2.1.1. Introduction

The Arctic Ocean contains a large amount of freshwater, and the freshwater export from the Arctic to the North Atlantic influence the stratification, and, hence, the Atlantic meridional overturning circulation (e.g. Aagaard et al. ; Aagaard and Carmack ; Holland et al. ). The Fram Strait represents a major gateway for freshwater transport, both as liquid freshwater and as sea ice, from the Arctic Ocean to the North Atlantic through the East Greenland Current (e.g. Vinje et al. ; Fahrbach et al. ; Lique et al. ; Smedsrud et al. ; Rabe et al. ; Figure 2.1.1). Two main factors contributing to this are the vicinity to the area north of Greenland where the thickest multi-year pack ice in the Arctic resides, and the fact that the Fram Strait is the largest (and deepest) gateway between the Arctic Ocean and the World Ocean. The transport of sea ice through the Fram Strait is therefore important for the mass balance of the perennial sea-ice cover in the Arctic and represents an annual loss corresponding to about 10% of the total Arctic perennial sea-ice volume (e.g. Vinje et al. ; Rampal et al. ). Indeed, sea ice export through the Fram Strait has been found to explain 54% of the variations in Arctic winter multi-year sea ice volume changes (Ricker et al. ). However, while satellites provide high-quality data on the Arctic sea-ice extent, estimates of the sea-ice thickness, and, hence, total volume of the Arctic sea ice has up until recently been rather limited (e.g. Ricker et al. ), and consequently model re-analyses are often used for assessing sea-ice volume and transport (e.g. Zhang et al. ).

A large part of the interannual variability in the sea-ice export through the Fram Strait is explained by the large-scale synoptic forcing, while thermal wind forcing across the Fram Strait represents a persistent, although declining, atmospheric forcing (van Angelen et al. ). Moreover, the geostrophic winds across Fram Strait have been stronger in the 2000s compared with the period 1960s–1990s, which has caused an increase in the sea-ice transport, more than compensating for the decrease in the sea-ice concentration in the Fram Strait over the same period (Widell et al. ; Smedsrud et al. ). As an example, in 2007 anomalous wind conditions over the Arctic contributed to a strengthened transpolar drift and increased sea-ice export through the Fram Strait, reducing the amount of multi-year sea ice within the Arctic (Smedsrud et al. ; Zhang et al. ). However, Bi et al. () found a decrease in the sea-ice volume export of 600 km³/year in the period 2011–2014 compared to the periods 1990–1994 and 2003–2008. They attributed this decline first and foremost to changes in sea-ice drift, and to a lesser extent to changes in sea-ice thickness and even less to a decrease in the sea-ice concentration.

Another gateway of major exchange between the Arctic and the North Atlantic oceans is the Barents Sea (e.g. Smedsrud et al. ). Although there is a considerable net sea-ice transport from the Nansen Basin of the Arctic Ocean to the Barents Sea shelf both from the north and from the east (e.g. Sorteberg and Kvingedal 2006; Lind et al. ; Figure 2.1.1), this sea ice melts locally within the Barents Sea. However, the freshwater input from the melting sea ice in the central Barents Sea is reported to be an important factor in maintaining the pool of Arctic Water, and, thus, the Arctic conditions and strong stratification of the northern Barents Sea (Lind et al. ). Moreover, the presence of Arctic Water maintains the Polar Front towards the southern Barents Sea dominated by warmer and more saline Atlantic Water (e.g. Loeng ). A borealization (e.g. Polyakov et al. ) of the Barents Sea, where the influence of Atlantic Water increases at the expense of the influence from Arctic Water, has been found to be ongoing due to an increase in the temperature of the Atlantic Water in the southwest (e.g. Årthun et al. ; Fossheim et al. ; Onarheim et al. ), and further due to increasing temperature in the atmosphere, and, hence, weaker heat loss from the ocean (Skagseth et al. ). A declining sea-ice import from the Arctic Ocean and a subsequent weakening of the Arctic Water reservoir further adds to the borealization (Lind et al. ).

Here, we present net modelled sea-ice area and volume transport through the Fram Strait and into the Barents Sea and compare the results with observation-base estimates reported in literature. Furthermore, we provide a scientific rationale for including these transport time series as Ocean Monitoring Indicators for the Copernicus Marine Environmental Monitoring Service.

2.1.2. Material and methods

The Arctic Monitoring and Forecasting Center model (product 2.1.1) is the TOPAZ4 system based on a North Atlantic and Arctic configuration of the HYCOM ocean model coupled to a modified version of the CICE3 sea ice model at a horizontal resolution of 12 km, assimilating various observations once a week, including sea-ice concentrations from OSI SAF and thin-ice thickness (from SMOS, since 2014) with an Ensemble Kalman Filter (Xie et al. 2018). The best estimate output is the average of the 100-members ensemble. For further information about the model system and data assimilation, see Sakov et al. (). For composite analysis shown in Figure 4, time periods of high/low sea ice area export are determined as those above/below 1 STD of the mean for the full monthly time series during the time period 1993–2019.

