Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model

Transcription

1 Journal of Oceanography, Vol. 57, pp. 207 to 234, 2001 Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model XIANGDONG ZHANG 1 * and JING ZHANG 2 1 Frontier Research System for Global Change, International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775, U.S.A.; and Chinese Academy of Meteorological Sciences, Beijing , P.R. China 2 Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, U.S.A. (Received 6 June 2000; in revised form 10 October 2000; accepted 14 November 2000) The Arctic Mediterranean is important for climate studies because of its unique thermodynamic characteristics and its potential role in freshwater export, which would influences air-sea and ice-sea interactions and may change the North Atlantic thermohaline circulation. It is difficult to obtain consistent and complete estimates of heat and freshwater budgets due to sparse observation. In this paper, we use a coupled Arctic ocean/sea-ice model with NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data, longterm gauged river runoff data, precipitation data and estimates of volume transports to examine heat and freshwater budgets and pathways in dynamically and thermodynamically consistence. The model implements Neptune effect, flux-corrected-transport algorithm and more sophisticated treatments of heat and freshwater fluxes. Uncertainties and deficiencies in the modeling were also evaluated. Results indicate that the Arctic Ocean is provided heat mainly from the Fram Strait branch of Atlantic water at about 46 TW, which is within the range in literature. The Barents Sea branch carries about 43 TW of net heat entering the Barents Sea, but only 2 TW of net heat enters the Arctic Ocean. The Atlantic water is significantly modified in the Barents Sea. About 39 TW of heat is lost, which is consistent with the range of estimates by Simonsen and Haugan (1996). The model suggests 79,422 km 3 of freshwater storage mainly distributing the Canada Basin, the Beaufort Sea and the Eurasian coast, which is in a good agreement with estimate by Aagaard and Carmack (1989). Freshwater origins from river runoff, precipitation and the Bering Strait throughflow. Liquid freshwater mainly exports via the Canadian Archipelago and Fram Strait at the rates of 3100 km 3 /yr and 1400 km 3 /yr. Sea-ice is dominantly transported through Fram Strait with 1923 km 3 /yr. Model discrepancies exist and climate drift is clear, which require comprehensive physical treatments of mixing processes and dense water processes in the model. Keywords: Heat and freshwater, budget and pathways, Arctic ocean, sea ice, coupled model. 1. Introduction Worthington (1970) refers to the area including the Arctic Ocean and the Nordic Seas as the Arctic Mediterranean (AM). Understanding and modeling climate state in this area is important for two reasons. First, thermodynamic characteristics are unique: sea-ice is highly reflective, reducing the solar radiation absorbed; albedo anomaly may cause atmospheric circulation changes and sea-ice/albedo feedback amplifies anthropogenic effects; and the AM is a heat source for the atmosphere, modu- * Corresponding author. xdz@iarc.uaf.edu Copyright The Oceanographic Society of Japan. lated by sea-ice cover. Second, the AM is a key linkage of freshwater (FW) transport over the globe, which has implications for thermohaline circulation (THC) variation and is associated with decadal or interdecadal climate variability. In this paper we examine thermodynamics and FW in a coupled Arctic ocean/sea-ice model and make comparison with literature, understanding physics and model deficiencies while analyzing overall budgets and pathways. The domain for analysis extends from Norway and Fram Strait to the Bering Strait. We further divide this domain into two parts: the Barents Sea and the Arctic Ocean, the latter including the Kara, Laptev and East Siberian Seas (see Fig. 1). 207

2 Fig. 1. Bathymetry. A H represent each vertical section for calculation of heat and freshwater budgets. Efforts to evaluate an overall heat budgets for the AM began with Mosby (1962) and have been pursued in subsequent studies (Vowinkel and Orvig, 1970; Aagaard and Greisman, 1975; Rudels, 1987; Hopkins, 1991; Simonsen and Haugan, 1996). Broadly, the AM gains heat mainly by oceanic transports from the Atlantic Ocean and the Pacific Ocean through the Greenland-Iceland-Norwegian Sea (GIN Sea) and the Bering Strait and loses heat to atmosphere and sea-ice. However, estimates vary widely, ranging from 3.8 TW to 11.4 TW through the Bering Strait (1 TW = W and reference temperature = 0.1 C; positive value means the Arctic Ocean gains heat); 0.1 TW to 7.8 TW through the Canadian Archipelago; 17.6 TW to 68.4 TW for inflow and 1.2 TW to 14.3 TW for outflow through Fram Strait. Based on these estimates, Simonsen and Haugan (1996) used their preferred scheme and estimated heat loss of 222 TW over the AM, with 86 TW and 136 TW occurring over the Arctic Ocean and the Barents Sea. Nakamura and Oort (1988) estimated the atmospheric heat transport across 70 N and radiative losses based on satellite observations. They got 37 TW of total heat loss north of 70 N. If there is no heat storage in surface in annual mean, this value should be balanced by oceanic transports. Large discrepancies exist. Analyses of FW present different challenges. Approximately 10% of runoff from the world s rivers flows into the AM (Arctic System Science, 1990). Precipitation is estimated at nearly half of its riverine input from the poleward atmospheric moisture flux convergence (Walsh et al., 1994). Relative fresh surface water, with a salinity of about 32.5 ppt, is carried from the Pacific to the Arctic via the Bering Strait. Overall, the AM receives FW from these sources and exports it through channels 208 X. Zhang and J. Zhang

