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Changes in Ocean Temperature in the in the Twenty-First Century

ZHENXIA LONG AND WILL PERRIE Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada

(Manuscript received 3 June 2016, in final form 6 April 2017)

ABSTRACT

Possible modifications to ocean temperature in the Barents Sea induced by change are explored. The simulations were performed with a coupled ice–ocean model (CIOM) driven by the surface fields from the Canadian Regional Climate Model (CRCM) simulations. CIOM can capture the observed water volume inflow through the Barents Sea Opening. The CIOM simulation and observations suggest an increase in the Atlantic water volume inflow and heat transport into the Barents Sea in recent decades resulting from en- hanced storm activity. While seasonal variations of sea ice and sea surface temperature in CIOM simulations are comparable with observations, CIOM results underestimate the sea surface temperature but overestimate ice cover in the Barents Sea, consistent with an underestimated heat transport through the Barents Sea Opening. Under the SRES A1B scenario, the loss of sea ice significantly increases the surface solar radiation and the ocean surface heat loss through turbulent heat fluxes and longwave radiation. Meanwhile, the lateral heat transport into the Barents Sea tends to increase. Thus, changes in ocean temperature depend on the heat balance of solar radiation, surface turbulent heat flux, and lateral heat transport. During the 130-yr simulation period (1970–2099), the average ocean temperature increases from 08 to 18C in the southern Barents Sea, mostly due to increased lateral heat transport and solar radiation. In the northern Barents Sea, ocean tem- perature decreases by 0.48C from the 2010s to the 2040s and no significant trend can be seen thereafter, when the surface heat flux is balanced by solar radiation and lateral heat transport and there is no notable net heat flux change.

1. Introduction et al. 2011; Årthun et al. 2012; Smedsrud et al. 2013; Onarheim et al. 2015). Warm saline Atlantic water enters the Barents Sea The cold outflow from the Barents Sea accounts for mainly through the Barents Sea Opening (BSO; Fig. 1a; approximately half of the Atlantic water flow into the Blindheim 1989; Furevik 2001; Ingvaldsen et al. 2002; central Ocean (Rudels et al. 1994; Schauer et al. Skagseth et al. 2008, 2011; Rudels et al. 2013). On av- 1997; Maslowski et al. 2004; Lien and Trofimov 2013; erage, the mean volume and heat transports are esti- 2 Rudels et al. 2013; Long and Perrie 2015). On its way mated to be 2.3 Sv (1 Sv [ 106 m3 s 1) and 70 TW through the Barents Sea, the Atlantic water is modified (Smedsrud et al. 2013), but there is a rapid loss of heat as a result of the mixing with surrounding water and the as a result of atmospheric cooling in winter (Midttun associated transformation, through cooling and ice for- 1985; Hakkinen and Cavalieri 1989; Zhang and Zhang mation (Midttun 1985). In the northwestern Barents 2001; Serreze et al. 2007; Årthun and Schrum 2010; Sea, the modified Atlantic water enters Nansen Basin Smedsrud et al. 2010; Årthun et al. 2011). The strongest 2 through the Victoria Channel, and the average water heat flux is about 500 W m 2 near the marginal ice zone volume flux is estimated to be about 0.4 Sv (Maslowski in winter, which can cool the warm saline Atlantic water et al. 2004; Aksenov et al. 2010; Årthun et al. 2011). all the way to the ocean bottom (Hakkinen and However, most of the Atlantic water in the Barents Sea Cavalieri 1989). Moreover, the warm Atlantic water continues to move northeastward into the Kara Sea inflow keeps the southern Barents Sea largely ice free between Franz Josef Land and Novaya Zemlya (Loeng and increases air–sea interactions (Helland-Hansen and et al. 1997; Gammelsrod et al. 2009), where it enters the Nansen 1909; Sandø et al. 2010; Beszczynska-Moller central , through the St. Anna Trough (Simonsen and Haugan 1996; Schauer et al. 2002; Corresponding author: William Perrie, william.perrie@dfo-mpo. Gammelsrod et al. 2009). Recent studies suggest that the gc.ca inflow from the St. Anna Trough plays an important role

DOI: 10.1175/JCLI-D-16-0415.1 For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/ PUBSReuseLicenses). Unauthenticated | Downloaded 09/24/21 07:54 AM UTC 5902 JOURNAL OF CLIMATE VOLUME 30

century and in the 1970s, but warmer in the 1930s–50s and in recent decades. As part of the mulitdecadal var- iations in the Barents Sea, the temperature at 100–150 m increased by approximately 48C from the late 1970s to the later part of the 2000–10 decade, because of a com- bination of oceanic and atmospheric changes (Levitus et al. 2009). For example, the ocean temperature at the Barents Sea Opening increased by about 18C in recent decades, which enhanced the heat transport into the Barents Sea (Skagseth et al. 2008; Årthun et al. 2012). In addition, the increases in solar radiation and surface air temperature may also play an important role (Levitus et al. 2009). Overall, while the ocean temperature in the Barents Sea is dominated by multidecadal variability (Levitus et al. 2009), a positive trend has also been identified (Boitsov et al. 2012). In a recent study (Long and Perrie 2015), we showed that under the SRES A1B scenario the ocean temper- ature in the northern Barents Sea tends to decrease, resulting from the enhanced air–sea interactions asso- ciated with the ice loss, which reduces the heat transport into the central Arctic Ocean. The objective of this study is to investigate the processes associated with the changes of the ocean temperature in the Barents Sea in the twenty-first century, focusing on the heat balance and the role of Arctic storms. Section 2 describes the model, the experimental design, and the methodology for storm tracking and heat flux computation. Section 3 shows the comparisons between the CIOM simulations and available observations. The simulated changes of ocean temperature in the Barents Sea are discussed in section 4. Section 5 discusses biases in our model simu- lations, as well as their impacts on our results. Section 6 presents the conclusions.

