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The Seasonality of Convective Events in the Labrador Sea [Journal of Climate](Journal of Climate Via Acquire Media NewsEdge) ABSTRACT Modeling deep convection is a key challenge for climate science. Here two simulations of the Labrador Sea circulation obtained with the Regional Ocean Modeling System (ROMS) run at a horizontal resolution of 7.5 km are used to characterize the response of convection to atmospheric forcing and its seasonal variability over the period 1980-2009. The integrations compare well with the sparse observations available. The modeled convection varies in three key aspects over the 30 years considered. First, its magnitude changes greatly at decadal scales. This aspect is supported by the in situ observations. Second, the initiation and peak of convection (i.e., initiation and maximum) shift by 2-3 weeks between strong and weak convective years. Third, the duration of convection varies by approximately one month between strong and weak years. The last two changes are associated with the variability of the time-integrated surface heat fluxes over the Labrador Sea during winter and spring, while the first results from changes in both atmospheric heat fluxes and oceanic conditions through the lateral inflow of warm Irminger Water from the boundary current system to the basin interior. Changes in surface heat fluxes over the convective region are linked to large-scale modes of variability, the North Atlantic Oscillation and Arctic Oscillation. Implications for modeling the climate variability of the Labrador basin are discussed. 1. Introduction The meridional overturning circulation (MOC) plays a critical role in transporting heat across latitudes in the ocean, and its variability has significant impacts on the global climate system (Bryden et al. 2005). The North Atlantic branch of the MOC is characterized by deep water formation in few specific locations, including the Nordic Seas and the Labrador Sea (Dickson et al. 1996; Marshall et al. 2001). Here in winter and early spring the ocean releases heat to the atmosphere and the surface waters become dense enough to mix by convective instability (Kuhlbrodt et al. 2007). In the Labrador Sea, deep convection takes places in the deeper portion of the basin, seaward of the western continental slope, and forms the Labrador Sea Water (LSW) that sometimes reaches as deep as 2000 m, exits the Labrador Sea, and becomes a distinct component of the North Atlantic Deep Water, feeding the MOC (Talley and McCartney 1982; Marshall et al. 1998; Lazier et al. 2002; Rhein et al. 2002; Yashayaev et al. 2003; Yashayaev 2007). The LSW variability therefore influences the MOC, and it has been suggested that an intensification of the convective activity in the Labrador Sea will lead to an intensification of the MOC, with an overall increase in poleward heat transport (Eden and Willebrand 2001). The formation of LSW displays strong interannual variability that is influenced by the atmospheric fluxes, which are highly variable at the latitudes under consideration, and by the characteristics of the Irminger Current (Myers et al. 2007; Rattan et al. 2010). The Irminger Current flows along the Greenland coast and its warm and salty subsurface water is brought to the Labrador Sea interior through predominately anticyclonic mesoscale eddies, the Irminger rings (Lilly et al. 2003; Katsman et al. 2004; Hátún et al. 2007; Bracco et al. 2008; Chanut et al. 2008; Rykova et al. 2009; Gelderloos et al. 2011; Luo et al. 2012, hereinafter LBYD12). Since the mid-1990s the Irminger Current has experienced continuous warming, which has been linked to the concurrent weakening of the subpolar gyre (Holland et al. 2008). Such weakening, in turn, may be the expression of the subpolar gyre decadal variability (Häkkinen and Rhines 2004; Böning et al. 2006). The Labrador Sea convection has been sampled by high-frequency hydrographic measurements at Ocean Weather Station Bravo (OWSB) from 1945 until 1974 with 24 years of continuous recording (e.g., Lazier 1980; Sathiyamoorthy and Moore 2002), by moorings and Profiling Autonomous Lagrangian Circulation Explorer (P-ALACE) floats in the second half of the 1990s (e.g., Marshall et al. 1998; Lavender et al. 2000; Avsic et al. 2006), by gliders (Frajka-Williams et al. 2014), by hydrographic surveys usually conducted in late spring or summer and at least yearly from 1990 by the Bedford Institute of Oceanography (BIO), and by Argo profiling floats since June 2002. The surveys primarily sample the AR7WWorld Ocean Circulation Experiment (WOCE)/ Climate Variability and Predictability (CLIVAR) line extending from Newfoundland (53.678N, 55.58W) to the west coast of Greenland (60.58N, 48.258W), and have been extensively analyzed (e.g., Lazier et al. 2002; Yashayaev et al. 2003; Lu et al. 2007; Yashayaev 2007; Yashayaev et al. 2007; Yashayaev and Loder 2009). Argo floats, on the other hand, provide temperature and salinity measurements of the upper 2000m of the water column, and represent a dataset that is continuous in time but irregular in space (Yashayaev and Loder 2009; LBYD12). Focusing on the last three decades (1980-2009), in situ data show that the convection in the Labrador Sea intensified in the late 1980s and early 1990s and has weakened since 1995, with a limited recovery in the 2007/ 08 winter (Våge et al. 2009; Yashayaev and Loder 2009). Various external causes have been proposed to influence the onset and intensity of convection, including local and remote atmospheric forcing, the Irminger Current conditions, and the state of the subpolar gyre (Marshall and Schott 1999; Lazier et al. 2002; Straneo 2006; Straneo et al. 2010). The variability of convective events, other than their interannual intensity, however, have been- and can be-investigated only for limited time spans using observations (Straneo 2006; Gelderloos et al. 2012) given their sparseness in space and/or time. On the modeling side, until recently the attribution of variability of convective events in the Labrador Sea has been attempted only for decadalmodulations (Mizoguchi et al. 2003) because of the generally poor representation of the details of LSW formation (Canuto et al. 2004; Tréguier et al. 2005). LBYD12, using a regional ocean model, were able to reproduce the interannual component as well, and to quantify the relative importance of the atmospheric forcing and of the Irminger Current conditions. Here we build on two of the numerical simulations described in LBYD12 to zoom in on the seasonal scales. We analyze how the time of initiation, peak, and seasonality of convection vary in years of intense versus weak activity, with immediate application to monitoring planning. Additionally, we explore the drivers of those changes, and we discuss the modeling challenges. Both ocean-only and coupled climate models display large biases and divergent behaviors in simulating the formation of deep water masses and their variability (Canuto et al. 2004; MacMartin et al. 2013). By analyzing the interplay of oceanic and atmospheric forcings in the representation of the seasonal cycle and of the interannual modulation of LSW in the North Atlantic in realistic simulations, we hope to provide a base to validate and test the representation of the Atlantic MOC in coupled climate models. 2. Model configuration The Regional Ocean Modeling System (ROMS) is a free-surface, primitive equation model based on the Boussinesq approximation and hydrostatic balance (Shchepetkin and McWilliams 2003, 2005). Here ROMS is configured in the Labrador Sea over the domain 518- 668N, 358-658W(Fig. 1a), with a horizontal resolution of 7.5km and 30 vertical layers, 8 of which are confined to the upper 300 m. The nonlocal K-profile parameterization (KPP) scheme is used to parameterize vertical mixing (Large et al. 1994). The integration period begins in January 1980 and ends in December 2009. The bathymetry is derived from the 20 gridded elevations/ bathymetry for the world (ETOPO2) (Sandwell and Smith 1997). A modified Shapiro smoother (Penven et al. 2008) is applied to the original bathymetric data to avoid pressure gradient errors. The smoother is applied everywhere except for three small regions around Cape Desolation. Retaining the original bathymetric details in these regions does not affect significantly the bottom velocities. However, these details are critical for a correct representation of the eddy-generation along the West Greenland coast, as shown by Bracco et al. (2008). A detailed discussion of this problem is contained in appendix A of Luo et al. (2011, hereinafter LBD11). Boundaries are open to the east, south, and north sides of the domain, where the velocity, temperature and salinity fields are nudged to the Simple Ocean Data Assimilation (SODA) ocean reanalysis version 2.1.6 (Carton and Giese 2008). A modified radiation boundary condition is also applied following Marchesiello et al. (2001). SODAhas been evaluated against other ocean reanalysis products in LBYD12, and it presents the advantage of reproducing quite realistically the lateral and vertical extent of the Irminger Current at the northeast corner of the domain. As mentioned, the time period investigated in this work extends from1980 to 2009. Since SODA2.1.6 ends in 2008, boundary conditions of 2008 are repeated for the computation of 2009. The two years are comparable in the observational records. Surface fluxes are from the National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) renalaysis data (1980-2009). Over the period November 1999-June 2009 the surface wind data consist of monthly averages of the spatial blending of highresolution satellite data [SeaWinds instrument on the Quick Scatterometer (QuikSCAT) satellite, hereinafter QSCAT] and the NCEP reanalysis (Milliffet al. 2004). To avoid a long-term driftof SST linked to the errors in the NCEP-NCAR heat fluxes (QNCEP) (Josey 2001), values are corrected by the National Oceanic and Atmospheric Administration (NOAA) extended SST (SSTNOAA) (Smith and Reynolds 2004) on a monthly time scale and 28 3 28 resolution, according to QMod 5 QNCEP 1 dQMod/dSSTMod 3 (SSTMod 2 SSTNOAA), where the subscript Mod indicates modeled quantities.1 Nudging to the monthly surface salinity climatology provided by the World Ocean Atlas 2009 (WOA09; Antonov et al. 2010) partially accounts for the seasonal cycle of the freshwater fluxes associated with sea ice melting and the Hudson River outflow. Those anomalies dominate the seasonal variability of the surface salinity field along the western coast of the basin. In this study, therefore, we do not account for the interannual variability of the surface freshwater fluxes except for the eastern and southern