1. Introduction
The Barents Sea is the hotspot of Arctic warming (Lind et al. 2018), contributing to “Arctic Amplification” (Rantanen et al. 2022) and “Arctic Ocean Amplification” (Shu et al. 2022). This is linked to the largest regional sea ice loss anywhere in the Arctic (Chen et al. 2016; Onarheim et al. 2018). Although atmospheric forcings have been argued to dominate the interannual-decadal winter sea ice variability in the northern Barents Sea (NBS) (e.g., Liu et al. 2022; Olonscheck et al. 2019), internal atmosphere–ocean–sea ice feedback plays a critical role in determining the sea ice conditions (Simpkins 2023; Rieke et al. 2023). Oceanic heat transport, primarily driven by the inflow of warm and saline Atlantic water (AW) through the Barents Sea Opening (BSO, Fig. 1; Furevik 2001; Skagseth et al. 2008), is one of the key elements involved in coupled atmosphere–ocean–sea ice feedbacks in this region (Smedsrud et al. 2013). A significant part of the oceanic heat carried by the AW is released to the atmosphere (Serreze et al. 2007; Smedsrud et al. 2010) over a relatively shallow depth in the southern Barents Sea (SBS; mean depth: ∼230 m), leading to local warming of the surface air temperature (Screen and Simmonds 2010). Part of the retained oceanic heat broadly defines the southward extent of the sea ice in the NBS. The increase in the strength and temperature of the AW inflow into the Barents Sea has been found to decrease the sea ice extent in the NBS, making it a key predictor of present and future sea ice extent in the NBS (Årthun et al. 2012, 2019).
Climatological (1993–2021) winter mean (ONDJFM) depth-averaged AW (salinity > 34.9 psu) temperature in the Nordic seas. The blue contour shows the mean SIE (15% SIC). The black circles denote the position of three sections used in this study: Svinøy (63°N–3°E), BSO (73°N–20°E), and Kola section (71.5°N–33.5°E). Black dashed contours are bottom topography drawn at 1000-m and 200-m levels. The thick black line represents the Eastern Barents Sea section. The Atlantic (Arctic) water flows are marked as green (black) arrows.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Apart from the AW inflow, interannual variability of sea ice concentration (SIC) in the Barents Sea is influenced by sea ice import and atmosphere–ocean heat fluxes in the SBS (Efstathiou et al. 2022). Sea ice is imported into the NBS through the northern and eastern openings and driven directly by winds (von Schuckmann et al. 2021) and by westward flowing Arctic water masses (Fig. 1). A significant decrease in sea ice import has been observed since the mid-2000s which further reduces the new sea ice formation due to a reduction in ocean stratification and vertical mixing of the warmer waters underneath the colder surface water (Lind et al. 2018). Recently, the heat loss in the SBS has decreased while it has increased in the NBS where sea ice has disappeared (Skagseth et al. 2020; Shu et al. 2021). Thus, while AW inflow is expected to remain a key predictor for the variability of sea ice extent in the NBS (Årthun et al. 2019), the role of atmosphere–ocean–sea ice interactions within the Barents Sea may strengthen in a rapidly changing Barents Sea climate. Given the crucial role of sea ice in driving the Arctic climate and its variability (Screen and Simmonds 2010; Dai et al. 2019; Deng and Dai 2022), it is imperative to understand its role in driving the atmosphere–ocean–sea ice feedbacks in the Barents Sea.
Although sea ice in the NBS has been steadily decreasing since the beginning of satellite record, here, in this study, we focus on the decline trend since the mid-2000s, which coincides with a decadal cooling trend in AW intrusion. We attempt to delineate the role of atmosphere–ocean feedback within the Barents Sea in driving the recent declining trend of SIC in the NBS. Further, we highlight the role of sea ice loss in driving this observed atmosphere–ocean feedback through results from idealized coupled numerical modeling experiments. The following section describes the observational datasets and modeling experiments used in the study. Results and Discussion in section 3 explain atmospheric and oceanic conditions associated with the observed sea ice changes in the NBS and further followed by results from numerical experiments highlighting the role of sea ice loss in driving those. Summary and conclusions are presented in section 4.