2. Model description and experiment design A coupled ice–ocean model (CIOM) was implemented FIG. 1. (a) Model domain and (b) the area indicated by thick black lines in (a), where the BSO between and is in the Arctic Ocean (Yao et al. 2000; Wang et al. 2005; indicated in (a), and A and B in (b) represent the northern Barents Long et al. 2012), based on the Princeton Ocean Model Sea and the southern Barents Sea, respectively. The shading shows (POM; Blumberg and Mellor 1987) and a multicategory the bathymetry (m) as indicated by the color bar. ice model (Hibler 1979, 1980). It was successfully applied to studies of the impacts of climate change in the Arctic in the heat balance in the central Arctic Ocean. Specif- Ocean, including freshwater content and sea surface ically, because of the reduced heat transport from the height (Long and Perrie 2013, 2015). A detailed de- Barents Sea and increased surface heat loss, the ocean scription of CIOM can be found in Long et al. (2012) and temperature associated with the Atlantic water layer Long and Perrie (2013, 2015). Only a summary is given in tends to decrease under the SRES A1B scenario (Long this section specifying the model setup. and Perrie 2015). a. Ocean model There is a significant multidecadal variation in the ocean temperature in the Barents Sea (Levitus et al. The CIOM domain is centered on the central Arctic 2009; Boitsov et al. 2012). On average, the ocean tem- Ocean on a rotated spherical surface with the North perature was relatively colder at the beginning of the last Pole at 888N, 131.58E(Fig. 1a). Its horizontal resolution

Unauthenticated | Downloaded 09/24/21 07:54 AM UTC 1AUGUST 2017 L O N G A N D P E R R I E 5903 is 0.29830.258 with 25 vertical sigma levels. For exam- Hydrographic Climatology (PHC) data by Steele et al. ple, for an ocean point with a depth of 3500 m, the ver- (2001). In this methodology, we first computed the T and tical resolution is about 6 m for the upper seven layers, S anomalies of the CGCM3 outputs from their long- 380 m near the bottom, and 60 m between 200 and 400 m. term means (1979–2008), and then added them to the To minimize numerical errors, the bottom topography is PHC climatology to get lateral boundary boundaries for smoothed so that DH/H is smaller than 0.2, where DH CIOM. Forced with the modified T and S variables, is the difference in the depths of adjacent grids while H CIOM was successfully applied to study the impacts of is the mean of the grids (Mellor et al. 1994). In addition, climate change on the freshwater content in the Beau- the Neptune effect is implemented so that the model fort Sea and the Atlantic Water Layer in the central simulation can include the cyclonic rim currents associ- Arctic Ocean (Long and Perrie 2013, 2015). No ‘‘nudg- ated with topographic stress (Holloway 1992). The ing’’ or restoration procedures are used. Neptune velocity U* is estimated from the bathymetry, Riverrunoffisamajorfreshwatersourceforthe and the difference between ocean currents U and U* Arctic Ocean (Serreze et al. 2006; Long and Perrie (U 2 U*) is used to compute the viscosity term to pa- 2013). There are 13 major rivers along the Arctic coast rameterize the interactions between eddies and the and the river runoff in the Barents Sea is estimated to 2 bottom topography (Holloway 1992). be about 632 km3 yr 1, which is a major contribution to Because of the presence of sea ice, the vertical mixing the low salinity Barents Seawater (Dankers and in the Arctic Ocean is relatively weak (Fer 2009), but the Middelkoop 2008; Schauer et al. 2002; Smedsrud et al. increased vertical ocean heat transport due to loss of sea 2010). The runoff from the rivers is prescribed as ice has been shown to play an important role in the future precipitation minus evaporation (P 2 E) using monthly change of Atlantic water in the central Arctic Ocean climatological river runoff observations (Prange and (Long and Perrie 2015).The vertical mixing coefficients in Lohmann 2004) for 1970–99. In addition, to represent the CIOM are estimated using a second-order turbulence impacts of climate change, a positive trend is added for the 2 closure scheme (Mellor and Yamada 1982). In addition, years from 2000 to 2099 with an amplitude of 0.12% yr 1, the background mixing coefficients depend on local ice giving a total increase of 4.15 km3 (Wu et al. 2005). 2 2 concentrations, ranging from 1 to 2 3 10 5 m2 s 1 for ver- 2 2 2 b. Ice model tical eddy viscosity and from 5 3 10 6 to 1 3 10 5 m2 s 1 2 2 for eddy diffusivity. An extra 3 3 10 5 m2 s 1 is added The sea ice component of CIOM is based on a multi- to the background viscosity and diffusivity for the category ice thickness distribution function (Thorndike water depths above 70 m to approximately represent the et al. 1975; Hibler 1980) and a viscous–plastic sea ice effects of surface waves and eddies (Fer 2009). dynamics model (Hibler 1979). It has seven categories The barotropic transports are specified along open of ice thickness and is able to estimate heat, moisture, boundaries, based on observations (Beszczynska-Moller and momentum fluxes at the ice–ocean interface et al. 2011). The inflows through Bering Strait (0.8 Sv) as determined by appropriate boundary processes and the Norwegian Sea (8.5 Sv) are balanced by the (Mellor and Kantha 1989). Total downward shortwave outflows through the Canadian Archipelago (2.3 Sv) and radiation is estimated, following Shine and Crane along the east coast of Greenland (7.0 Sv). However, the (1984), with the cloud correction formulation of Reed baroclinic transports are estimated using radiation (1977) and sea ice albedo is determined from snow boundary conditions. As shown in section 4a, the At- thickness, ice surface temperature (Koltzow 2007), and lantic water inflow into the Barents Sea is mainly driven ice thickness. In addition, longwave radiation is given by surface wind associated with the storms in the by the Smith and Dobson (1984) parameterization, and Barents Sea (Bengtsson et al. 2004; Skagseth et al. 2008), turbulent heat fluxes and wind stress are estimated and the slight changes that may occur in the lateral using bulk formulas. In CIOM, the surface fluxes are boundary conditions have no significant impacts on the defined as the sum of sensible heat flux, latent heat flux, changes of Atlantic water in the Barents Sea (Long and and longwave radiation, whereas solar radiation is Perrie 2015). considered separately because of its penetration pro- Recent studies have shown that there are significant cess. Air–ice and air–water drag coefficients are set 2 biases in the ocean temperature and salinity variables to 2.75 3 10 3 (Prinsenberg and Peterson 2002)and 2 from the Third Generation Canadian Coupled Global 1.1 3 10 3, respectively, while the ice–water drag co- 2 Climate Model (CGCM3) simulations (Long and Perrie efficient is 5.5 3 10 3 (Shirasawa and Ingram 1991). 2015). To provide the lateral boundary conditions for The ice model provides POM with heat, moisture, and CIOM, the CGCM3 monthly temperature T and salinity momentum fluxes, and POM provides surface tempera- S fields are modified using the Polar Science Center ture, salinity, and current to the ice model, as feedback