model boundaries. We consider two simulations forced by the same atmospheric forcings, consisting of monthly varying NCEP- NCAR heat andmomentumfluxes, but by different ocean boundary conditions. In the first simulation (CLIMA), we nudge the open boundaries to monthly mean climatological values obtained by averaging the SODA monthly output from 1980 to 2009 (where 2009 is identical to 2008). In the second simulation (VARY), we retain the interannual variability in the boundary conditions without any further averaging. Initial conditions for both integrations are derived from a spinup run, forced by climatological monthly averaged NCEP-NCAR atmospheric fluxes and SODA boundary conditions that extend for 50 years after a stationary state is reached. CLIMA and VARY are then initiated in 1976 and the first four years of simulations are discarded. Additionally, we investigate if using high-frequency surface heat fluxes (daily) and winds (6 hourly) to force ROMS influences the representation of convective events in the Labrador Sea performing a third run limited to the period November 1999-December 2004. The setup is identical to VARY but for the frequency of the atmospheric forcing products. No significant changes were detected in the representation of LSW formation. The outcome of this comparison is summarized in the appendix. 3. Validation of model output and potential temperature variability A detailed validation of the model representation of the surface circulation is provided in LBD11. It is found that ROMS reproduces accurately the Labrador Sea circulation and its variability compared to altimeter data, from seasonal to interannual scales, including the surface eddy kinetic energy (EKE) along the Greenland coast and in the convective area (Fig. 1a). Independently of the forcing fields used, and although the horizontal resolution of the model is just below the Rossby radius of deformation (;13 km) of the basin, the model captures the observed eddy variability. In particular, most statistics related to the Irminger ring population are in good agreement with observations, with the exception of the lifespan of large eddies (6-7 months in CLIMA and 8-11 months in VARY, versus 12-18 months in observations). Consequently, fewer than observed Irminger rings migrate as far south as 588S in the model. The interannual variability of potential temperature (PT) through the water column over the period 1980- 2009 is discussed in LBYD12. Modeled potential temperature values are compared with hydrographic surveys along theAR7Wline (Lazier et al. 2002; Yashayaev 2007; Straneo 2006; van Aken et al. 2011) and with Argo data from the summer of 2002 in the so-called central Labrador Sea (CLS), defined accordingly to Yashayaev and Loder (2009) as the region comprised by the 3250-m isobaths and within 150km of the AR7W hydrographic line. The CLS is not the region of greatest convective activity, but is close enough to be affected by the spreading of LSW within weeks from the events, and it is where the most uniform-in time and space-in situ data coverage over the period considered is found. The model representation matches well the observations from the base of the mixed layer to 2500 m; below such depth ROMS is approximately half a degree too warm compared to in situ data and less uniformly stratified than observed. This discrepancy is likely due to poor representation of verticalmixing at depth and/or to insufficient model vertical resolution; SODA boundary conditions may further contribute to the model bias. The PT in the first half of the record (1980-94) is characterized by the alternation of warmer and colder periods, while the second half (1995-2009) is dominated by a warming trend beginning around 1995 in both CLIMA and VARY (Fig. 1b). The modeled interannual variations are consistent with hydrographic observations (LBYD12); for example, the model successfully captures the strong convection events in 1982-84 and in the early 1990s, the reduction in the convective activity after 1995, and the partial recovery in 2008. Independent of the integration considered, the intensity of convection is reduced significantly after 1995 inbothCLIMAandVARY. LBYD12 showed that the warming in CLS results from the combined changes in local heat fluxes and warming of the Irminger Current, which has been reported continuously since 1995 (Böning et al. 2006; Straneo 2006) and is realistically represented in SODA. Irminger Current water is advected by Irminger eddies into the central portion of the basin, where it facilitates restratification (Katsman et al. 2004; LBD11). Moving to seasonal scales, LBYD12 compared the potential temperature seasonal cycle in ROMS with the observed one by Argo floats from mid-2002 (see their Fig. 6) and found very good agreement between the two. The Argo period, however, is characterized by weak convective episodes in all years except 2008, and it is not representative of the interannual variability observed during the 30 years under investigation. Therefore, as further validation, in Fig. 2 we present a comparison of the seasonal cycle of heat content and salinity in ROMS and P-ALACE float data covering 1996-2000 in the top 200m and in a deeper level, extending from 200 to 1300 m, following the analysis in Straneo (2006) for the CLS. This period includes four strong convective events. The general behavior is well