, Kohler J, Pohjola V, Moore J, Igarashi M, Karlöf L, Martma T, Meijer H, Motoyama H, Vaikmäe R, van de Wal R S W. Two ice-core δ18O records from Svalbard illustrating climate and sea-ice variability over the last 400 years. Holocene, 2005c, 15: 501-509 CrossRef Google Scholar

[22] Jones P. The reliability of global and hemispheric surface temperature records. Adv Atmos Sci, 2016, 33: 269-282 CrossRef ADS Google Scholar

[23] Jones P D, Mann M E. Climate over past millennia. Rev Geophys, 2004, 42: RG2002 CrossRef ADS Google Scholar

[24] Kaufman D S, Schneider D P, McKay N P, Ammann C M, Bradley R S, Briffa K R, Miller G H, Otto-Bliesner B L, Overpeck J T, Vinther B M, Abbott M, Axford Y, Bird B, Birks H J B, Bjune A E, Briner J, Cook T, Chipman M, Francus P, Gajewski K, Geirsdottir A, Hu F S, Kutchko B, Lamoureux S, Loso M, MacDonald G, Peros M, Porinchu D, Schiff C, Seppa H, Thomas E. Recent warming reverses long-term Arctic cooling. Science, 2009, 325: 1236-1239 CrossRef PubMed ADS Google Scholar

[25] Kekonen T, Moore J, Perämäki P, Mulvaney R, Isaksson E, Pohjola V, van W R S. The 800 year long ion record from the Lomonosovfonna (Svalbard) ice core. J Geophys Res, 2005, 110: D07304 CrossRef ADS Google Scholar

[26] Kinnard C, Zdanowicz C M, Fisher D A, Isaksson E, de Vernal A, Thompson L G. Reconstructed changes in Arctic sea ice over the past 1450 years. Nature, 2011, 479: 509-512 CrossRef PubMed ADS Google Scholar

[27] Lewis E R, Schwartz S E. 2004. Sea Salt Aerosol Production: Mechanisms, Methods, Measurements, and Models—A Critical Review. Washington D C: American Geophysical Union.152. Google Scholar

[28] Liu J, Curry J A, Wang H, Song M, Horton R M. Impact of declining Arctic sea ice on winter snowfall. Proc Natl Acad Sci USA, 2012, 109: 4074-4079 CrossRef PubMed ADS Google Scholar

[29] Liu J, Chen Z, Francis J, Song M, Mote T, Hu Y. 2016. Has Arctic sea ice loss contributed to increased surface melting of the Greenland ice sheet? J Clim, 29: 3373–3386. Google Scholar

[30] McCusker K E, Fyfe J C, Sigmond M. Twenty-five winters of unexpected Eurasian cooling unlikely due to Arctic sea-ice loss. Nat Geosci, 2016, 9: 838-842 CrossRef ADS Google Scholar

[31] Motoyama H, Watanabe O, Goto-Azuma K, Igarashi M, Miyahara M, Nagasaki T, Karloef L, Isaksson E. 2001. Activities of the Japanese Arctic Glaciological Expedetion in 1999 (JAGE 1999). Technical Report. Memoirs of National Institute of Polar Research. Special issue, 54: 253–260. Google Scholar

[32] Muscheler R, Joos F, Beer J, Müller S A, Vonmoos M, Snowball I. Solar activity during the last 1000 yr inferred from radionuclide records. Quat Sci Rev, 2007, 26: 82-97 CrossRef ADS Google Scholar

[33] Opel T, Fritzsche D, Meyer H. Eurasian Arctic climate over the past millennium as recorded in the Akademii Nauk ice core (Severnaya Zemlya). Clim Past, 2013, 9: 2379-2389 CrossRef ADS Google Scholar

[34] Overland J, Francis J A, Hall R, Hanna E, Kim S J, Vihma T. 2015. The melting Arctic and midlatitude weather patterns: Are they connected? J Clim, 28: 7917–7932. Google Scholar

[35] PAGES 2k Consortium. 2013. Continental-scale temperature variability during the past two millennia. Nat Geosci, 6: 339–346. Google Scholar

[36] Petoukhov V, Semenov V A. A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. J Geophys Res, 2010, 115: D21111 CrossRef ADS Google Scholar

[37] Röthlisberger R, Mulvaney R, Wolff E W, Hutterli M A, Bigler M, De A M, Hansson M E, Steffensen J P, Udisti R. Limited dechlorination of sea-salt aerosols during the last glacial period: Evidence from the European Project for Ice Coring in Antarctica (EPICA) Dome C ice core. J Geophys Res, 2003, 108: 4526 CrossRef ADS Google Scholar