Unauthenticated | Downloaded 09/24/21 07:54 AM UTC 5904 JOURNAL OF CLIMATE VOLUME 30 variables. POM and the ice model exchange variables at integrated for 60 yr to reach stability for ocean cur- every time step. rents, sea ice, ocean temperature, and salinity, for simulation of the present climate, driven by the two c. Experiment rounds of the CRCM surface variables for 1970–99. Our objective is to investigate the processes associ- There is no restoration or nudging for ocean temper- ated with the changes in the Barents Sea temperature in ature and salinity. the twenty-first century, particularly in regard to the The focus of our analyses is the ice–ocean simulations heat balance and the role of storms. Because of its coarse of the Barents Sea (Fig. 1b) from 1979 to 2099. Although horizontal resolution, a global climate model tends to the Barents Sea is largely ice free in summer (Fig. 2a), underestimate the high wind events, such as storms there is significant ice cover in the northern Barents Sea (Long et al. 2009). The resolution of the atmospheric in winter (Fig. 3a). Based on the observed average po- output of CGCM3 is 2.58 and for the ocean output is sition of the ice edge in winter (Fig. 3a), the Barents Sea 1.858, which are too coarse to simulate detailed ocean is divided into the northern Barents Sea (box A in circulation features like the ice edge (Long and Perrie Fig. 1b) and the southern Barents Sea (box B in Fig. 1b). 2015). To simulate the storm climatology and climate The results are not sensitive to the definition of the change in the Arctic, the Canadian Regional Climate boxes, based on our analyses, which is discussed in Model (CRCM) is used to downscale CGCM3 simula- section 5. tions for 1970–2099 to provide high-resolution (45 km) d. Cyclone activity surface driving fields for CIOM. In this methodology, CGCM3 outputs provide CRCM with initial and Our study will specifically consider how changes in the boundary conditions (winds, geopotential height, tem- storm activity in the Barents Sea can be correlated with perature, specific humidity, sea ice, and sea surface the water volume transport through the Barents Sea temperature) and CRCM outputs provide driving fields Opening. To detect and track the storms (Long et al. for CIOM [surface air temperature, specific humidity, 2009; Long and Perrie 2012), we first make an analysis of precipitation, total cloud cover, sea level pressure the SLP fields to identify local minima, where a candi- (SLP), and 10-m winds]. date SLP center must satisfy the following criteria: We follow the SRES A1B climate change scenario 1) local minimum of less than 1010 hPa within a radius (IPCC 2007), which assumes increasing carbon dioxide of 240 km and emissions until about 2050, and then decreasing emis- 2) at least one closed isobar on a 4-hPa increment. sions thereafter. As shown in section 4, it is notable that a decrease in emissions after 2050 could potentially Second, we use a simple nearest neighbor search in or- affect the eventual temperature projections for the der to track the individual storms from the preceding Barents Sea. CRCM simulations can capture the basic (6 h) time step. If a storm falls within 600 km of a storm patterns of sea level pressure and surface air tempera- that was identified in the preceding time step, it is as- ture found in NCEP–NCAR reanalyses. For example, sumed to be a continuation of the previous storm; oth- CRCM has a reasonable simulation of the Beaufort high erwise, it is considered a new storm. A candidate SLP in the Beaufort Sea and the low pressure system in the center is required to have a lifetime of at least 24 h. We eastern Arctic. The low pressure system over the use ‘‘track density’’ to measure the storm activity, which Barents Sea and Nordic seas is an extension of the Ice- is defined as the number of storm tracks passing any landic low and responsible for transporting warm, moist given grid point. Results regarding annual storm-track Atlantic air into the Arctic. While CRCM is able to density and water volume transport are presented in capture the overall features of this low pressure system, section 4. it is underestimated by about 3 hPa, compared to NCEP e. Water volume and heat transports reanalysis data (Long and Perrie 2013). Moreover, the 6-hourly surface fields from the CRCM simulations ÐÐThe lateral heat transport is computed as 2 y y can be successfully applied in studying the impacts of A(T T0) dA, where A is the lateral area, and is the climate change (Long and Perrie 2013, 2015). The current normal to the area, which is positive (negative) if related details, concerning the surface fields from the the water flows into (out of) one of the selected boxes