We have chosen to calculate the sea-ice area and volume transport through the Fram Strait across the 79°N latitude. In some other studies the section is chosen differently. Generally, Spreen et al. () found a convergence between a northern (80°N) and southern (76°N) section in summer (i.e. the transport at 80°N is larger than further south/downstream at 76°N), while in winter they found a divergence (i.e. the transport at 80°N was smaller than further south due to local ice production in the Greenland Sea). Thus, our results may not be directly comparable to results reported from the literature.

2.1.3. Results and discussion

The average monthly modelled sea ice export through the Fram Strait, both volume and area, follows the observations in terms of seasonal cycle, with a maximum in winter/spring (Oct–Apr) and a minimum in summer (Jul–Aug; Figure 2.1.2a,c). The maximum area export is found in March, with an average export of 133 × 10³ km², and with a standard deviation of 36 × 10³ km². However, because the maximum is governed both by the maximum sea-ice extent and favourable wind conditions, the actual month of the maximum area transport may vary between years. The minimum area export decreases to close to zero in July (9 × 10³ km²) but with a standard deviation of 20 × 10³ km². For the full year, the average annual modelled sea-ice area export is 989 × 10³ km². This is about 10% larger than the estimate of 880 × 10³ km² reported by Smedsrud et al. () for the period 1935–2014, based on observations of satellite radar images and surface pressure observations and estimated across 79°N. Moreover, they reported some tendency of a positive trend during recent decades. Similar results were reported by Zamani et al. (), although they used a different section located further upstream at 82°N that likely increases the transport estimate in summer and decreases the transport estimate in winter (Spreen et al. ). Zamani et al. () estimated an annual sea-ice area transport of 860 × 10³ km² for the period 1990–2010. Moreover, they found a positive trend of +10% per decade (i.e. an increase of around 90 × 10³ km²/year per decade). On the contrary, our model results indicate a negative, statistically significant (p < 0.05) trend of – 1.0 × 10³ km²/month per year (i.e. on the order of – 100 × 10³ km²/year per decade) for the period 1993–2019. However, we also find that the trend varies with the season, with the largest trend seen in winter while being close to zero in late spring and summer (Figure 2.1.2a). For the full period 1993–2019, this trend represents a 28% reduction in area transport. Other observation-based estimates based on ice motion and concentration fields are lower (Bi et al. ). They reported an average maximum sea-ice area transport of 78 × 10³ km² in March, and an annual average area export totalling 644 × 10³ km² (Tables 2.1.1 and 2.1.2).

Average modelled sea-ice volume export through the Fram Strait exhibits a seasonal cycle comparable to that of the sea-ice area export (Figure 2.1.2c), with a maximum of 167 km³ in March, and a minimum of 13 km³ in July and August. However, the variability is large, with a maximum standard deviation in February (88 km³) and a minimum standard deviation in August of 22 km³ implying that there are also months where the net sea-ice transport is directed northwards. Indeed, the maximum modelled monthly sea-ice volume export is 353 km³ (April 1995), while the minimum modelled monthly sea-ice volume export is −34 km³ (July 2004; Figure 2.1.3c). Moreover, as for the sea-ice area transport, the actual month of the maximum area transport may vary between years. Our modelled estimates are comparable with observation-based estimates. Spreen et al. () reported an average monthly sea-ice volume export estimate of 217 km³ for the years 2003–2008, varying between 92 and 420 km³, which is higher than our modelled estimates. Note, however, that Spreen et al. () used a different section at 80°N which tended to overestimate the transport compared to further south in summer, and slightly underestimate in winter. Moreover, our results suggest that there was indeed an elevated export during the years 2003–2008 (Figure 2.1.3b,c). On the other hand, for the period 2010–2017, Ricker et al. () using a section located at 82°N reported that monthly export estimates varied between 21 and 540 km³. Annual export varied between 1250 km³ for the year 2012–2013 and 1910 km³ for the year 2011–2012 (Ricker et al. ), which is close to the average annual transport estimate of 1267 km³ found in our model results. Based on both satellite and numerical model data Zhang et al. () estimated an annual average sea-ice volume transport of 1132 km³, ranging from 10 km³/month in August to 145 km³/month in March. On the higher end, Spreen et al. () reported an average annual sea-ice volume transport of 2400 ± 640 km³, which they considered to be a conservative estimate, based on satellite measurement of sea-ice drift and upward-looking sonar for measuring sea-ice thickness. Based on linear regression, we find a statistically significant (p < 0.05) trend of −2.2 km³/month per year during the period 1993–2019. This trend represents a decrease in the sea-ice volume transport of 43% over the period, which is larger than the relative reduction in sea-ice area transport, implying also a reduction in the average sea-ice thickness during the period. As for the sea-ice area transport, the trend in sea-ice volume transport through the Fram Strait varies with season. A strong, negative trend is found in winter and partly autumn (October), while a weak, positive trend is found in early summer (Figure 2.1.2c).