3 in the Canadian Archipelago and by exchanges with the Atlantic Ocean. Sea-ice is other source of FW, with area varying from a minimum of km 2 in September to km 2 in March in an average thickness of 3 5 m over the Arctic Ocean (Barry et al., 1993). Aagaard and Carmack (1989) estimated FW budgets based on estimates of salinity and water volume transports in the historical literature. Steele et al. (1996) tried to estimate FW budgets with their simple model. Gerdes and Schauer (1997) also made estimation between the Arctic Ocean, the Barents Sea and the Atlantic Ocean using their coupled ocean/sea-ice model. Similar to heat budgets, uncertainties attend each of the terms in overall FW budgets (Aagaard and Carmack, 1989; Carmack, 2000). Uncertainty about overall heat and FW budgets and pathways in the AM is problematic not only for Arctic climate but globally. Sea-ice/snow cover, contrasting strong absorption of solar radiation by open water, has global impact on surface energy budgets. Export of FW is believed to influence the strength of Atlantic THC (Manabe and Stouffer, 1988; Walsh and Chapman, 1990; Aagaard and Carmack, 1994; Griffies and Bryan, 1997). A localized anomaly in FW export, the Great Salinity Anomaly (GSA), was observed (Dickson et al., 1988; Aagaard and Carmack, 1989; Maslanik et al., 1991; Hakkinen, 1993). Recent coupled ocean-atmosphere model (CGCM) produced a GSA-like oscillation with a time scale about year in the Greenland Sea (Delworth et al., 1997). Enhanced transport of FW from the Arctic may weaken the North Atlantic THC. The study of Griffies and Bryan (1997) also indicates that anomalous FW transport from the Arctic Ocean is one of main physical mechanisms affecting the North Atlantic multidecadal climate variability. All of these demonstrate importance in better understanding Arctic heat and FW budgets and pathways. However, estimates of heat and FW budgets and pathways in the state-of-the-art global coupled models are not satisfactory due to climate drift and deficiencies, particularly in the Arctic Ocean where serious model-observation difference happens (Gent et al., 1998). We employ a coupled Arctic ocean/sea-ice model. The advantages of our model are that the almost all real terms of external heat and freshwater fluxes are explicitly solved with recently recommended parameterizations and applied to the modeling; all internal heat and freshwater processes are explicitly diagnosed; the synchronous coupling of ocean and sea-ice is implemented; the recently suggested fluxcorrected-transport algorithm and Neptune effect are enabled and the long-term integrations of 120 years have been carried out. These allow detailed inspection of budgets and pathways and analyses of annual cycle with dynamical and thermodynamical consistency and help to understand performance of treatments of model physics. Discrepancies emerge, in part from uncertain data and uncertain methods of flux calculations, and in part from deficient model representations that we seek to identify. 2. Model Description We developed a coupled Arctic ocean/sea-ice model based on the GFDL/NOAA MOM2.0 (Pacanowski, 1995). The sea-ice model follows Hibler (1979) and Parkinson and Washington (1979) with snow treatment after Oberhuber et al. (1993). Recognizing the importance of the path of Atlantic inflow into the Arctic Ocean and Barents Sea, the parameterization of Neptune effect (Nazarenko et al., 1998) was enabled. The weakly diffusive, monotonic advection algorithm (flux-correctedtransport, FCT) is also used (Gerdes et al., 1991). We adopted model grids from Nazarenko et al. (1998). The horizontal resolution is 55 km. There are 29 levels vertically, ranging from ocean surface down to 4350 m at the bottom with thickness from 10 m near the surface to 290 m in the deep ocean. They emphasized that their model was designed for studying Arctic circulation and contaminants. In order for our model to be suitable for climate studies, sea-ice and ocean models are coupled synchronously to assure heat and freshwater conserved. More sophisticated parameterizations of heat and freshwater fluxes are implemented. A summary of flux parameterizations is given in Subsection 2.1. In the present study we apply comparatively weaker restoring terms as measures of model and data deficiencies, except for full fluxes as calculated from parameterizations. The forcing data are described in Subsection Flux schemes and parameters Over many years of research, a number of methods for estimating fluxes among ocean, sea-ice and atmosphere have been proposed. Simonsen and Haugan (1996), for example, intercompare results from different parameterizations. It is alarming that overall budgets are sensitive to differences among these parameterizations. In the present paper, exhaustive flux scheme intercomparisons were not carried out. Here we list the parameterizations used for the results, having attempted to choose parameterizations that are representative and may be recommended from previous studies. Surface heat fluxes contain downwelling shortwave and longwave radiation, outgoing longwave radiation, sensible and latent heat fluxes, turbulent heat flux at ocean and sea-ice interface, penetration of shortwave radiation through bare sea-ice and remaining heat flux after seaice melts. Presently, the last three terms are combined as the oceanic heat flux to measure heat flux between ocean and sea-ice. Two parameterization schemes are adopted for downwelling radiation, as recommended by Key et al. Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 209

4 (1996) for Arctic sea-ice modeling. Recently, Hanesiak et al. (2000) also verified that these two schemes are preferred for sea-ice modeling with data from 1998 International North Water (NOW) Polynya project. Downwelling shortwave radiation under clear sky is given by (Shine, 1984): SW S0 cos Z clr = cos Z + ( cos Z) 10 e The parameterization for estimating the downwelling shortwave radiation under cloudy condition is: SW 05. ( cos Z) cos Z cld = ατ 2 ( ) () 1 ( 2) So, the total downwelling shortwave radiation is expressed as: ( ) + () SW = 1 c SW csw 3 all clr cld where S 0 is the solar constant; Z the solar zenith angle; e the water vapor pressure at surface; τ the cloud optical depth; α the surface albedo; c the fractional cloud cover and taken from Parkinson and Washington (1979). Downwelling longwave radiation under clear sky condition is (Efimova, 1961): LW = σt e. 4 clr a ( ) ( ) Jacobs (1978) gave total downwelling longwave radiation as: LW = LW c 5 all clr ( ) ( ) where σ is the Stefan-Boltzmann constant; T a the 2 m air temperature. Sensible and latent heat fluxes are calculated from the bulk aerodynamic formulae (Large and Pond, 1981, 1982): r H = ρ c C V T T sen a p H a a sfc r H = ρ LC V q q lat a E a a sfc ( ) ( 6) ( ) ( 7) where ρ a is the air density; c p the air specific heat; L the latent heat of vaporization or sublimation; r V a the 10 m wind velocity; T sfc the surface temperature of sea-ice or Fig. 2. (a) Sea-ice thickness (m) and superimposed velocity (cm/s); (b) heat content ( Cm) and (c) freshwater storage (m) within uppermost 210 m and superimposed vertical averaged velocity (cm/s). 210 X. Zhang and J. Zhang