2. Observational data and modeling experiment
Satellite observation of SIC on a polar stereographic projection is obtained from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, version 1 (Cavalieri et al. 1996). Gridded (0.25 by 0.25) observations of altimeter-derived monthly mean sea level anomalies from the 1993 to 2012 mean are obtained from Copernicus Marine Services (https://doi.org/10.48670/moi-00148).
In situ temperature and salinity observations are obtained from the International Council for the Exploration of the Sea (ICES; https://ocean.ices.dk/core/iroc). We further use a coupled ocean and sea ice data assimilation system, TOPAZ4b (Xie et al. 2017; Bertino and Lisæter 2008; https://doi.org/10.48670/moi-00007), which uses the deterministic ensemble Kalman filter (DEnKF) to assimilate multiple types of ocean and sea ice observations simultaneously (Xie et al. 2023). The TOPAZ4b system has been extensively evaluated for the Nordic seas and the Barents Sea (Chatterjee et al. 2018; Lien et al. 2016; Raj et al. 2019; Xie et al. 2017, 2019, 2023).
Atmospheric products are obtained from fifth major global reanalysis produced by ECMWF (ERA5) (Hersbach et al. 2020; https://doi.org/10.24381/cds.f17050d7) with a resolution of 0.25° by 0.25°. We restrict our analysis with monthly mean data averaged over an extended boreal winter season Oct–Mar (ONDJFM) for the period 1993–2021, for which the altimeter and TOPAZ4b products are available.
Following the Polar Amplification Model Intercomparison Project (PAMIP) protocol (Smith et al. 2019), three coupled climate model outputs which are available at the Earth System Grid Federation (ESGF, at the time of this study) are used in this study. The details of the model components are provided in Table 1. For each of the models, outputs from two extended simulations (100 years) using external forcing from CMIP6 corresponding to year 2000 are used. In the reference simulation (pa-pdSIC-ext), SIC is initialized by constraining toward present-day conditions from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST; Rayner et al. 2003). In the future simulation (pa-futArcSIC-ext), SIC is constrained toward reduced SIC values obtained from the CMIP5 ensemble using the following method [for details see Smith et al. (2019)]. For each CMIP5 model, the 30-yr time period that corresponds to present-day conditions (14.24°C), and a 2° warmer world (15.67°C) compared to preindustrial conditions (13.67°C), is chosen and averaged for SIC. Afterward, at each grid point, a linear quantile regression across the models between future and present-day values simulated by the model ensemble is computed. For the future, the lower quartile regression is used for SIC in order to give more weight to models with less sea ice and to increase the signal.
Details of the models used in the study. All the outputs are obtained from https://esgf-node.ipsl.upmc.fr/search/cmip6-ipsl/.
The ways to achieve the desired present-day and future SIC values differ among the models. This means that the three models do not agree with the given present-day and future SIC conditions to the same extent. In the case of NorESM2-LM, SIC is constrained by continually nudging (with a time scale of 5 days) toward the desired present-day and future SIC values. Whereas in the CNRM-CM6-1, the albedo of sea ice and conductivity of snow over sea ice have been modified to produce the reduced sea ice values. In the EC-Earth3 model, a method analogous to SIC nudging using the heat flux adjustment is used [see Simon et al. (2022) and Acosta Navarro et al. (2022) for details]. In the CNRM-CM6-1, the albedo of sea ice and conductivity of snow over sea ice have been modified to produce the present-day and the reduced SIC values. For all three model configurations, the difference between “pa-futArcSIC-ext” and “pa-pdSIC-ext,” averaged over these last 50 years of the simulation, is considered as a response to changes in the Arctic sea ice only and is shown in this study. As in the case with observational and reanalysis data, here also we use extended winter (ONDJFM)-averaged data computed from monthly mean outputs. For comparison, all the model outputs are regridded to 1° by 1° resolution using bilinear interpolation. Statistical significance of the responses for spatial fields is calculated by the standard two-tailed Student’s t test followed by applying false discovery rate (FDR) control to overcome the possible overestimation in rejection of null hypothesis (Wilks 2016).