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.1.1. Map showing the location of the sections across the Fram Strait between Greenland and Spitsbergen, the Barents Sea north between Svalbard and Franz Josef Land, and the Barents Sea east between Franz Josef Land and Novaya Zemlya, used to estimate the area and volume of sea ice transport. Mean sea ice drift speed during the time period 1993–2019 is overlaid in arrows. Black isobaths are drawn at 500-meter intervals.

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The model results do not show any statistically significant trend in the sea-ice thickness in the Fram Strait. However, there are some indications of decreasing thickness from the 1990s to the 2000s, a period during which Spreen et al. , observed a negative trend in thickness of 15–21% per decade. This period was followed by an increase in the average modelled thickness from 2015 and onwards. Moreover, the first half of the period corresponds to the period when Hansen et al. () reported a decline in the average sea-ice thickness in the Fram Strait from 3.0 m during the 1990s to 2.2 m during the period 2008–2011.

The Barents Sea ice area and volume transport seasonal cycle differ somewhat from that in the Fram Strait. A maximum is seen in late winter/early spring (April–May), along with a secondary maximum in December (Figure 2.1.2b,d). The modelled seasonal sea-ice area transport maximum is 69 × 10³ km² in April, while the maximum sea-ice volume transport is 64 km³ in May. A seasonal minimum in both area and volume transport is found in summer (Jul-Sep), with minimum values of 2 × 10³ km² and 5 km³, respectively. A secondary minimum is found in January (and also Feb-Mar for volume).

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.1.2. Seasonal cycle of modelled sea-ice area and volume transport and corresponding trend. (a) Black line shows monthly average sea-ice area transport through the Fram Strait for the period 1993–2019 (positive values southward). Grey shading shows the corresponding ±1 standard deviation. Red, broken line shows the linear trend per year for each month. (b) Similar to (a), but for sea-ice area transport into the Barents Sea (positive values into the Barents Sea). Note that the scale on the y axes are similar in (a) and (b). (c) Similar to (a), but showing sea-ice volume transport through the Fram Strait. (d) Similar to (c), but showing for the Barents Sea. Note that the scale on the y axes are similar in (c) and (d).

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Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.1.3. Time series showing modelled sea-ice thickness, area and volume transport. (a) Average monthly sea-ice thickness in the Fram Strait (black line). The red line shows the linear trend for the period 1993–2019. (b) Twelve-month cumulative sea-ice area transport through the Fram Strait (black line; positive southward). The red line shows the linear trend for the period 1993–2019. (c) Similar to (b), but showing sea-ice volume transport through the Fram Strait. (d) Similar to (a) but showing for the Barents Sea. The broken red lines show the linear trend for the periods 1993–2006 and 2007–2019, respectively. (e) Similar to (b), but showing sea-ice area transport into the Barents Sea. The broken red lines show the linear trend for the periods 1993–2006 and 2007–2019, respectively. (f) similar to (e), but showing sea-ice volume transport into the Barents Sea.

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As for the Fram Strait, the time series of both sea-ice area and volume transport show large variability, although the sea-ice transport into the Barents Sea shows smaller seasonal variability than the sea-ice transport through the Fram Strait (Figures 2.1.2 and 2.1.3). Moreover, we find no significant trend in the modelled sea-ice area transport into the Barents Sea, while the volume transport exhibit a statistically significant (p < 0.05) linear trend of −1.5 km³/year for the period 1993–2019, representing a total reduction of 84% over the period, using a linear regression analysis. However, there are some indications of a minimum during the 2000s, when the seasonal maximum seems to be more or less absent, while large seasonal maxima have ocurred in recent years leading to an increase in total volume transport (2014, 2017, and 2019; Figure 2.1.3f). While we did not find a significant trend in the sea-ice area transport overall, the linear regression indicated a reduction in the area transport of nearly 40% from 1993 to 2019. Moreover, there was an apparent minimum in the sea-ice area transport around 2007, followed by an apparent increase, especially after 2015 (Figure 2.1.3e). This contrasts with the findings of Lind et al. (), who reported a strong decline in the sea-ice area import to the Barents Sea from the 2000s until 2016. Our results show that the average thickness of the sea ice entering the Barents Sea decreased strongly between 1993 and 2005 (Figure 2.1.3d). From 2005 and onwards, however, there is no trend in the modelled thickness of the sea-ice entering the Barents Sea. Indeed, while we did not find a statistically significant change in the drift speed of the sea ice entering the Barents Sea (not shown), there is a statistically significant (p < 0.05), negative trend in the thickness of the sea ice that enters the Barents Sea, with a total reduction of 89% from 1993 to 2019 when using linear regression, but with the major part taking place prior to 2005. Similar to the Fram Strait, there was a strong increase in both the sea-ice area and volume transport in 2019 compared to the preceding years. This finding is in line with the reporting of the sea ice conditions around the Svalbard archipelago returning to ‘normal’ in 2019 through a combination of preconditioning from anomalous advection of thick multi-year sea ice from the Arctic Ocean and strong, northerly winds in the region (see Section 4.1 in this issue).

