- Email: [email protected]
The influence of oceanic convection in primary production
Ecological Modelling 138 (2001) 115– 126 www.elsevier.com/locate/ecolmodel
The influence of oceanic convection in primary production Henning Wehde a,*, Jan O. Backhaus b, Else Nøst Hegseth c a
Institute of Oceanography, Uni6ersity of Hamburg, Troplowitzstr. 7, D-22529 Hamburg, Germany b Oceanography Laboratories, Uni6ersity of Li6erpool, Li6erpool L69 3BX, UK c The Norwegian College of Fisheries Science, Uni6ersity of Tromsø, N-9037 Tromsø, Norway
Abstract The influence of Oceanic Convection in Primary Production was investigated by both, numerical model studies and field observations. Cruises with RV VALDIVIA were conducted in the North Atlantic/Nordic Seas in Spring with the purpose of investigating a hypothesised relationship between Oceanic Convection and phytoplankton dynamics in winter in open oceans. In the ocean phytoplankton would sink down into deep waters after the breakdown of the seasonal thermocline in autumn. The mechanism that in spring reliably initiates phytoplankton blooms by bringing cells back to the surface has yet only rarely been investigated. The orbital motions of the water caused by Convection carries plankton up and down. Cells may therefore intermittently get back to the surface to receive enough light to stay alive during a winter. During VALDIVIA Cruise 176 (March 1999) a YOYO-station, covering 16 profiles measured every hour were conducted, which showed a high temporal variability of convective penetration. A phytoplankton model was coupled to a 2.5 dimensional non-linear, non-hydrostatic Convection model. In the first numerical study plankton was simulated by an Eulerian approach, in which plankton was introduced as an Eulerian tracer to investigate the temporal variability of the water column observed during the YOYO-station. The aim of the second numerical study is the provision of quantitative estimates of CONTACT times of water parcels, i.e. plankton that was carried by the water motions, with the uppermost water column, where light is available for growth. This was done by a Lagrangian approach in which plankton ensembles are simulated by Lagrangian tracers and a realistic stratification obtained during RV VALDIVIA Cruise 141 is prescribed as background field. In both cases the model domain is a vertical ocean slice. Horizontal dimensions of the model domain are chosen in accordance with expected convective aspect ratios, which vary between 1 and 3. Special attention was paid on the influence of Convection on the temporal variability of Chlorophyll a content in the water column. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Numerical modelling; Dispersion of phytoplankton; Phytoplankton spring bloom; Temporal variability
1. Introduction
* Corresponding author. E-mail address: [email protected] (H. Wehde).
Phytoplankton plays an important role in the productivity of the higher trophic levels (e.g. Townsend et al., 1994). For zooplankton, especially Calanus finmarchicus one of the important
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species in the northern pelagic systems, the availability of phytoplankton is necessary for production. After the erosion of the seasonal thermocline in autumn in the ocean phytoplankton sink down into the deep waters during a winter period. Typical sinking rates of marine phytoplankton, mostly diatoms, cover a wide range from a few meters up to several hundred meters per day (Smayda, 1970; von Bodungen et al., 1981; Billett et al., 1983; Platt et al., 1983; Passow, 1991). Cells might sink during a winter season to the depth of thousand meters in the deep ocean and consequently would not be available in the upper water column. The mechanism that reliably maintains cells into the upper water column has yet only been rarely investigated. New investigations show that this mechanism is the open ocean Convection (Backhaus et al., 1999). In the open oceans winter Convection, driven by a negative buoyancy of waters at the sea surface, which results from a cooling of the ocean may penetrate down to the depth of the perennial thermocline. This thermocline is situated at depths of several hundred meters, i.e. well beneath the surface Ekman layer. In the North Atlantic, for instance, Sub-polar Mode Water masses are formed in winter by Convection in the vicinity of the polar front (McCartney and Talley, 1982; van Aken and Becker, 1996). These waters may cover the upper 200– 600 m of the water column. On a shelf Convection may penetrate to the seabed, thereby affecting the entire water column. The sinking of water masses, however, is compensated due to the conservation of mass by an upward motion. Convective dynamics can be visualised by vertical orbital cells, which cover the entire convective mixed layer. Typical downward velocities in a fully developed Convection cell may be in the order of 10 cm s − 1, whereas upward motions are generally less energetic 5 cm s − 1 and cover a larger area in the horizontal. The aspect ratio of Convection (Ka¨ mpf and Backhaus, 1998), i.e. the relation between the horizontal separation of plumes and their vertical extent, has been found to be in the order of 1:3 (vertical versus horizontal scale). Detailed studies of Oceanic Convection in the open water column were conducted by Backhaus
(1995), Backhaus and Wehde (1997), Ka¨ mpf and Backhaus (1998) and Backhaus and Ka¨ mpf (1999). For an overview of the present knowledge about Convection see Marshall and Schott (1999). Plankta within the upper water column affected by Convection would accordingly be dispersed by the convective dynamics, covering the entire convectively mixed layer, which deepens during a winter. The orbital motion carries the plankta up and down. Cells therefore intermittently get back to the surface to receive enough light to stay alive during a winter. This investigation of the relationship between Oceanic Convection and phytoplankton dynamics was specially aimed at the Pre-bloom dynamics of phytoplankton in order to better understand the factors controlling the Primary Production.