CRCM simulations and the implementation of CIOM shown in Fig. 1b. Here, T is ocean temperature and T0 is in the Arctic Ocean, are given by Long and Perrie the reference temperature, which is set to 08C. Since (2013, 2015).ForcedwiththesurfaceCRCMfields, the lateral boundaries for boxes A and B are closed, the

CIOM was integrated from 1970 to 2099 in this study. lateral heat transport is not sensitive to T0. For the As part of the initialization methodology, CIOM was Barents Sea Opening, the lateral heat transport is

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FIG. 2. Ice concentration in September, showing averages (1980– FIG.3.AsinFig. 2, but for March. 2009) for (a) HadISST, (b) CIOM results, and (c) the differences between CIOM results and HadISST.

Unauthenticated | Downloaded 09/24/21 07:54 AM UTC 5906 JOURNAL OF CLIMATE VOLUME 30 computed along the section between Svalbard and Norway, and there may be a bias in the estimate of heat transport because of its dependence on T0 (Montgomery 1974; Schauer and Beszczynska-Möller 2009; Årthun et al. 2012). However, the temperature changes in the Barents Sea are discussed based on the heat budget in the boxes A and B, and the bias will not affect the conclusion. The water volume for the Barents Sea ÐÐOpening is computed for the whole water column as y A dA.

3. Present climate a. Heat fluxes The ocean heat transport through the Barents Sea Opening is a major heat source for the Barents Sea, which can affect the ice cover and air–sea interactions and plays an important role in the Barents Sea climate variability (Smedsrud et al. 2010; Sandø et al. 2010; Årthun et al. 2012; Onarheim et al. 2015). The observed mean water volume transport through the Barents Sea Opening is about 2.3 Sv, and the associated heat flux is about 70 TW (Smedsrud et al. 2013). However, the CIOM simulations suggest about 2.3-Sv Atlantic water volume transport and about 55-TW heat flux into the Barents Sea during the period 1980–2000 (Fig. 4). Therefore, although CIOM simulates the magnitudes of the water volume transport well, it underestimates the ocean heat transport through the Barents Sea Opening. The heat entering the southern Barents Sea is largely lost as turbulent heat fluxes and longwave radiation (Sandø et al. 2010; Smedsrud et al. 2010; Beszczynska- Moller et al. 2011). In terms of model evaluation, during the period 1980–2000, the simulated net heat transport into the southern Barents Sea through lateral bound- aries is about 40 TW (Fig. 5b). Both CIOM simulations and previous studies (Smedsrud et al. 2010) suggest that solar radiation contributes about 25 TW (Fig. 5b). In addition, CIOM simulations suggest that 60 TW is lost to the atmosphere in the southern Barents Sea (Fig. 5b), while about 15 TW is lost to atmosphere in the northern Barents Sea (Fig. 5a), which is consistent with previous studies (Smedsrud et al. 2010, 2013). In recent decades, observations also show increased Atlantic water inflow and associated heat transport into the Barents Sea through the Barents Sea Opening Å FIG. 4. (a) Water volume transport (Sv) through the BSO, (b) heat (Skagseth et al. 2008; rthun et al. 2012). The annual transport (TW) through the BSO (black) and its 9-yr smoothing upward trend in heat flux is 2.5 TW, which is due to a results (red), (c) average ocean temperature (8C) along the BSO positive trend in the water volume transport combined (black) and its 9-yr smoothing results (green) and observed water with an increase in ocean temperature (Skagseth et al. temperature (50–200 m) at the Fugløya– section (red), 8 2008; Årthun et al. 2012). Although the CIOM simula- and (d) average water temperature ( C) above 200 m at the Kola section for CIOM simulation (red) and observations (black). tion shows an increase in the heat transport through the