[38] Röthlisberger R, Crosta X, Abram N J, Armand L, Wolff E W. Potential and limitations of marine and ice core sea ice proxies: An example from the Indian Ocean sector. Quat Sci Rev, 2010, 29: 296-302 CrossRef ADS Google Scholar

[39] Screen J A, Simmonds I. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 2010, 464: 1334-1337 CrossRef PubMed ADS Google Scholar

[40] Screen J A, Simmonds I. Declining summer snowfall in the Arctic: Causes, impacts and feedbacks. Clim Dyn, 2012, 38: 2243-2256 CrossRef ADS Google Scholar

[41] Serreze M C, Holland M M, Stroeve J. Perspectives on the Arctic’s shrinking sea-ice cover. Science, 2007, 315: 1533-1536 CrossRef PubMed ADS Google Scholar

[42] Shapiro I, Colony R, Vinje T. 2003. April sea ice extent in the Barents Sea, 1850–2001. Polar Res, 22: 5–10. Google Scholar

[43] Soon W, Connolly R, Connolly M. Re-evaluating the role of solar variability on Northern Hemisphere temperature trends since the 19th century. Earth-Sci Rev, 2015, 150: 409-452 CrossRef Google Scholar

[44] Suo L, Otterå O H, Bentsen M, Gao Y, Johannessen O M. External forcing of the early 20th century Arctic warming. Tellus Ser A-Dyn Meteorol Oceanol, 2013, 65: 20578 CrossRef Google Scholar

[45] Tang Q, Zhang X, Yang X, Francis J A. Cold winter extremes in northern continents linked to Arctic sea ice loss. Environ Res Lett, 2013, 8: 014036 CrossRef ADS Google Scholar

[46] Trouet V, Esper J, Graham N E, Baker A, Scourse J D, Frank D C. Persistent positive North Atlantic oscillation mode dominated the medieval climate anomaly. Science, 2009, 324: 78-80 CrossRef PubMed ADS Google Scholar

[47] Vare L L, Massé G, Belt S T. A biomarker-based reconstruction of sea ice conditions for the Barents Sea in recent centuries. Holocene, 2010, 20: 637-643 CrossRef Google Scholar

[48] Walsh J E. Intensified warming of the Arctic: Causes and impacts on middle latitudes. Glob Planet Change, 2014, 117: 52-63 CrossRef ADS Google Scholar

[49] Wu B Y, Su J Z, Zhang R H. Effects of autumn-winter Arctic sea ice on winter Siberian High. Chin Sci Bull, 2011, 56: 3220-3228 CrossRef Google Scholar

[50] Wu B Y, Yang K. 2016. Roles of Arctic sea ice and the preceding summer Arctic atmospheric circulation anomalies in the atmospheric circulations anomalies of 2011/2012 and 2015/2016 winters (in Chinese). Acta Meteorol Sin, 74: 683–696. Google Scholar

[51] Wu B Y, Bian L G, Zhang R H. 2004. Effects of the winter AO and the Arctic sea ice variations on climate variation over East Asia (in Chinese). Chin J Polar Res, 16: 211–220. Google Scholar

[52] Xiao C, Dou T, Sneed S B, Li R, Allison I. An ice-core record of Antarctic sea-ice extent in the southern Indian Ocean for the past 300 years. Ann Glaciol, 2015, 56: 451-455 CrossRef ADS Google Scholar

[53] Yang K, Jiang D. Interannual climate variability change during the Medieval Climate Anomaly and Little Ice Age in PMIP3 last millennium simulations. Adv Atmos Sci, 2017, 34: 497-508 CrossRef ADS Google Scholar

[54] Yang X, Pyle J A, Cox R A. Sea salt aerosol production and bromine release: Role of snow on sea ice. Geophys Res Lett, 2008, 35: L16815 CrossRef ADS Google Scholar

  • Figure 1

    Comparison and combination of the B-K SIE data from NASA and NSIDC. (a) Sea ice time series after combination (1956–2012); the yellow box indicates the overlapping period of the two data sets. (b) Comparison of the two series during the overlapping period (1979–2006). (c) Scatter plot showing the least squares fitting results of the two series (the x and y axes represent the NSIDC and NASA SIE data, respectively).

  • Figure 2

    Proxy data types and spatial distributions. The numbers next to the points indicate the quantity of data.

  • Figure 3

    Reconstruction results of the ordinary least squares regression (OLSR). (a) SLR reconstruction results; (b) OR reconstruction results. The insets represent the fitting results and the raw data pairs of the two reconstruction steps (1402–1993 and 1289–1401). The x and y axes represent the proxy data and the sea ice instrumental data, respectively.

  • Figure 4

    The PCR reconstruction result of the B-K SIE.