5 snow or first level ocean temperature T o from model; q a the 2 m specific humidity; q sfc the surface specific humidity derived from T sfc ; C H and C E are the sensible and latent heat transfer coefficients, respectively. During spring and summer, relatively warm air may appear and be advected over the cold ocean surface. Using a constant heat exchange coefficient means a larger heat flux into the ocean than if a stability dependent coefficient is applied (Simonsen and Haugan, 1996). Therefore, in our model, C H and C E are corrected for atmospheric stability (Large and Pond, 1981, 1982). An approximate constant coefficient is taken as over sea-ice/snow following Maykut (1977). Turbulent heat flux at ocean/sea-ice interface, H w, is parameterized as (Ebert and Curry, 1993): H = ρ c C T T 8 w o po t o f ( ) () where ρ o is the density of ocean water; c po the ocean specific heat; C t the bulk transfer coefficient, taken as m/s; and T f the freezing temperature. Penetration of Shortwave radiation through bare seaice is given by (Grenfell and Maykut, 1977): SW = SW 10. e 9 p h ( i ) ( ) where SW 0 is the shortwave radiation absorbed at sea-ice surface; and h i the sea-ice thickness. Surface FW fluxes consist of precipitation, evaporation, river runoff, snow melt and sea-ice growth or melt. They are treated as negative salt fluxes when FW enters the ocean and positive salt fluxes when FW leaves the ocean. In conversion of FW flux to salt flux, the constant reference salinity 34.8 ppt (Aagaard and Carmack, 1989; Steele et al., 1996) is used over the total domain, which keeps salt conserved over global. When calculating FW flux resulting from the sea-ice growth or melt, it is assumed that the salinity of sea-ice is 4.0 ppt (Fichefet and Maqueda, 1997). Over sea-ice, snowfall is parameterized from precipitation, following Weatherly and Walsh (1996): P s 10. Ta < 5 C = 10. ( Ta + 5 C) C Ta 5 C 00. Ta < 5 C ( 10) where P s is the fraction of precipitation falling as snow. Snowfall contributes to snow growth over sea-ice. Considering stable stratification of the Arctic Ocean, ocean horizontal and vertical viscosity coefficients are taken as cm 2 /s and 8.0 cm 2 /s, respectively. The Fig. 2. (continued). Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 211

6 horizontal and vertical diffusivity coefficients are set to be zero due to the FCT algorithm, in which implicit diffusion has been taken into account. 2.2 Forcing data The climate monthly windstress, 2 m air temperature, 2 m air specific humidity, surface pressure and 10 m windspeed are prepared from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data from (Kalnay et al., 1996). Precipitation is constructed from the Corrected Monthly Precipitation Dataset (Legates and Willmott, 1990) and re-interpolation is made by the Cressman method to remove unreasonable values north of Spitzbergen, caused by different data sources when the precipitation dataset was compiled (Legates, personal communication, 1998). Hibler and Bryan (1987) and Zhang et al. (1998) used climate river runoff data from eight major rivers. In our modeling, thirteen major rivers along the Eurasian and the North American continents are included, as shown in Fig. 1. The river runoff data is from long-term observations (from 1950s to 1980s) supplied by NSIDC and Becker (1995). Usually, climate drift could not be completely prohibited in the state-of-the-art coupled models. To limit drift and measure model fidelity, we include surface level restoring of temperature and salinity on time scale of 50 days to Levitus (1982) data. As Zhang et al. (1998) summarized, other models used 11 or 30 days for their surface level restoring. The restoring time scale is longer than others, putting weaker constraint on modeling. Diagnosed heat flux and FW flux from restoring terms help to understand uncertainties in modeling. As for effects of restoring conditions on Arctic ocean/sea-ice modeling, see discussions by Zhang et al. (1998). Inflowing water properties from the Bering Strait and portions of the GIN Sea are given from Levitus (1982) data. Volume transports through open boundaries are from Nazarenko et al. (1998), with inflow at the Bering Strait fixed at 0.85 Sv (with no annual cycle) after Coachman and Aagaard (1988) who estimated long term mean 0.85 Sv. Outflow through the Canadian Archipelago is set at 1.7 Sv after Fissel et al. (1988). Volume conservation for this rigid-lid model implies net GIN Sea inflow of 0.85 Sv with spatial distribution. The model was integrated over 120 years with the asynchronous strategy after Bryan (1984) under representing annual cycle of forcing from initial temperature and salinity from Levitus (1982) without initial sea-ice. The model achieved an approximately stable state in its sea-ice and upper ocean properties. Last 5 years mean is used as model climate. Annual mean sea-ice thickness and motion, upper ocean heat content and FW storage with composited volume averaged velocity are shown in Figs. 2(a), (b) and (c), where heat content and FW storage are defined by Fig. 2. (continued). 212 X. Zhang and J. Zhang