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suggest a temperature decrease in the early 1990s and an increase in the late 1990s. b. Ocean temperature and salinity Warm Atlantic waters enter the southern Barents Sea through the Barents Sea Opening and rapidly lose heat through intense air–sea interactions and surface heat fluxes (Figs. 6–8). For example, the ocean temperature at 80 m is 58–68C near the Barents Sea Opening, but rapidly decreases from 48–58C near the northern Norwegian coast to from 218 to 08C in the northeastern Barents Sea (Fig. 7). Similar patterns can be seen in the ocean tem- peratures at 150 m and at the surface (Figs. 6 and 8). While the CIOM simulation shows the warm Atlantic water in the southern Barents Sea and cold water in the northeastern Barents Sea, the CIOM overestimates the ocean temperatures at depths of 80 and 150 m by about 18–28C near the St. Anna Trough, and underestimates temperatures in the southern Barents Sea (Figs. 7 and 8). In addition, the CIOM simulations can reproduce the seasonal variation of sea surface temperature in PHC data (Fig. 6d), but significantly underestimate the sea surface temperature in the southern Barents Sea (Fig. 6c). Moreover, observations show that the ocean temper- atures in the southern Barents Sea tend to increase in recent decades, but the magnitude of temperature in- crease is underestimated in the CIOM simulations

FIG. 5. Heat fluxes (TW) into the (a) northern Barents Sea and (Levitus et al. 2009; Figs. 9a,b). The area-averaged (b) southern Barents Sea, as indicated in Fig. 1b, showing the net ocean temperature in the CIOM simulations linearly heat flux through lateral boundary (green), surface heat flux increases from about 20.18C in the 1980s to about 0.28C (black), solar radiation (red), and total net heat flux (blue). in the 2010s in the southern Barents Sea (Fig. 9b). However, there is no significant change in the northern Barents Sea Opening, its magnitude is significantly un- Barents Sea (Fig. 9a). In the southern Barents Sea, the derestimated. The simulated heat transport increases simulated increases in the ocean temperature are mainly from about 58 TW in the late 1990s to about 63 TW in associated with the enhanced heat transport through the the mid-2010s with an annual increase of about 0.5 TW Barents Sea Opening, decreased surface heat flux, and (Fig. 4b). increased solar radiation (Figs. 4 and 5). Consistent with the observed temperature increase at Because of the Atlantic water inflow through the the Fugløya–Bear Island section (738N, 208E), the av- Barents Sea Opening, the sea surface salinity is rela- erage temperature along the Barents Sea Opening in the tively high in the southern Barents Sea. The sea surface CIOM simulation does increase from about 3.78Cin salinity is about 34.5–35 psu near the Barents Sea 1980 to about 4.08C in 2015 (Fig. 4c); but the magnitude Opening, and gradually decreases eastward, reaching of the temperature increase is notably underestimated, about 33.5–34 psu in the northern Barents Sea. While compared to observations (Skagseth et al. 2008; Årthun the CIOM simulation shows the salinity decrease from et al. 2012). Moreover, while the simulated temperature the southern Barents Sea to the northeastern Barents at the Kola section (71.58N, 33.58E) shows the observed Sea, it underestimates the salinity values by 0.5–1.5 psu increase in 1980–2015, the CIOM simulation un- in the southern Barents Sea and along the Norwegian derestimates the ocean temperature by about 18C coast (Fig. 10), suggesting an underestimated vertical (Fig. 4d). In addition, the average ocean temperature mixing in the Barents Sea. along the Barents Sea Opening shows significant de- c. Ice concentration cadal variations (Fig. 4c). For example, both the simu- lation (Fig. 4c) and the observations (Drinkwater et al. The presence of sea ice effectively modifies the ex- 2014; Levitus et al. 2009, Smedsrud et al. 2013; Zhang 2015) change of heat, moisture, and momentum between the

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FIG. 6. Annual ocean temperature (8C) at surface, showing av- FIG.7.AsinFigs. 6a–c, but at 80 m. erages (1980–2009) for (a) CIOM results, (b) PHC data, and (c) the differences between CIOM results and HadISST. (d) Seasonal variations of sea surface temperature for CIOM results (black) and PHC data (red), averaged over Fig. 1b.

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atmosphere and the ocean, compared to open water conditions (Andreas et al. 2010). When the ocean is fully covered with sea ice, the presence of ice reduces the exchanges of heat, moisture, and momentum between the atmosphere and the ocean compared to conditions in the marginal ice zone (MIZ). When ice forms, it in- fluences the salinity through brine rejection; the for- mation of dense bottom water associated with the brine rejection is a regular phenomenon in the Barents Sea (Midttun 1985; Årthun et al. 2011). Furthermore, the cold bottom water moves into the central Arctic Ocean through the Victoria Channel and St. Anna Trough, affecting the heat balance at intermediate layers, and playing an important role in the Arctic Ocean ventila- tion (Long and Perrie 2015). On a seasonal time scale, the ice cover in the Barents Sea is strongly correlated with air temperature, and shows significant seasonal variations (Fig. 11). While the northern Barents Sea is covered with sea ice in winter, the southern Barents Sea is dominated by open water (Fig. 3), influenced by the warm Atlantic water inflow. The minimum in ice cover occurs in August–September when the Barents Sea is almost ice free (Fig. 2), mostly due to increased solar radiation and reduced surface heat loss. Compared to observations such as represented by HadISST (Rayner et al. 2003), CIOM simulates the September ice cover (Fig. 2) and seasonal variation of ice cover reasonably well (Fig. 11a), but notably over- estimates the March ice concentration in the central Barents Sea (Fig. 3). Figure 11a gives the time series of ice area averaged over the domain shown in Fig. 1b. While the model simulation shows a reasonable seasonal variation, the simulated minimum ice cover occurs in August, one month earlier than in observed data from HadISST (Fig. 11). In addition, CIOM significantly overestimates the ice cover from October to June.