  • Figure 5

    Comparison of statistics among the different PLSR models built using a different number of PCs. (a1)–(c1) Represent the first reconstruction step (1402–1993), and (a2)–(c2) represent the second reconstruction step (1289–1401).

  • Figure 6

    The PLSR reconstruction result of the B-K SIE.

  • Figure 7

    The results of the different reconstruction methods and their comparisons with the SIE instrumental data. (a) and (b) show the SIE sequence comparisons for the calibration period during the two reconstruction steps (1402–1993 and 1289–1401, respectively). OBS represents the SIE observation data sequence. (c) and (d) show the results of the entire reconstruction period with 30-year smoothing, and SYN in (d) represents the final SIE synthesis results for the reconstruction.

  • Figure 8

    B-K SIE reconstruction result from AD1289–1993.

  • Figure 9

    Comparison of our autumn B-K SIE reconstruction result with other relevant climatic reconstruction sequences. (a) Our reconstruction result for autumn B-K SIE; (b) reconstruction of Barents Sea ice conditions in spring based on IP25 (Vare et al., 2010); (c) reconstructed Arctic SIE in August (Kinnard et al., 2011); (d) Arctic temperature reconstruction results (Kaufman et al., 2009) and CRUTEM3 Arctic temperature data; (e) NAO reconstruction series (Cook et al., 2002; Trouet et al., 2009); and (f) the reconstruction of the Siberian High index in winter (SH Index) (D’Arrigo et al., 2005).

  • Table 1   Details of the proxy dat

    Label

    Type

    Location

    Latitude

    Longitude

    Period

    Correlation

    Source

    P1

    Ice core δ18O

    SA

    79.8°N

    24°E

    1400–1998

    −0.49**

    Isaksson et al., 2005a

    P2

    Ice core MSA

    SL

    78.9°N

    17.4°E

    1121–1996

    −0.32*

    Isaksson et al., 2005b

    P3

    Ice core Na+

    SL

    78.9°N

    17.4°E

    1121–1996

    −0.31*

    Kekonen et al., 2005

    P4

    Ice core Na+

    SZ

    80.5°N

    94.8°E

    900–1998

    −0.33**

    Opel et al., 2013

    P5

    Ice core δ18O

    SA

    79.8°N

    24°E

    1280–1998

    −0.46**

    Isaksson et al., 2005c

    P6

    Ice core δ18O

    FJL

    81°N

    64°E

    1225–1996

    −0.50**

    Henderson, 2002

    P7

    Tree Ring Width

    FL

    69°N

    25°E

    0–2005

    −0.35**

    Helama et al., 2010

    P8

    Ice core Na+

    SA

    79.8°N

    24°E

    1303–1998

    −0.30*

    Motoyama et al., 2001

    P9

    Ice core Na+

    FJL

    81°N

    64°E

    1227–1996

    −0.36**

    Henderson, 2002

    ** indicates significance at the 95% confidence level, and * indicates significance at the 90% confidence level. The proxy data all utilize a 1-year resolution. SA: Svalbard Austfonna; SL: Svalbard Lomonosofonna; SZ: Severnaya-Zemlya; FJL: Franz Joseph Land; and FL: Finnish Lapland

  • Table 2   Correlation coefficients between the proxy data

    Proxy 1

    Proxy 4

    Proxy 5

    Proxy 6

    Proxy 7

    Proxy 9

    Proxy 1

    1.00

    0.32

    0.58*

    0.28

    0.36*

    0.23

    Proxy 4

    1.00

    0.47*

    0.01

    −0.06

    0.40*

    Proxy 5

    1.00

    0.20

    0.13

    0.61*

    Proxy 6

    1.00

    0.30

    0.29

    Proxy 7

    1.00

    0.19

    Proxy 9

    1.00

    * indicates significance at the 95% confidence level.

  • Table 3   Comparison of statistics when using different models

    Model

    Proxy data quantity

    Correlation coefficient

    Explained variance

    RE

    D-W statistic

    F statistic

    SLR-1

    6

    0.62

    0.36

    0.31

    1.99

    21.99

    SLR-2

    5

    0.57

    0.32

    0.26

    1.97

    17.62

    OR-1

    6

    0.66

    0.43

    0.17

    2.10

    3.95

    OR-2

    5

    0.64

    0.40

    0.19

    2.20

    4.34

    PCR-1

    6

    0.63

    0.40

    0.28

    2.04

    11.50

    PCR-2

    5

    0.60

    0.36

    0.23

    2.03

    9.70

    PLSR-1

    9

    0.65

    0.42

    0.14

    2.14

    8.17

    PLSR-2

    8

    0.61

    0.37

    0.12

    2.15

    6.70

    The correlation coefficients and the F statistics all exceed the 99% significance level. Labels 1 and 2 after the model names in the Method column represent the two reconstruction steps.

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