represented both at the surface and at depth. The model slightly underestimates the amplitude of the heat content cycle and overestimates the salinity one in the surface layer.At depth the seasonal evolution of ROMS heat content is within the standard deviation of the observations, while the modeled salinity does not agree with the P-ALACE data and does not display evident seasonal variations. While a similar lack of seasonality was noticed by Straneo (2006) using OWSB data over the period 1964-74 independently of the inclusion of Great Salinity Anomaly years (Dickson et al. 1988), we cannot exclude a model bias. Indeed, the representation of salinity at high latitudes poses a challenge to ocean modeling, as previously noticed by Tréguier et al. (2005) analyzing the variability of the North Atlantic subpolar gyre in four high-resolution models. Nonetheless, we can conclude that ROMS provides a good representation of seasonal changes in potential temperature also in periods of strong convection. 4. Seasonality of convective events in the Labrador Sea a. Vertical velocity and convection Ocean deep convection takes place within vertical plumes of O(1) km in radius and vertical extent of about 2km (Marshall and Schott 1999). The water is mixed vertically in the plumes, and then homogenized within the so-called mixed patch through horizontal mixing. The model adopted in this investigation (and more generally all ocean models used for climate studies) does not have sufficient horizontal resolution to represent directly the convective process. The integral effect of the convective plumes and their impact on vertical mixing and temperature and salinity distributions, however, can be parameterized (Send and Marshall 1995). In ROMS they are accounted for by the nonlocal KPP scheme. KPP assumes that the vertical turbulent fluxes of momentum, heat, and salinity (or any other tracer) can be expressed as the sum of a downgradient flux and a nonlocal contribution. Convective events can then be characterized by any quantity directly affected by such fluxes, from the absolute value of the vertical velocity field, to temperature and/or salinity profiles, ormixed layer depth (MLD) and turbulent kinetic energy. Vertical velocities present the advantage over the other quantities in defining convective episodes, and in particular in defining initiation and duration of convection, by allowing a clearcut threshold. This cannot be achieved as easily using temperature or density profiles because following strong convective events the water mixed at depth during the convective season remains in the central portion of the Labrador basin for long enough to influence the potential temperature or density averages for the following year (see, e.g., Fig. 13 in LBYD12). Figure 3 shows the mean seasonal cycle of the absolute value of the vertical velocity field jwj averaged over depths comprised between 150 and 2000masmodeled by ROMS during the 30 years considered. The top 150mare excluded as this part of the water column is strongly influenced by surface momentum forcing [see, e.g., Koszalka et al. (2009) for an analysis of relative contributions to w in an idealized wind-driven domain]. High values of jwj are found at all times along the boundary current system in correspondence of steep gradients of the continental slope, broadly covering the areas comprised between the 1000- and 2000-m isolines. In those areas eddy generation by baroclinic instability contributes to high level of surface EKE, and the eddies extend from the ocean surface to the slope (e.g., LBD11). In the basin interior, on the other hand, the largest vertical velocities are found only in late winter and early spring over a region encompassing the deeper portion of the basin east of the western continental slope as observed, among others, by Lavender et al. (2000), Pickart et al. (2002), and Frajka-Williams et al. (2014). This area, referred to as the convective region (CR), is approximated by the black box in Fig. 3 with coordinates 578-59.58N, 56.68-528W. We verified that in ROMS the same area identifies also the maximum MLD (Figs. 3e,f). Any MLD definition requires the use of an ad hoc threshold in temperature or density. In the Labrador Sea the density differences between the surface and the base of the mixed layer during convective events can be very small (Frajka-Williams et al. 2014), smaller than 0.01 kgm23, usually adopted in numerical studies (Lazier et al. 2002). A robust observational constrain is not available, and the ''correct'' threshold is likely to be one that accounts for seasonal changes and interannual variability, particularly in presence of trends. In this work the MLD is defined as the depth at which density differences with the surface are equal to 0.008 kgm23. As a further test, we compared the modeled convective region from 2003 to 2009 with the one identified by the MLD in the Argo data. In both datasets, convection is patchy, and approximately located over a smaller area than the CLS or the CR regions, and close to the intersection of the two. Whenever the average over the period is considered, the agreement between model and observations on the extent of the mixed patch is very good (not shown). The time series of jwj andMLDin CLIMAandVARY and their differences are presented in Fig. 4. Compared to the few observational estimates the modeled