7 and HTc = T Tref dz 11 FW s Depth ( ) ( ) Sref S = dz 12 Depth S ref ( ) where T and T ref are the ocean temperature and reference temperature; S and S ref the ocean salinity and reference salinity, respectively. Because seawater density and specific heat are constant, they are ignored in (11). The integral is made from surface to 210 m, where the bottom of halocline is. 3. Heat Budgets and Pathways 3.1 Diagnoses We have analyzed the approximately cyclo-stationary regime from the last 5-year modeling, treating separately the Arctic Ocean and the Barents Sea (Fig. 1) while treating separately the sea-ice and liquid ocean in each domain. In Fig. 3, the annual cycle of net surface heat fluxes over the liquid ocean separately for the Arctic Ocean and the Barents Sea domains is shown. Radiation is a dominant term in heat budgets. In Figs. 3(a) and (b), over the Arctic Ocean and the Barents Sea, net downwelling longwave radiation arrives at about 700 TW and 350 TW; outgoing longwave radiation reaches about 750 TW and 400 TW, respectively. The amplitude of net downwelling longwave radiation is larger than that of net downwelling shortwave radiation throughout the year. The radiation into the Arctic Ocean and the Barents Sea is much influenced by sea-ice and snow cover. The maxima of net downwelling shortwave and longwave radiation into ocean lags those of downwelling radiation from forcing due to high percentage of sea-ice and snow cover in winter and spring (not shown). For the Arctic Ocean, net downwelling shortwave radiation, longwave radiation and outgoing longwave radiation reach their maxima in July and August; but for the Barents Sea, the maximum downwelling shortwave radiation occurs in July while downwelling and outgoing longwave radiation in September. Because the Barents Sea is only partly covered by sea-ice and snow even during winter, longwave radiation reaches the ocean throughout the year. For both the Arctic Ocean and the Barents Sea, the ocean gains heat from downwelling radiations, and the outgoing longwave radiation makes the ocean lose most of its heat gain. Sensible and latent heat fluxes are much less than each term of radiations but they sometimes reach almost the same order as net total radiation. Sensible and latent heat fluxes always make ocean cold, as shown in Figs. 3(c) and (d). In the Arctic Ocean, sensible and latent heat fluxes are much affected by interactions of atmosphere/ sea-ice/ocean. Amplitude of air temperature is larger than that of ocean surface temperature throughout the year (not shown). In spring, sea-ice cover is beginning to decrease and sensible heat flux between ocean and atmosphere appears and becomes large. From March to May, ocean surface temperature is higher than air temperature so that heat loss by sensible heat flux increases and reaches its one extreme value in May. With air temperature increases rapidly and approaches ocean surface temperature from May to June, sensible heat flux decreases. From June to August, air temperature remains near 0 C but ocean surface temperature still increases due to radiation and lateral oceanic heat transports, so that the sensible heat flux begins to increase again. During August to September, air temperature decreases rapidly and becomes much lower than ocean surface temperature. Therefore the sensible heat flux increases rapidly and reaches its maximum in September. A similar process accounts for variation of latent heat flux in the Arctic Ocean throughout the year. In wintertime, the sensible and latent heat fluxes between ocean and atmosphere are much reduced due to development of sea-ice cover in the Arctic Ocean. Of interest, in the Barents Sea latent heat flux is larger than sensible heat flux from summer to fall, with strong evaporation. This means latent heat flux may have a greater contribution to the Atlantic water modification in the Barents Sea. Oceanic heat flux measures heat exchange between ocean and sea-ice. Its annual cycle over the Arctic Ocean is much different from that over the Barents Sea, as shown in Fig. 3. Over the Arctic Ocean (Fig. 3(e)), oceanic heat flux reaches a minimum in April because the ocean is almost covered by sea-ice and ocean surface temperature approaches freezing temperature. From April through July, the sea-ice cover reduces and the increased ocean surface temperature causes larger oceanic heat flux. From July through September, oceanic heat flux decreases again due to the smaller sea-ice cover. After September the oceanic heat flux increases as the sea-ice cover increases while there is a large difference between ocean surface temperature and freezing temperature. In the Barents Sea, as depicted in Fig. 3(f), from April to September the oceanic heat flux is small due to the small area of sea-ice cover; in winter, oceanic heat flux increases as the seaice cover develops. The Barents Sea is the region where marginal zone of sea-ice locates and ocean surface temperature is high, so oceanic heat flux is relatively large compared with that in the Arctic Ocean in terms of their sea-ice area. Table 1 summarizes annual mean surface forcing terms for the Arctic Ocean and Barents Sea. Over both domains, radiative forcing of open water is a net heating Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 213

8 214 X. Zhang and J. Zhang Fig. 3. Annual cycle of radiation over (a) the Arctic Ocean and (b) the Barents Sea; annual cycle of sensible and latent heat fluxes over (c) the Arctic Ocean and (d) the Barents Sea; oceanic heat fluxes over (e) the Arctic Ocean and (f) the Barents Sea.

9 Table 1. Annual mean surface heat budgets of the Arctic Ocean and the Barents Sea domains (unit: TW. DWN SWR: net downwelling shortwave radiation; DWN LWR: net downwelling longwave radiation; OUT LWR: outgoing longwave radiation; SEN FLX: sensible heat flux; LAT FLX: latent heat flux; O/IC FLX: ocean/sea-ice heat transfer; RES FLX: heat flux caused by restoring condition). of 70 TW and 41 TW, respectively. For the region that is covered by seasonal sea-ice in winter, ocean water gains radiation and becomes warm in summer; during winter, ocean is covered by sea-ice and does not lose radiative heat directly, radiative heat loss lets sea-ice forming and reduces sea-ice temperature. Oceanic heat flux makes seaice melt and ocean lose heat. Meanwhile, about 13 TW and 38 TW of heat over the Arctic Ocean and the Barents Sea are lost to atmosphere by sensible and latent heat fluxes. The surface level restoring-to-levitus (1982) terms provide an annual mean heating of the Arctic Ocean by 34 TW and an annual mean loss from the Barents Sea of 20 TW. Overall, the surface energy budgets plus restoring term lead to annual mean heat losses of 19 TW and 39 TW from the Arctic Ocean and the Barents Sea, respectively. These values are much smaller than estimates of 86 TW and 136 TW by Simonsen and Haugan (1996) with their preferred parameterization. However, based on estimates of volume transport and temperature in literature, Simonsen and Haugan (1996) suggested that the surface heat loss from the Barents Sea is only within TW. Our estimate of overall heat loss from the Barents Sea with the model is in good accordance within this range. It is smaller than the estimate of 74 TW by Gerdes and Schauer (1997) in their modeling. Surface heat losses are mainly compensated by lateral ocean transports: HT = dl c T T u dz t ( ) ( ) L ρ Depth o po ref n 13 where u n is the ocean velocity normal to vertical sections. Annual cycles of net oceanic heat transport through the nine vertical sections (Fig. 1) are shown in Fig. 4. The Arctic Ocean gains heat by throughflow via the Bering Strait and the western Canadian Archipelago relative to the 0.1 C reference temperature. Through the Bering Strait (passage A), large heat transport into the Arctic Ocean takes place from summer to fall with the maxima appearing in September (Fig. 4(a)). The heat transports into the Arctic Ocean via the western passage of Canadian Archipelago (passage B) and out of the Arctic Ocean via eastern passage (passage C) (Figs. 4(b) and (c)). Atlantic water known to enter the Arctic Ocean has two main pathways: part of the water goes through Fram Strait and the remainder takes a route through the Barents Sea (Gerdes and Schauer, 1997). Fram Strait (passage D) is the most important for oceanic heat transport. Heat transport into the Arctic Ocean is much greater than that out of the Arctic Ocean, yielding a net heating of about 15 TW each month throughout the year (Fig. 4(d)). In the Arctic domain, the Fram Strait branch is covered by a layer of light Arctic water that shields the Atlantic water from further contact with the atmosphere (Carmack, 1990). The main passage of ocean heat transport between the Arctic Ocean and the Barents Sea is the passage between the Franz Josef Land and the Novaya Zemlya (passage F). The annual cycle of heat transport through this passage is depicted in Fig. 4(e). The maximum value occurs during late summer and autumn. As depicted in Fig. 4(f), the Barents Sea gets a large amount of heat from the GIN Sea through the passage between the Spitzbergen and Norway (passage H). Annual means of these heat transports are listed in Table 2 and are compared with previously published estimates listed in Table 3. Our estimate through the Bering Strait is within the range of the former estimates. But estimates through the Canadian Archipelago and Fram Strait are different. The estimate through the Bering Strait is about 7.7 TW, larger than the estimates of Vowinkel and Orvig (1970), Aagaard and Greisman (1975), Hopkins (1991) but smaller than those of Mosby (1962), and Rudels (1987). In their calculations, Mosby (1962), Aagaard and Greisman (1975) and Hopkins (1991) assumed 1.2 Sv and 1.5 Sv of volume transport, larger than more recent observation (Coachman and Aagaard, 1988; Roach et al., 1995). The values used by Vowinkel and Orvig (1970) and Rudels (1987) are 1.0 Sv and 0.8 Sv, which are close to ours in the simulation, but their averaged temperature are 0.9 C and 3.3 C caused much different heat transports. The estimate via the Canadian Archipelago in the modeling indicates that the Arctic Ocean loses heat by transports about 1.3 TW in annual mean. This is different from former estimates of heat gain from 0.1 TW to 7.8 TW. In order to estimate, Vowinkel and Orvig (1970) used Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 215

