Ice winter severity in the western Baltic Sea in the period of 1301–1500: comparison with other relevant data

Schmelzer, Natalija; Holfort, Jürgen

doi:10.1002/joc.2337

Cited by 10 publications

(7 citation statements)

References 11 publications

(7 reference statements)

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“…6A). A consistent pattern between the Low Countries and the western Baltic in winter is reasonable because both areas are controlled by the NAO determining the severity of winters (Schmelzer and Holfort, 2011). Also the Baltic ice winter severity index values derived from documentary sources (Hagen and Feistel, 2005;Koslowski and Glaser, 1999;Schmelzer and Holfort, 2011) shows the mid-18th century warmth bracketed by severe winters around AD 1700 and 1800 (Fig.…”

Section: Regional Comparison Of Temperature Variabilitymentioning

confidence: 96%

“…A) Polish Winter Thermal Index (Przybylak et al, 2005) for the period AD 1780e1999 (yellow line) and Winter Thermal Index for AD 1400e1800 (orange line) (Przybylak, 2011). B) Baltic ice winter severity index (Koslowski and Glaser, 1999;Schmelzer and Holfort, 2011). C) Winter (DeceFeb) temperature in the Netherlands (van Engelen et al, 2001).…”

Section: Regional Comparison Of Temperature Variabilitymentioning

confidence: 98%

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A chrysophyte-based quantitative reconstruction of winter severity from varved lake sediments in NE Poland during the past millennium and its relationship to natural climate variability

Hernández‐Almeida

Grosjean

Przybylak

et al. 2015

Quaternary Science Reviews

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a b s t r a c tChrysophyte cysts are recognized as powerful proxies of cold-season temperatures. In this paper we use the relationship between chrysophyte assemblages and the number of days below 4 C (DB4 C) in the epilimnion of a lake in northern Poland to develop a transfer function and to reconstruct winter severity in Poland for the last millennium. DB4 C is a climate variable related to the length of the winter. Multivariate ordination techniques were used to study the distribution of chrysophytes from sediment traps of 37 low-land lakes distributed along a variety of environmental and climatic gradients in northern Poland. Of all the environmental variables measured, stepwise variable selection and individual Redundancy analyses (RDA) identified DB4 C as the most important variable for chrysophytes, explaining a portion of variance independent of variables related to water chemistry (conductivity, chlorides, K, sulfates), which were also important. A quantitative transfer function was created to estimate DB4 C from sedimentary assemblages using partial least square regression (PLS). The twocomponent model (PLS-2) had a coefficient of determination of R 2 cross ¼ 0.58, with root mean squared error of prediction (RMSEP, based on leave-one-out) of 3.41 days. The resulting transfer function was applied to an annually-varved sediment core from Lake _ Zabi nskie, providing a new sub-decadal quantitative reconstruction of DB4 C with high chronological accuracy for the period AD 1000e2010. During Medieval Times (AD 1180e1440) winters were generally shorter (warmer) except for a decade with very long and severe winters around AD 1260e1270 (following the AD 1258 volcanic eruption). The 16th and 17th centuries and the beginning of the 19th century experienced very long severe winters. Comparison with other European cold-season reconstructions and atmospheric indices for this region indicates that large parts of the winter variability (reconstructed DB4 C) is due to the interplay between the oscillations of the zonal flow controlled by the North Atlantic Oscillation (NAO) and the influence of continental anticyclonic systems (Siberian High, East Atlantic/Western Russia pattern). Differences with other European records are attributed to geographic climatological differences between Poland and Western Europe (Low Countries, Alps). Striking correspondence between the combined volcanic and solar forcing and the DB4 C reconstruction prior to the 20th century suggests that winter climate in Poland responds mostly to natural forced variability (volcanic and solar) and the influence of unforced variability is low.