MLD appears generally too deep. This bias is directly linked to the deep layers in ROMS being less uniformly stratified than observed. The correlation between jwj and MLD has coefficientR50.9. Increasing the density threshold in the MLD criterion to the more common 0.01 kgm23 (e.g., Tréguier et al. 2005) does not affect the correlation but further increases the maximum MLD in the last 10 years of the integration, when a warming trend is apparent. If a threshold of 0.02 kgm23 or higher is used instead, the correlation decreases dramatically and the mixed layer reaches the ocean bottom during most events. From the jwj time series we separate years of strong and weak convection using a threshold of 0.85 3 1023ms21. This allows us to group 15 years (1982, 1983, 1984, 1985, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1999, 2000, 2002, and 2008) in the strong convection category and 15 years (1980, 1981, 1986, 1987, 1995, 1996, 1997, 1998, 2001, 2003, 2004, 2005, 2006, 2007, and 2009) in the weak convection category. For 6 of the 30 years considered a change in the threshold by 610% could modify their classification, and we choose to include three of those normal events in each category. While the jwj criterion provides a differentiation similar to the one of MLD exceeding (or not) 1000m in observational data (e.g., Pickart et al. 2002), the classification inVARY does not perfectly match the observations. For example, the winter of 1999 is commonly categorized as having weak convection, while 1997 is seen as strong. This is captured in CLIMA but not in VARY, even if the two runs have similar Irminger Current inflow over the 1995-99 period, and is associated with the (modeled) internal ocean variability. In our analysis, we retain the same groups in CLIMA to simplify the comparison and have an equal number of events in each group. The vertical velocity time series in Figs. 4a and 4b are highly correlated (correlation coefficientR50.95), but according to the chosen w threshold four events classified as weak in VARY would follow under the strong category in CLIMA. We verified that our conclusions do not depend on the details of the classification in CLIMA, or on the jwj threshold in VARY. The interannual variability of convective events that emerges from the vertical velocity field is consistent with the one from potential temperature or potential density over the same region (Figs. 5 and 6). The classification of weak and strong years does not change with the variable used, but the differences between VARY and CLIMA, indicative of the influence of the Irminger Current on convective activity, appear amplified (Fig. 5c). For the first half of the record the potential temperature averaged between 150- and 2000-m depth over the CLS domain is greater in CLIMA by about 0.078C on average, and vertical velocities display large differences but of alternating sign, so that their average is close to zero. After 1995, potential temperature (density) in VARY is consistently higher (lower) than in CLIMA, and the absolute vertical velocities are mostly higher in CLIMA. The potential temperature warming trend is consistent with the one found in the incoming Irminger Current at the model boundary (see LBYD12, their Fig. 9). Overall, the boundary current contribution explains about half of the warming recorded in VARY in the CR or CLS regions after 1995. It is important to notice that the Irminger Current warming recorded after 1995 is not unprecedented, at least according to SODA, but is part of the decadal variability of the system. The period from 1958 to 1970 was indeed characterized by an Irminger Current as warm as during the first decade of the twenty-first century. b. Seasonality and strength of convection The seasonal cycle of convective events over the Labrador Sea from1980 to 2002 cannot be easily quantified in the observations due to their limited time and/or space coverage except for the P-ALACE period (1996-2000) (Straneo 2006; Lavender et al. 2000). Shipboard and hydrographic surveys have sampled late spring and summer, moorings provides continuous time series but at one location, and floats have been deployed only for limited time intervals. Since mid-2002 Argo data, complemented by the K1 mooring (deployed in 1995 near the former BRAVOstation at about 25-kmdistance; e.g., Avsic et al. 2006) and at times by gliders, enabled measuring the seasonal cycle with greater confidence. Here we compare the seasonality of weak and strong convective events using the modeled jwj, and we find that they differ in the timing of their initiation, maxima, and shutdown (Fig. 7a). On average, weak events initiate from two (CLIMA) to three (VARY) weeks after the strong ones, they reach their peak of intensity two or three weeks later, and terminate approximately two weeks earlier. This behavior is common to all weak events, independent of the decade considered, and is further amplified if the six ''normal'' years are excluded from the calculation. Consequently, the convective activity in weak years is approximately one month shorter than in strong ones and shifted further into spring. The reduced intensity, shifted seasonality, and shortened duration of convection in the CR for weak events in both integrations are associated predominately to reduced heat fluxes and wind intensity in winter (Figs. 7b,c). It is noticeable that atmospheric