Interannual variability of the North Sea primary production: comparison from two model studies

Continental Shelf Research 20 (2000) 129}151

Interannual variability of the North Sea primary production: comparison from two model studies Morten D. Skogen!,*, Andreas Moll" !Institute of Marine Research, Division of Marine Environment, Pb.1870, N-5817 Bergen-Nordnes, Norway "Institut fu( r Meereskunde, Universita( t Hamburg, Troplowitzstr.7, D-22529 Hamburg, Germany Received 5 June 1998; received in revised form 20 April 1999; accepted 25 June 1999

Abstract The North Sea is known to be a very productive area. Several models and in situ measurements have been used to quantify the primary production and its spatial variability, but large uncertainties still exist. Except for general statements about the level of production, very little is known about the interannual variability of it. In this paper two state of the art ecological models have been run with realistic forcing for 10 di!erent years to investigate this interannual variability. The focus has been on di!erences due to changing wind "elds, and di!erences due to changes in river discharges. Separated into ERSEM boxes, both spatial and temporal variability is discussed. The models suggest that the interannual variability in the North Sea primary production is around 15%, and that the variability locally is higher than this, thus an increase in one area is often compensated by a decrease somewhere else. The impact of the river nutrient inputs is estimated to be less than 10% of the total production. The modelled variation in primary production, can in both models be related to, and explained from, actual variability found in the modeled physics. The large variability in primary production found due to these changes in the underlying physical "elds, suggests that a realistic three-dimensional circulation model is essential for this kind of modelling. ( 2000 Elsevier Science Ltd. All rights reserved. Keywords: North Sea; Modeling; Intercomparison; Primary production; Temporal variations; Nutrients

1. Introduction There is an increasing concern about the ecological e!ects of anthropogenic nutrient inputs to the North Sea (Salomons et al., 1988; Lancelot et al., 1990; Charnock et al., 1994; SuK ndermann, 1994). Nutrients enter the North Sea as riverine * Corresponding author. Tel.: 0047-55-238-461; fax: 0047-55-238-584. E-mail address: [email protected] (M.D. Skogen) 0278-4343/00/$ - see front matter ( 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 8 - 4 3 4 3 ( 9 9 ) 0 0 0 6 9 - 2

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and atmospheric inputs. For the German Bight Radach et al. (1990) showed clearly how nutrients and phytoplankton concentrations, and other ecosystem variables, had changed. Similar changes were observed by Cadee (1992) for the Dutch Wadden Sea. To date it is not clear from observations to what degree the southern and central North Sea is a!ected by anthropogenic nutrients. The primary production is a!ected by the changes in nutrient inputs, and in many areas this has caused severe problems. There seems, e.g. to have been an increasing trend of harmful #agellate blooms in the coastal areas of the southern North Sea (Lancelot et al., 1991). Probably, the most extreme case was the Chrysocromolina polylepis bloom in spring 1988 extending as far north as the Norwegian west coast (Dundas et al., 1989; Maestrini and Graneli, 1991). Related to the problems with algae, and environmental questions in general, there has been an increasing political interest in eutrophication issues, and at the second. International Conference on the Protection of the North Sea (London, 1987), all countries around the North Sea agreed on reducing the input of nutrients by 50% between 1985 and 1995 for those areas where nutrients cause, or are likely to cause, pollution. To investigate the e!ects of these reductions, the capacity to quantify primary production is an important task. It is also important to quantify and to study the variability of the primary production in space and time because of its importance as a possible regulating mechanism for the higher trophic levels. Measurements of in situ primary production is a time consuming and expensive task, and therefore relatively few measurements are available both in space and time. Joiris et al. (1982) estimated the annual production in the Belgian coastal zone to be 320 gC m~2 yr~1, and Fransz and Gieskes (1984) proposed the production in the southern North Sea to be between 200 and 250 gC m~2 yr~1. In the northern North Sea, Steele (1956) found the production to be in the interval 54}127 gC m~2 yr~1. During the NERC North Sea Project from August 1988 to October 1989, Joint and Pomroy (1993) estimated the annual production for individual ICES-boxes in the southern North Sea. Their estimates were from 79 gC m~2 yr~1 in box 3b (Britain South East) to 261 gC m~2 yr~1 in box 5a (German Bight). In the North Sea Quality Status Report (Anon, 1993) the mean annul production of the North Sea south o! 55.303 is believed to vary between 150 and 250 gC m~2 yr~1. There have been no surveys to estimate the primary production for the whole North Sea over an annual cycle, thus data are lacking. A review of the phytoplankton dynamics and primary productivity of the North Sea can be found in Reid et al. (1990) and Holligan (1989). With the well-known patchiness of algae, rapid variability and uncertain amounts of recirculation of nutrients, gross estimates (from sparse data) of average production over a certain ocean area and over a certain time have very large uncertainties. Therefore, more or less sophisticated models have been used as a tool to study both the annual cycle, short-term variability and annual primary production of the North Sea. Skogen et al. (1995) modeled the annual cycle of 1985 and Moll (1995) 1986 using coupled three-dimensional physical, chemical, biological models, while using the ERSEM box model (Baretta et al., 1995), Lenhart et al. (1997) have reported production estimates for 1988/1989. Several model to model intercomparison studies of ecological models in the North Sea, have been performed during the last years. As a part of the North Sea Task Force a study in 1992 involved "ve di!erent models, and

