scholarly journals Winter Coastal Divergence as a Predictor for the Minimum Sea Ice Extent in the Laptev Sea

2019 ◽  
Vol 32 (4) ◽  
pp. 1063-1080 ◽  
Author(s):  
Charles Brunette ◽  
Bruno Tremblay ◽  
Robert Newton

Seasonal predictability of the minimum sea ice extent (SIE) in the Laptev Sea is investigated using winter coastal divergence as a predictor. From February to May, the new ice forming in wind-driven coastal polynyas grows to a thickness approximately equal to the climatological thickness loss due to summer thermodynamic processes. Estimating the area of sea ice that is preconditioned to melt enables seasonal predictability of the minimum SIE. Wintertime ice motion is quantified by seeding passive tracers along the coastlines and advecting them with the Lagrangian Ice Tracking System (LITS) forced with sea ice drifts from the Polar Pathfinder dataset for years 1992–2016. LITS-derived landfast ice estimates are comparable to those of the Russian Arctic and Antarctic Research Institute ice charts. Time series of the minimum SIE and coastal divergence show trends of −24.2% and +31.3% per decade, respectively. Statistically significant correlation ( r = −0.63) between anomalies of coastal divergence and the following September SIE occurs for coastal divergence integrated from February to the beginning of May. Using the coastal divergence anomaly to predict the minimum SIE departure from the trend improves the explained variance by 21% compared to hindcasts based on persistence of the linear trend. Coastal divergence anomalies correlate with the winter mean Arctic Oscillation index ( r = 0.69). LITS-derived areas of coastal divergence tend to underestimate the total area covered by thin ice in the CryoSat-2/SMOS (Soil Moisture and Ocean Salinity) thickness dataset, as suggested by a thermodynamic sea ice growth model.

2013 ◽  
Vol 7 (1) ◽  
pp. 349-363 ◽  
Author(s):  
T. Krumpen ◽  
M. Janout ◽  
K. I. Hodges ◽  
R. Gerdes ◽  
F. Girard-Ardhuin ◽  
...  

Abstract. Variability and trends in seasonal and interannual ice area export out of the Laptev Sea between 1992 and 2011 are investigated using satellite-based sea ice drift and concentration data. We found an average total winter (October to May) ice area transport across the northern and eastern Laptev Sea boundaries (NB and EB) of 3.48 × 105 km2. The average transport across the NB (2.87 × 105 km2) is thereby higher than across the EB (0.61 × 105 km2), with a less pronounced seasonal cycle. The total Laptev Sea ice area flux significantly increased over the last decades (0.85 × 105 km2 decade−1, p > 0.95), dominated by increasing export through the EB (0.55 × 105 km2 decade−1, p > 0.90), while the increase in export across the NB is smaller (0.3 × 105 km2 decade−1) and statistically not significant. The strong coupling between across-boundary SLP gradient and ice drift velocity indicates that monthly variations in ice area flux are primarily controlled by changes in geostrophic wind velocities, although the Laptev Sea ice circulation shows no clear relationship with large-scale atmospheric indices. Also there is no evidence of increasing wind velocities that could explain the overall positive trends in ice export. The increased transport rates are rather the consequence of a changing ice cover such as thinning and/or a decrease in concentration. The use of a back-propagation method revealed that most of the ice that is incorporated into the Transpolar Drift is formed during freeze-up and originates from the central and western part of the Laptev Sea, while the exchange with the East Siberian Sea is dominated by ice coming from the central and southeastern Laptev Sea. Furthermore, our results imply that years of high ice export in late winter (February to May) have a thinning effect on the ice cover, which in turn preconditions the occurence of negative sea ice extent anomalies in summer.


2016 ◽  
Vol 29 (16) ◽  
pp. 5879-5891 ◽  
Author(s):  
James Williams ◽  
Bruno Tremblay ◽  
Robert Newton ◽  
Richard Allard

Abstract There has been an increased interest in seasonal forecasting of the Arctic sea ice extent in recent years, in particular the minimum sea ice extent. Here, a dynamical mechanism, based on winter preconditioning, is found to explain a significant fraction of the variance in the anomaly of the September sea ice extent from the long-term linear trend. To this end, a Lagrangian trajectory model is used to backtrack the September sea ice edge to any time during the previous winter and quantify the amount of sea ice advection away from the Eurasian and Alaskan coastlines as well as the Fram Strait sea ice export. The late-winter anomalous sea ice drift away from the coastline is highly correlated with the following September sea ice extent minimum . It is found that the winter mean Fram Strait sea ice export anomaly is also correlated with the minimum sea ice extent the following summer . To develop a hindcast model of the September sea ice extent—which does not depend on a priori knowledge of the minimum sea ice extent—a synthetic ice edge initialized at the beginning of the melt season (1 June) is backtracked. It is found that using a multivariate regression model of the September sea ice extent anomaly based on ice export from the peripheral Arctic seas and Fram Strait ice export as predictors reduces the error by 38%. A hindcast model based on the mean December–April Arctic Oscillation index alone reduces the error by 24%.