changes in the reanalysis are found only between November and March, and both heat and momentum fluxes do not show any significant difference through the remaining of the year. Also, the atmospheric fluxes display a substantial change in intensity, but almost no shiftof seasonality in their annual cycle. In weak years, it takes at least two weeks more for the convection to start because of the reduced heat flux and associated wind intensity. Figure 7 reveals also that the convection period defined by jwj does not coincide with the period during which the heat flux to the atmosphere forces convective mixing. The offset at initiation is associated with the excess buoyancy accumulated in the upper 150-200m between May and August, when the surface heat fluxes are, on average, positive. Such excess buoyancy needs to be removed (Bailey et al. 2005; Gelderloos et al. 2012; Frajka-Williams et al. 2014) before convection deeper than 150m can take place. Once removed, it is enough that the surface heat fluxes remain negative, even if weakly, for the model requirement for convective instability to be satisfied, for convection to continue in the top 200-300mof the water column, and for jwj to remain large at those depths. The input of warm, salty Irminger water transported from the western Greenland coast to the center of the Labrador basin by the Irminger rings increases the stratification, and consequently more heat has to be released to the atmosphere for the convective instability to begin, further delaying its initiation. The impact of the boundary current interannual variability on convection is quantified as the difference betweenVARYand CLIMA and it ismore prominent in weak than in strong years, due to the significant warming of Irminger Current experienced since 1995 (Stein 2005; Myers et al. 2007). For instance, the maximum absolute value of the CR-averaged vertical velocities in VARY for weak years is 0.5 3 1023ms21, to be compared 0.7 3 1023ms21 in CLIMA, and it is achieved about a week later (Fig. 7a). In contrast, mean jwj in VARY and CLIMA are almost identical in strong convective years. c. Strength of convection and heat fluxes Figure 8 shows the relation between the strength of convection, measured by the absolute value of w averaged over the period in which jwj . 0.2ms21, and the surface heat fluxes averaged over the CR in different seasons for all years, or weak and strong years separately. Ahigh correlation coefficient (R) implies that the modeled convection intensity is regulated by the local surface heat fluxes. The Labrador Sea convection occurs in late winter and spring, and the correlation between vertical velocities in the CR and the atmospheric heat fluxes is the greatest when heat fluxes from December to April are considered. Coefficients are generally higher in CLIMA than in VARY (Figs. 8a,b) but are greater than 0.85 in both cases when all years are considered. In CLIMA the contribution of the Irminger rings to the restratification is constant through the years (aside from the intrinsic interannual variability in ring shedding discussed in LBD11), and the interannual variability of the convective activity is driven exclusively by the heat fluxes. In VARY the year-by-year changes in the Irminger Current temperature modulate the heat flux forcing by contributing warmer or cooler than average waters to Labrador Sea interior depending on the year considered. The wintertime heat flux, particularly in January and February, is the most important (Figs. 8c,d) since the conditions for the initiation of the convective events are set. Moreover, the accumulated heat flux in winter is larger than in spring (Fig. 7b). On the other hand, the delayed onset in weak years requires considering early spring, March and April, together with January and February (and perhaps December) to obtain a statistical significant relation for weak events inVARY, and greatly improve the correlation in CLIMA.2 In contrast, the atmospheric forcing averaged over three, six, and nine months prior of the inception of convection does not influence the convective activity, in agreement with the analysis by Straneo (2006), who showed that the positive heat fluxes into the ocean in late spring and summer (May-August) are absorbed in the upper 200m and are then released in autumn and early winter (September- December). The strength of convection depends also on the inflow of Irminger Current waters: maximum correlations achieved in VARY are all slightly smaller than in CLIMA, and the slopes describing the linear relation between vertical velocities and heat fluxes change more dramatically between strong and weak years. Notwithstanding the modulation at decadal scales associated with changes of the Irminger Current characteristics, the seasonal variability of the convective activity in the Labrador Sea appears controlled to a large extent by the local heat fluxes immediately before and during the convective season. Heat fluxes over the CR result, in part, from large-scale atmospheric anomalies and during the winter season are correlated with both the North Atlantic Oscillation (NAO) (Dickson et al. 1996) and the Arctic Oscillation (AO) (Thompson and Wallace 1998) (see Table 1). 