4. Impacts of climate change in the Barents Sea a. Water volume and heat transport through the Barents Sea Opening We explore the correlation between the changes in the storm activity in the Barents Sea and the water volume transport through the Barents Sea Opening. Under the SRES A1B scenario, the Arctic warms faster as a result of positive feedback, namely because of the reduced surface albedo associated with the loss of snow and ice at high latitudes. Concomitantly, the north– FIG.8.AsinFigs. 6a–c, but at 150 m. south temperature gradient in the Northern Hemi- sphere tends to decrease causing the northeastward shift of the storm tracks (Long et al. 2009). Although the changes in the storm tracks are subject to competing

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FIG. 9. Area-average ocean temperature (8C) over the (a) northern Barents Sea and (b) the southern Barents Sea, as indicated in Fig. 1b. The red curve in (b) shows the 9-yr smoothing results for the average temperature in the southern Barents Sea. The average ocean temper- ature is the integral of ocean temperature divided by the total water volume. thermodynamic influences, our simulations suggest that winds associated with the cyclonic atmospheric circula- the reduced temperature gradient dominates the pro- tion enhance the wind-driven oceanic inflow through the cess, consistent with Shaw et al. (2016). Barents Sea Opening (Bengtsson et al. 2004; Ingvaldsen Using the methodology outlined in section 2d, the et al. 2004; Skagseth et al. 2008). However, it is note- simulated annual storm-track density in the Barents Sea worthy that the change in storm intensity is weak, and is about 16–18 storms per year in 1980–99 and there is a there is no significant correlation between the water significant increase after the 2000s (Fig. 12), consistent volume transport through the Barents Sea Opening and with previous observational studies (Zhang et al. 2008; the storm intensity in the Arctic. Benestad et al. 2016). In addition, the changes in the The maximum increases in the storm activity in the storm-track density in the Barents Sea are significantly Barents Sea occur in 2000–19, and the increases are correlated with the water volume transport through the relatively weak thereafter, showing multidecadal varia- Barents Sea Opening (Fig. 13), because the westerly tions (Fig. 12). Correspondingly, the simulated water

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volume transport through the Barents Sea Opening in- creases from 2.3 Sv in the 1980s to 2.7 Sv in the 2020s, but decreases after the 2030s, and there is no significant trend (Fig. 4a). The associated ocean heat transport has a similar change, but shows significant multidecadal vari- ability (Fig. 4b), mostly due to variations of ocean tem- perature (Fig. 4c), as shown in Drinkwater et al. (2014) and Levitus et al. (2009). The correlation between the water volume and heat transports is 0.67. Although other recent studies suggest a decrease in northward heat transport in the northern North Atlantic (Yeager et al. 2015), the heat transport through the Barents Sea Opening tends to increase in 2000–19, because of the increased storm-track density. In contrast to the de- crease of the water volume transport after 2030s, there are no significant changes in the heat transport, which is mostly due to the temperature increase in the Barents Sea Opening (Fig. 4c), consistent with recent studies (Smedsrud et al. 2013; Sandø et al. 2014). The average heat transport after the 2030s is about 65 TW, which is about 10 TW higher than the average during 1980–2000. b. Ocean temperature The average ocean temperature in the northern Barents Sea decreases from about 20.28C in the 2010s to about 20.58C in the 2030s, and there is no significant change thereafter (Fig. 9a). For example, the tempera- ture at 80 m is from about 218 to 08C in 1980–99, but slowly decreases after 2000–19, and the decrease reaches 218C in the northwestern Barents Sea by the end of the century, in 2080–99 (Fig. 14). While the changes at a depth of 150 m show similar patterns (Fig. 15), the sea surface temperature in the northern Barents Sea tends to increase, and the maximum in- crease is about 28C in the northwestern Barents Sea in the period of 2080–99 (Fig. 16). In the southern Barents Sea, the average ocean temperature tends to increase from the 1980s to the 2090s. The average temperature increases from about 08C in the 2000s to about 18C in the 2090s (Fig. 9b). Meanwhile, the warm water at 80 m is limited to coastal areas during 1980–99, but slowly expands northeast- ward, and dominates the southern Barents Sea in 2080–99. The maximum increase in ocean temperature is about 38C in 2080–90 (Fig. 14). Similar patterns can be seen at 150 m, but the warming is relatively weaker than at 80 m (Fig. 15). The maximum increase in ocean temperature occurs at the surface with a magnitude of FIG. 10. Annual sea surface salinity, showing averages (1980– 58C in the central Barents Sea in 2080–99 (Fig. 16). 2009) for (a) CIOM results, (b) PHC data, and (c) the differences between CIOM results and PHC data. Consistent with previous studies, the average ocean temperature in the southern Barents Sea shows sig- nificant mulitidecadal variability (Drinkwater et al.

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6 2 FIG. 11. Ice area in the Barents Sea (10 km ) showing (a) averages (1980–2009) for HadISST data (red) and CIOM results (black) and (b) CIOM results in November (black) and linear trend (red). Any grid point is considered as open water if ice concentration is below 0.15.