2. Materials and methods
2.1. Obser6ations and data To investigate the hypothesised relationship between Oceanic Convection and Primary Production, which we call Phyto-Convection (Backhaus et al., 1999) and to extend the hypothesis to the open ocean Cruises with RV VALDIVIA (Backhaus, 1999a,b) were conducted in Spring 1999. The Cruises covered a nearly meridional section through the northern North Atlantic and Nordic Seas, running from 52 to 75°N, avoiding shallow areas and topographic structures which may cause upwelling phytoplankton. A YOYO-station at 58°N, 24° 25.0 W covering 16 CTD-casts measured every hour was conducted to receive informations about the highly temporal variability of the water column during active Oceanic Convection. Observations on both Cruises were carried out with a rosette sampler, which incorporated a CTD with an optical fluorescence sensor. Biological samples from the upper thousand meters were taken. Due to low winter concentrations of plankton five CTD-casts, each with 170 l water, were necessary to obtain enough water from different depths to ensure sampling of a sufficient amount of phytoplankton cells. The water was filtered through a net (mesh size 25 mm) on the deck,
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thereby concentrated to a sample of 250 ml. Water for a biomass profile from the entire water column was collected with an additional CTDcast. These data served to calibrate the optical fluorescence sensor mounted on the CTD. Water from each cast was also used for a calibration of the CTD. A shipborne meteorological station monitored 3 hourly meteorological parameters that were used to force the model. For the second numerical study we have used a T, S-Profile obtained from RV VALDIVIA Cruise 141 (Quadfasel, 1994) for the prescribed background field and 6-h meteorological data provided by the ECMWF (European Centre for Medium Range Weather Forecast) for the atmospherical forcing of the model.
2.2. The coupled phytoplankton con6ection model (PCM) A coupled phytoplankton Convection model (PCM) (Backhaus et al., 1999; Wehde and Backhaus, 2000) was applied to investigate the relationship between Oceanic Convection and Primary Production. Special attention was paid to the temporal highly variable water column that is influenced by active Convection. The non-hydrostatic, 2.5-dimensional ocean model, which is based on the non-linear, primitive Boussinesq equations for an incompressible fluid and further details about its numerical scheme are described in detail in Ka¨ mpf and Backhaus (1998). The model utilises the equidistant numerical Arakawa C grid (Mesinger and Arakawa, 1975). In contrast to previous Convection studies, which considered the rotational phase of Convection (see Marshall and Schott, 1999), our grid is isotropic to avoid any distortions of convective dynamics. The model domain is a vertical ocean slice assuming vanishing normal gradients of all variables. The time step depends on the courant number of the applied explicit numerical advection scheme for both momentum and water mass properties and lies in the range 5– 45 s for the experiments discussed below. Cyclic boundary conditions at the open lateral boundaries of the model domain are applied, thereby excluding lateral advection by the large-scale flow. Indepen-
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dent conservation equations for heat and salt are linked to the momentum equations via a non-linear equation of state (International association for the physical sciences of the ocean, IAPSO Working Group, 1981). The model predicts the spatial and temporal evolution of T, S (density), non-hydrostatic pressure and flow fields from an initial horizontally homogeneous temperature and salinity profile. The turbulent eddy viscosity, and diffusivity, in the ocean model are parameterised by a simple diagnostic one-equation turbulence closure scheme (Kochergin, 1987; Backhaus, 1995). Coefficients for turbulent exchange of momentum and diffusion of water mass properties are assumed equal. The validity of this concept is confirmed by our previous Convection studies (Backhaus and Wehde, 1997; Backhaus and Ka¨ mpf, 1999; Ka¨ mpf and Backhaus, 1999). The high spatial and temporal resolution of the model allows to resolve a good deal of the turbulent spectrum that is usually parameterised in larger scale models. The ocean model is forced with fluxes of momentum and heat computed from bulk formulae (Gill, 1982). For the computation of the heat flux the sea surface temperature (SST), predicted by the model, and prescribed atmospheric data (air temperature, humidity, wind speed, and cloudiness) are used. The thermodynamic forcing comprises sensible and latent heatfluxes and short- and long-wave radiation (Friehe and Schmitt, 1976). The phytoplankton model is described in detail in Backhaus et al. (1999) and Wehde and Backhaus (2000). Therefore only a brief description is given here. The phytoplankton model applied in this study is based on the phytoplankton model developed by Moll (1995, 1998). The model predicts changes on phytoplankton stock due to gross Primary Production, respiration, mortality and grazing. We created a process-study void of any second order effects by reducing our model to essential mechanisms only. In our simple model respiration, mortality and grazing are assumed proportional to the phytoplankton stock. Following Liebig’s law the gross Primary Production is calculated from the minimum of the limitation functions for light and nutrients. We used Steele (1962) formulation for underwater light intensity
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including photoinhibition as limitation function for light. The amount of incoming short wave solar radiation depending on time, latitude, and observed local cloudiness, is calculated after Dobson and Smith (1988). The Michaelis– Menton relationship is applied to describe nutrient limitation. The sinking of tracers representing spores was set to a constant rate of 120 m per day, in order to simulate observed sinking rates of diatom spores (Degens, 1989). Vegetative cells are simulated by reducing the sinking velocity of tracers to 1 m per day (Moll, 1995). The ecological parameters used in this study are listed in Table 1.