5. Discussion and conclusions In this paper, two regional simulations of the Labrador Sea circulation in the period 1980-2009 are used to investigate changes in the seasonal cycle of convective events. The numerical integrations, CLIMA and VARY, differ in their lateral oceanic boundary conditions and allow for isolating the impact of atmospheric forcing, through heat and momentum fluxes, and oceanic forcing, through changes in the properties of the incoming currents in the basin, on the interannual and seasonal variability of convective events. Both CLIMA and VARY reproduce well the observed circulation, the surface eddy kinetic energy, and its interannual variability. In particular ROMS simulates realistically the population of Irminger rings, and the surface EKE agrees with observational estimates from altimeter data along the west coast of Greenland, where the rings are formed, and in the central portion of the basin where convection occurs (Luo et al. 2011). Additionally, the evolution of potential temperature throughout the water column is well represented (LBYD12) up to 2500-m depth. As expected, VARY reproduces satellite and hydrographic observations more realistically than CLIMA by accounting for the changes in the Irminger Current. In ROMS the region characterized by convective activity is found seaward of the western continental slope in agreement with observational (Lavender et al. 2000; Pickart et al. 2002) and numerical studies (Mizoguchi et al. 2003). A recent work by Zhu et al. (2014) related the ability of amodel to properly simulate the localization of deep convection in the Labrador Sea to its representation of eddy-induced lateral fluxes, associated with the Irminger rings and smaller eddies formed by baroclinic instability along the boundary current system. A number of previous studies have indeed shown limitations in this respect, likely due to coarse resolution (Willebrand et al. 2001) and/or parameterization choices (Canuto et al. 2004). The analysis presented indicate that the annual changes in the strength of convection in the Labrador Sea are predominately determined by local atmospheric forcing, consistent with previous studies (Delworth and Greatbatch 2000; Eden and Willebrand 2001; Bentsen et al. 2004). Heat fluxes over the CR from December to April correlate highly with the oceanic vertical velocities averaged between 150- and 2000-m depth in both simulations, with the wintertime heat flux having larger impacts in years of strong convection (Dickson et al. 1996), and spring heat fluxes being as important as winter ones during weak convective episodes. In contrast, the atmospheric forcing averaged over three and six months prior of the inception of convection does not influence the convective activity, in agreement with the analysis by Straneo (2006). The state of the Irminger Current contributes to the modulation of the convective activity through the Irminger rings, which carry warm and salty water to the convective area and increase the stratification through lateral mixing. Its variability, however, plays only a secondary role in the thirty years considered, as manifested by the difference of vertical velocity between CLIMA and VARY (Fig. 4c). More quantitatively, the comparison between the seasonal cycle of jwj in CLIMA and VARY (Fig. 7a) indicates that the interannual modulation of the boundary current is responsible for a further reduction of about 25% in the maximum of the mixing intensity. The seasonal cycle of Labrador Sea convection has been observed since the deployment of Argo floats in the basin, but we do not have observations that are continuous in time and space prior to the summer of 2002. Here we show that weak and strong convective events are characterized not only by different intensity, but also by a different seasonal cycle. Both initiation and peak of convection for weak events in VARY are delayed by about three weeks compared to strong ones. Additionally, the duration of convective activity is approximately one month shorter for weak episodes. Those characteristics are linked to the reduced atmospheric cooling observed between December and April-but not in other months-in the climatology of the heat fluxes during weak years. The seasonal cycle of the atmospheric heat and momentum fluxes is almost unaltered, but variations in surface cooling rates are translated in changes in intensity, seasonality and duration of ocean convection. Those changes are important for understanding the variability in the oxygen drawdown and carbon sequestration in the basin. Finally, local heat fluxes reflect atmospheric variability at broader scales, and in winter are significantly correlated with NAO/AO. In light of previous work, our analysis suggests that a realistic representation of the interannual variability of LSW formation can be achieved also in a hydrostatic model, but at least two ingredients are required. First, the ocean model resolution has to be below the Rossby deformation radius to allow for the direct representation of lateral eddy fluxes. Canuto et al. (2004) have shown that models where the eddies are parameterized display large biases independently of the vertical mixing scheme adopted. The recent analysis of glider data by Frajka- Williams et al. (2014) further pinpointed to the importance of horizontal variations in density over short distances (tens of kilometers) in the convective area for restratifying the region. Variations at those scales (1-2 grid points), and of about 1/ 3 of the observed value (;0.003 