2014; Levitus et al. 2009; Smedsrud et al. 2013; In addition, the increase in the lateral heat transport is Zhang 2015). relatively weak and increases from about 5 TW in the 2000s to about 10 TW in the 2090s. Therefore, the c. Heat balance in the Barents Sea changes in solar radiation and lateral heat transport tend The temperature decrease in the northern Barents to partly offset the impacts of the enhanced surface heat Sea from the 2010s to the 2030s is mainly associated with flux. In terms of net heat flux, the northern Barents Sea the increased surface heat flux (Fig. 5a). Under the cli- loses heat from the 2000s to the 2030s, but reaches mate change scenario, the average surface heat flux in- equilibrium thereafter (Fig. 5a). Correspondingly, the creases from 15 TW in 2000s to about 30 TW in the average ocean temperature decreases from the 2000s to 2090s. However, the solar radiation and lateral heat the 2040s, and there is no significant trend from the transport tend to increase the ocean temperature. The 2040s to the 2090s (Fig. 9a). average solar radiation gradually increases from about By comparison, in the southern Barents Sea, the in- 10 TW in the 2000s to about 20 TW in the 2090s (Fig. 6a). creased lateral heat transport and solar radiation play

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FIG. 12. Annual storm-track density in 1980–99 and the track-density differences for periods relative to the track density in 1980–99. important roles in the ocean temperature increases changes in the northern Barents Sea, the surface heat (Fig. 5b). Under the SRES A1B scenario, the solar ra- flux increases from about 60 TW in the 2000s to about diation increases from about 20 TW in the 2000s to 100 TW in the 2090s, which partly offsets the impacts about 50 TW in the 2090s. Meanwhile, the lateral heat resulting from the increased lateral advection and solar transport increases from 40 to about 60 TW in the 2020s, radiation, and the net heat flux tends to increase ocean but there is no significant trend thereafter. Similar to the temperature (Figs. 5b and 9b).

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underestimates the heat transport through the Barents Sea Opening and its increase in recent decades. While the sea surface salinity is underestimated by 0.5– 1.5 psu in the southern Barents Sea, the CIOM sea sur- face temperatures are underestimated by 28–48C in the southern Barents Sea and 0.58–1.58C in the northern Barents Sea. Moreover, the ice concentration is over- estimated in the southern Barents Sea, compared to observations. The biases in the CIOM simulations are consistent with previous studies. For example, Sandø et al. (2014) used ROMS to downscale GISS-AOM (ROMS-G) and NCAR CCSM3 (ROMS-N) simulations, following the IPCC SRES A1B scenario (IPCC 2007). Compared to observations, ROMS-G underestimates the ocean salin- ity (temperature) but significantly overestimates the ice FIG. 13. Correlation coefficient between water volume transport cover in the southern Barents Sea. While ROMS-N has a through the Barents Sea Opening and annual storm-track density. Only the coefficients that have significance at the 99% level are shown. reasonable simulation of water volume transport through the Barents Sea Opening, it underestimates the associ- Therefore, changes in the ocean temperature in the ated heat transport, as shown in the CIOM simulation. Barents Sea depend on the heat balance among lateral It is noteworthy to point out that CIOM has a rea- ocean heat transport, solar radiation, and surface heat flux sonable simulation of the ocean response to atmospheric (Sandø et al. 2010; Smedsrud et al. 2010). Under the SRES surface forcing. Compared to observations, it can re- A1B scenario, more heat is lost to the atmosphere in the produce seasonal variations of ice cover (Fig. 11a) and northern Barents Sea before the 2040s, and the ocean sea surface temperature (Fig. 6d) in the Barents Sea. temperature tends to decrease. However, the southern Consistent with previous studies (Bengtsson et al. 2004; Barents Sea receives more heat through solar radiation Ingvaldsen et al. 2004; Skagseth et al. 2008), the simu- and ocean heat transport than is lost to the atmosphere lated water volume transport through the Barents Sea through the turbulent heat flux and longwave radiation, Opening shows a strong correlation with the storm-track and thus the ocean temperature tends to increase. density in the Barents Sea (Fig. 13). In particular, CIOM has a reasonable simulation of water volume transport d. Air–sea interactions through the Barents Sea Opening and ice concentration The changes in solar radiation and surface heat flux in September. Therefore, CIOM can be a useful tool to (Fig. 5) are mainly related to the loss of sea ice in the simulate the ocean response to the changes in atmo- Barents Sea. Because of the increases in surface air spheric surface forcing under the SRES A1B scenario temperature in the Barents Sea and the lateral heat (Long and Perrie 2013, 2015). transport (Fig. 5), there is a decreasing linear trend in Under the SRES A1B scenario, the overestimated ice the ice cover in the Barents Sea (Smedsrud et al. 2013; concentration in the southeastern and central Barents Sandø et al. 2014; Figs. 3b and 11). For example, the Sea can cause overestimates in ice loss and changes in northern Barents Sea is mostly covered with sea ice in surface solar radiation and turbulent heat flux. Since the November in the 2000s but is largely ice free in the 2090s net effect of surface solar radiation and surface heat flux (Fig. 17), and the total ice cover decreases from about is heat loss from the ocean (Fig. 5), the overestimated ice 2 3 106 to about 1 3 106 km2 in November (Fig. 11b). loss in the southeastern and central Barents Sea may Furthermore, the loss in sea ice significantly reduces cause overestimates in the net heat loss and un- surface albedo and increases the solar radiation ab- derestimates in the temperature increase in the southern sorbed by the ocean (Fig. 5), but increases the ocean Barents Sea. In addition, temperature changes near the heat loss through the turbulent heat fluxes and longwave bottom are mainly located near the Norwegian coast radiation in the Barents Sea (Fig. 5). (Fig. 15) where there is no significant sea ice presence (Figs. 2 and 3). Indeed, both CIOM simulations (Fig. 16) and previous studies (Sandø et al. 2014) show increased 5. Discussion sea surface temperatures in the southern Barents Sea. The CIOM simulations for the present climate have In this study, the Barents Sea is divided into the been discussed in detail in section 3. Overall, CIOM northern Barents Sea (box A in Fig. 1b) and the