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Section: Regional Comparison Of Temperature Variabilitymentioning

confidence: 96%

Section: Regional Comparison Of Temperature Variabilitymentioning

confidence: 98%

A chrysophyte-based quantitative reconstruction of winter severity from varved lake sediments in NE Poland during the past millennium and its relationship to natural climate variability

Hernández‐Almeida

Grosjean

Przybylak

et al. 2015

Quaternary Science Reviews

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“…Both the accumulated areal ice volume [6] and the ice severity index [7] are calculated from the observation stations data. Schmelzer uses the maximal ice extent, the accumulated areal ice volume [8] and the ice severity index [9] to describe ice seasons. Winter severity is described through the time series of ice cover appearance and disappearance dates [10][11][12].…”

Section: Earth and Planetary Sciencesmentioning

confidence: 99%

Classifying the Ice Seasons 1982-2016 Using the Weighted Ice Days Number as a New Winter Severity Characteristic

Rjazin¹,

Alari

Pärn

2017

EUREKA: Physics and Engineering

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Sea ice is a key climate factor and it restricts considerably the winter navigation in severe seasons on the Baltic Sea. So determining ice conditions severity and describing ice cover behavior at severe seasons are necessary. The ice seasons severity degree is studied at the years 1982 to 2016. A new integrative characteristic named the weighted ice days number of the season is introduced to determine the ice season severity. The ice concentration data on the Baltic Sea published in the European Copernicus Programme are used to calculate the maximal ice extent and the weighted ice days number of the seasons. Both the ice season severity characteristics are used to classify the winters with respect of severity. The ice seasons 1981/82, 1984/85, 1985/86, 1986/87, 1995/96 and 2002/03 are classified as severe by the weighted ice days number. Only three seasons of this list are severe by both the criteria. We interpret this coincidence as the evidence of enough-during extensive ice cover in these three seasons. In the winter 2010/11 ice cover extended widely for some time, but did not last longer. At 2002/03 and a few other ice seasons the Baltic Sea was ice-covered in moderate extent, but the ice cover stayed long time. For 11 winters (32 % of the period) the relational weighted ice days number differs considerably (> 10 %) from the relational maximal ice extent. These winters yield one third of the studied ice seasons. Statistically every 6th winter is severe by the weighted ice days number whereas only statistically every 8th winter is severe by the maximal ice extent on the Baltic. Hence there are more intrinsically severe seasons than the maximal ice extent gives. The maximal ice extent fails to account with the ice cover durability. The weighted ice days number enables to describe the ice cover behavior more representatively. Using the weighted ice days number adds the temporal dimension to the ice season severity study.

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“…The papers of Woodruff et al (2011) and Wilkinson et al (2011) report on recent developments in marine dataset development and data archeology. They are complimented by the articles of Palmer & Brohan (2011), ), Smith et al (2011 and Thomas & Swail (2011), addressing error estimation and quantification of biases in surface marine climatologies of individual variables and fluxes. The paper by Winterfeldt et al (2011) provides an analysis of marine winds from satellites, reflecting the growing importance of satellite observations for marine climatology.…”

mentioning

confidence: 99%

“…The paper by Winterfeldt et al (2011) provides an analysis of marine winds from satellites, reflecting the growing importance of satellite observations for marine climatology. Contributions from Yasunaka & Hanawa (2011), Wolter & Timlin (2011), Walczowski & Piechura (2011), and Schmelzer & Holfort (2011 …”

mentioning

confidence: 99%

Achievements in marine climatology

Gulev¹,

Woodruff²

2011

Intl Journal of Climatology

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Ice winter severity in the western Baltic Sea in the period of 1301–1500: comparison with other relevant data

Cited by 10 publications

References 11 publications

A chrysophyte-based quantitative reconstruction of winter severity from varved lake sediments in NE Poland during the past millennium and its relationship to natural climate variability

A chrysophyte-based quantitative reconstruction of winter severity from varved lake sediments in NE Poland during the past millennium and its relationship to natural climate variability

Classifying the Ice Seasons 1982-2016 Using the Weighted Ice Days Number as a New Winter Severity Characteristic

Achievements in marine climatology

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