2.3. Experimental set-up Experiments with the PCM were conducted to study the influence of Convection in Primary Production. In the first experiment (henceforth indicated by YOYO) we followed the conditions of the YOYO-station observed during the spring Cruise 1999. Here the phytoplankton was modelled with an Eulerian approach. The second experiment (henceforth indicated by CONTACT) was initialised by a T, S-Profile obtained during RV VALDIVIA Cruise 141 and the plankton was simulated by the Lagrangian approach. The vertical respectively, the horizontal dimensions of the ocean slice must be chosen in dependence to the expected aspect ratio, in order to account for a process-oriented spatial resolution of Convection. For experiment YOYO we used a model domain of 500 m for the vertical and 3000 m for the Table 1 Ecological parameters used in the coupled model Quantity Optimum light intensity Extinction coefficient Maximum growth rate of phytoplankton Sinking velocity of spores Mortality rate Grazing rate Respiration rate Phosphate half saturation constant
Value 46 0.09 1.5 120 0.05 0.5 0.06 0.06
Unit W m−2 m−1 day−1 m day−1 day−1 day−1 day−1 mmol PO4–P m−3
horizontal dimension, for experiment CONTACT 1500 m respectively, 14 000 m. In case of YOYO the ocean slice is resolved by an isotropic grid size of 5 m. During CONTACT we used a resolution of 10 m. For CONTACT a record of six hourly meteorological forcing were available from the ECMWF; for experiment YOYO we used 3 hourly data, which are monitored with the shipborne meteorological station. The YOYO-run was initialised with the observed T, S-profile (Fig. 1). For this experiment we defined that the plankton concentration of 100 within the mixed layer (the upper 300 m of the water column) and beneath we set it to zero. The prescribed profile served as initialisation for a process-study, which was conducted with the intention to simulate typical conditions in stratification and vertical displacement of tracer during active Oceanic Convection. This profile is prescribed for the entire model domain as initial condition implying homogeneity in the horizontal. Experiment CONTACT was initialised by a T, S-profile (Fig. 8) obtained during RV VALDIVIA Cruise 141. The applied cyclic boundary conditions account for a closed system; it excludes lateral advection and allows investigating convective modification of the water column in isolation. In all experiments the model was dynamically initialised from a state of rest. In regard to Lagrangian transport the CONTACT experiment were initialised by a 700 m thick surface layer in which tracers were evenly distributed. A number of 105 631 tracers were considered in the experiment. A high number of tracers were chosen to ensure a high resolution in our dispersion study. Based upon our previous experience in Convection modelling (Backhaus, 1995; Ka¨ mpf and Backhaus, 1998; Backhaus et al., 1999) we expected a high temporal and spatial variability of tracer distributions as a consequence of the complex convective dynamics.
3. Results
3.1. Experiment YOYO The aim of the experiment YOYO was to ex-
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plain and to understand the mechanism, which leads to the development of the water column during active convective conditions. For an overview of the transformation, which took place during the station, a couple of profiles were shown in the Figs. 1– 4. Starting with the Fig. 1, which shows the water column at the 8th of March 1999 at 14:30 h the relatively homogeneous water column, shows a high variability during the further course of the station, which is caused by the onset of Oceanic Convection. Fig. 2 displays the profile, which was measured at midnight. This profile is characterised by a strong minima in Chlorophyll a content at 300 m water depth. Beneath this minimum down to the bottom of the mixed layer and above up to the surface there was a higher Chlorophyll a content observed. Four hours later the position of the water with low Chlorophyll a content has changed (Fig. 3). Now the minimum is located at 200 m depth. A decreasing tendency in differences of the water masses could be observed. This tendency was remained during the following profiles and at the end of the YOYO-station only small differences were observed. Also a warming of the uppermost water column has taken place (Fig. 4 10:00 h). This warming during the day allows an increased plankton growth in the small thermocline, which is now established. During the next night the new onset of Convection may lead to another distribution of newly produced biomass down into the water column. The numerical model study YOYO supported the hypothesis that the observed transformations at the YOYO station were caused by Oceanic Convection. Forced by the measured meteorology the model predicted qualitatively same results as measured during the station. In Fig. 5 the predicted concentration of plankton after 24 simulation hours was displayed. Remember that the content within the mixed layer was defined as 100 and beneath as 0 and that in the simulation the ocean starts at rest, which explains delay in time of the model. The model predicts water with low Chlorophyll a content that is lifted up into the upper part of
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the mixed layer. The results show the high variability in both horizontal and vertical scale. In the further course of the model experiment the ongoing Convection leads to a homogenisation of the water column, which is shown in Fig. 6, only at few positions the strong gradients are predicted now. In Fig. 7 selected profiles from the ocean slice were displayed to show the high spatial variability more clear. At some positions of the ocean slice we have homogeneous distributions as we observed during the end of the YOYO-station and some showed the high differences in the vertical Chlorophyll a content.
3.2. Experiment CONTACT The goal of this study is the provision of quantitative estimates of CONTACT times of tracers, i.e. plankton with the uppermost water column to improve the hypothesis that the plankton could stay alive during the winter months under active oceanic convective conditions. A realistic initial stratification observed on the RV VALDIVIA Cruise 141 at station 8 (Fig. 8) is prescribed as backround field. The simulation cover a period of 33 days. Transient atmospheric forcing is determined from ECMWF-data. The atmospheric forcing leads to a mean heat loss of 599.7 W m − 2 of the ocean during the simulation period. These high loss rates erode the initial polar surface layer within the first 10 days of the simulation, which is shown in Fig. 9. This dramatic water mass transformation continues during the following simulation days and leads due to the persistent heat loss of the ocean which is caused by strong winds and very low air temperatures at these period of the year in the central Greenland Sea to an penetration depth of convetion down to 1300 m during the following 20 days (Fig. 10). The tracers, which were introduced into the water column, are now affected by the orbital convective motions and dispersed within the mixed layer. This orbital motions cause a frequent return of the tracers into the euphotic layer and so they are able to receive light for growth. The duration for each
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Fig. 1. T, S-Profile measured at Station 5, the station which was followed by the YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 24° 25.00 W, Date: 8th of March, 14:30 h.