3. Results and discussion
a. Factors contributing to recent observed trends of sea ice loss in the Barents Sea
Sea ice extent (SIE, identified as 15% SIC contour) in the Barents Sea was reduced by almost 40% between 1993–2005 and 2006–21 (Fig. 2). The reduction is most prominent in the NBS. The spatial pattern of changes in SIC resembles the dominant mode of interannual variability in SIC in the Barents Sea, which is mainly driven by the inflow of heat through the BSO, by sea ice import from the eastern Barents Sea and surface heat fluxes in the SBS (Efstathiou et al. 2022). Here, we investigate the changes in these factors during the recent period (2006–21) and how they might have contributed to the sea ice loss in the NBS.
Change in SIC (color) between 2006–21 and 1993–2005 from satellite observation. The contour lines represent the mean SIE averaged for 1993–2005 (blue) and 2006–21 (red). The inset shows the time series of SIE (million sq. km) anomaly in the Barents Sea.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
The temporal evolutions of temperature and salinity, both from in situ measurements and TOPAZ4b reanalysis, are shown for three key regions in Fig. 3. The regions are representatives of the AW pathway toward the Barents Sea (see Fig. 1). The Svinøy section is located upstream of the AW pathway before the AW enters the Barents Sea through the BSO. The Kola section in the southeastern Barents Sea exhibits significant modifications of the AW as it loses heat to the atmosphere over a shallower SBS. The increasing trends in temperature and salinity of the AW during 1993–2005, in both Svinøy and BSO, reverse during the period 2006–21. This cooling and freshening of AW are due to decadal variability in subpolar North Atlantic gyre (Chafik et al. 2019), which largely controls the AW intrusion in the Nordic seas (Hátún et al. 2005). However, downstream in the Kola section, although salinity shows a decreasing trend after the mid-2000s, the temperature trend does not show an obvious decline. This indicates that during its course through the SBS, the AW undergoes reduced heat loss.
(a),(c),(e) Temperature and (b),(d),(f) salinity anomalies in (a),(b) Svinøy (63°N–3°E), (c),(d) BSO (73°N–20°E), and (e),(f) Kola section (71.5°N–33.5°E) averaged over upper 200 m from in situ observation (red) and TOPAZ reanalysis (blue). The locations of the sections are marked in Fig. 1. Trends for corresponding periods that are significant at 95% confidence level are in bold.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
The change in turbulent (sensible + latent) heat flux during the period 2006–21 is shown in Fig. 4a. Consistent with the findings of Skagseth et al. (2020), there is reduced heat loss (positive values) in the SBS, while heat loss increases (negative values) in the NBS, where sea ice is lost. Moore et al. (2022) also highlighted similar change in heat loss spatial patterns by calculating the turbulent heat flux anomaly along the pathway of AW in the Barents Sea. The reduced heat loss in the SBS allowed warmer water to reach the NBS, as depicted by the northward migration of the 0°C isotherm in Fig. 4a. The mixed-layer depth changes are consistent with the spatial pattern of change in heat loss, with a deeper mixed layer in the NBS and a shallower mixed layer in the SBS (Fig. 4b). The deeper mixed layer in the NBS can further accelerate the sea ice loss due to the vertical mixing of warm and saline AW that resides below the cooler and fresher Arctic waters in the NBS (Lind et al. 2018). This is also evident by the collocation of maximum mixed-layer depth increase and change in sea ice extent (contour of 15% sea ice concentration) in the NBS (Figs. 2 and 4b).