A major driver for the interannual variability of the Fram Strait sea-ice transport is the synoptic atmospheric circulation (e.g. van Angelen et al. ). Using ± 1 standard deviation to define high/low monthly transports, we find dipole patterns in the large-scale mean sea-level pressure and corresponding cross-sectional winds associated with anomalous sea-ice transport through all the three sections investigated (Figure 2.1.4). This result indicates that atmospheric forcing is a major driver also for the variability in the modelled sea-ice transport, and in agreement with findings based on observations (e.g. Tsukernik et al. ). However, our model results indicate a statistically significant, negative trend in the sea-ice area transport through the Fram Strait, opposite of the reported positive trend from increasing winds in recent decades in observations (e.g. Smedsrud et al. ) and model simulations (e.g. Zamani et al. ). Moreover, the main driver of the trend found in our model results is a negative trend in the sea-ice drift (not shown). On the other hand, the average modelled sea-ice concentration does not show any significant trend. Note, that although a negative trend in sea-ice volume transport was also found based on observations by Spreen et al. (), they concluded that a decrease in sea-ice thickness was the main driver of the negative trend. Possible explanations for this discrepancy include differences in the calculation of the area transport, uncertainties in the estimation of sea-ice drift (e.g. Sumata et al. ), and errors relating to the parameterisation of wind drag on sea ice in the model (e.g. Chikhar et al. ). Moreover, different studies refer to different areas for defining the Fram Strait. However, results presented by Spreen et al. () indicate that the transport estimates are not sensitive to the exact flux gate location. A thorough investigation of these matters is beyond the scope of this study, but we will point out some aspects that could be further elaborated in future studies. Our model results show larger sea-ice drift on the Greenland shelf in the western Fram Strait (Figure 2.1.1) than observed (Smedsrud et al. , see their Figure 2). This discrepancy points to differences in the treatment of fast ice and its impact on sea-ice drift in the model and the observation-based datasets. The current model configuration utilised in this study include a sea-ice model with an elastic-viscous-plastic rheology (Hunke and Dukowicz ), while an improved sea-ice model using a Maxwell elastic-brittle rheology (Dansereau et al. ), which takes into account ice deformation, will be implemented in the near future.

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

https://doi.org/10.1080/1755876X.2021.1946240

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Figure 2.1.4. Composite sea-level pressure anomalies during periods of high sea-ice transport (left) and low sea-ice transport (right) through the Fram Strait (top; a,b), the Barents Sea north section (middle; c,d) and through the Barents Sea east section (bottom; e,f).

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Differences in the position of Fram Strait sea-ice export estimation may affect the transport estimates in several ways. Complex recirculation patterns within the Fram Strait area (e.g. Beszczynzka-Möller et al. ) cause uncertainties in the northward and southward sea-ice drift estimations dependent on the position of the transect used. Depending on the season, sea ice freezing or melting occurs along-stream from north to south in the Fram Strait (e.g. Spreen et al. ). Additionally, the West Spitsbergen Current flowing northward in the eastern parts of the Fram Strait is more or less ice free all year round at 79°N, while further north there is varying presence of sea ice, also depending on the northward flow of Atlantic Water (e.g. Ivanov et al. ; Polyakov et al. ).

The relation between the sea-ice thickness and drift to the total sea-ice volume import in the Barents Sea points toward a change in the properties of the sea ice upstream of the Barents Sea, that is, in the Nansen Basin of the Arctic Ocean (in agreement with the findings of a thinning sea ice cover by Polyakov et al. ), rather than a change in atmospheric conditions affecting the general circulation, as the main driver of the changes in the sea-ice volume import to the Barents Sea during the period 1993–2019. However, our results indicate that the preconditioning through decreasing sea-ice thickness from less multi-year sea ice present in the Nansen Basin was a main driver of the decline in the sea-ice import to the Barents Sea in the 1990s and the first half of the 2000s, whereas after the mid-2000s, the area transport has increased (while the thickness has remained more or less constant), which indicates that changes to the general atmospheric circulation may have played an increasingly important role in the most recent decade.

2.2.1. Introduction

Ocean heat content (OHC) is an important quantitative variable in the Earth’s climate system, and provides a unique measure of the current status and prospects of global warming (von Schuckmann et al. ; Cheng et al. ). In the upper 700 m of the near-global (60°N-60°S) ocean, area averaged OHC has increased at a rate of 0.3 ± 0.1 Wm⁻² during 1960–2018 and the rate increased to 0.9 ± 0.1 Wm⁻² over the period 2005–2018 (von Schuckmann et al. ). The pan-Arctic (here defined as north of 60°N) – a region where near-surface warming has been reported to occur faster than the global average (e.g. Serreze and Barry ) – is usually not represented in the near-global global analysis of OHC, predominantly due to the fact of low subsurface temperature data coverage in this area. Recent studies have shown that the Arctic OHC is warming at a rate close to the global warming rate (e.g. Mayer et al. ; von Schuckmann et al. ; Mayer et al. ). Under anthropogenic pressure, Arctic sea-ice cover is declining, thereby altering the ocean-atmosphere heat exchange through larger areas of open water. In addition, increased ocean heat transport to the Arctic is pushing oceanic conditions typical of sub-polar regions (e.g. a comparatively weak stratification) downstream into the northern polar basin, a process termed ‘Atlantification’ (e.g. Polyakov et al. ) affecting also ocean-ice fluxes (Polyakov et al. ). Thus, the OHC and its spatial distribution within the Arctic is a relevant metric at the interface of oceanic transports, surface fluxes, sea ice melt, and the global energy inventory.

