Modelled interannual variability of vertical organic matter export related to phytoplankton bloom dynamics – a case-study for the NW Mediterranean

Introduction Conclusions References


Introduction
The dynamics regulating the vertical flux of organic matter in the ocean determine the partitioning of carbon between surface and deep ocean and the transfer of organic matter to higher trophic levels.These dynamics affect both climate and the ocean's Figures ability to sustain fisheries.Primary production of organic matter occurs all year round, with a seasonal bloom at all mid-latitude oceans.Timing and intensity of the bloom show latitudinal and interannual variability mainly determined by the variability in atmospheric forcing (Henson et al., 2009;Ueyama and Monger, 2005;Waniek, 2003).Henson et al. (2009) showed that the onset of the bloom in the North Atlantic, between 40 • N and 45 • N, can vary from year to year by as much as 20 weeks.This area represents the transition between subpolar light-limited and subtropical nutrient-limited environments (Dutkiewicz et al., 2001).The NW Mediterranean Sea is enclosed between these latitudes and its seasonal bloom shows high variability concurrent with its latitudinal counterpart in the North Atlantic Ocean.
The interannual timing, intensity and space variability of the NW Mediterranean bloom has been studied using remote sensing chlorophyll (Bosc et al., 2004;Barale et al., 2008).Both works reported the anticipation of the bloom in SeaWiFS (1998SeaWiFS ( -2003) ) data with respect to historical CZCS (1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986) data.Barale et al. (2008) also noted a significant interannual variability in the size of the bloom area.Volpe et al. (2012) suggested that the spatial-temporal extent of the NW Mediterranean bloom is related to the amount of nutrients transported to the upper layer during the deep water formation process and especially during the autumn-winter preconditioning phase.Nevertheless, to which extent the bloom variability is connected to the variability of the vertical flux of organic matter remains under discussion.
The depth of the mixed layer is commonly related to the onset of blooms according to the "critical depth hypothesis" (Sverdrup, 1953).Since the hypothesis assumes phytoplankton to be homogeneously distributed over the mixed layer, the depth of this portion of the water column regulates its mean exposure to light.In winter, the mixed layer is generally deeper than a critical depth in such a way that the vertically integrated net phytoplankton community growth is negative because the losses exceed the gains in terms of biomass.The bloom develops as soon as the mixed layer, at the end of winter, shoals to become shallower than the critical depth.According to this theory, the interannual variability in the timing of the bloom would be the result of the interannual Figures variability in the timing of re-stratification.In the Irminger basin (NE Atlantic), Henson et al. (2006) observed a tendency for the bloom to start later with higher mean winter wind forcing and thus with deeper mixed layer.The authors described a preconditioning effect of the winter atmospheric forcing on the bloom timing in the sense that a deeper mixed layer would take longer to shoal up to the critical depth.
The critical-depth hypothesis has been questioned as a predictor of the onset of the bloom, after growing evidence of blooms taking place in deep mixed layers (Townsend et al., 1992;Eilertsen, 1993;Dale et al., 1999;Koertzinger et al., 2008).Behrenfeld (2010) proposed a decoupling between phytoplankton growth and zooplankton grazing during the winter deepening of the mixed layer as the trigger of the bloom.Huisman et al. (1999) used a turbulent diffusion model to show that a bloom can develop if turbulent mixing is less than some critical value, regardless of the depth of the mixed layer.Recently, Taylor and Ferrari (2011) related this critical turbulent diffusivity to the atmospheric forcing, showing that a bloom can develop when the atmospheric cooling shuts off even in the absence of stratification.The authors focused their analysis on thermal convection pointing out, however, that their results can be extended to scenarios with turbulence generated by wind forcing and evaporation.
Several authors have pointed out the importance of wind-induced mixing during the bloom period as the key forcing process contributing to the interannual variability in both timing and intensity of the bloom (Ueyama and Monger, 2005;Waniek, 2003).
Wind-induced mixing episodes are expected to have an impact on the export flux as high biomass surface water is mixed with low-biomass underneath water.The effectiveness of vertical mixing in exporting organic matter to the depths has been described before.Ho and Marra (1994) ascribed a significant part of the Northeast Atlantic export of primary production to intermittent early spring vertical mixing.Bishop et al. (1986) showed how variations of the mixed layer in a warm-core ring were able to remove up to 67 % of primary production.Gardner et al. (1995) described a day-night "mixed-layer pump" as an important mechanism to sustain new primary production and to remove particles from surface waters.Koeve et al. (2002)  of the mixed layer in the Northeast Atlantic were able to interrupt the spring bloom and transport particles to depth through convective mixing.
Based on numerical simulations validated against field data, we relate the interannual variability in time and intensity of the bloom to the interannual variability in the export flux of organic matter in the NW Mediterranean Sea.We hypothesize that windinduced mixing episodes during the bloom are responsible for shaping both the bloom development and the export flux by effectively redistributing phytoplankton at depth.The interannual variability in the frequency and intensity of wind forcing during the bloom would thus account for a significant part of the interannual variability in the bloom characteristics and in the vertical flux of organic matter.We evaluate the effectiveness of the close-to-zero heat flux, as proposed by Taylor and Ferrari (2011), as predictor for the onset of the bloom in our numerical simulation and stress the role of wind mixing in driving both the heat flux and the distribution of phytoplankton at depth.The present numerical study is based on a newly implemented hydrodynamic model setting for the Western Mediterranean Sea, coupled to a newly developed biogeochemical model (Bernardello, 2010).Model validation is performed with reconstructed mean dynamic topography, argo float data and remote sensing chlorophyll.