Fig. 2. T, S and Chlorophyll a Profile measured at YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 24° 25.00 W, Date: 9th of March, 0:00 h.
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Fig. 3. T, S and Chlorophyll a Profile measured at YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 24° 25.00 W, Date: 9th of March, 4:00 h.
Fig. 4. T, S and Chlorophyll a Profile measured at YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 240 25.00 W, Date: 9th of March, 10:00 h.
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CONTACT with the uppermost water column is about 240 min and varies by only 20% over the simulation period (Fig. 11). The highly variable penetration depth of Convection seems to have no influence in the duration of tracer’s staying near the ocean surface (Fig. 11). Due to the larger orbital motions only the travel time from one to the other CONTACT has been enlarged.
4. Conclusions Our observations along the meridional section and the results, which we have obtained with the numerical model studies, confirmed the existence of Phyto-Convection (Backhaus et al., 1999). The relatively high concentrations of phytoplankton observed at great depths in winter, i.e. well beneath the wind mixed Ekman layer, can only be caused by convective dynamics. This was confi-
rmed by modelling studies, which we conducted for oceanic stratification and atmospheric conditions observed during RV VALDIVIA Cruises (Backhaus, 1999a,b; Quadfasel, 1994) and by the results presented in this investigation. Without exceptions all CTD-casts measured during the spring RV VALDIVIA Cruises contained water rich of Chlorophyll a within the convective mixed layer. The observed concentrations were in the range between 0.05 and 0.7 mmg m − 3. In the mean 95% of the Chlorophyll a content was located within the convective mixed layer whose bottom was defined by the so called 0.5° criterion (You, 1995). The Chlorophyll a values beneath the thermocline were at the lowest level, which can be detected by the fluorimeter. Only plankton within the mixed layer can receive enough light to stay alive during winter, caused by the intermittently return
Fig. 5. Predicted tracer — concentration after 24 simulation hours for run YOYO.
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Fig. 6. Predicted tracer — concentration after 48 simulation hours for run YOYO.
winter could be regarded as the prebloom phase of phytoplankton, which plays the essential role in the lifecycle of Calanus finmarchicus as reported by Niehoff et al. (1999).
Acknowledgements
Fig. 7. Selected Predicted Profiles from the ocean slice of tracer-concentration after 24 simulation hours run YOYO. Position of Profiles in the model slice at: A = 250 m, B= 1450 m and C = 2700 m.
to the surface due to the convective orbital motions. According to our theory of Phyto-Convection in the North Atlantic Ocean the entire
This work was partly funded by the Deutsche Forschungsgemeinschaft (SFB 512) and, within the TASC project, by the European Commission under contract MAS3-CT95-0039. In this investigation we have used model components, which were developed with partial support from the Deutsche Forschungsgemeinschaft (DFGSFB318) and the European Union (DG-XII, MAST II and III), within the European Sub-Polar Ocean Project (ESOP-1 and ESOP-2) (MAS2-CT93-0057 and MAS3-CT95-00 15). We would like to thank the Captains and Crews of RV VALDIVIA for their perfect support during our field surveys.
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Fig. 8. Initial T, S Profile for simulation CONTACT, obtained during station 8 RV VALDIVIA Cruise at 75.00°N and 2° 30.00 W, Date: 16th of February, 22:30 h.
Fig. 9. Predicted temperature after 10 simulation days, run CONTACT.
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Fig. 10. Predicted temperature after 30 simulation days, run CONTACT.
Fig. 11. Predicted mean CONTACT duration for tracer from various depth levels, run CONTACT.