(Shade) Change in winter mean (a) turbulent heat flux (w m−2; positive downward, from ERA5) and (b) mixed-layer thickness (m; from TOPAZ4b) between 2006–21 and 1993–2005. In (a) and (b), the contours represent the location of 0°C isotherm and SIE (from TOPAZ4b), respectively, averaged for the period (blue) 1993–2005 and (red) 2006–21. Dotted regions indicate statistically significant change at 95% confidence level.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Next, we investigate the impact of the reduced heat loss in the SBS on the sea ice condition in the NBS region. Figure 5a shows the dominant mode of winter mean interannual heat flux variability in the Barents Sea. The dipole pattern with reduced heat loss in the SBS and enhanced heat loss in the NBS is negatively correlated with SIC in the NBS and shows intensification during the period 2006–21 (Fig. 5b, positive PC1 values after 2006). While the enhanced heat loss in the NBS can be due to reduced sea ice cover, the impact of reduced heat loss in SBS on the SIC in NBS is evident through a lagged response of SIC to heat loss (Fig. 5c) and also consistent with earlier studies (e.g., Efstathiou et al. 2022). During the period 2006–21, reduced heat loss in the SBS caused lateral transport of warmer water toward the NBS and increased the SST anomaly therein (Fig. 6a). The reduced heat loss also helps in extending the “Atlantification” poleward (Shu et al. 2022) by reducing the modification of AW in its course to the NBS. This is evident through a poleward migration of 0°C isotherm in the NBS associated with reduced heat loss in the SBS, as shown in Fig. 6b. Thus, even though AW temperature itself had a cooling trend during 2006–21, due to reduced heat loss in the SBS, warmer waters continued to reach NBS and favored warming and retreat of SIE therein.
(a) The first EOF of winter mean turbulent heat flux (sensible + latent) in the Barents Sea. The boxes represent the SBS (25°–45°E; 70°–74°N) and NBS (30°–50°E; 76°–80°N) regions used in this study. The spatial pattern is multiplied by the standard deviation of the corresponding time series (first principal component). (b) Scatterplot between the time series (principal component) associated with the EOF (eigenvector) shown in (a) and SIC anomaly in the NBS from both TOPAZ4b reanalysis (dots) and satellite observation (crosses). The colors represent the year as shown in the color bar. (c) Time series of averaged turbulent heat flux anomaly in the SBS (red) and SIC anomaly in the NBS (blue, reversed left y axis). The inset shows the correlation values at zero lag and lag 1, i.e., heat flux in the SBS leading by 1 year.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
(a) Time series of turbulent heat flux anomaly in the SBS (red) and SST anomaly in the NBS (blue). (b) Time series of turbulent heat flux anomaly in the SBS (red) and location of 0°C isotherm averaged over 30°–50°E (blue). Correlation values at lag zero and lag 1 (turbulent heat flux leading by 1 year) shown in the top left corners.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Another source of SST variation in the NBS is the inflow of Arctic water (ArcW) from the eastern Barents Sea (Fig. 1). Figure 7a shows that reduced heat loss and decreased salinity (due to fresher AW inflow, Fig. 3) during 2006–21 can increase the steric SSH in the SBS and contribute to inducing an anomalous SSH gradient between the NBS and SBS. This, in turn, can weaken the westward flow of ArcW as shown by the anomalous eastward currents during 2006–21 in Fig. 7b. Volume transport anomalies of ArcW (T < 0°C) and AW (T > 0°C) are shown in Fig. 7c. As the heat loss of the AW reduces, the eastward outflow of AW through the Eastern Barents Sea (Fig. 1) increases. In contrast, the inflow of ArcW is reduced during 2006–21, as represented by negative anomalies indicating weaker inflow of ArcW from the east. This can lead to further warming in the NBS and favor sea ice loss in the NBS.
