Seasonal forecast of sea ice extent in the Barents sea

Earlier, the authors established a close relationship between the temperature of water coming from the North Atlantic and the sea ice extent (SIE) in the Barents Sea, which accounts for up to 75 % of the inter-annual variability of the monthly SIE from January to June. In turn, temperature variations of the incoming Atlantic water are affected from anomalies of sea surface temperature (SST) in the low latitudes of the North Atlantic. These dependences served as the basis for the development of a forecast method. The empirical orthogonal functions decomposition of the SIE set from January to June for 1979–2014 was used. The main component of decomposition reflects 83 % of the inter-annual variability of SIE from January to June. Regression model of forecast is based on the relation of the main component with SST anomalies taking into account the delay. Comparison of prognostic and actual values of the climatic component for each of the 6 months showed the correctness of forecasts with a lead time of 27 to 32 months is 83 %, and for the prediction of the initial values of SIE 79 %. Appealing to the second predictor — SST anomalies in the Norwegian Sea allowed to improve the quality of the forecast of the observed values of SIE. At the same time, the forecast advance time was reduced to 9–14 months.

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The link between the Barents Sea and ENSO events simulated by NEMO model

Ocean Science ◽

10.5194/os-8-971-2012 ◽

2012 ◽

Vol 8 (6) ◽

pp. 971-982 ◽

Cited By ~ 3

Author(s):

V. N. Stepanov ◽

H. Zuo ◽

K. Haines

Keyword(s):

Sea Ice ◽

North Atlantic ◽

Barents Sea ◽

Southern Oscillation ◽

Similar Response ◽

Enso Events ◽

Ice Volume ◽

The North ◽

The Barents Sea ◽

The North Atlantic

Abstract. An analysis of observational data in the Barents Sea along a meridian at 33°30' E between 70°30' and 72°30' N has reported a negative correlation between El Niño/La Niña Southern Oscillation (ENSO) events and water temperature in the top 200 m: the temperature drops about 0.5 °C during warm ENSO events while during cold ENSO events the top 200 m layer of the Barents Sea is warmer. Results from 1 and 1/4-degree global NEMO models show a similar response for the whole Barents Sea. During the strong warm ENSO event in 1997–1998 an anomalous anticyclonic atmospheric circulation over the Barents Sea enhances heat loses, as well as substantially influencing the Barents Sea inflow from the North Atlantic, via changes in ocean currents. Under normal conditions along the Scandinavian peninsula there is a warm current entering the Barents Sea from the North Atlantic, however after the 1997–1998 event this current is weakened. During 1997–1998 the model annual mean temperature in the Barents Sea is decreased by about 0.8 °C, also resulting in a higher sea ice volume. In contrast during the cold ENSO events in 1999–2000 and 2007–2008, the model shows a lower sea ice volume, and higher annual mean temperatures in the upper layer of the Barents Sea of about 0.7 °C. An analysis of model data shows that the strength of the Atlantic inflow in the Barents Sea is the main cause of heat content variability, and is forced by changing pressure and winds in the North Atlantic. However, surface heat-exchange with the atmosphere provides the means by which the Barents sea heat budget relaxes to normal in the subsequent year after the ENSO events.

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Predictability of the Barents Sea Ice in Early Winter: Remote Effects of Oceanic and Atmospheric Thermal Conditions from the North Atlantic

Journal of Climate ◽

10.1175/jcli-d-14-00125.1 ◽

2014 ◽

Vol 27 (23) ◽

pp. 8884-8901 ◽

Cited By ~ 33

Author(s):

Takuya Nakanowatari ◽

Kazutoshi Sato ◽

Jun Inoue

Keyword(s):