10 216 X. Zhang and J. Zhang Fig. 4. Annual cycle of ocean heat transport through (a) the Bering Strait; (b) the western and (c) the eastern passage of the Canadian Archipelago; (d) Fram Strait; (e) the passage between the Franz Josef Land and the Novaya Zemlya; and (f) the passage between the Spitsbergen and Norway.

11 Table 2. Annual mean lateral heat budgets into the Arctic Ocean and the Barents Sea domains (reference temperature = 0.1 C, unit: TW). Net lateral budgets: 22.9 (Arctic Ocean domain); 40.5 (Barents Sea domain). *Positive toward the Arctic Ocean. Table 3. Estimates of annual mean lateral heat budgets into the Arctic Ocean and the Barents Sea domains (reference temperature = 0.1 C, unit: TW). Bering Strait Canadian Archipelago Fram Strait Barents Sea* Mosby (1962) In Out Total Vowinkel and Orvig (1970) In Out Total Aagaard and Greisman (1975) In Out Total Rudels (1987) In Out Total Hopkins (1991) In Out Total *Heat exchange between the Arctic Ocean and the Barents Sea, positive toward the Arctic Ocean domain. water volume transport 1.0 Sv with temperature C; Aagaard and Greisman (1975), Hopkins (1991) used 2.1 Sv with 0.7 C; Mosby (1962) used 1.1 Sv with 1.8 C; and Rudels (1987) used 1.0 Sv with 0.9 C, respectively. These are different by an order of two. In our simulation, the volume transport through the Canadian Archipelago is prescribed as 1.7 Sv, corresponding to more recent estimate (Fissel et al., 1988) with temperature distribution obtained from the model simulation. The largest heat exchange occurs through Fram Strait. A major heat gain of the Arctic Ocean is from the West Spitzbergen Current (WSC). In the model, about 46 TW heat enters the Arctic Ocean through Fram Strait. It is smaller than the estimates by Aagaard and Greisman (1975) and Hopkins (1991) but larger than by Mosby (1962), Vowinkel and Orvig (1970) and Rudels (1987). There is about 32 TW of heat loss due to outflows, much larger than the former estimates. The net heat budget through Fram Strait in the model is much less than the estimates by Aagaard and Greisman (1975), Hopkins Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 217