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FIG. 14. Annual ocean temperature (8C) at 80 m in 1980–99 simulated by CIOM, and annual ocean temperature differences, relative to the annual ocean temperature in 1980–99. southern Barents Sea (box B in Fig. 1b), based on the temperature averaged over the subdomains in Fig. 18c average observed ice edge in March for the present cli- are similar to those shown in Fig. 9, and the correlation mate (Fig. 3a). To understand the sensitivity of our re- coefficients are 0.98 for box A and 0.81 for box B. For sults to the definition of these two areas, boxes A and B example, the temperature averaged over box A de- (Fig. 1b), the northern Barents Sea is extended south- creases from 20.28C in the 1990s to 20.68C in the 2030s, ward so that it includes most of the central Barents and no significant change can be seen after the 2040s. Sea (Fig. 18c). The resulting time series of ocean However, the temperature averaged over box B

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FIG. 15. As in Fig. 14, but at 150 m. gradually increases from about 08C in the 1980s to about observations (Rayner et al. 2003; Skagseth et al. 2008; 1.58C in the 2090s. Smedsrud et al. 2010; Rudels et al. 2013), the CIOM sim- ulations can capture the observed seasonal variations of the sea ice cover in the Barents Sea as well as the observed 6. Conclusions magnitudes of water volume through the Barents Sea A coupled ice–ocean model (CIOM) is implemented in Opening. Over the present climate period (1980–2009), the Arctic Ocean to simulate the impacts of climate change both the CIOM simulation and observations suggest a on the ocean temperature in the Barents Sea. Compared to positive trend in the Atlantic water volume and associated

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FIG. 16. As in Fig. 14, but at the surface. heat transports through the Barents Sea Opening, because CIOM simulations, with overestimates in the ice concen- of enhanced storm-track density in the region. However, tration and underestimates in the ocean temperature in the most of the heat from the Barents Sea Opening is lost in southern Barents Sea. Moreover, although CIOM can the southern Barents Sea through the air–sea interactions, reproduce the water volume transport through the Barents whereas the surface heat flux in the northern Barents Sea is Sea Opening, it underestimates the associated the heat relatively weak, as suggested in the observations. There- transport. Therefore, the conclusions from this study are fore, CIOM is capable of simulating oceanic responses to more qualitative rather than quantitative. the changes in atmospheric surface forcing. It is notewor- We investigated the future changes in ocean temper- thy to point out that there are significant biases in the ature through the heat balance among the lateral heat

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FIG. 17. Ice concentrations in November.

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cover in the Barents Sea. While the reduced albedo asso- ciated with the ice loss significantly increases the solar ra- diation absorbed by the ocean, the ice loss increases the ocean heat loss through the enhanced turbulent heat fluxes and longwave radiation. In addition, there is an increasing trend in the lateral heat transport into the Barents Sea through the Barents Sea Opening during the period from the 1980s to the 2020s, which stabilizes thereafter. The changes of the ocean temperature in the southern Barents Sea show a different pattern from that in the northern Barents Sea. In the southern Barents Sea, the average ocean temperature tends to increase under the SRES A1B scenario, because of the increased lateral heat transport and solar radiation. Although there is an increase in the heat loss through the turbulent heat flux, the net impacts of the heat balance tend to increase the ocean temperature. However, in the northern Barents Sea, the heat loss through the turbu- lent heat flux and longwave radiation is dominant from about the 1980s to the 2030s, and the average ocean temperature decreases from about 20.28C in the 2010s to about 20.68C in the 2040s, but stabilizes thereafter. In addition, the changes in the arctic storm activity play an important role in the increased lateral heat transport through the Barents Sea Opening. The results in this study are obtained from one- member simulation, and there are still some significant uncertainties. As an example, although both the CIOM simulations and previous studies suggest reduced ice cover in the northern Barents Sea and increased ocean temperature in the southern Barents Sea (Sandø et al. 2014), the changes in the ocean temperature in the northern Barents Sea are still uncertain (Smedsrud et al. 2013; Sandø et al. 2014).

Acknowledgments. Support for this research comes from the Department of Fisheries and Oceans of Canada Aquatic Climate Change Adaptation Service Program (ACCASP) initiative and Canada’s Office of Energy Research and Development and the Office of Naval Research (Grant N00014-15-1-2611). We also acknowledge helpful discussions and comments by col- leagues at FAMOS meetings at WHOI.

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