The Nordic Seas (Norwegian, Greenland, and Iceland Seas) is a region of major water mass transformation in the northern loop of the global thermohaline circulation (e.g. Aagaard et al. ; Mauritzen ). Here, saline and relatively warm Atlantic Water flows through the Norwegian Sea to the east en-route to the Arctic Ocean, while colder and fresher water masses of Arctic origin flows southward through the Greenland Sea to the west. Especially the northern part of the Norwegian Sea, the Lofoten Basin, is a reservoir of Atlantic Water and represents a major heat sink, with strong and persistent heat loss to the atmosphere, and as will be shown in this contribution, above-average regional warming. The OHC as an integrated measure of the hydrographic conditions in the Norwegian Sea represent a robust indicator and precursor of the ocean heat transport to the Arctic Ocean (e.g. Furevik ). The variability in the OHC locally in the Nordic Seas is mainly a product of local air–sea fluxes and advection. Several studies have indicated that variation in ocean heat loss to the atmosphere can explain about half of the year-to-year OHC changes in the Norwegian Sea (e.g. Mork et al. ). Other studies have revealed that advection is the primary cause of interannual to decadal heat content variability in this area (e.g. Carton et al. 2011; Asbjørnsen et al. 2019). Thus, advection tends to play a dominating role in the OHC variability in the Norwegian Sea on time scales longer than one year (Mork et al. ).

Quantification of ocean warming in the high north is crucial for a better understanding of Arctic change. However, earlier assessments of Arctic OHC examined neither the spatial details of the trends nor the robustness of the results, which were obtained largely from reanalyses. Here we assess Arctic OHC in more detail than before and also examine the agreement of reanalysis products and in-situ observations for a better understanding of uncertainties.

2.2.2. Data & methods

OHC integrated over the upper 1000 m of the Norwegian Sea is calculated from Argo data (CORA-GLOBAL-5.1, Ref No 2.2.1), and is presented as anomalies (OHCA), relative to the World Ocean Atlas 2018 (WOA18; Locarnini et al. ) climatology using the latest averaging period, 2005–2017. For each Argo profile, the temperature climatology is interpolated horizontally and vertically to match the location and vertical resolution of the Argo profile (Mork et al. ). The advantage of using anomalies is that they are independent of the reference value. For each Argo profile, OHC anomalies are calculated above the reference depth h as (1) $\mathrm{OHC}=c_p{\rho }_0{\int }_{-h}^0(T-T_{\mathrm{clim}})dz,$(1) where c_p is the heat capacity (4.0 × 10³ Jkg⁻¹ K⁻¹), ρ₀ is a reference density (1030 kgm⁻³), and z is the vertical axis with z = 0 at the sea surface. Subscript ‘clim’ indicates climatological data from WOA18, and is a function of month, depth and location. The integrated depth, h, is set to 1000 m, as the upper 1000 m of the Norwegian Sea comprises the bulk of the Atlantic Water flow towards the Arctic. Monthly means with uncertainties (standard deviation) are calculated from all OHC anomalies for the Norwegian and Lofoten basins within each month.

To cover the full Arctic, we compute OHC from the Global Ocean Reanalysis Ensemble product (GREP; product ref. 2.2.2) at a ¼° spatial and monthly temporal resolution. We present results for the upper 300, 700 m, upper 1000 m and full-depth (average depth north of 60 N to 1240 m, maximum depth > 4600 m) OHC, covering 1993–2019. In addition to the GREP, we also present results from CMEMS ARMOR3D (Ref No 2.2.3; Guinehut et al. ). ARMOR3D is a weekly global product with a 1/4° spatial resolution and 33 vertical levels. It provides temperature, salinity, geostrophic currents and mixed layer gridded fields from 1993 to present. Satellite altimetry and sea surface temperature are combined with in situ data by optimal interpolation. In situ data include vertical profiles from moorings, scientific campaigns, autonomous profilers, gliders, ships of opportunity, sea mammals, as well as surface data from various buoys and ferry boxes. Satellite data cover most of the Arctic in summer (altimetry goes up to 82°N), and there is some data near Svalbard even in winter.

Anomalies of the GREP and ARMOR3D data are calculated with respect to their 1993–2014 climatology. For the comparison with Argo data, we use the same climatology but additionally remove the long-term-means of the period for which Argo data is available (2002–2019 for the Norwegian Basin and 2005–2019 for the Lofoten Basin). Additionally, we provide regional averages for the ice-free ocean and ice-covered ocean. We use 30% annual mean sea ice concentration based on the GREP ensemble mean as a threshold for sea ice cover.