2012 ◽  
Vol 6 (4) ◽  
pp. 2891-2930 ◽  
Author(s):  
T. Krumpen ◽  
M. Janout ◽  
K. I. Hodges ◽  
R. Gerdes ◽  
F. Girard-Ardhuin ◽  
...  

Abstract. Variability and trends in seasonal and interannual ice area export out of the Laptev Sea between 1992 and 2011 are investigated using satellite-based sea ice drift and concentration data. We found an average winter (October to May) ice area transport across the northern and eastern Laptev Sea boundaries (NB and EB) of 3.48 × 105 km2. The average transport across the NB (2.87 × 105 km2) is thereby higher than across the EB (0.61 × 105 km2), with a less pronounced seasonal cycle. The total Laptev Sea ice area flux significantly increased over the last decades (0.85 × 105 km2/decade, p > 0.95), dominated by increasing export through the EB (0.55 × 105 km2/decade, p > 0.90), while the increase in export across the NB is small (0.3 × 105 km2/decade) and statistically not significant. The strong coupling between across-boundary SLP gradient and ice drift velocity indicates that monthly variations in ice area flux are primarily controlled by changes in geostrophic wind velocities, although the Laptev Sea ice circulation shows no clear relationship with large-scale atmospheric indices. Also there is no evidence of increasing wind velocities that could explain the overall positive trends in ice export. Following Spreenet al. (2011), we therefore assume that changes in ice flux rates may be related to changes in the ice cover such as thinning and/or a decrease in concentration. The use of a back-propagation method revealed that most of the ice that is incorporated into the Transpolar Drift is formed during freeze-up and originates from the central and western part of the Laptev Sea, while the exchange with the East Siberian Sea is dominated by ice coming from the Central and South-Eastern Laptev Sea. Furthermore, our results imply that the late winter (February to May) ice area flux may at least partially control the summer sea ice extent in the Laptev Sea.


2020 ◽  
Author(s):  
Anna Timofeeva ◽  
Vladimir Ivanov ◽  
Alexander Yulin ◽  
Stepan Khotchenkov

<p>The Laptev Sea is influenced by synoptic regions of the Atlantic-Eurasian sector of the Northern Hemisphere. Types of large-scale processes are consider according to the G. J. Vangengeim typization: West (W) circulation form, with dominating zonal transport of air masses, East (E) and meridional (C) circulation forms with opposite phases of geographic orientation in the troposphere of the anticyclones ridges axes, blocking the Western transfer of air masses and developing the meridional circulation at high and middle latitudes. The Laptev Sea ice extent at the end of the melting season has a strong interannual variability, the oscillations amplitude reaches 86%.</p><p>The paper considers analysis of long-term trends of the large-scale atmosphere processes realignment and multiyear variability of the air temperature and ice cover anomalies in the Laptev Sea. According to multiyear course of integral anomalies values four steady periods of homogeneous  tendency of climatic processes revealed and described for data series from 1942 to 2019 (air reconnaissance and satellite data).</p><p>The types of ice conditions development (severe, medium, mild) at the end of the melting season were determined for the entire series of observations. More than half of cases during 78 years are distinguished as medium type of ice conditions. The repeatability of severe and mild types is almost the same numerically but varies in time according to revealed periods.</p><p>During 1942-1947 years in the Laptev Sea the “warming” period occurred (same for the whole polar region), known as the warming of the Arctic of 30th. At this period positive temperature anomalies and negative anomalies of sea ice extent (mean -2%) were dominated. During subsequent period 1948-1989 years the positive temperature trend has changed to the steady negative. The most dramatic temperature drops were observed in the 60-70<sup>th</sup>. Positive ice anomalies increased (mean 9%), in August Laptev Sea remained mostly covered by ice. Of the 42 years 28 refer to the medium type of ice conditions, 11 to the severe. During the period 1990-2004 years frequent interannual rearrangements of the atmosphere circulation and multidirectional fluctuations of temperature and ice cover anomalies were observed. On average, the temperature and ice cover during the period are close to the long-term norm. After 2005 temperature regime in the polar climate system has changed. This period is the warmest for the whole observations series in the Laptev Sea. Ice extent at the end of the melting season steady decreases and shows dramatic growth of negative anomalies values and occur of extremely low anomaly for the entire observation period (up to -54-55%). The average negative ice anomaly for the period is -26.4 %. Of the 15 years 9 refer to the mild type of ice conditions.</p>