Sea Ice ◽

North Atlantic ◽

Barents Sea ◽

Temperature Anomaly ◽

Early Winter ◽

Subsurface Temperature ◽

The North ◽

The Barents Sea ◽

Subsurface Temperature Anomaly ◽

The North Atlantic

Abstract Predictability of sea ice concentrations (SICs) in the Barents Sea in early winter (November–December) is studied using canonical correlation analysis with atmospheric and ocean anomalies from the NCEP Climate Forecast System Reanalysis (CFSR) data. It is found that the highest prediction skill for a single-predictor model is obtained from the 13-month lead subsurface temperature at 200-m depth (T200) and the in-phase meridional surface wind (Vsfc). T200 skillfully predicts SIC variability in 35% of the Barents Sea, mainly in the eastern side. The T200 for negative sea ice anomalies exhibits warm anomalies in the subsurface ocean temperature downstream of the Norwegian Atlantic Slope Current (NwASC) on a decadal time scale. The diagnostic analysis of NCEP CFSR data suggests that the subsurface temperature anomaly stored below the thermocline during summer reemerges in late autumn by atmospheric cooling and affects the sea ice. The subsurface temperature anomaly of the NwASC is advected from the North Atlantic subpolar gyre over ~3 years. Also, Vsfc skillfully predicts SIC variability in 32% of the Barents Sea, mainly in the western side. The Vsfc for the negative sea ice anomalies exhibits southerly wind anomalies; Vsfc is related to the large-scale atmospheric circulation patterns from the subtropical North Atlantic to the Eurasian continent. This study suggests that both atmospheric and oceanic remote effects have a potential impact on the forecasting accuracy of SIC.

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The link between the Barents Sea and ENSO events reproduced by NEMO model

Ocean Science Discussions ◽

10.5194/osd-9-2121-2012 ◽

2012 ◽

Vol 9 (3) ◽

pp. 2121-2151

Author(s):

V. N. Stepanov ◽

H. Zuo ◽

K. Haines

Keyword(s):

Sea Ice ◽

North Atlantic ◽

Barents Sea ◽

Southern Oscillation ◽

Similar Response ◽

Enso Events ◽

Ice Volume ◽

The North ◽

The Barents Sea ◽

The North Atlantic

Abstract. An analysis of observational data in the Barents Sea along a meridian at 33°30´ E between 70°30´ and 72°30´ N has reported a negative correlation between El Niño/La Niña-Southern Oscillation (ENSO) events and water temperature in the top 200 m: the temperature drops about 0.5 °C during warm ENSO events while during cold ENSO events the top 200 m layer of the Barents Sea is warmer. Results from 1 and 1/4-degree global NEMO models show a similar response for the whole Barents Sea. During the strong warm ENSO event in 1997–1998 an anticyclonic atmospheric circulation is settled over the Barents Sea instead of a usual cyclonic circulation. This change enhances heat loses in the Barents Sea, as well as substantially influencing the Barents Sea inflow from the North Atlantic, via changes in ocean currents. Under normal conditions along the Scandinavian peninsula there is a warm current entering the Barents sea from the North Atlantic, however after the 1997–1998 event this current is weakened. During 1997–1998 the model annual mean temperature in the Barents Sea is decreased by about 0.8 °C, also resulting in a higher sea ice volume. In contrast during the cold ENSO events in 1999–2000 and 2007–2008 the model shows a lower sea ice volume, and higher annual mean temperatures in the upper layer of the Barents Sea of about 0.7 °C. An analysis of model data shows that the Barents Sea inflow is the main source for the variability of Barents Sea heat content, and is forced by changing pressure and winds in the North Atlantic. However, surface heat-exchange with atmosphere can also play a dominant role in the Barents Sea annual heat balance, especially for the subsequent year after ENSO events.