(a) Time series of turbulent heat flux anomaly (red) and steric SSH anomaly in the SBS (blue). (b) Change in winter mean SSH (cm) and associated surface geostrophic currents (cm s−1) between 2006–21 and 1993–2005. The currents are shown only for magnitude >1 cm s−1 for clarity and in the region 75°–78°N to highlight the anomalous eastward flow. (c) Volume transport anomaly [Sv (1 Sv ≡ 106 m3 s−1)] of ArcW (blue) and AW (red) across the Eastern Barents Sea (see Fig. 1). Volume transport is calculated from TOPAZ reanalysis, and negative values indicate anomalous eastward transport.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Another source of SST variation in the NBS is the inflow of ArcW from the eastern Barents Sea (Fig. 1). Figure 7a shows that reduced heat loss and decreased salinity (due to fresher AW inflow, Fig. 3) during 2006–21 can increase the steric SSH in the SBS and contribute to inducing an anomalous SSH gradient between the NBS and SBS. This, in turn, can weaken the westward flow of ArcW as shown by the anomalous eastward currents during 2006–21 in Fig. 7b. Volume transport anomalies of ArcW (T < 0°C) and AW (T > 0°C) are shown in Fig. 7c. As the heat loss of the AW reduces, the eastward outflow of AW through the Eastern Barents Sea (Fig. 1) increases. In contrast, the inflow of ArcW is reduced during 2006–21, as represented by negative anomalies indicating weaker inflow of ArcW from the east. This can lead to further warming in the NBS and favor sea ice loss in the NBS.
Thus, in summary, our results indicate that apart from wind-driven reduced sea ice import (Lind et al. 2018) and atmospheric forcings (Liu et al. 2022; Olonscheck et al. 2019), internal feedbacks associated with reduction in heat loss in the SBS contributed in continued sea ice loss in the NBS during 2006–21, despite the cooling trend in the AW intrusion during this period. The effects of reduced heat loss in the SBS on sea ice in the NBS are realized through lateral transport of warmer water to the NBS and reduced Arctic water import from the eastern Barents Sea.
b. Role of sea ice loss
As sea ice is one of the critical parameters driving feedback mechanisms with local and remote influences, we now test the hypothesis that the observed recent changes in the Barents Sea (as discussed in the previous section) are driven by sea ice loss. Here, responses to reduced sea ice in the Arctic Ocean from three coupled climate models are analyzed (see section 2). Note that, since the sea ice is constrained in those models in different ways (as discussed in section 2), the reduction in SIC in sensitivity experiments differs in magnitude as can be seen in Fig. 8. The large-scale sea level pressure response to reduced sea ice (Fig. 9) is consistent with atmosphere-only model responses, which shows a strengthening of high-pressure anomalies extending from Greenland to Siberia (Smith et al. 2022). This anomalous high pressure may allow warmer air from lower latitudes to flow into the Barents Sea region and increase the surface air temperature (SAT). Further, SAT in the Barents Sea region can also increase due to local warming, which is maximum in this region compared to the rest of the Arctic (Rantanen et al. 2022). Future projections from CMIP6 models show a larger increase in SAT compared to SST, which can contribute to the reduced heat loss in the SBS (Shu et al. 2021). Responses of SAT and SST to sea ice reduction also show a larger increase in the former (Fig. 10), indicating the role of sea ice loss in driving the reduced heat loss in the SBS. The heat loss response to sea ice reduction is shown in Fig. 11, which shows a similar seesaw pattern with increased heat loss in the NBS and decreased heat loss in the SBS as found in the recent period as well (Fig. 4a). Thus, the observed recent reduction in heat loss in the SBS can be driven, at least partly, by sea ice loss in the NBS. Note that, the magnitude of heat loss response is weaker in NorESM-LM, consistent with weaker sea ice reduction compared to the other models (Fig. 8).