The model
The hydrodynamic component of this model is the Stony Brook Parallel Ocean Model (sbPOM), a parallelized version of the Princeton Ocean Model (POM) (Blumberg and Mellor, 1987).The model domain includes the Western Mediterranean Sea between the Atlantic side of the strait of Gibraltar and the Sicily channel.The horizontal resolution is 1/20 • so that the mesh size is constant in longitude (5560 m) and decreases northwards (from 4456 m to 3964 m).In the vertical dimension the grid is resolved by Figures

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Full bottom.The bottom topography is obtained from the ETOPO1 1 arc-minute global relief model (Amante and Eakins, 2009), after bilinear interpolation.The atmospheric forcing is prescribed by using archived forecast analysis data provided by the European Centre for Medium Range Weather Forecast (ECMWF) with a spatial resolution of 0.25 • and a time-step of 6 h.These data are used as inputs to a set of bulk-formulas used to represent air-sea boundary processes (see Estournel et al. (2009) as an example).Daily outputs of temperature, salinity and velocities from the Mediterranean Forecasting System (MFS) high resolution model are used as lateral boundary conditions.Data come from the implementation MFS1671 with a horizontal resolution of 1/16 • and 72 unevenly spaced vertical levels, based on the numerical code OPA8.1 (Tonani et al., 2008(Tonani et al., , 2009;;Pinardi and Coppini, 2010).The MFS1671 fields are used for fluxes directed into our domain while the model computes the outward fluxes.
The model is initialized at rest using MEDAR-MEDATLAS climatology for temperature and salinity.A spin-up of 13 yr is performed.During this phase the model is forced by repeating the same year for the atmospheric forcing and the open lateral boundaries.Both datasets are obtained by averaging ten years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) of ECMWF and MFS1671 data, respectively.At the end of the 13th yr the interannual simulation starts by prescribing the interannual forcing for the period 2001-2010.In order to avoid drift in the simulation, during the spin-up and the period 2001-2010, temperature and salinity fields are restored to the climatology values with a timescale of 30 days.This timescale is short enough to control the drift of the simulation for the period studied and is long enough to leave most of the surface interannual signal untouched.
A newly developed biogeochemical component is linked to the above physical module.This is an aggregate-type model based on previous work (Fasham et al., 1990;Varela et al., 1992;Baham ón and Cruzado, 2003).It consists of different compartments representing nitrate, ammonium, phytoplankton, bacteria, zooplankton, detritic matter and dissolved organic matter and uses nitrogen as currency.In order to better represent the vertical flux of organic matter, particulate matter is split into small and large detritus and dissolved organic matter into labile and semi-labile fractions.Large Figures

