scholarly journals Recurrent transitions to Little Ice Age-like climatic regimes over the Holocene

2021 ◽  
Author(s):  
Samuli Helama ◽  
Markus Stoffel ◽  
Richard J. Hall ◽  
Phil D. Jones ◽  
Laura Arppe ◽  
...  
Keyword(s):  
Sea Ice ◽  
Tree Ring ◽  
Little Ice Age ◽  
Arctic Sea Ice ◽  
Ice Age ◽  
Late Nineteenth Century ◽  
Climate Modelling ◽  
Sea Ice Extent ◽  
Cold Temperatures ◽  
Tree Ring Data

AbstractHolocene climate variability is punctuated by episodic climatic events such as the Little Ice Age (LIA) predating the industrial-era warming. Their dating and forcing mechanisms have however remained controversial. Even more crucially, it is uncertain whether earlier events represent climatic regimes similar to the LIA. Here we produce and analyse a new 7500-year long palaeoclimate record tailored to detect LIA-like climatic regimes from northern European tree-ring data. In addition to the actual LIA, we identify LIA-like ca. 100–800 year periods with cold temperatures combined with clear sky conditions from 540 CE, 1670 BCE, 3240 BCE and 5450 BCE onwards, these LIA-like regimes covering 20% of the study period. Consistent with climate modelling, the LIA-like regimes originate from a coupled atmosphere–ocean–sea ice North Atlantic-Arctic system and were amplified by volcanic activity (multiple eruptions closely spaced in time), tree-ring evidence pointing to similarly enhanced LIA-like regimes starting after the eruptions recorded in 1627 BCE, 536/540 CE and 1809/1815 CE. Conversely, the ongoing decline in Arctic sea-ice extent is mirrored in our data which shows reversal of the LIA-like conditions since the late nineteenth century, our record also correlating highly with the instrumentally recorded Northern Hemisphere and global temperatures over the same period. Our results bridge the gaps between low- and high-resolution, precisely dated proxies and demonstrate the efficacy of slow and fast components of the climate system to generate LIA-like climate regimes.

scholarly journals Impact of Volcanic Eruptions on Decadal to Centennial Fluctuations of Arctic Sea Ice Extent during the Last Millennium and on Initiation of the Little Ice Age

2018 ◽  
Vol 31 (6) ◽  
pp. 2145-2167 ◽  
Author(s):  
Joanna Slawinska ◽  
Alan Robock
Keyword(s):  
Sea Ice ◽  
Little Ice Age ◽  
Volcanic Eruptions ◽  
Arctic Sea Ice ◽  
Ice Age ◽  
Last Millennium ◽  
Sea Ice Extent ◽  
Decadal Scale ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

This study evaluates different hypotheses of the origin of the Little Ice Age, focusing on the long-term response of Arctic sea ice and oceanic circulation to solar and volcanic perturbations. The authors analyze the Last Millennium Ensemble of climate model simulations carried out with the Community Earth System Model at the National Center for Atmospheric Research. The authors examine the duration and strength of volcanic perturbations, and the effects of initial and boundary conditions, such as the phase of the Atlantic multidecadal oscillation. They evaluate the impacts of these factors on decadal-to-multicentennial perturbations of the cryospheric, oceanic, and atmospheric components of the climate system. The authors show that, at least in the Last Millennium Ensemble, volcanic eruptions are followed by a decadal-scale positive response of the Atlantic multidecadal overturning circulation, followed by a centennial-scale enhancement of the Northern Hemispheric sea ice extent. It is hypothesized that a few mechanisms, not just one, may have to play a role in consistently explaining such a simulated climate response at both decadal and centennial time scales. The authors argue that large volcanic forcing is necessary to explain the origin and duration of Little Ice Age–like perturbations in the Last Millennium Ensemble. Other forcings might play a role as well. In particular, prolonged fluctuations in solar irradiance associated with solar minima potentially amplify the enhancement of the magnitude of volcanically triggered anomalies of Arctic sea ice extent.

scholarly journals Evidence for extreme export of Arctic sea ice leading the abrupt onset of the Little Ice Age

2020 ◽  
Vol 6 (38) ◽  
pp. eaba4320
Author(s):  
Martin W. Miles ◽  
Camilla S. Andresen ◽  
Christian V. Dylmer
Keyword(s):  
Sea Ice ◽  
Little Ice Age ◽  
Abrupt Onset ◽  
Arctic Sea Ice ◽  
Ice Age ◽  
The Arctic ◽  
Ocean Stratification ◽  
Proxy Records ◽  
Arctic Sea ◽  
Robust Evidence