12 (1991), Mosby (1962) and Vowinkel and Orvig (1970) but close to the estimate by Rudels (1987). Simonsen and Haugan (1996) argued that estimates by Aagaard and Greisman (1975) and Hopkins (1991) seem too large and they attributed this to their assumed too large transport, compared with the currently preferred water volume transport of Sv by WSC (Jonsson and Foldvik, 1992; Rudels et al., 1994). Aagaard and Greisman (1975) assumed 7.1 Sv volume transport into and out of the Arctic Ocean with average temperature of 2.2 C and 0.1 C, respectively. Hopkins (1991) reviewed estimates prior to 1985 and obtained an inflow of 7.2 Sv at 1.8 C and an outflow of 7.6 Sv at 0.2 C. In our simulation, about 5.1 Sv and 5.6 Sv water transports into and out of the Arctic Ocean. A net outflow of 0.5 Sv through Fram Strait in the modeling is pretty close to the newest estimate of 0.4 Sv by Hopkins (1991). According to Table 3, although estimates of heat transports by WSC into the Arctic Ocean by Mosby (1962) and Vowinkel and Orvig (1970) are much less than those by Aagaard and Greisman (1975) and Hopkins (1991), the Arctic Ocean obtains heat from outflow of the Arctic cold water, other than losing heat by outflow of warm water, relative to the reference temperature in their estimates. So, their net heat transports through Fram Strait are not too small. At present there is a controversial issue as to whether the Arctic Ocean loses heat by outflow of warm water or gets heat by cold Arctic water outflow through Fram Strait. Modeling results support the former point. Furthermore, as for heat transport through Fram Strait, there are uncertainties affecting the estimates by observations. As argued by Simonsen and Haugan (1996), Mosby (1962), Vowinkel and Orvig (1970), and Aagaard and Greisman (1975) assumed inflowing water is balanced by outflowing water through Fram Strait, whereas Hopkins (1991) and Rudels (1987) concluded a net outflow from the Arctic Ocean; on the other hand, Mosby (1962) and Hopkins (1991) included an inflow of deep water produced within the Greenland Sea gyre in their calculation while Aagaard and Greisman (1975) argued that the net deep flow is small and does not have significant effect on the budgets. Because estimates of volume transports and water temperature vary each year, these uncertainties affect one in getting a reliable estimate of climate mean heat transport. In the modeling, the forcing data is based on multidecadal mean. Long-term modeling results may give an estimate of modeled climate mean. By the way, the estimate in this study is made by the integration of surface to bottom water so that it includes contributions of both upper and deep flows. Also as shown in Table 2, the Barents Sea gains an annual mean heat of 51 TW from the GIN Sea inflow and only loses about 10 TW by outflow returning to the GIN Sea. That is much less than the heat loss by outflows from Fram Strait. So, there is about 43 TW net heat gain for the Barents Sea through the passage between Spitzbergen and Norway. The major branch of heat transport from the Barents Sea to the Arctic Ocean is the flow through the passage F with 6 TW of net annual mean heat entering the Arctic Ocean. About 4.4 TW of heat from the Arctic Ocean through passage E originates from the WSC. Comparing heat budget terms of the Barents Sea, in spite of more net heat entering the Barents Sea from the GIN Sea, only a small part of heat from the Barents Sea enters the Arctic Ocean through the passage F. Atlantic water loses most of its heat and is strongly modified in the Barents Sea, supporting a speculation before (Hakkinen and Cavalieri, 1989; Gerdes and Schauer, 1997). Overall, net annual mean heat transports into the Arctic Ocean and the Barents Sea are about 23 TW and 41 TW. From the GIN Sea, the net total heat entering both the Arctic Ocean and the Barents Sea is about 57 TW. The heat import from both the GIN Sea and the Barents Sea is about 54 TW, which coincides with the range TW by Simonsen and Haugan (1996). We estimated budgets with the model and reviewed their difference from those in literature. Lateral oceanic transports and radiation supply heat to the Arctic Ocean and the Barents Sea and then heat is released to sea-ice and atmosphere to arrive at an energy balance. From this point of view, the estimates of 86 TW and 136 TW of net surface heat losses over the Arctic Ocean and the Barents Sea by Simonsen and Haugan (1996) obviously could not be balanced by oceanic heat transport with the abovementioned estimates. When they estimated surface fluxes, they used blended data from COADS, ECMWF and others and adopted the advective heat budget for the Nordic Seas as a main constraint. They applied estimate of the advective heat import to the Nordic Seas about 300 TW. Of this, TW continues to the Arctic Ocean. They also supposed that the heat transports through the Canadian Archipelago and the Bering Strait balance (from our model result and former estimates listed in Tables 2 and 3, this might not be suitable) and estimated the heat loss from the Nordic Seas to be TW. This estimate was taken as a constraint to obtain their preferred parameterizations. As they indicated, their estimate of heat loss from the Arctic Ocean with the preferred parameterization is overestimated compared with the advective estimates. In Gerdes and Schauer (1997) modeling, the model is only forced by Hellerman and Rosenstein (1983) windstress and restoring conditions to Levitus (1982) climatological winter temperature and salinity. Particularly, in their modeling, total heat transport into the Arctic Ocean and the Barents Sea is about 71 TW but about 74 TW heat is lost at the surface of the Barents Sea. They attributed this to there being a net heat loss by ocean trans- 218 X. Zhang and J. Zhang

13 port through Fram Strait (i.e., the Arctic Ocean loses heat through Fram Strait and gets heat from the atmosphere) and their model did not reach equilibrium (Gerdes, personal communication, 1998). Heat budgets and pathways in the modeling were estimated and compared with estimates in literature. However, on the other respects, the estimates with our model are still affected by modeling climate drift, even if we have applied a restoring condition. During integration, the ocean becomes warmer slowly. This means the model has not completely reached climate equilibrium. The ocean equilibrium state depends on small-scale processes that are highly parameterized in the model. It is thus not advisable to integrate the model into equilibrium because the final state would differ substantially from the observations (Gerdes and Schauer, 1997). Observations indicated equilibration times of several hundred years for the deep basin. For the Canada Basin, Macdonald et al. (1993) estimates a ventilation time of around 500 years whereas the waters of the deep Eurasian Basin are renewed on a 200-year time scale (Schlosser et al., 1995). Long-term integration is still a challenge for coupled Arctic ocean/ sea-ice model. Our model in this study has been integrated for 120 years. Comparing Tables 1 and 2, there is a net heat remainder of about 4 TW in annual mean in the Arctic domain. This amount could be accounted for by model climate drift and deficiency. This will be discussed next section. 3.2 Interpretive analyses In order to identify pathways and internal transfers of heat, we first examine the path of Atlantic Water circulation. This is seen in Fig. 5 where temperature and velocity plotted on the surface of maximum temperature are indicated. The model captures the Fram Strait and the Barents Sea branches of the Atlantic water, as shown in Fig. 5. The former moves eastward along the Nansen Basin Fig. 5. maximum temperature and vertically averaged volume transport within upper 210 m. Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 219