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Full and small detritus and phytoplankton are vertically redistributed at each time-step assuming sinking rates of 210 m, 1.5 m and 0.8 m per day, respectively.Some specific processes are modified with respect to the reference works and some degree of complexity is added by allowing variable C : N ratios in both detritus and dissolved organic matter.
The biogeochemical component is initialized using nitrate and chlorophyll vertical profiles compiled by Manca et al. (2004) using EU/MEDAR/MEDATLAS II and MATER databases.The rest of the variables are initialized at low values.The biogeochemical spin-up starts on the 9th yr of the hydrodynamic spin-up and runs for four years.During this phase and the following interannual simulation, the open lateral boundary conditions are prescribed from seasonal climatological values for nitrate and chlorophyll.

The area of the bloom
In order to avoid coastal dynamics we limit the analysis to the area of the bloom defined as the set of pixels where chlorophyll concentration is higher than 0.5 mg m −3 , in the spring MODIS-Aqua climatology, and bottom depth is higher than 200 m in the model topography.This area (Fig. 1) is similar to the bloom area identified by D'Ortenzio and d'Alcala (2009) from K-means cluster analysis of SeaWiFS remote sensing chlorophyll, confirming the consistency of our criteria.
The bloom area roughly coincides with the center of the general cyclonic circulation that characterizes the NW Mediterranean Sea (Millot, 1999).On the northern boundary, the northern current flows along the slope in the SW direction.This current forms from the joining of the Western and the Eastern Corsican currents flowing northwards on both sides of Corsica (Taupiere- Letage and Millot, 1986).The southern boundary of the gyre is less well defined because of the intense mesoscale activity that characterizes the North Balearic front.This front separates the northern cold, salty and older Modified Atlantic Water (MAW) from the southern warm, fresher and younger MAW.
The area selected is known as a region where deep wintertime mixing and deepwater formation take place.The cyclonic circulation leads to an uplift of the isopycnals 9098 Figures

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Full forming a dome centered on the south of the Gulf of Lions at 42 • N 5 • E. During winter the Mistral from the Rhone Valley and the Tramontana from the north side of the Pyrenees blow over the area.These winds are cold and dry and typically occur in strong bursts, lasting for a few days, that are able to erode the near-surface stratification and expose the weakly stratified waters underneath (Leaman and Schott, 1991;Mertens and Schott, 1998).Deep convection can then occur with a consequent nutrient enrichment of the upper layers that will fuel the next spring bloom.However, the deep-water formation process is very irregular and can be completely absent during some years (Mertens and Schott, 1998).This variability is likely to be reflected also in bloom dynamics.

Data treatment
The present analysis is focused on the period from 1 December to 31 May from 2001 to 2010 (9 yr), as we are interested in the interannual variability of spring bloom dynamics.However, as the Aqua-MODIS data series starts in June 2002, this 9-yr period is reduced to 8 yr for the purpose of the satellite-model data comparison.
Hydrodynamic model results are validated by comparison between modelled Mean Dynamic Topography (MDT) with associated geostrophic circulation and data-model reconstruction.MDT is the sea elevation due to the mean oceanic circulation.The only MDT available for the Mediterranean Sea (hereafter called RioMDT) was reconstructed by combining oceanic observations from altimetry and in-situ measurements and outputs from an ocean general circulation model with no data assimilation for the period 1993-1999 by Rio et al. (2007).The bloom area defined for this study is superimposed on both MDTs as a reference for the discussion (Fig. 1).
To validate the model estimate of the Mixed Layer Depth (MLD) we use Argo floats data obtained from the http://www.coriolis.eu.org/CoriolisData Assembly Center.The float data are part of the MedArgo Program (Poulain et al., 2007) started in 2003.We select float profiles for our specific bloom area and for the period of the simulation.The Introduction