Arctic sea ice affects climate on seasonal to decadal time scales, and models suggest that sea ice is essential for longer anomalies such as the Little Ice Age. However, empirical evidence is fragmentary. Here, we reconstruct sea ice exported from the Arctic Ocean over the past 1400 years, using a spatial network of proxy records. We find robust evidence for extreme export of sea ice commencing abruptly around 1300 CE and terminating in the late 1300s. The exceptional magnitude and duration of this “Great Sea-Ice Anomaly” was previously unknown. The pulse of ice along East Greenland resulted in downstream increases in polar waters and ocean stratification, culminating ~1400 CE and sustained during subsequent centuries. While consistent with external forcing theories, the onset and development are notably similar to modeled spontaneous abrupt cooling enhanced by sea-ice feedbacks. These results provide evidence that marked climate changes may not require an external trigger.

Climate-induced treeline mortality during the termination of the Little Ice Age in the Greater Yellowstone Ecoregion, USA

The Holocene ◽  
2021 ◽  
pp. 095968362110116
Author(s):  
Maegen L Rochner ◽  
Karen J Heeter ◽  
Grant L Harley ◽  
Matthew F Bekker ◽  
Sally P Horn
Keyword(s):  
Climate Change ◽  
Tree Ring ◽  
Little Ice Age ◽  
Climate Changes ◽  
Frost Damage ◽  
Ice Age ◽  
Spatial And Temporal Variability ◽  
Whitebark Pine ◽  
Engelmann Spruce ◽  
Greater Yellowstone

Paleoclimate reconstructions for the western US show spatial variability in the timing, duration, and magnitude of climate changes within the Medieval Climate Anomaly (MCA, ca. 900–1350 CE) and Little Ice Age (LIA, ca. 1350–1850 CE), indicating that additional data are needed to more completely characterize late-Holocene climate change in the region. Here, we use dendrochronology to investigate how climate changes during the MCA and LIA affected a treeline, whitebark pine ( Pinus albicaulis Engelm.) ecosystem in the Greater Yellowstone Ecoregion (GYE). We present two new millennial-length tree-ring chronologies and multiple lines of tree-ring evidence from living and remnant whitebark pine and Engelmann spruce ( Picea engelmannii Parry ex. Engelm.) trees, including patterns of establishment and mortality; changes in tree growth; frost rings; and blue-intensity-based, reconstructed summer temperatures, to highlight the terminus of the LIA as one of the coldest periods of the last millennium for the GYE. Patterns of tree establishment and mortality indicate conditions favorable to recruitment during the latter half of the MCA and climate-induced mortality of trees during the middle-to-late LIA. These patterns correspond with decreased growth, frost damage, and reconstructed cooler temperature anomalies for the 1800–1850 CE period. Results provide important insight into how past climate change affected important GYE ecosystems and highlight the value of using multiple lines of proxy evidence, along with climate reconstructions of high spatial resolution, to better describe spatial and temporal variability in MCA and LIA climate and the ecological influence of climate change.

scholarly journals Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Extent ◽  
Pacific Side ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

scholarly journals Sources of multi-decadal variability in Arctic sea ice extent

2012 ◽  
Vol 7 (3) ◽  
pp. 034011 ◽  
Author(s):  
J J Day ◽  
J C Hargreaves ◽  
J D Annan ◽  
A Abe-Ouchi
Keyword(s):  
Sea Ice ◽  
Decadal Variability ◽  
Arctic Sea Ice ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

scholarly journals A 368-year maximum temperature reconstruction based on tree-ring data in the northwestern Sichuan Plateau (NWSP), China

2016 ◽  
Vol 12 (7) ◽  
pp. 1485-1498 ◽  
Author(s):  
Liangjun Zhu ◽  
Yuandong Zhang ◽  
Zongshan Li ◽  
Binde Guo ◽  
Xiaochun Wang
Keyword(s):  
Tree Ring ◽  
Land Surface ◽  
Temperature Reconstruction ◽  
Temperature Variability ◽  
Ice Age ◽  
Maximum Temperature ◽  
Tree Ring Data ◽  
The Mean ◽  
Extreme Cold ◽  
The 19Th Century