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van Aken, H.M., Becker, G., 1996. Hydrography and through-flow in the north eastern North Atlantic Ocean: the NANSEN project. Prog. Oceanog. 18, 297 – 346. Backhaus, J.O., 1995. Prozess-studien zur Ozeanischen Konvektion. Habilitationsabhandlung. Inst. Meereskunde, Univ. Hamburg. In German. Backhaus, J.O., Ka¨ mpf, J., 1999. Simulations of sub-mesoscale oceanic Convection and ice-ocean interaction in the Greenland Sea. Deep-Sea Res. II 46, 1427 – 1455. Backhaus, J.O., Wehde, H., 1997. Convection in the Baltic Sea — a numerical process study. In: Ozsoy, E., Mikaelyan, A. (Eds.), NATO ASI-series: ‘Sensitivity to change: Black Sea, Baltic Sea and North Sea. Kluwer Academic Publcations, pp. 295 – 309. Backhaus, J.O., Wehde, H., Hegseth, E.N., Ka¨ mpf, J., 1999. ‘Phyto Convection’ — on the role of oceanic Convection in primary production. Mar. Ecol. Prog. Ser. 189, 77 –92. Backhaus, J.O., 1999. ‘Phyto Convection’ in the northern North Atlantic. Cruise Report of RV VALDIVIA Cruise c 176. Backhaus, J.O., 1999. Oceanic Convection in the Nordic Seas. Cruise Report of RV VALDIVIA Cruise c 178. Billett, D.S.M., Lampitt, R.S., Rice, A.L., Mantoura, R.F.C., 1983. Seasonal sedimentation of phytoplankton to the deep-sea benthos, vol. 302. Nature, London, pp. 520 –522. von Bodungen, B., von Bro¨ ckel, K., Smetacek, V., Zeitschel, B., 1981. Growth and sedimentation of the phytoplankton spring bloom in the Bornholm Sea (Baltic Sea). Kieler Meeresforsch. Sonderh. 5, 49 –60. Degens, E.T., 1989. Perspektives in Biogeochemistry. Springer Verlag, Berlin, Heidelberg. Dobson, F.W., Smith, S.D., 1988. Bulk models of solar radiation at sea. Q. J. R. met. Soc. 114, 165 – 182. Friehe, C.A., Schmitt, K.F., 1976. Parametrisation of air-sea interface fluxes of sensible heat and moisture by the bulk aerodynamic formulas. J. Phys. Oceanogr. 6, 801 – 809. Gill, A.E., 1982. Atmosphere Ocean Dynamics. Academic Press, San Diego, CA. IAPSO Working Group, 1981. The practical salinity scale 1978 and the international equation of state of seawater 1980, UNESCO Technical Papers in Marine Sci. 36, U.N. Educ. Sci. and Cult. Organ., Paris, pp. 124. Ka¨ mpf, J., Backhaus, J.O., 1998. Shallow, brine-driven free Convection in polar oceans: nonhydrostatic numerical process studies. J. Geophys. Res. 103 (C3), 5557 –5593. Ka¨ mpf, J., Backhaus, J., 1999. Ice-ocean interactions during shallow Convection under conditions of steady winds:
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The influence of oceanic convection in primary production Henning Wehde a,*, Jan O. Backhaus b, Else Nøst Hegseth c a
Institute of Oceanography, Uni6ersity of Hamburg, Troplowitzstr. 7, D-22529 Hamburg, Germany b Oceanography Laboratories, Uni6ersity of Li6erpool, Li6erpool L69 3BX, UK c The Norwegian College of Fisheries Science, Uni6ersity of Tromsø, N-9037 Tromsø, Norway
Abstract The influence of Oceanic Convection in Primary Production was investigated by both, numerical model studies and field observations. Cruises with RV VALDIVIA were conducted in the North Atlantic/Nordic Seas in Spring with the purpose of investigating a hypothesised relationship between Oceanic Convection and phytoplankton dynamics in winter in open oceans. In the ocean phytoplankton would sink down into deep waters after the breakdown of the seasonal thermocline in autumn. The mechanism that in spring reliably initiates phytoplankton blooms by bringing cells back to the surface has yet only rarely been investigated. The orbital motions of the water caused by Convection carries plankton up and down. Cells may therefore intermittently get back to the surface to receive enough light to stay alive during a winter. During VALDIVIA Cruise 176 (March 1999) a YOYO-station, covering 16 profiles measured every hour were conducted, which showed a high temporal variability of convective penetration. A phytoplankton model was coupled to a 2.5 dimensional non-linear, non-hydrostatic Convection model. In the first numerical study plankton was simulated by an Eulerian approach, in which plankton was introduced as an Eulerian tracer to investigate the temporal variability of the water column observed during the YOYO-station. The aim of the second numerical study is the provision of quantitative estimates of CONTACT times of water parcels, i.e. plankton that was carried by the water motions, with the uppermost water column, where light is available for growth. This was done by a Lagrangian approach in which plankton ensembles are simulated by Lagrangian tracers and a realistic stratification obtained during RV VALDIVIA Cruise 141 is prescribed as background field. In both cases the model domain is a vertical ocean slice. Horizontal dimensions of the model domain are chosen in accordance with expected convective aspect ratios, which vary between 1 and 3. Special attention was paid on the influence of Convection on the temporal variability of Chlorophyll a content in the water column. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Numerical modelling; Dispersion of phytoplankton; Phytoplankton spring bloom; Temporal variability
1. Introduction
* Corresponding author. E-mail address: [email protected] (H. Wehde).
Phytoplankton plays an important role in the productivity of the higher trophic levels (e.g. Townsend et al., 1994). For zooplankton, especially Calanus finmarchicus one of the important
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species in the northern pelagic systems, the availability of phytoplankton is necessary for production. After the erosion of the seasonal thermocline in autumn in the ocean phytoplankton sink down into the deep waters during a winter period. Typical sinking rates of marine phytoplankton, mostly diatoms, cover a wide range from a few meters up to several hundred meters per day (Smayda, 1970; von Bodungen et al., 1981; Billett et al., 1983; Platt et al., 1983; Passow, 1991). Cells might sink during a winter season to the depth of thousand meters in the deep ocean and consequently would not be available in the upper water column. The mechanism that reliably maintains cells into the upper water column has yet only been rarely investigated. New investigations show that this mechanism is the open ocean Convection (Backhaus et al., 1999). In the open oceans winter Convection, driven by a negative buoyancy of waters at the sea surface, which results from a cooling of the ocean may penetrate down to the depth of the perennial thermocline. This thermocline is situated at depths of several hundred meters, i.e. well beneath the surface Ekman layer. In the North Atlantic, for instance, Sub-polar Mode Water masses are formed in winter by Convection in the vicinity of the polar front (McCartney and Talley, 1982; van Aken and Becker, 1996). These waters may cover the upper 200– 600 m of the water column. On a shelf Convection may penetrate to the seabed, thereby affecting the entire water column. The sinking of water masses, however, is compensated due to the conservation of mass by an upward motion. Convective dynamics can be visualised by vertical orbital cells, which cover the entire convective mixed layer. Typical downward velocities in a fully developed Convection cell may be in the order of 10 cm s − 1, whereas upward motions are generally less energetic 5 cm s − 1 and cover a larger area in the horizontal. The aspect ratio of Convection (Ka¨ mpf and Backhaus, 1998), i.e. the relation between the horizontal separation of plumes and their vertical extent, has been found to be in the order of 1:3 (vertical versus horizontal scale). Detailed studies of Oceanic Convection in the open water column were conducted by Backhaus
(1995), Backhaus and Wehde (1997), Ka¨ mpf and Backhaus (1998) and Backhaus and Ka¨ mpf (1999). For an overview of the present knowledge about Convection see Marshall and Schott (1999). Plankta within the upper water column affected by Convection would accordingly be dispersed by the convective dynamics, covering the entire convectively mixed layer, which deepens during a winter. The orbital motion carries the plankta up and down. Cells therefore intermittently get back to the surface to receive enough light to stay alive during a winter. This investigation of the relationship between Oceanic Convection and phytoplankton dynamics was specially aimed at the Pre-bloom dynamics of phytoplankton in order to better understand the factors controlling the Primary Production.