Conclusions References
Tables Figures

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Full Finally, MODIS data and model estimate are averaged over the area of the bloom and compared (Fig. 3).We calculate the maximum range of variability in the timing of the bloom following Henson et al. (2009).First, for each grid element, the onset of the bloom is determined for each year and for both series (model and MODIS).To this end, the method proposed by Siegel et al. (2002) is modified by considering the onset of the bloom as the first week of the year when the chlorophyll concentration is 10 % (instead of 5 %) above the median value for the period January-May (instead of the whole year).We obtain a map for each year (and both series) representing the onset date of the bloom.For each pixel the maximum and minimum values across the eight years are selected to define the maximum range of variability in the bloom onset date over the period 2003-2010.These maps are shown in Fig. 4 with the area of the bloom superimposed for comparison.
In Table 1 we present a synthesis of model results that are used throughout the analysis.MLD is obtained from daily averages of temperature and salinity fields.wind forcing applied to the model.MLD, HF and WS are presented as the average over the bloom area of daily mean values for each year.We present also the day of the maximum MLD and the week of the bloom onset (referred to 1 January) for both the model and MODIS data.These dates are calculated also from the spatial average.Model data for primary production (PP), export flux (EF) and phytoplankton biomass (PHY) are reported in terms of nitrogen as daily total (PP and EF) and daily mean (PHY).PP and PHY are calculated as depth-integrated values in the layer between the surface and 75 m depth while EF is considered at 75 m depth.EF includes contributions from zooplankton, detritus, dissolved organic matter, phytoplankton and bacteria.It takes into account the vertical transport as a result of advection, diffusion and, for phytoplankton and detritus, gravitational sinking.Sinking can contribute only positively to the export flux while advection and diffusion can operate also upwards, giving rise to negative contributions.In this sense, EF is a measure of the daily net vertical export flux of organic nitrogen at a fixed depth.We choose 75 m depth to characterize the export from the euphotic zone.The MLD during winter is almost always deeper than 75 m thus resuspension of organic nitrogen is very likely.However, contributions to EF from resuspension are taken into account in the definition of EF itself.Another reason for the choice of the EF reference depth is that we are interested in mixing events that operate at daily timescale.Such mixing events are primarily wind-induced and their typical length-scale in the area during winter is ∼80 m according to the Obukhov length relation.