14 through Fram Strait and the later leaves the Barents Sea to enter the Arctic Ocean through the St. Anna Trough. Within the Barents Sea, the Atlantic water experiences strong modification and loses a large part of heat. Two branches meet with very different properties. At the confluence, the maximum temperature of the Fram Strait branch is about 2 C higher than the Barents Sea branch. The colder and denser water from the Barents Sea was demonstrated to be an important source for the Arctic Ocean deep water and lower halocline formation (Nansen, 1906; Aagaard et al., 1981; Swift et al., 1983; Midttun, 1985). The modeled characteristics of two Atlantic water branches are consistent with observations of the R/V Polarstern cruise ARK IX/4 from 6th August to 5th October 1993 and from a former modeling study (Gerdes and Schauer, 1997). Figure 5 shows higher temperature of the Atlantic water than the real world. We tried to figure out a potential cause responsible for this. The so-called Neptune effect seems help to establish cyclonic circulation at intermediate level with forcing Atlantic water going into the Arctic Ocean (Nazarenko et al., 1998). But, meantime, the Neptune velocity brings additional heat into the Arctic. The Neptune velocity is arbitrary and hard to be verified with observations. The parameter L is defined to be 4 km to characterize horizontal scale of the Neptune velocity in the Arctic Ocean Nazarenko et al. (1998). We used the same value in this modeling work. When we reduced it to half, maximum temperature decrease of the Atlantic water in the Eurasian Basin can reach up to 1.3 C. We argue about the necessity and performance of Neptune effect. The useful point of Neptune effect is that it forces the Atlantic warm and salt water to go far into the Arctic Ocean to cause a cyclonic circulation. When we examine the real world, the cyclonic circulation might attribute to dense water processes. In the Arctic Ocean, the momentum flux into the ocean is very small due to sea-ice cover. Stratification plays a dominant role in determining circulation. In the current simulations, the stratification in the Eurasian Basin is not robust, where ocean water tends to be fresher because the Atlantic signal cannot be preserved. Correct treatment of dense water spreading in the Eurasian Basin from the Barents Sea, including Atlantic signal, and adjacent shelf seas may help keep stratification and therefore produce correct cyclonic circulation under the Coriolis force. The Neptune effect does not describe these physical processes and forces the warm Atlantic water directly to go far into the Arctic Ocean while the dense water processes bring the modified (colder and denser) Atlantic water to feed the Arctic intermediate and deep water. The water properties are completely different. On the other hand, Gerdes and Schauer (1997) model is also based on the GFDL model. They got a cyclonic circulation at the Atlantic water level without Neptune effect. They attributed this to the fact that the Atlantic inflow must be vigorous enough and model must be able to preserve the density signal such that the Atlantic water can reach the Canadian Basin following the periphery of the basin to establish the cyclonic circulation at depth. We seek further insight by evaluating term balances of the thermodynamic equation integrated over three layers: 0 to 200 m, 200 to 1000 m and below 1000 m. The upper 200 m of the ocean contains surface and halocline waters where the bulk of freshwater in the Arctic Ocean lies. The bottom depth of 200 m represents an Arctic-average halocline base depth. (Steele et al., 1996). It is also roughly the maximum depth of the freshwater-containing Polar Water in the East Greenland Current, as defined by Aagaard and Coachman (1968). From 200 m to 1000 m, Atlantic layer locates (Barry et al., 1993). Stable deep water is below 1000 m. For consistence and convenience, the Barents Sea is also separated in the same way. As described in Section 2, FCT is used for tracer advection so that explicit horizontal and vertical diffusions are set to be zero. The thermodynamic equation can be written as: T = r + 1 Q V T t ρ c z o p + convection ( 14 ) where x is the zonal direction in the model grids; y the meridional direction; z the vertical direction; and Q the ocean surface heat flux, including restoring term. Table 4 displays each term of volume-averaged thermodynamic equation from the monthly mean of last five years model simulation. The total model domain, including both the Arctic Ocean and the Barents Sea from surface to bottom, gains heat from advection, i.e., lateral oceanic heat transports, and loses heat by surface heat fluxes, consistent with above results. Advective heat flux in y direction is dominant due to major heat advection occurring from the GIN Sea into the Arctic Ocean and the Barents Sea. This implies that heat input from outside is important for thermodynamics of the Arctic Ocean. For the upper and intermediate layers of the Arctic Ocean, advective heat fluxes in y direction are the largest ones, which emphasize importance of oceanic heat transports through Fram Strait. In the upper layer, advective heat fluxes in x and vertical directions are almost of the same order, both making ocean get heat. Because Atlantic water gradually sinks with its moving, heat is transported by the advection in y direction into the Arctic Ocean and then redistributed by advections in x and vertical directions. This upper layer also gets heat by convection from intermediate layer. Because of stable stratification, 220 X. Zhang and J. Zhang

15 Table 4. Annual mean regional volume averaged term of thermodynamic equation (unit: W/m 2 ) and temperature (unit: C). V r T Convection Surface flux (T) t T u(t) x v(t) y w(t) z Total Domain Upper Arctic Middle Arctic Lower Arctic Upper Barents Lower Barents contribution from convection is relatively smaller. In the intermediate layer, advection in x makes ocean lose heat that implies this term limits warm water spread all the Arctic Ocean from the Nansen Basin where the warmest Atlantic water accumulates due to inflow of the Atlantic water. The Atlantic layer loses heat by vertical advection and convection. The Arctic deep ocean obtains heat from both horizontal advections and convection but loses heat through vertical advection. For the upper Barents Sea, much of the heat loss occurs at surface and main heat gain is from all the terms of advection, consistent with above budget analysis. Within this layer, convection also plays an important role and makes ocean get heat. Horizontal advections are much dominant. It is interesting that the low layer of the Barents Sea is warmer than the upper layer. The low layer of the Barents Sea loses heat to upper layer via vertical advection and convection. From Table 4, strong convection occurs in the Barents Sea. Temperature tendency results from imbalance of ocean heat transport and surface heat flux, as indicated in Table 4. The local rate of volume averaged temperature of total domain from last 5 years mean, which represents the mean climate drift during this period, is about C/yr, which accounts for the remaining heat of 4 TW in above analysis. In detail, characteristics of temperature tendency in the three layers of the Arctic Ocean are different. The local rates of volume-averaged temperature from last 5 years mean for the mixed layer and halocline, the Atlantic layer and deep layer are about 0.036, and C/yr, respectively. For the upper layer, the main source responsible for heat flux imbalance is that more advective heat enters the Arctic but less surface heat loses. As noticed in Table 1, the restoring condition supplies additional heat to the ocean under sea-ice that implies Levitus (1982) temperature is larger than freezing temperature. We acquire a negative trend of temperature occurring within the Atlantic layer, which results from imbalance between advections and convection. In fact, this negative trend is caused by the spin-up problem. When we spin-up the model from Levitus (1982) temperature and salinity with rest motion, we use explicit vertical diffusion with relatively large coefficient (0.6 cm 2 /s) to help oceanic circulation established. Meanwhile the Atlantic layer becomes much warmer. After explicit vertical diffusion is removed in this modeling integration, excess heat content is released. On the other hand, our model has not arrived at equilibrium. The deep layer gets heat from lateral oceanic transports and convection but there is no process to make ocean lose heat or balance its heat gain. This causes warmer climate drift. From the values of total domain, we can simply say the climate drift is caused by imbalance between lateral heat flux and surface heat flux. But for the deep ocean, we could not figure out a negative process to balance heat gain. Large horizontal advection might imply that inflowing deep water is too warm, as shown in Table 4, consistent with deficiency in total domain. Parameterization of mixing processes is a potential problem. On the other hand, the dense water processes have Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 221