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Understanding cyclone variability in the Barents Sea

10.5194/egusphere-egu2020-10690 ◽

2020 ◽

Author(s):

Erica Madonna ◽

Gabriel Hes ◽

Clio Michel ◽

Camille Li ◽

Peter Yu Feng Siew

Keyword(s):

Climate Variability ◽

Sea Ice ◽

North Atlantic ◽

Barents Sea ◽

The Arctic ◽

High Latitudes ◽

The North ◽

The Barents Sea ◽

The North Atlantic ◽

Cyclone Frequency

<p>Extratropical cyclones are a key player for the global energy budget as they transport a large amount of moisture and heat from mid- to high-latitudes. One of the main corridors for cyclones entering the Arctic from the North Atlantic is the Barents Sea, a region that has experienced the largest decrease in winter sea ice during the past decades. On the one hand, some studies showed that moisture transported by cyclones to the Arctic can lead to drastic temperature increases and sea ice melt. On the other hand, it has been suggested that the location of the sea ice edge can influence the tracks of cyclones. Therefore, it is crucial to understand what controls cyclone tracks through the Barents Sea into the Arctic to explain and potentially predict climate variability at high latitudes.</p><p>To address this question, we track cyclones from 1979 to 2018 in the ERA-Interim data set, characterizing and quantifying them depending on their genesis location and path. The focus is on cyclones entering the Barents Sea from the North Atlantic as they carry the most moisture into the Arctic. Despite a clear declining trend in sea ice in the Barents Sea, our results show neither significant changes in cyclone frequency nor in their tracks. However, we find that the large-scale flow and in particular the presence or absence of blocking in the Barents Sea influence the cyclone frequency in this region, providing a potential mechanism that controls high latitude climate variability.</p>

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A 120 000-year record of sea ice in the North Atlantic?

Climate of the Past ◽

10.5194/cp-15-2031-2019 ◽

2019 ◽

Vol 15 (6) ◽

pp. 2031-2051 ◽

Cited By ~ 2

Author(s):

Niccolò Maffezzoli ◽

Paul Vallelonga ◽

Ross Edwards ◽

Alfonso Saiz-Lopez ◽

Clara Turetta ◽

...

Keyword(s):

Sea Ice ◽

North Atlantic ◽

Ice Core ◽

Arctic Sea Ice ◽

First Year ◽

Sea Ice Extent ◽

Nordic Seas ◽

The North ◽

Arctic Sea ◽

The North Atlantic

Abstract. Although it has been demonstrated that the speed and magnitude of the recent Arctic sea ice decline is unprecedented for the past 1450 years, few records are available to provide a paleoclimate context for Arctic sea ice extent. Bromine enrichment in ice cores has been suggested to indicate the extent of newly formed sea ice areas. Despite the similarities among sea ice indicators and ice core bromine enrichment records, uncertainties still exist regarding the quantitative linkages between bromine reactive chemistry and the first-year sea ice surfaces. Here we present a 120 000-year record of bromine enrichment from the RECAP (REnland ice CAP) ice core, coastal east Greenland, and interpret it as a record of first-year sea ice. We compare it to existing sea ice records from marine cores and tentatively reconstruct past sea ice conditions in the North Atlantic as far north as the Fram Strait (50–85∘ N). Our interpretation implies that during the last deglaciation, the transition from multi-year to first-year sea ice started at ∼17.5 ka, synchronously with sea ice reductions observed in the eastern Nordic Seas and with the increase in North Atlantic ocean temperature. First-year sea ice reached its maximum at 12.4–11.8 ka during the Younger Dryas, after which open-water conditions started to dominate, consistent with sea ice records from the eastern Nordic Seas and the North Icelandic shelf. Our results show that over the last 120 000 years, multi-year sea ice extent was greatest during Marine Isotope Stage (MIS) 2 and possibly during MIS 4, with more extended first-year sea ice during MIS 3 and MIS 5. Sea ice extent during the Holocene (MIS 1) has been less than at any time in the last 120 000 years.