Results
The two MDT reproduce the main cyclonic circulation in the northern sector, roughly coinciding with the bloom area defined for this study (Fig. 1).In both model and data, the northern current originates in the NE sector after joining of the eastern and Western Ibiza channel while in the model MDT it appears somewhat more intense on the Italian coast and starts decreasing along the Spanish coast, in agreement with current measurements of ∼5 cm s −1 off the Ebro delta (Font et al., 1995).From climatological studies Font et al. (1988) described the deflection of one branch of the northern current that would then return cyclonically to the northeast to form the Balearic current.
Both our model and data represent this deflection and the resultant Balearic current flowing towards the center of the Algero-Provenc ¸al Basin.Here, between the Balearic Islands and Corsica the mean flow is not well defined as this area is characterized by strong mesoscale circulation across the North Balearic frontal zone.The model depicts a dominant NE flux that eventually joins the northward eastern Corsican current and closes the cyclonic circulation around the bloom area.
Model MLD is reasonably validated by ARGO float data.An example of this validation is shown in Fig. 2, for years 2005 and 2008.The model tends to slightly overestimate the MLD throughout the winter in both years but its time evolution is reasonably reproduced in both cases.There is no clear difference in the mixed layer evolution between the two years for both data and model.However, Argo-float data are sparse in space and the drift between subsequent profiles (up to 30 km) means they rarely profile the same water column twice (Smith et al., 2008).Furthermore, Argo floats drift with the prevailing currents and are found primarily in the southern and northern part of the bloom area during 2005 and 2008 respectively, along the path of the main cyclonic circulation.The northern sector is more directly exposed to the wind forcing than the southern side, suggesting that the representation of the mean mixed layer for the whole bloom area obtained from these locations is likely to be negatively/positively biased respectively in 2005/2008.
The absolute values of the MLD predicted by the model are in good agreement with those observed in past studies of deep water formation.In particular, the absolute magnitude of the marked interannual variations predicted by our model in both MLD and HF (Table 1) agree with those reconstructed by observations and numerical modelling by Mertens and Schott (1998) 2005), using the same MLD criteria used here.Nevertheless, in the climatology, a value as high as 960 m is reported in March for a grid element in front of the Gulf of Lions that roughly coincides with an area of well documented deep-water formation, often referred to as the MEDOC area (MEDOC, 1970).In this and other successive studies (Gascard, 1978;Marshall and Schott, 1999)  over the bloom area, the maximum variability in the timing of the bloom is lower for both series as can be observed in Table 1.In this case, the agreement between MODIS and simulated data is generally good except for 2009 when a transient increase in MODIS chlorophyll, on the third week, is wrongly interpreted as the onset of the bloom by our chosen criteria.
MLD and HF show evident interannual variability with years characterized by a less severe heat loss having shallower MLD and vice versa (Table 1).The average heat loss over the 9 yr period is −86 W m −2 .We use this value as a threshold to separate cold from warm years.During cold years (2005,2006,2009,2010), the onset of the bloom tends to occur later than during warm years (2002,2003,2007,2008).The same separation holds if the MLD is considered instead of HF.Mean phytoplankton biomass (PHY) and primary production (PP) show lower values during cold years while the export flux (EF) does not show the same behavior.Higher than average values of EF occur during both warm (i.e.2008) and cold (i.e.2006) years as well as for lower than average EF values (i.e. 2007 and 2005).We consider a comparison between years 2005 and 2008 as an example of interannual variability.The two years differ strongly in the mean MLD (57 %) and HF (56 %), as well as in bloom dynamics (Fig. 3).
The PP is fairly constant throughout the winter and tends to increase during the spring-bloom as can be observed for years 2005 and 2008 in Fig. 5.In both years (2005 and 2008) the peaks of EF are always associated to a sudden deepening of the mixed layer caused by a wind episode and the associated heat loss (Figs. 5 and 6).The vertical mixing redistributes the upper water column properties at depth resulting in a net downward transport of organic matter.This seems to affect the PP only partially, as PP never goes below a background value close to the winter average.The model estimates a mean winter PP (December-February) ranging from 0. In Fig. 7 we show the cumulative export flux for years 2001 to 2010, the 10 yr mean, and the maximum range of interannual variability calculated as the difference between the year with the highest value and the year with the lowest value (at each day).The cumulative EF grows throughout the winter and stabilizes in April as vertical mixing decreases.The final maximum range of interannual variability is around 800 mmol N m −2 (∼66 % of the final mean accumulated EF), half of which is accumulated during December and the other half during March.Although the cumulative EF keeps growing during January and February, the maximum range of interannual variability is almost constant during this period (dotted line, Fig. 7).We focus the discussion on the export flux, excluding the contribution from December because this is likely to be affected by the model overestimation of phytoplankton biomass during this period.

Discussion
Cold years tend to have a deeper mixed layer and a later bloom onset date.This relationship seems to agree with the winter preconditioning effect postulated by Henson et al. (2006) in the sense that a deeper mixed layer would take longer to re-stratify and thus would result in a later bloom.However, pulses of high primary production have often been observed in absence of thermal stratification (Townsend et al., 1992;Eilertsen, 1993;Dale et al., 1999;Koertzinger et al., 2008) demonstrating that a shallow mixed layer is not a necessary condition for a bloom to start.Huisman et al. (1999)