Trend estimates are based on the ordinary least squares method and are provided for the full 1993–2019 period. The uncertainty estimate used for significance testing takes into account random and structural errors as follows. Random errors are estimated from the standard errors of the linear regression coefficients of the GREP ensemble mean and the Argo OHC evolutions, respectively, taking temporal auto-correlation into account. Structural uncertainty for the GREP is estimated from the spread in the four OHC trends computed for the four reanalyses separately, divided by $\sqrt{n-1}$ ($\sqrt{3}$). For the Argo, 100 synthetic time series were constructed and the structural uncertainty was estimated by the standard deviation of the linear regression coefficients of these 100 time series. The synthetic time series were constructed by creating 100 random numbers for each month that were normally distributed around the monthly OHC estimate with a standard deviation equalling the uncertainty during the respective month. Random and structural errors are added in quadrature to obtain the uncertainty estimate used for significance testing.

2.2.3. Results

2.2.3.1. Reanalysis – observation comparison

Before examining the OHC in the pan-Arctic region from the gridded products (GREP and ARMORD3D), we perform a comparison between the estimated OHC from the reanalyses and observations based on Argo. The region is limited to the Lofoten and Norwegian basins of the Norwegian Sea, and the depth range is from the surface to 1000 m depth. The OHC is estimated according to equation (1). Due to limitations in the availability of Argo observations, the observation-based estimates are limited to the period June 2002 to July 2018 in the Norwegian basin and March 2005 to September 2018 in the Lofoten basin, respectively. In the comparison, the analysis of both the reanalysis-based and observation-based time series include the period covered by observations only. The time series based on the reanalyses and the observations are shown in Figure 2.2.1. Generally, OHCA estimates from both the GREP and ARMOR3D follow the observations in terms of both magnitude and variability. However, the observation-based estimates display larger month-to-month variability (Figure 2.2.1), which could be related to sampling noise in the observations that is smoothed by data assimilation. Based on monthly averages, the correlation, R, between the de-trended GREP and observation-based estimates is 0.59 (p < 0.001) in the Norwegian basin and 0.56 (p < 0.001) in the Lofoten basin. However, when we filter the time series using a 12-month moving boxcar window (i.e. annual averages), the correlation coefficients increase to R = 0.85 (p < 0.001) and R = 0.90 (p < 0.001) in the Norwegian and Lofoten basins, respectively. Another noteworthy feature of Figure 2.2.1 is that the agreement between the GREP and ARMOR3D is degraded prior to the availability of Argo data, which demonstrates the strong constraint that Argo provides on ocean state estimates.

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.2.1. Time Series of 0–1000 m ocean heat content anomalies in the Lofoten (top) and Norwegian (bottom) basins estimated from Argo (Ref. No. 2.2.1) and the Global Ocean Reanalysis Ensemble product (Ref. No. 2.2.2). Note that GREP and Argo data represent three-monthly averaged OHCA, while ARMOR3D data represents annual OHCA.

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Figure 2.2.1. Time Series of 0–1000 m ocean heat content anomalies in the Lofoten (top) and Norwegian (bottom) basins estimated from Argo (Ref. No. 2.2.1) and the Global Ocean Reanalysis Ensemble product (Ref. No. 2.2.2). Note that GREP and Argo data represent three-monthly averaged OHCA, while ARMOR3D data represents annual OHCA.

The trends in the reanalysis-based OHC estimates are comparable to the observation-based estimates in both basins (1.22 ± 0.85 Wm⁻² and 1.69 ± 0.92 Wm⁻² in the Norwegian basin, 3.75 ± 0.96 Wm⁻² and 3.16 ± 1.35 Wm⁻² in the Lofoten basin, with 95% confidence intervals computed as described in the Data & Methods section). All trends are significant at the 95% level. Moreover, the individual trend estimates fall within the uncertainty range (1σ) of the associated estimate from the reanalyses/observations. Thus, there is a close agreement between the reanalysed and observed OHC estimates in both the Norwegian Sea basins, both in terms of trend during the 2000s and inter-annual variability. While there is a statistically significant correlation also on monthly timescales, this correlation is rather weak.

2.2.3.2. Ocean heat content in the high North from reanalyses

Figure 2.2.2a presents linear trends of upper 700 m OHC over 1993–2019. We focus on the spatial features that are statistically significant on the 95% level. Widespread and significant warming is present in the upper 700 m in basically all ice-free ocean north of 60N. Maximum warming is found in the Barents and Norwegian seas, with regional trends in the Norwegian Sea exceeding 6 Wm⁻², which is almost twice as high compared to the upper 300 m OHC trends (not shown). Strongest warming in the Barents Sea occurs in the southeastern part, which is in agreement with the findings of Skagseth et al. (). Weak but significant warming is present also in the shelf seas along the Siberian coast. Moderate but still significant warming is found also in the Beaufort Gyre, an area that is ice-covered most of the year. Weak and largely insignificant cooling is present around the Amundsen Basin. It is important to note that observational data in the sea-ice-covered areas is scarce, but at least the moderate warming in the Beaufort Gyre seems consistent with observation-based estimates. For example, Timmermans et al. () found a halocline warming of ∼0.3 Wm⁻² during 1992–2015 in this region (based on the numbers in their Figure 1).