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were focusing on the year 1985 and the possible e!ects of a 50% reduction of anthropogenic nutrient inputs (De Vries, 1992). In a similar study in 1996 involving eight models (OSPAR, 1998), the models were also compared to climatological (1980}1990) data for nutrients and chlorophyll using a cost function. A more complete list of models covering the whole or parts of the North Sea can be found in Fransz et al. (1991) and in Moll (1995). So far the main concern for primary production estimates based on both model simulations and observations have been to come up with typical values for annual and peak production for di!erent areas. In this work our main focus is neither to improve the accuracy of such an estimate, nor to come up with new ones. Instead we will focus on the inter annual variability of the primary production, and its possible causes. To do this two coupled three-dimensional physical, chemical, biological model systems, NORWECOM (Skogen, 1993; Skogen et al., 1995) and ECOHAM1 (Moll, 1995), have been used. Both models have in previous works (Skogen et al., 1995; Moll, 1998) been validated (Dee, 1995) in the frame of estimates of ICES box primary production (Joint and Pomroy, 1992), and taken part in the ASMO intercomparison of eutrophication models (OSPAR, 1998). In the present study each model has been run for 10 di!erent years (1985}1994). To isolate the variability of the North Sea primary production, due to varying solar radiation and river inputs, these forcing data are "xed for an annual cycle. Results are reported on changes due to di!erent wind forcing, and thereby North Sea strati"cation, circulation and Atlantic in#ow. Finally, one year is run with changing river inputs to investigate the importance of this forcing.

2. The NORWECOM model The NORWegian ECOlogical Model system (NORWECOM) is a coupled physical, chemical, biological model system applied to study primary production and dispersion of particles ("sh larvae and pollution). The model is fully described in Skogen (1993). See also Aksnes et al. (1995); Skogen et al. (1995). The physical module is based on the three dimensional, primitive equation, time dependent, wind and density driven Princeton Ocean Model (POM). The model is fully described in Blumberg and Mellor (1987). In the present study the model is used with a horizontal resolution of 20]20 km2 on an extended North Sea (see Fig. 1). In the vertical, 12 bottom following sigma layers are used. The biological model is coupled to the physical model through the subsurface light, the hydrography and the horizontal and the vertical movement of the water masses. The prognostic variables are: inorganic nitrogen, phosphorus and silicate, two di!erent types of phytoplankton (diatoms and #agellates), detritus (dead organic matter), light and turbidity. The forcing variables for the circulation are six-hourly hindcast atmospheric pressure "elds provided by the Norwegian Meteorological Institute (DNMI) (Eide et al., 1985; Reistad and Iden, 1998), 6-hourly wind stress (translated from the pressure "elds by assuming neutral air}sea stability), four tidal constituents and freshwater runo!. In the lack of data on the surface heat #uxes, a `relaxation towards

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Fig. 1. Bottom topography, North Sea 20]20 km2 for the NORWECOM model.

climatologya method is used (Cox and Bryan, 1984). During calm wind conditions, the surface temperature "eld will adjust to the climatological values after about 10 days (Oey and Chen, 1992). The net evaporation precipitation #ux is set to zero. Initial values for velocities, water elevation, temperature and salinity are taken from monthly climatologies (Martinsen et al., 1992). Interpolation between monthly "elds are also used at all open boundaries, except at the in#ow from the Baltic where the volume #uxes have been calculated (Stigebrandt, 1980) from the modeled water elevation in Kattegat and the climatological monthly mean freshwater runo! to the Baltic. To absorb inconsistencies between the forced boundary conditions and the model results, a 7 gridcell `Flow Relaxation Schemea (FRS) zone (Martinsen and Engedahl, 1987) is used around the open boundaries. The incident irradiation is modeled using a formulation based on Skartveit and Olseth (1986, 1987). Data for global daily radiation from 1990 is taken from a station at Taastrup (Denmark) (Anon, 1991). Nutrients (inorganic nitrogen, phosphorus and silicate) are added to the system from the rivers and from the atmosphere (only