Difference in winter (ONDJFM) mean SIC (%) between the pa-futArcSIC-ext and pa-pdSIC-ext experiments.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Winter (ONDJFM) mean SLP (mb) response (difference between pa-futArcSIC-ext and pa-pdSIC-ext experiments) to the Arctic sea ice loss shown in Fig. 8. Regions within the black contour indicate significant response at 95% confidence level.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Winter (ONDJFM) mean SAT and SST response (difference between pa-futArcSIC-ext and pa-pdSIC-ext experiments) in the SBS to sea ice loss. The error bars represent the standard errors in each case.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Winter (ONDJFM) mean turbulent heat flux (sensible + latent; w m−2; positive downward) response (difference between pa-futArcSIC-ext and pa-pdSIC-ext experiments) to Arctic sea ice loss. For clarity, only significant responses at 95% confidence level are drawn.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
As discussed in the previous section, the reduction in heat loss in the SBS can influence the NBS sea ice conditions in two ways: 1) by transporting warmer waters downstream and thus increasing the SST in the NBS and 2) through a weaker Arctic water and sea ice inflow. SST response to reduced sea ice shows profound warming in the NBS, along the boundary where AW meets the colder Arctic water (Fig. 12). Figure 13 shows the response in upper ocean geostrophic currents and SSH to a reduction in sea ice in the Arctic Ocean. Anomalous eastward upper ocean currents along the largest SSH gradient (positive/negative SSH response in the SBS/NBS) can be found in the NBS. As discussed earlier, this weakens the flow of Arctic water into the NBS. Figure 13 also shows the MLD response to sea ice reduction, depicting a deepening of MLD in the NBS, particularly along the weaker fresh and cold Arctic water inflow region. The reduced freshwater in this region can weaken the upper ocean stratification, deepen the mixed layer in this region, and consequently lead to the warming of the upper ocean in the NBS as shown by Lind et al. (2018).
Winter (ONDJFM) mean sea surface temperature (°C) response (difference between pa-futArcSIC-ext and pa-pdSIC-ext experiments) to Arctic sea ice loss. For clarity, only significant responses at 95% confidence level are drawn.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
Winter (ONDJFM) mean mixed-layer depth (m; color), SSH (cm; contour) responses (difference between pa-futArcSIC-ext and pa-pdSIC-ext experiments) overlaid with surface geostrophic currents (cm s−1). The area-averaged SSH response is removed from the actual SSH response. The thick line represents the zero contour line.
Citation: Journal of Climate 37, 24; 10.1175/JCLI-D-24-0020.1
In summary, we find that the observed reduced heat loss in the SBS and its potential impact on sea ice conditions in the NBS can be reproduced in coupled model experiments with reduced sea ice in the Arctic Ocean. This indicates the existence of sea ice loss–driven positive feedback in the Barents Sea: larger atmospheric warming compared to sea surface temperature in response to sea ice loss allows reduced heat loss in the SBS. As a result, less modified and warmer AW reaches the downstream NBS. Further, the reduced heat loss increases the SSH in the SBS and induces an SSH gradient between the NBS and SBS. This causes anomalous eastward geostrophic flow and weakens the Arctic water inflow to the NBS. These act together, along with stronger vertical mixing, to reduce the sea ice in the NBS further, closing the feedback loop.
4. Conclusions
In this study, we investigate continued winter sea ice loss in the Barents Sea, despite a cooling trend in the Atlantic water temperature during the period 2006–21. We highlight that besides a reduced wind-driven sea ice import (Lind et al. 2018), internal atmosphere–ocean feedback has played a prominent role in sea ice reduction in the NBS. We suggest that sea ice in the NBS has already reached a point where it can drive a coupled atmosphere–ocean feedback regulated by reduced heat loss in the SBS, favoring further sea ice decline. Climate model projections show that while heat loss is expected to reduce in the SBS, it increases in the NBS, leading to enhanced Atlantification (Shu et al. 2021). Comparable responses from idealized coupled model experiments indicate the pivotal role of sea ice loss in driving the observed and projected changes in the Barents Sea climate.
Acknowledgments.
SC acknowledges Director, National Centre for Polar and Ocean Research (NCPOR), for providing support. NCPOR is fully funded by the Ministry of Earth Sciences (MoES), Govt. of India. The work was initiated during CMIP6 bootcamp (2022) at Denmark organized by CLIVAR-Northern Oceans Regional Panel. SC acknowledges WCRP and Nansen Scientific Society, Bergen, for financial support to attend the bootcamp. JAS was funded by the NERC ArctiCONNECT project (Grant NE/V005855/1). Authors acknowledge Rym Msadek, Aleksi Nummelin, and Pablo Ortega for valuable information on PAMIP simulations. This is NCPOR Contribution Number J-32/2024-25.
Data availability statement.
All datasets used in the study are freely available, and their respective sources are mentioned in section 2.
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