2. Materials and methods
2.1. Obser6ations and data To investigate the hypothesised relationship between Oceanic Convection and Primary Production, which we call Phyto-Convection (Backhaus et al., 1999) and to extend the hypothesis to the open ocean Cruises with RV VALDIVIA (Backhaus, 1999a,b) were conducted in Spring 1999. The Cruises covered a nearly meridional section through the northern North Atlantic and Nordic Seas, running from 52 to 75°N, avoiding shallow areas and topographic structures which may cause upwelling phytoplankton. A YOYO-station at 58°N, 24° 25.0 W covering 16 CTD-casts measured every hour was conducted to receive informations about the highly temporal variability of the water column during active Oceanic Convection. Observations on both Cruises were carried out with a rosette sampler, which incorporated a CTD with an optical fluorescence sensor. Biological samples from the upper thousand meters were taken. Due to low winter concentrations of plankton five CTD-casts, each with 170 l water, were necessary to obtain enough water from different depths to ensure sampling of a sufficient amount of phytoplankton cells. The water was filtered through a net (mesh size 25 mm) on the deck,
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thereby concentrated to a sample of 250 ml. Water for a biomass profile from the entire water column was collected with an additional CTDcast. These data served to calibrate the optical fluorescence sensor mounted on the CTD. Water from each cast was also used for a calibration of the CTD. A shipborne meteorological station monitored 3 hourly meteorological parameters that were used to force the model. For the second numerical study we have used a T, S-Profile obtained from RV VALDIVIA Cruise 141 (Quadfasel, 1994) for the prescribed background field and 6-h meteorological data provided by the ECMWF (European Centre for Medium Range Weather Forecast) for the atmospherical forcing of the model.
2.2. The coupled phytoplankton con6ection model (PCM) A coupled phytoplankton Convection model (PCM) (Backhaus et al., 1999; Wehde and Backhaus, 2000) was applied to investigate the relationship between Oceanic Convection and Primary Production. Special attention was paid to the temporal highly variable water column that is influenced by active Convection. The non-hydrostatic, 2.5-dimensional ocean model, which is based on the non-linear, primitive Boussinesq equations for an incompressible fluid and further details about its numerical scheme are described in detail in Ka¨ mpf and Backhaus (1998). The model utilises the equidistant numerical Arakawa C grid (Mesinger and Arakawa, 1975). In contrast to previous Convection studies, which considered the rotational phase of Convection (see Marshall and Schott, 1999), our grid is isotropic to avoid any distortions of convective dynamics. The model domain is a vertical ocean slice assuming vanishing normal gradients of all variables. The time step depends on the courant number of the applied explicit numerical advection scheme for both momentum and water mass properties and lies in the range 5– 45 s for the experiments discussed below. Cyclic boundary conditions at the open lateral boundaries of the model domain are applied, thereby excluding lateral advection by the large-scale flow. Indepen-
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dent conservation equations for heat and salt are linked to the momentum equations via a non-linear equation of state (International association for the physical sciences of the ocean, IAPSO Working Group, 1981). The model predicts the spatial and temporal evolution of T, S (density), non-hydrostatic pressure and flow fields from an initial horizontally homogeneous temperature and salinity profile. The turbulent eddy viscosity, and diffusivity, in the ocean model are parameterised by a simple diagnostic one-equation turbulence closure scheme (Kochergin, 1987; Backhaus, 1995). Coefficients for turbulent exchange of momentum and diffusion of water mass properties are assumed equal. The validity of this concept is confirmed by our previous Convection studies (Backhaus and Wehde, 1997; Backhaus and Ka¨ mpf, 1999; Ka¨ mpf and Backhaus, 1999). The high spatial and temporal resolution of the model allows to resolve a good deal of the turbulent spectrum that is usually parameterised in larger scale models. The ocean model is forced with fluxes of momentum and heat computed from bulk formulae (Gill, 1982). For the computation of the heat flux the sea surface temperature (SST), predicted by the model, and prescribed atmospheric data (air temperature, humidity, wind speed, and cloudiness) are used. The thermodynamic forcing comprises sensible and latent heatfluxes and short- and long-wave radiation (Friehe and Schmitt, 1976). The phytoplankton model is described in detail in Backhaus et al. (1999) and Wehde and Backhaus (2000). Therefore only a brief description is given here. The phytoplankton model applied in this study is based on the phytoplankton model developed by Moll (1995, 1998). The model predicts changes on phytoplankton stock due to gross Primary Production, respiration, mortality and grazing. We created a process-study void of any second order effects by reducing our model to essential mechanisms only. In our simple model respiration, mortality and grazing are assumed proportional to the phytoplankton stock. Following Liebig’s law the gross Primary Production is calculated from the minimum of the limitation functions for light and nutrients. We used Steele (1962) formulation for underwater light intensity
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including photoinhibition as limitation function for light. The amount of incoming short wave solar radiation depending on time, latitude, and observed local cloudiness, is calculated after Dobson and Smith (1988). The Michaelis– Menton relationship is applied to describe nutrient limitation. The sinking of tracers representing spores was set to a constant rate of 120 m per day, in order to simulate observed sinking rates of diatom spores (Degens, 1989). Vegetative cells are simulated by reducing the sinking velocity of tracers to 1 m per day (Moll, 1995). The ecological parameters used in this study are listed in Table 1.