Conclusions References
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Full more recently Taylor and Ferrari (2011) related the beginning of the bloom to a critical threshold of turbulent diffusivity coinciding with the decrease of the heat loss to the atmosphere.Crucial to their analysis is the distinction between a mixed layer with a uniform density and a mixing layer with a uniform density and active turbulence (Brainerd and Gregg, 1995).In other words, there is a time-lag between the shutting off of the heat loss from the sea surface and the re-stratification.During this time the low active turbulence allows an increase in the average time of exposure of phytoplankton to light even if the mixed layer is still deep.Our results show that the close-to-zero heat flux is indeed a better estimator than the mixed layer depth for the bloom timing (Fig. 8).
Although we do not explicitly calculate the Sverdrup's critical depth, Fig. 8 shows how the bloom can start when the mixed layer is several hundred meters deep but the heat flux is always approaching zero.As a consequence we notice that there would be no preconditioning effect on the timing of the bloom since this seems to be independent from the depth of the mixed layer.In our example, winter 2005 is colder than winter 2008 and a higher portion of the winter is characterized by intense wind forcing, higher heat loss and hence a deeper mixed layer.In winter 2008 a less intense storminess both decreases the mean MLD and increases the probability of an early onset of the bloom.We suggest then that Figures a deeper mixed layer and a later bloom are both consequences of a long and intense winter forcing but are not directly related as the maximum MLD has no direct influence on the timing of the bloom.
Our model results suggest that the frequency of wind episodes regulates the intensity of blooms (Figs. 5 and 6).In general, weather conditions tend to improve with the transition from winter to spring.However, as pointed out by Waniek (2003), this is not a smooth transition and passing weather systems may interrupt the development of the bloom by mixing the phytoplankton at depth.For example, in 2008 (Fig. 5) the spring bloom is interrupted by two main wind episodes at the beginning and at the end of March.These two events act as a control on the maximum biomass accumulation at the surface, by physically transporting phytoplankton at depth and by decreasing their average light exposure thus limiting growth.By contrast, a relatively calm weather period following the onset of the 2005 spring bloom allows phytoplankton to grow undisturbed and reach higher concentrations than in 2008.As a consequence of these results and following on the previous part of the discussion about the timing of the bloom, we posit that wind-induced mixing during the bloom period is a key forcing agent contributing to interannual variability in both the intensity and timing of the blooms, in agreement with the satellite chlorophyll analysis performed by Ueyama and Monger (2005) for the North Atlantic.
Model results indicate that the export flux is driven by the combination of available surface biomass and vertical mixing.About half of the maximum range of interannual variability in EF is accumulated in March (Fig. 7).In particular, the interruptions of the bloom as those observed in 2008 are associated to the peaks in EF that are responsible for this half of the interannual variability.During January and February, EF stays at a background level, very close to PP indicating that mixed conditions are favorable to an efficient transport of organic matter at depth.No interannual variability is added during these two months because those years characterized by more intense winter mixing (i.e.2005) tend to have lower biomass at the surface than those years characterized by a shallower winter mixed layer (i.e.2008).

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Full Since EF is driven by the combination between biomass availability at the surface and vertical mixing, the result is a compensation that leads to an almost year-to-year constant winter EF.
We have found that the separation between cold and warm years does not apply for EF.However, the portion of interannual variability in EF, accumulated in March (about half of the total), is determined by the interannual variability in wind forcing during this month.If we consider the frequency of windy days during March, calculated as the percentage of days with average wind above the 10-yr average mean daily value for the same month, this correlates well (r = 0.9, p < 0.01) with the March mean daily EF (Fig. 9).Therefore, March is a key period during which a significant part of the interannual variability in the total EF is determined.This is because the range of variability in the date of the bloom onset is centered on the first week of this month (week 8.4) amplifying the effect of the interannual variability of wind-induced mixing episodes on EF.In other words, the bloom has already started during, at least, a part of March, every year.This means that there is abundance of surface biomass to be exported at depth by eventual wind-driven mixing episodes.
Importantly, our results suggest that satellite chlorophyll could be used to identify years with higher EF.Counterintuitively, years with a bloom of intermittent nature characterized by low maximum chlorophyll concentrations are likely to also be years of high EF while years characterized by an intense uninterrupted bloom would have lower EF.
The bloom area considered in this study lies between 40.5 • N and 44 behaviors ranging from the southern subpolar up to the transitional.We therefore emphasize the relevance of our results also for an important portion of the North Atlantic where high interannual variability has been observed in the timing and intensity of the spring bloom (Henson et al., 2009;Ueyama and Monger, 2005).Shifts in storm tracks and modes of atmospheric circulation are responsible for the interannual variability in the passage of weather systems.The transition to springtime is a critical moment when the passage of these weather systems is able to modulate bloom dynamics and consequently the vertical export of organic matter.