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Soviet Fishing in the Barents Sea and the North Atlantic

Geographical Review ◽

10.2307/212659 ◽

1964 ◽

Vol 54 (3) ◽

pp. 386 ◽

Cited By ~ 5

Author(s):

Ronald A. Helin

Keyword(s):

North Atlantic ◽

Barents Sea ◽

The North ◽

The Barents Sea ◽

The North Atlantic

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Seasonal Prediction from Arctic Sea Surface Temperatures: Opportunities and Pitfalls

Journal of Climate ◽

10.1175/jcli-d-18-0016.1 ◽

2018 ◽

Vol 31 (20) ◽

pp. 8197-8210 ◽

Cited By ~ 6

Author(s):

Erik W. Kolstad ◽

Marius Årthun

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Arctic Sea Ice ◽

Sea Surface ◽

Sea Ice Extent ◽

Norwegian Sea ◽

The Barents Sea ◽

Arctic Sea ◽

Lagged Correlation ◽

Sst Anomalies

Arctic sea ice extent and sea surface temperature (SST) anomalies have been shown to be skillful predictors of weather anomalies in the midlatitudes on the seasonal time scale. In particular, below-normal sea ice extent in the Barents Sea in fall has sometimes preceded cold winters in parts of Eurasia. Here we explore the potential for predicting seasonal surface air temperature (SAT) anomalies in Europe from seasonal SST anomalies in the Nordic seas throughout the year. First, we show that fall SST anomalies not just in the Barents Sea but also in the Norwegian Sea have the potential to predict wintertime SAT anomalies in Europe. Norwegian Sea SST anomalies in spring are also significant predictors of European SAT anomalies in summer. Second, we demonstrate that the potential for prediction is sensitive to trends in the data. In particular, the lagged correlation between Norwegian Sea SST anomalies in spring and European SAT anomalies in summer is considerably higher for raw data than linearly detrended data, largely due to warming SST and SAT trends in recent decades. Third, we show that the potential for prediction has not been stationary in time. One key result is that, according to two twentieth-century reanalyses, the strength of the negative lagged correlation between Barents Sea SST anomalies in fall and European SAT anomalies in winter after 1979 is unprecedented since 1900.

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Examining Internal and External Contributors to Greenland Climate Variability Using CCSM3

Journal of Climate ◽

10.1175/jcli-d-12-00845.1 ◽

2013 ◽

Vol 26 (24) ◽

pp. 9745-9773 ◽

Cited By ~ 7

Author(s):

Heather J. Andres ◽

W. R. Peltier

Keyword(s):

Climate Variability ◽

Sea Ice ◽

North Atlantic ◽

Volcanic Aerosol ◽

Solar Insolation ◽

Sea Ice Extent ◽

The North ◽

Temperature And Precipitation ◽

External Sources ◽

The North Atlantic

Abstract Greenland climate variability is connected to internal and external sources of global climate forcing in six millennium simulations using Community Climate System Model, version 3. The external forcings employed are consistent with the protocols of Paleoclimate Modelling Intercomparison Project Phase 3. Many simulated internal climate modes are characterized over the years 850–1850, including the Atlantic meridional overturning circulation (AMOC), the Atlantic multidecadal oscillation (AMO), the east Atlantic pattern (EA), the El Niño–Southern Oscillation, the North Atlantic Oscillation (NAO), the North Atlantic sea ice extent, and the Pacific decadal oscillation (PDO). Lagged correlation and multivariate regression methods connect Greenland temperatures and precipitation to these internal modes and external sources of climate variability. Greenland temperature and precipitation are found to relate most strongly to North Atlantic sea ice extent, the AMO, and the AMOC, that are themselves strongly interconnected. Furthermore, approximately half of the multidecadal variability in Greenland temperature and precipitation are captured through linear relationships with volcanic aerosol optical depth, solar insolation (including total solar irradiance and local orbital variability), the NAO, the EA, and the PDO. Relationships are robust with volcanic aerosol optical depth, solar insolation, and an index related to latitudinal shifts of the North Atlantic jet. Differences attributable to model resolution are also identified in the results, such as lower variability in the AMOC and Greenland temperature in the higher-resolution simulations. Finally, a regression model is applied to simulations of the industrial period to show that natural sources alone only explain the variability in simulated Greenland temperature and precipitation up to the 1950s and 1970s, respectively.

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