2.3. Experimental set-up Experiments with the PCM were conducted to study the influence of Convection in Primary Production. In the first experiment (henceforth indicated by YOYO) we followed the conditions of the YOYO-station observed during the spring Cruise 1999. Here the phytoplankton was modelled with an Eulerian approach. The second experiment (henceforth indicated by CONTACT) was initialised by a T, S-Profile obtained during RV VALDIVIA Cruise 141 and the plankton was simulated by the Lagrangian approach. The vertical respectively, the horizontal dimensions of the ocean slice must be chosen in dependence to the expected aspect ratio, in order to account for a process-oriented spatial resolution of Convection. For experiment YOYO we used a model domain of 500 m for the vertical and 3000 m for the Table 1 Ecological parameters used in the coupled model Quantity Optimum light intensity Extinction coefficient Maximum growth rate of phytoplankton Sinking velocity of spores Mortality rate Grazing rate Respiration rate Phosphate half saturation constant
Value 46 0.09 1.5 120 0.05 0.5 0.06 0.06
Unit W m−2 m−1 day−1 m day−1 day−1 day−1 day−1 mmol PO4–P m−3
horizontal dimension, for experiment CONTACT 1500 m respectively, 14 000 m. In case of YOYO the ocean slice is resolved by an isotropic grid size of 5 m. During CONTACT we used a resolution of 10 m. For CONTACT a record of six hourly meteorological forcing were available from the ECMWF; for experiment YOYO we used 3 hourly data, which are monitored with the shipborne meteorological station. The YOYO-run was initialised with the observed T, S-profile (Fig. 1). For this experiment we defined that the plankton concentration of 100 within the mixed layer (the upper 300 m of the water column) and beneath we set it to zero. The prescribed profile served as initialisation for a process-study, which was conducted with the intention to simulate typical conditions in stratification and vertical displacement of tracer during active Oceanic Convection. This profile is prescribed for the entire model domain as initial condition implying homogeneity in the horizontal. Experiment CONTACT was initialised by a T, S-profile (Fig. 8) obtained during RV VALDIVIA Cruise 141. The applied cyclic boundary conditions account for a closed system; it excludes lateral advection and allows investigating convective modification of the water column in isolation. In all experiments the model was dynamically initialised from a state of rest. In regard to Lagrangian transport the CONTACT experiment were initialised by a 700 m thick surface layer in which tracers were evenly distributed. A number of 105 631 tracers were considered in the experiment. A high number of tracers were chosen to ensure a high resolution in our dispersion study. Based upon our previous experience in Convection modelling (Backhaus, 1995; Ka¨ mpf and Backhaus, 1998; Backhaus et al., 1999) we expected a high temporal and spatial variability of tracer distributions as a consequence of the complex convective dynamics.
3. Results
3.1. Experiment YOYO The aim of the experiment YOYO was to ex-
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plain and to understand the mechanism, which leads to the development of the water column during active convective conditions. For an overview of the transformation, which took place during the station, a couple of profiles were shown in the Figs. 1– 4. Starting with the Fig. 1, which shows the water column at the 8th of March 1999 at 14:30 h the relatively homogeneous water column, shows a high variability during the further course of the station, which is caused by the onset of Oceanic Convection. Fig. 2 displays the profile, which was measured at midnight. This profile is characterised by a strong minima in Chlorophyll a content at 300 m water depth. Beneath this minimum down to the bottom of the mixed layer and above up to the surface there was a higher Chlorophyll a content observed. Four hours later the position of the water with low Chlorophyll a content has changed (Fig. 3). Now the minimum is located at 200 m depth. A decreasing tendency in differences of the water masses could be observed. This tendency was remained during the following profiles and at the end of the YOYO-station only small differences were observed. Also a warming of the uppermost water column has taken place (Fig. 4 10:00 h). This warming during the day allows an increased plankton growth in the small thermocline, which is now established. During the next night the new onset of Convection may lead to another distribution of newly produced biomass down into the water column. The numerical model study YOYO supported the hypothesis that the observed transformations at the YOYO station were caused by Oceanic Convection. Forced by the measured meteorology the model predicted qualitatively same results as measured during the station. In Fig. 5 the predicted concentration of plankton after 24 simulation hours was displayed. Remember that the content within the mixed layer was defined as 100 and beneath as 0 and that in the simulation the ocean starts at rest, which explains delay in time of the model. The model predicts water with low Chlorophyll a content that is lifted up into the upper part of
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the mixed layer. The results show the high variability in both horizontal and vertical scale. In the further course of the model experiment the ongoing Convection leads to a homogenisation of the water column, which is shown in Fig. 6, only at few positions the strong gradients are predicted now. In Fig. 7 selected profiles from the ocean slice were displayed to show the high spatial variability more clear. At some positions of the ocean slice we have homogeneous distributions as we observed during the end of the YOYO-station and some showed the high differences in the vertical Chlorophyll a content.