2017 ◽  
Author(s):  
Polona Itkin ◽  
Thomas Krumpen

Abstract. Recent studies based on satellite observations have shown that there is a high statistical connection between the late winter (Feb-May) sea ice export out the Laptev Sea, and the ice coverage in the following summer. By means of airborne sea ice thickness surveys made over pack ice areas in the southeastern Laptev Sea, we show that years of offshore directed sea ice transport have a thinning effect on the late winter sea ice cover, and vice versa. Once temperature rise above freezing, these thin ice zones melt more rapidly and hence, precondition local anomalies in summer sea ice cover. The preconditioning effect of the winter ice dynamics for the summer sea ice extent is confirmed with a model sensitivity study where we replace the inter-annual summer atmospheric forcing by a climatology. In the model, years with high late winter sea ice export always result in a reduced sea ice cover, and vice versa. We conclude that the observed tendency towards an increased ice export further accelerates ice retreat in summer. The mechanism presented in this study highlights the importance of winter ice dynamics for summer sea ice anomalies in addition to atmospheric processes acting on the ice cover between May and September. Finally, we show that ice dynamics in winter not only precondition local summer ice extent, but also accelerate fast ice decay.


1997 ◽  
Vol 17 (2) ◽  
pp. 205-233 ◽  
Author(s):  
H. Eicken ◽  
E. Reimnitz ◽  
V. Alexandrov ◽  
T. Martin ◽  
H. Kassens ◽  
...  

2020 ◽  
Vol 14 (7) ◽  
pp. 2189-2203
Author(s):  
H. Jakob Belter ◽  
Thomas Krumpen ◽  
Stefan Hendricks ◽  
Jens Hoelemann ◽  
Markus A. Janout ◽  
...  

Abstract. The gridded sea ice thickness (SIT) climate data record (CDR) produced by the European Space Agency (ESA) Sea Ice Climate Change Initiative Phase 2 (CCI-2) is the longest available, Arctic-wide SIT record covering the period from 2002 to 2017. SIT data are based on radar altimetry measurements of sea ice freeboard from the Environmental Satellite (ENVISAT) and CryoSat-2 (CS2). The CCI-2 SIT has previously been validated with in situ observations from drilling, airborne remote sensing, electromagnetic (EM) measurements and upward-looking sonars (ULSs) from multiple ice-covered regions of the Arctic. Here we present the Laptev Sea CCI-2 SIT record from 2002 to 2017 and use newly acquired ULS and upward-looking acoustic Doppler current profiler (ADCP) sea ice draft (VAL) data for validation of the gridded CCI-2 and additional satellite SIT products. The ULS and ADCP time series provide the first long-term satellite SIT validation data set from this important source region of sea ice in the Transpolar Drift. The comparison of VAL sea ice draft data with gridded monthly mean and orbit trajectory CCI-2 data, as well as merged CryoSat-2–SMOS (CS2SMOS) sea ice draft, shows that the agreement between the satellite and VAL draft data strongly depends on the thickness of the sampled ice. Rather than providing mean sea ice draft, the considered satellite products provide modal sea ice draft in the Laptev Sea. Ice drafts thinner than 0.7 m are overestimated, while drafts thicker than approximately 1.3 m are increasingly underestimated by all satellite products investigated for this study. The tendency of the satellite SIT products to better agree with modal sea ice draft and underestimate thicker ice needs to be considered for all past and future investigations into SIT changes in this important region. The performance of the CCI-2 SIT CDR is considered stable over time; however, observed trends in gridded CCI-2 SIT are strongly influenced by the uncertainties of ENVISAT and CS2 and the comparably short investigation period.


2011 ◽  
Vol 30 (1) ◽  
pp. 6425 ◽  
Author(s):  
Jens A. Hölemann ◽  
Sergey Kirillov ◽  
Torben Klagge ◽  
Andrey Novikhin ◽  
Heidemarie Kassens ◽  
...  

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