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.2.2. Linear OHC trends (converted to Wm⁻²) (a) of the upper 700 m and (b) below 700 m for 1993–2019 from the GREP (Ref. No. 2.2.2). Stippling denotes regions where trends are significant at the 95% confidence level. Figure (b) additionally indicates the location of water bodies referred to in the text: Iceland Sea (IS), Norwegian Sea (NS) with two basins Lofoten Basin (LB) and Norwegian Basin (NB), Greenland Sea (GS), and Barents Sea (BS).

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Figure 2.2.2. Linear OHC trends (converted to Wm⁻²) (a) of the upper 700 m and (b) below 700 m for 1993–2019 from the GREP (Ref. No. 2.2.2). Stippling denotes regions where trends are significant at the 95% confidence level. Figure (b) additionally indicates the location of water bodies referred to in the text: Iceland Sea (IS), Norwegian Sea (NS) with two basins Lofoten Basin (LB) and Norwegian Basin (NB), Greenland Sea (GS), and Barents Sea (BS).

Figure 2.2.2b shows linear trends of OHC below 700 m. In the Norwegian and Greenland Seas, substantial warming is present at these depths, attaining values greater than 5 Wm⁻². Thus, full-depth OHC trends in the Nordic Seas exceed 10 Wm⁻² regionally. In contrast, penetration of warming OHC trends below 700 m into the central Arctic is progressing relatively slowly according to the results from the GREP.

We now turn to regionally averaged OHC evolution during 1993–2019. Figure 2.2.3 presents a time series of upper 700 m OHC anomalies for the pan-Arctic, including results for the two sub-regions (ice-covered and ice-free). Pan-Arctic upper 700 m OHC has increased since 1993, with a much larger contribution from the ice-free Arctic Ocean. One should note that the ice-free ocean covers only ∼37% of the total ocean area north of 60°N. This is consistent with Figs 2.2.2a and b showing particularly strong warming in the Greenland and Norwegian Seas. Remarkably rapid warming occurred in the ice-free Arctic ocean during 2002–2004, which can also be seen in the pan-Arctic OHC. More in-depth diagnostics reveal that this rapid warming signal persists when removing Argo data in an observing system experiment (not shown), suggesting that this is not an artefact from increased data coverage and is indeed a real climate signal. The long-term OHC increase and interannual signals, including the rapid warming in 2002–2004, are consistently shown also by ARMOR3D. Even in the data-sparse regions under sea ice, ARMOR3D yields similar results as the GREP.

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.2.3. OHC anomaly (OHCA) of the upper 700 m in 10²¹ J relative to the 1993–2014 climatology for the Arctic Ocean north of 60 N and the partition into ice-covered regions (under_seaice) and ice-free regions (no_seaice). The partition is based on the annual mean sea ice concentration using a 30% threshold. Curves represent the GREP (Ref. No. 2.2.2) ensemble mean, and the shading represents the intra-ensemble spread. The dashed lines represent results from ARMOR3D (Ref. No. 2.2.3; based on annual mean values).

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Figure 2.2.3. OHC anomaly (OHCA) of the upper 700 m in 10²¹ J relative to the 1993–2014 climatology for the Arctic Ocean north of 60 N and the partition into ice-covered regions (under_seaice) and ice-free regions (no_seaice). The partition is based on the annual mean sea ice concentration using a 30% threshold. Curves represent the GREP (Ref. No. 2.2.2) ensemble mean, and the shading represents the intra-ensemble spread. The dashed lines represent results from ARMOR3D (Ref. No. 2.2.3; based on annual mean values).

Finally, we present area-averaged OHC trends for the pan-Arctic as well as the contributions from ice-free and ice-covered ocean in Figure 2.2.4. The 1993–2019 warming rate for the pan-Arctic was 0.4 ± 0.1 Wm⁻² (0.44 ± 0.07 Wm⁻² when allowing two decimals) in the 0–300 m layer and 0.6 ± 0.2 Wm⁻² (0.57 ± 0.16 Wm⁻²) in the 0–700 m layer. The trend is enhanced by a factor of ∼1.3 when integrating down to 700 m, while the uncertainty increases by a factor of ∼2.1. This indicates that the signal-to-noise ratio, defined as the ratio of the trend and its uncertainty, is smaller for the 0–700 m layer compared to the 0–300 m layer. For the full-depth ocean, warming is further enhanced to 0.7 ± 0.2 Wm⁻² (0.74 ± 0.19 Wm⁻²).