3.2. Experiment CONTACT The goal of this study is the provision of quantitative estimates of CONTACT times of tracers, i.e. plankton with the uppermost water column to improve the hypothesis that the plankton could stay alive during the winter months under active oceanic convective conditions. A realistic initial stratification observed on the RV VALDIVIA Cruise 141 at station 8 (Fig. 8) is prescribed as backround field. The simulation cover a period of 33 days. Transient atmospheric forcing is determined from ECMWF-data. The atmospheric forcing leads to a mean heat loss of 599.7 W m − 2 of the ocean during the simulation period. These high loss rates erode the initial polar surface layer within the first 10 days of the simulation, which is shown in Fig. 9. This dramatic water mass transformation continues during the following simulation days and leads due to the persistent heat loss of the ocean which is caused by strong winds and very low air temperatures at these period of the year in the central Greenland Sea to an penetration depth of convetion down to 1300 m during the following 20 days (Fig. 10). The tracers, which were introduced into the water column, are now affected by the orbital convective motions and dispersed within the mixed layer. This orbital motions cause a frequent return of the tracers into the euphotic layer and so they are able to receive light for growth. The duration for each
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Fig. 1. T, S-Profile measured at Station 5, the station which was followed by the YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 24° 25.00 W, Date: 8th of March, 14:30 h.
Fig. 2. T, S and Chlorophyll a Profile measured at YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 24° 25.00 W, Date: 9th of March, 0:00 h.
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Fig. 3. T, S and Chlorophyll a Profile measured at YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 24° 25.00 W, Date: 9th of March, 4:00 h.
Fig. 4. T, S and Chlorophyll a Profile measured at YOYO-station of RV VALDIVIA Cruise 176 at 58°N and 240 25.00 W, Date: 9th of March, 10:00 h.
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CONTACT with the uppermost water column is about 240 min and varies by only 20% over the simulation period (Fig. 11). The highly variable penetration depth of Convection seems to have no influence in the duration of tracer’s staying near the ocean surface (Fig. 11). Due to the larger orbital motions only the travel time from one to the other CONTACT has been enlarged.
4. Conclusions Our observations along the meridional section and the results, which we have obtained with the numerical model studies, confirmed the existence of Phyto-Convection (Backhaus et al., 1999). The relatively high concentrations of phytoplankton observed at great depths in winter, i.e. well beneath the wind mixed Ekman layer, can only be caused by convective dynamics. This was confi-
rmed by modelling studies, which we conducted for oceanic stratification and atmospheric conditions observed during RV VALDIVIA Cruises (Backhaus, 1999a,b; Quadfasel, 1994) and by the results presented in this investigation. Without exceptions all CTD-casts measured during the spring RV VALDIVIA Cruises contained water rich of Chlorophyll a within the convective mixed layer. The observed concentrations were in the range between 0.05 and 0.7 mmg m − 3. In the mean 95% of the Chlorophyll a content was located within the convective mixed layer whose bottom was defined by the so called 0.5° criterion (You, 1995). The Chlorophyll a values beneath the thermocline were at the lowest level, which can be detected by the fluorimeter. Only plankton within the mixed layer can receive enough light to stay alive during winter, caused by the intermittently return
Fig. 5. Predicted tracer — concentration after 24 simulation hours for run YOYO.
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Fig. 6. Predicted tracer — concentration after 48 simulation hours for run YOYO.
winter could be regarded as the prebloom phase of phytoplankton, which plays the essential role in the lifecycle of Calanus finmarchicus as reported by Niehoff et al. (1999).
Acknowledgements
Fig. 7. Selected Predicted Profiles from the ocean slice of tracer-concentration after 24 simulation hours run YOYO. Position of Profiles in the model slice at: A = 250 m, B= 1450 m and C = 2700 m.
to the surface due to the convective orbital motions. According to our theory of Phyto-Convection in the North Atlantic Ocean the entire
This work was partly funded by the Deutsche Forschungsgemeinschaft (SFB 512) and, within the TASC project, by the European Commission under contract MAS3-CT95-0039. In this investigation we have used model components, which were developed with partial support from the Deutsche Forschungsgemeinschaft (DFGSFB318) and the European Union (DG-XII, MAST II and III), within the European Sub-Polar Ocean Project (ESOP-1 and ESOP-2) (MAS2-CT93-0057 and MAS3-CT95-00 15). We would like to thank the Captains and Crews of RV VALDIVIA for their perfect support during our field surveys.
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Fig. 8. Initial T, S Profile for simulation CONTACT, obtained during station 8 RV VALDIVIA Cruise at 75.00°N and 2° 30.00 W, Date: 16th of February, 22:30 h.
Fig. 9. Predicted temperature after 10 simulation days, run CONTACT.
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Fig. 10. Predicted temperature after 30 simulation days, run CONTACT.
Fig. 11. Predicted mean CONTACT duration for tracer from various depth levels, run CONTACT.
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