Conclusions
Model results show a clear connection between the year-to-year variability of the spring phytoplankton bloom and the year-to-year variability of the vertical export flux of organic matter.Late blooms and deep mixed layers are both the result of intense wind forcing but are not necessarily related to each other.The close-to-zero surface heat flux seems to be a better predictor for the bloom timing than the onset of stratification.The bloom onset is centered, on average, on the first week of March with earlier blooms starting Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | showed how storm-induced variations Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |MLD is calculated (in both data and model) as the depth at which potential temperature or potential density vary by more than ∆T = 0.2• C or ∆σ θ = 0.03 kg m −3 relative to their values at 10 m depth as inde Boyer Montegut et al. (2004).The model output is sampled at the location and day of each valid Argo-float profile to allow model-data comparison (Fig.2).We use chlorophyll level-3 8-day composite maps from sensor Aqua-MODIS (2009.1 Ocean Color Reprocessing) obtained from the NASA Ocean Color Home Page.Images are interpolated to the model grid because their resolution (∼1/16 pixel km −2 ) is higher than that of the model (∼1/23 pixel km −2 ).The data series obtained spans from June 2002 to December 2010 for a total of 391 maps.The surface chlorophyll estimated by the model is averaged at 8-day intervals to match the MODIS data series.
The net heat flux (HF) represents the sum of shortwave and longwave radiation, latent and sensible heat assuming the positive sign for heat gained by the ocean.Wind speed (WS) is the magnitude of the resultant of the meridional and zonal components of the Introduction Discussion Paper | Discussion Paper | Discussion Paper | Corsican currents as described by Taupiere-Letage and Millot (1986).In the RioMDT the northern current is clearly visible along the northern coast from Italy up to the Discussion Paper | Discussion Paper | Discussion Paper | for the period 1969-1994.The model winter MLD for the Discussion Paper | Discussion Paper | Discussion Paper | bloom area is deeper than the Mediterranean Sea monthly climatology elaborated by D'Ortenzio et al. ( the authors observed deep convection and a complete homogenization of the water column down to the bottom (>2000 m) over an area of 50-100 km in diameter.The model simulates deep homogenization of the water column also in the Ligurian subbasin, on the northeastern side of the bloom area.Recently, Smith et al. (2008) showed evidence of deep convection in the Western Ligurian subbasin during winter 2006 and in the Catalan Sea during winter 2005, both locations outside of the MEDOC area.Moreover, Hong et al. (2007) reported results from a numerical simulation showing how deep convection can extend into the Ligurian subbasin.Surface chlorophyll estimated by the model and by MODIS averaged over the bloom area is shown in Fig. 3.The timing and intensity of the spring bloom is well captured by the model although the yearly maximum concentration is systematically underestimated.The interannual variability that determines the differences in the shape of the bloom seems to be reasonably captured by the model as the modest discontinuous blooms of 2003, 2007, and 2008 are clearly distinguishable from the shorter, more intense blooms of 2005, 2006 and 2010.In general, the model tends to overestimate surface chlorophyll during December, simulating a fall peak that is not observed in MODIS data.The maximum range of variability in the timing of the bloom is shown for MODIS and model chlorophyll in Fig. 4. The bloom area is superimposed in both maps and shows, in the case of MODIS data, a strict coincidence with an area characterized by variability higher than 7-8 weeks.The model depicts a similar pattern, though more heterogeneous, with higher values (∼10 weeks) at the NE and SW sides and lower values (∼5-6 weeks) in the center of the bloom area.When chlorophyll is averaged Discussion Paper | Discussion Paper | Discussion Paper | 7 g C m −2 d −1 (2010) to 1.2 g C m −2 d −1 (2007) within the range of 0.1-2 g C m −2 d −1 measured by Mor án and Estrada (2005) in winter for the NW Mediterranean.The simulated export flux are comparable to sediment trap data collected in the bloom