kgm23), are present in the 3-day average density fields used in Fig. 6. Model resolution plays also an important role in the representation of the boundary current system and its instabilities. Second, the seasonal cycle and the interannual variability of the surface heat fluxes are both important. The vast majority of coupled climate models, including the ones adopted in phase 5 of the Coupled Model Intercomparison Project (CMIP5), have a biased seasonal cycle, with unrealistically large seasonal excursions, and spring (fall) surface atmospheric fields closely resembling the ones in winter (summer). On the positive side, the representation of the time integrated (monthly) effect of winter storms on the surface wind and heat fluxes is sufficient to achieve a realistic representation of LSW formation (see the appendix), suggesting that at least for models with a stratification comparable to ROMS a detailed representation of extreme winter events is not required if their average impacts are accounted for. Given the biases found in the representation of the Atlantic meridional overturning circulation in ocean and coupled climate models, and of the divergent behavior of the latter in future projections (e.g., MacMartin et al. 2013), the high correlation between the intensity of convective activity in the Labrador Sea and both localand large-scale atmospheric heat flux may provide an important test for validating climate models, while pointing to a simple way to parameterize and improve the representation of convection when coarser resolution is used. Acknowledgments. 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Bersch, 2007: Transformation of the Labrador Sea Water in the subpolar North Atlantic. Geophys. Res. Lett., 34, L22605, doi:10.1029/ 2007GL031812. Zhu, J. S., E. Demirov, Y. Zhang, and A. Polomska-Harlick, 2014: Model simulations of mesoscale eddies and deep convection in the Labrador Sea. Adv. Atmos. Sci., 31, 743-754, doi:10.1007/ s00376-013-3107-y. HAO LUO, ANNALISA BRACCO, AND FAN ZHANG School of Earth and Atmospherics Sciences, Georgia Institute of Technology, Atlanta, Georgia (Manuscript received 30 December 2013, in final form 3 June 2014) Corresponding author address: Dr. Annalisa Bracco, School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Dr., Atlanta, GA 30332. E-mail: [email protected] APPENDIX The Role of High Frequency Atmospheric Forcing The results presented in this work are obtained using ROMS forced by monthly atmospheric forcing fields interpolated to the model time step. In the Labrador Sea, convection is driven, predominantly, by the integral of the surface heat flux. This is shown, for example, by Yashayaev and Loder (2009) using NCEP heat fluxes and Argo data, and has been confirmed by our integrations (see Fig. 10 in LBYD12). The prominent role of the heat fluxes is further supported by the investigation of the recovery mechanisms of convection after the shut down due to the Great Salinity Anomaly by Gelderloos et al. (2012), and by the analysis of the 2005 convective season using Argo data and sea gliders performed by Frajka-Williams et al. (2014). This happens because over most of the ocean, including the convective region in the Labrador Sea as defined in the manuscript, wind mixing is limited to the top 200m of the water column even during strong events. Consequently, the use of higher-frequency winds (or/ and higher-frequency heat fluxes) does not substantially change the representation of deep convection in the center of the basin. The above discussion is supported by a 5-yr long simulation-from January 2000 to December 2004-identical in setup to VARY but forced by NCEP-NCAR daily heat fluxes and QSCAT- NCEP blended 6-h winds, referred to as VARY-HF in the following. Comparing the mean climatology of potential temperature in VARY-HF and VARY over the common period, it is found that the mean modeled temperatures associated with the high-frequency atmospheric fluxes are ;0.38C warmer immediately below the surface and within the upper 100m, and slightly cooler (;0.18C or less) in the deeper layers (Fig. A1), in agreement with results by Ezer (2000) over the North Atlantic, and by Cardona and Bracco (2012) in the South China Sea. The latter has shown that the high-frequency winds excite near-inertial waves as an ageostrophic expression of the eddy field, whenever a vigorous one is present, as in the case of the Labrador Sea. Enhanced mixing by near-inertial waves causes, in turn, the subsurface warming and the deeper cooling (the frequency spectra analysis reported in Cardona and Bracco has been repeated for this domain confirming their conclusions once the different Coriolis frequency is accounted for). The seasonal cycle of the SST anomalies (Fig. A2) and the interannual variability (Fig. A3) of potential temperature in the CR, however, do not depend on the frequency of the atmospheric forcing used, being the eddy field analogous in the two integrations everywhere but at the tip of Greenland, where the EKE in VARY-HF is twice as high as in VARY, and in better agreement with observations (Pickart et al. 2003). In conclusion, in our model we can exclude a significant role of the atmospheric forcing frequency in modulating strength and timing of modeled convective events in the Labrador Sea at seasonal to interannual scales. (c) 2014 American Meteorological Society |