Abstract. We present a reconstruction of July–August mean maximum temperature variability based on a chronology of tree-ring widths over the period AD 1646–2013 in the northern part of the northwestern Sichuan Plateau (NWSP), China. A regression model explains 37.1 % of the variance of July–August mean maximum temperature during the calibration period from 1954 to 2012. Compared with nearby temperature reconstructions and gridded land surface temperature data, our temperature reconstruction had high spatial representativeness. Seven major cold periods were identified (1708–1711, 1765–1769, 1818–1821, 1824–1828, 1832–1836, 1839–1842, and 1869–1877), and three major warm periods occurred in 1655–1668, 1719–1730, and 1858–1859 from this reconstruction. The typical Little Ice Age climate can also be well represented in our reconstruction and clearly ended with climatic amelioration at the late of the 19th century. The 17th and 19th centuries were cold with more extreme cold years, while the 18th and 20th centuries were warm with less extreme cold years. Moreover, the 20th century rapid warming was not obvious in the NWSP mean maximum temperature reconstruction, which implied that mean maximum temperature might play an important and different role in global change as unique temperature indicators. Multi-taper method (MTM) spectral analysis revealed significant periodicities of 170-, 49–114-, 25–32-, 5.7-, 4.6–4.7-, 3.0–3.1-, 2.5-, and 2.1–2.3-year quasi-cycles at a 95 % confidence level in our reconstruction. Overall, the mean maximum temperature variability in the NWSP may be associated with global land–sea atmospheric circulation (e.g., ENSO, PDO, or AMO) as well as solar and volcanic forcing.

scholarly journals Sea-ice induced growth decline in Arctic shrubs

2017 ◽  
Vol 13 (8) ◽  
pp. 20170122 ◽  
Author(s):  
Mads Forchhammer
Keyword(s):  
Sea Ice ◽  
Ring Width ◽  
Plant Productivity ◽  
Climatic Conditions ◽  
Arctic Sea Ice ◽  
Annual Growth ◽  
The Arctic ◽  
Growth Time ◽  
Sea Ice Extent ◽  
Negative Effect

Measures of increased tundra plant productivity have been associated with the accelerating retreat of the Arctic sea-ice. Emerging studies document opposite effects, advocating for a more complex relationship between the shrinking sea-ice and terrestrial plant productivity. I introduce an autoregressive plant growth model integrating effects of biological and climatic conditions for analysing individual ring-width growth time series. Using 128 specimens of Salix arctica , S. glauca and Betula nana sampled across Greenland to Svalbard, an overall negative effect of the retreating June sea-ice extent was found on the annual growth. The negative effect of the retreating June sea-ice was observed for younger individuals with large annual growth allocations and with little or no trade-off between previous and current year's growth.

scholarly journals Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

2012 ◽  
Vol 25 (5) ◽  
pp. 1431-1452 ◽  
Author(s):  
Alexandra Jahn ◽  
Kara Sterling ◽  
Marika M. Holland ◽  
Jennifer E. Kay ◽  
James A. Maslanik ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Sea Ice ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Motion Field ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Ensemble Mean

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.

Mechanisms for and Predictability of a Drastic Reduction in the Arctic Sea Ice: APPOSITE Data with Climate Model MIROC

2019 ◽  
Vol 32 (5) ◽  
pp. 1361-1380 ◽  
Author(s):  
J. Ono ◽  
H. Tatebe ◽  
Y. Komuro
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Forecast Errors ◽  
Drastic Reduction ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Arctic Sea

Abstract The mechanisms for and predictability of a drastic reduction in the Arctic sea ice extent (SIE) are investigated using the Model for Interdisciplinary Research on Climate (MIROC) version 5.2. Here, a control (CTRL) with forcing fixed at year 2000 levels and perfect-model ensemble prediction (PRED) experiments are conducted. In CTRL, three (model years 51, 56, and 57) drastic SIE reductions occur during a 200-yr-long integration. In year 56, the sea ice moves offshore in association with a positive phase of the summer Arctic dipole anomaly (ADA) index and melts due to heat input through the increased open water area, and the SIE drastically decreases. This provides the preconditioning for the lowest SIE in year 57 when the Arctic Ocean interior is in a warm state and the spring sea ice volume has a large negative anomaly due to drastic ice reduction in the previous year. Although the ADA is one of the key mechanisms behind sea ice reduction, it does not always cause a drastic reduction. Our analysis suggests that wind direction favoring offshore ice motion is a more important factor for drastic ice reduction events. In years experiencing drastic ice reduction events, the September SIE can be skillfully predicted in PRED started from July, but not from April. This is because the forecast errors for the July sea level pressure and those for the sea ice concentration and sea ice thickness along the ice edge are large in PRED started from April.

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