area.Lee et al. (2009) reported a mean daily export of organic carbon of Introduction the period March-May 2003 at 238 m depth at the DYFAMED station in the northeastern sector of the bloom area.The model estimates a mean EF of particulate organic carbon of ∼40 g C m −2 d −1 at the same depth, location and for the same period.Data from a neighboring area but from sediment traps deployed just below the euphotic zone (80 m) were presented byMiquel et al. (1994) for the period between mid April 1987 and mid November 1988.The authors reported for the second half of April 1987 a mean export of ∼4 mg N m −2 d −1 .The model estimate for the same period averaged over the 10 yr of the simulation gives ∼6.4 mg N m −2 d −1 .
Discussion Paper | Discussion Paper | Discussion Paper | Our examples from 2005 and 2008 are illustrative (Figs. 5 and 6).At the time of the bloom onset in 2005 the mean MLD is roughly twice deeper than in 2008 (∼800 m and ∼400 m, respectively) while the heat flux is symmetrically distributed around zero (∼+50 W m −2 and ∼−50 W m −2 , respectively).In both cases the bloom starts during a period of low wind forcing but 3 weeks later in 2005 than in 2008.In 2005 there are no low wind periods throughout the winter, except for a few days around mid January characterized, however, by intense heat loss and thus intense convective mixing.The bloom will start much later, by mid March, when a drastic decrease in wind together with an increase in solar radiation result in a sign inversion in the heat flux and a marked drop in the turbulent diffusivity.The same mechanism occurs in 2008 but 3 weeks earlier.
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | • N. Henson et al. (2009) defined a transition zone in the North Atlantic between 40 • N and 45 • N, based on the significance of the temporal correlation between weekly SeaWiFS chlorophyll concentration and MLD estimated from optimally interpolated Argo float data.North/south of this transition zone the correlation was negative/positive as expected for a subpolar (light limited)/subtropical (nutrient limited) environment.The same correlation for our model results (not shown) shows a variable (∼0-0.5),primarily negative correlation in the bloom area.This suggests that this area encompasses a variety of Introduction Discussion Paper | Discussion Paper | Discussion Paper | during low-wind periods in February.The frequency of wind episodes is a key factor controlling the onset and the following development of the bloom.The passage of weather systems in the transition from winter to spring can interrupt the development of the bloom by actively mixing phytoplankton at depth.This results in a net vertical export of organic matter, driven by a combination of surface biomass availability and vertical mixing.Since the bloom has already started during at least some part of March each year, the frequency of wind-driven mixing episodes during this month has a strong impact on the winter-spring accumulated export flux.Our simulation shows that at least half of the maximum interannual variability in this flux is determined during March.Importantly, our results show that years with less intense and discontinuous blooms are likely to have higher export flux than years with intense uninterrupted blooms.Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 2 .
Fig. 2. Comparison between the mixed layer depth estimated from Argo floats data (circles) and that estimated by the model (asterisks) for the years 2005 and 2008.In the above panels the positions of the floats are displayed.

Fig. 3 .
Fig. 3. MODIS and model chlorophyll concentration averaged over the area of the bloom.Only the period from 1 December to 31 May is shown for each year.As a consequence, the two series are not continuous and the gray vertical bars represent the interruptions (from 31 May to 1 December).

Table 1 .
Mean Mixed Layer Depth (MLD), mean daily vertically integrated nitrogen phytoplankton biomass (0-75 m, PHY) and primary production (0-75 m, PP), mean daily organic nitrogen export flux at 75 m depth (EF), mean daily neat heat flux (HF), mean daily wind speed (WSP), day of the maximum MLD, week of the bloom start for the model and for MODIS.
Fig. 1.Mean dynamic topography and geostrophic currents associated for the model (left) and Rio et al. (2007), (right).The bloom area is superimposed (red contour).