Copernicus Marine Service Ocean State Report, Issue 5

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Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), Signe Aaboe, Victor Alari, Brittany E. Alexander, Andrés Alonso-Martirena, Ali Aydogdu, Joel Azzopardi, Marco Bajo, Francesco Barbariol, Mirna Batistić, Arno Behrens, Sana Ben Ismail, Alvise Benetazzo, Isabella Bitetto, Mireno Borghini, Laura Bray, Arthur Capet, Roberto Carlucci, Sourav Chatterjee, Jacopo Chiggiato, Stefania Ciliberti, Giulia Cipriano, Emanuela Clementi, Paul Cochrane, Gianpiero Cossarini, Lorenzo D'Andrea, Silvio Davison, Emily Down, Aldo Drago, Jean-Noël Druon, Georg Engelhard, Ivan Federico, Rade Garić, Adam Gauci, Riccardo Gerin, Gerhard Geyer, Rianne Giesen, Simon Good, Richard Graham, Marilaure Grégoire, Eric Greiner, Kjell Gundersen, Pierre Hélaouët, Stefan Hendricks, Johanna J. Heymans, Jason Holt, Marijana Hure, Mélanie Juza, Dimitris Kassis, Paula Kellett, Maaike Knol-Kauffman, Panagiotis Kountouris, Marilii Kõuts, Priidik Lagemaa, Thomas Lavergne, Jean-François Legeais, Pierre-Yves Le Traon, Simone Libralato, Vidar S. Lien, Leonardo Lima, Sigrid Lind, Ye Liu, Diego Macías, Ilja Maljutenko, Antoine Mangin, Aarne Männik, Veselka Marinova, Riccardo Martellucci, Francesco Masnadi, Elena Mauri, Michael Mayer, Milena Menna, Catherine Meulders, Jane S. Møgster, Maeva Monier, Kjell Arne Mork, Malte Müller, Jan Even Øie Nilsen, Giulio Notarstefano, José L. Oviedo, Cyril Palerme, Andreas Palialexis, Diego Panzeri, Silvia Pardo, Elisaveta Peneva, Paolo Pezzutto, Annunziata Pirro, Trevor Platt, Pierre-Marie Poulain, Laura Prieto, Stefano Querin, Lasse Rabenstein, Roshin P. Raj, Urmas Raudsepp, Marco Reale, Richard Renshaw, Antonio Ricchi, Robert Ricker, Sander Rikka, Javier Ruiz, Tommaso Russo, Jorge Sanchez, Rosalia Santoleri, Shubha Sathyendranath, Giuseppe Scarcella, Katrin Schroeder, Stefania Sparnocchia, Maria Teresa Spedicato, Emil Stanev, Joanna Staneva, Alexandra Stocker, Ad Stoffelen, Anna Teruzzi, Bryony Townhill, Rivo Uiboupin, Nadejda Valcheva, Luc Vandenbulcke, Håvard Vindenes, Karina von Schuckmann, Nedo Vrgoč, Sarah Wakelin & Walter Zupa

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Figure 2.2.4. Linear OHC trends 1993–2019 for Arctic Ocean north of 60N and decomposition into ice-free and ice-covered ocean north of 60N (based on the 1993–2019 sea ice concentration climatology with a threshold of 30% concentration) estimated from the GREP (Ref. No. 2.2.2). Trends are converted to warming rates given in Wm⁻². The conversion factor from Wm⁻² to ZJ/yr is 0.51 for the pan-Arctic Ocean, 0.17 for the ice-free ocean, and 0.34 for the ice-covered ocean. Uncertainties are the 1σ-uncertainties.

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Figure 2.2.4. Linear OHC trends 1993–2019 for Arctic Ocean north of 60N and decomposition into ice-free and ice-covered ocean north of 60N (based on the 1993–2019 sea ice concentration climatology with a threshold of 30% concentration) estimated from the GREP (Ref. No. 2.2.2). Trends are converted to warming rates given in Wm⁻². The conversion factor from Wm⁻² to ZJ/yr is 0.51 for the pan-Arctic Ocean, 0.17 for the ice-free ocean, and 0.34 for the ice-covered ocean. Uncertainties are the 1σ-uncertainties.

Warming is weak in the ice-covered ocean (both in area-specific and area-integrated units), probably because sea ice melt takes up a substantial amount of extra energy and the ocean below is protected from the atmosphere above (Mayer et al. ), which is elaborated on in the discussion. Upper 300 m trends are 0.2 ± 0.1 Wm⁻². Extending to the full-depth ocean does not alter the obtained trend, but uncertainty is much increased (0.2 ± 0.2 Wm⁻²).

Strong warming is found in the ice-free ocean, with a warming trend of 1.0 ± 0.2 Wm⁻² in the upper 300 m, 1.4 ± 0.5 Wm⁻² in the upper 700 m layer, and 1.9 ± 0.7 Wm⁻² in the full-depth ocean. We note the much higher signal-to-noise ratio of the trends in the ice-free ocean compared to the ice-covered ocean, which likely is a result of the much better observational coverage.