16 not been appropriately represented in ocean models so far. Recent idealized experiments show improvements of deep ocean simulation with implementation of bottom boundary layer (Gnanadesikan, 1997). New treatment of dense water processes shows a hope to help improve Arctic modeling. For the Barents Sea, positive temperature trends also exist. In the upper layer, surface heat losses balance in lateral heat flux and convection. In the deep layer, lateral heat transports are compensated by convection to a great extent. Imbalance also exists. 4. Freshwater Budgets and Pathways 4.1 Diagnoses With a volume less than 1% of the global ocean volume, and a surface area less than 3% of global ocean surface, the Arctic collects a disproportionately large fraction of worldwide runoff. The annual mean of modeled distribution of FW storage within uppermost 210 m was shown in Fig. 2(c). Corresponding observational estimates based on annual means from the Levitus (1982), Gorshkov (1983) and EWG (Environmental Working Group, 1997) atlases are shown in Figs. 6(a), (b) and (c). In the model (Fig. 2(c)), a large FW storage occurs in the deep basin and shelf seas along the Eurasian landmass, such as the Laptev Sea and the East Siberian Sea, reflecting a contribution of river runoff. The Canada Basin contains a largest amount of FW. To a large extent, the distribution of FW storage in the model approximately corresponds to those from atlases and former results (Aagaard and Carmack, 1989). However an obvious difference of estimates in the Eurasian Basin exists. In the estimate of Aagaard and Carmack (1989), FW storage in the Eurasian Basin is much smaller than that in the Canada Basin due to a significant difference of stratification. In the model, the FW storage in the Eurasian Basin is larger than observations. A potential reason for this is that the dense and cold Barents Sea water could not reach and distribute in the Eurasian Basin properly. FW storage decreases rapidly approaching shelf break of southern Eurasian Basin due to a rapid increase of salinity with depth. Steele et al. (1996) estimated larger FW storage in the western Arctic than eastern Arctic, in agreement with observations, but values in the sectors in vicinity of the Chukchi Sea and the East Siberian Sea as well as north of the Spitsbergen seem too large. They obtained the maximum FW storage, 13 m, appearing in the vicinity of Chukchi Sea and East Siberian Sea. In spite of the fact that Pacific water is fresher than Atlantic water, there is still much saline water flowing into the Arctic Ocean. It seems not plausible to have maximum FW storage in this area, which may be caused by separation of diagnostic Fig. 6. Annual mean freshwater storage (m) with uppermost 210 m in (a) Levitus, (b) Gorshkov data and (c) EWG data. 222 X. Zhang and J. Zhang

17 areas. The FW storage north of the Spitsbergen seems larger than observation estimate, where there is saline water inflow through Fram Strait and the salinity increases with depth. In our current modeling, the total annual mean FW storage of the AM is about 73,855 km 3. Of this, the Arctic Ocean contains 73,160 km 3 and the Barents Sea contains 694 km 3. The total FW storage is close to the estimate by Aagaard and Carmack (1989). Aagaard and Carmack (1989) estimated the total FW storage to be 80,200 km 3 with 76,200 km 3 and 4,000 km 3 occurring in the Arctic Ocean and the Barents Sea, respectively, with reference salinity ppt. When we use the same reference salinity, we obtain 79,422 km 3, of which 77,961 km 3 in the Arctic Ocean and 1,461 km 3 in the Barents Sea. We estimated 75,380 km 3 of FW storage, with 75,175 km 3 in the Arctic Ocean and 206 km 3 in the Barents Sea, from Levitus (1982); 91,329 km 3, with 90,110 km 3 in the Arctic Ocean and 1,219 km 3 in the Barents Sea, from Gorshkov (1983); 74,579 km 3, with 74,173 km 3 in the Arctic Ocean and 406 km 3 in the Barents Sea, from EWG (1997). FW storage in Levitus (1982) and EWG (1997) is less than the estimates in our modeling and by Aagaard and Carmack (1989). But Gorshkov (1983) give a relative large FW storage. The estimate of 53,000 km 3 by Steele et al. (1996) with their simple model for the Arctic Ocean is much less than above-mentioned estimates. The other form in which FW is stored is sea-ice. Modeled annual mean sea-ice thickness was shown in Fig. 2(a), corresponding to a total sea-ice 18,781 km 3. Converted to liquid FW with the assumed sea-ice salinity of 4 ppt, this corresponds to 15,292 km 3, of which 15,075 km 3 and 217 km 3 occur in the Arctic Ocean and Barents Sea domains. Our total volume estimate is close to those of Aagaard and Carmack (1989) and of Steele et al. (1996) who estimate about 16,000 km 3 (as liquid FW equivalent). In Fig. 7 we show the annual cycle of net surface FW fluxes from main sources over the Arctic Ocean and the Barents Sea. Continent rivers supply considerable freshwater from spring to autumn (Fig. 7(a)) with maximum river runoff in June. In the Barents Sea the maximum river runoff occurs, with one month earlier than that in the Arctic Ocean (Fig. 7(b)). Because of the large sea-ice cover during the winter and spring, the precipitation contributes to snow development as snowfall and does not enter the ocean directly. Figure 7(c) shows that the Arctic Ocean gets maximum FW from precipitation less evaporation in August, which lags behind river runoff. In the Barents Sea (Fig. 7(d)), the maximum FW from precipitation less evaporation appears in September. According to the distribution of precipitation, main precipitation appears in the GIN Sea, the Barents Sea and west part of Eurasian shelf seas. FW Fig. 6. (continued). Heat and Freshwater Budgets and Pathways in the Arctic Mediterranean in a Coupled Ocean/Sea-ice Model 223