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133

inorganic nitrogen). Monthly data for freshwater runo! (or annual averaged data), including nutrient data, from main rivers are taken from Balin8 o (1993). In addition, extra freshwater is added along the Norwegian and Swedish coast to ful"ll requirements to estimated total freshwater runo! from these coastlines (Egenberg, 1993). The initial nutrient "elds are derived and extrapolated/interpolated (Ottersen, 1991) from data (obtained from ICES) together with some small initial amounts of diatoms and #agellates (2.75 mgN m~3). Very few (continuous) time series of nutrients are available from the in#ow of Atlantic water. At the open boundaries (outside the North Sea) nutrient values from station M (663N, 23E) from 1992 (F. Rey, pers. comm., 1993) have been used and assumed valid everywhere in the in#ow area. Nutrient data (monthly means) measured in the Baltic (ICES) are used for the water #owing into Kattegat.

3. The ECOHAM1 model The ECOlogical North Sea Model, HAMburg, Version 1 (ECOHAM1) is a threedimensional model system to study phytoplankton dynamics. It is the "rst step towards a German ecosystem model of the North Sea that is being developed at the Institute fuK r Meereskunde, Hamburg. The aim was to quantify the annual primary production under actual circulation and solar radiation forcing (Moll, 1997). The model is fully described in Moll (1995, 1998). The model is implemented on a "nite di!erence grid (Arakawa C) for an extended North Sea area (see Fig. 2), discretized on a 20]20 km2 grid. A maximum of 19 vertical layers are used with 5 m resolution from the surface to 50 m depth and with progressively increasing grid steps from layer 11 to 19 to span a maximum depth at the northeast boundary with the Atlantic. Two partial di!erential equations describe the spatio-temporal evolution in the phosphate and phytoplankton, and an ordinary di!erential equation describes the benthic detritus pool. Underwater light is calculated by a diagnostic ordinary di!erential equation that includes shelf-shading due to phytoplankton. Phytoplankton is represented by one state variable and the model formulations are based on a simple phosphorus cycle. Phosphate serves initially as a means to trigger the bloom of phytoplankton and later to limit the phytoplankton production. The model is conceptualized for a shelf sea including the shallow sea characteristic for the replenishment of the mixed layer with nutrients from the bottom. The water column dynamics are implemented in a three-dimensional frame, where phytoplankton and phosphate are transported by advection and di!usion. The primary production model is set up on the same grid as the underlaying circulation model (Pohlmann, 1996) and uses the daily forcing values to advect and di!use phytoplankton and phosphate. But, the biological reaction terms are not implemented within the circulation model. The primary production model is an independent transport model that uses the circulation model output, since no major e!ects from the biology back to the physics are expected, which makes long-term simulations much easier to implement. The actual oceanographic forcing is required for reliable simulations of the phytoplankton dynamics. The hydro-thermodynamic forcing is described in Pohlmann

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Fig. 2. Bottom topography, North Sea 20]20 km2 for the ECOHAM1 model.

(1996) and in Moll (1998). Another important forcing for primary production simulations is solar radiation with its daily cycle. The total irradiance at the surface I is 0 calculated every 30 min using the octa model by Dobson and Smith (1988). This method was already tested by Moll and Radach (1991) for the German Bight and for areas in the North Sea by PaK tsch (1994).

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135

River loads have been taken from compilations of the North Sea Task Force (Anon, 1992), provided as monthly mean values of the main continental and British rivers entering the North Sea. In total about 43 kT yr~1 of phosphate-P are introduced into the coastal strip by rivers over one year. The nutrient contributions by the rivers are implemented as a source term for the grid cell o! the river mouth, reaching from the Scottish Coast (Firth of Forth, Tyne and Tees), the British Coast (Humber and Thames), the Belgium Coast (Scheldt), the Dutch Coast (Haringvliet, Niewe Waterweg, Nordzeekanal and lake Ijssel), into the German Bight (Ems, Weser and Elbe). The monthly loads are interpolated to give daily values. The model is initialized with climatological mean phosphate at all grid points in the ERSEM boxes obtained from Radach and Lenhart (1995), interpolated to January 1st 1985. Phytoplankton values for January and December are sparse, therefore a constant value of 0.1 mg Chl m~3 for the coastal areas, and 0.02 mg Chl m~3 for the central and northern North Sea was prescribed. The initial detritus content at the bottom was prescribed as 1 gC m~2 for the whole North Sea. Phosphate values at the boundaries obtained from Radach and Lenhart (1995) were prescribed as annual monthly means and interpolated to assign values for each day. A no-#ux condition was used for phytoplankton because data were lacking for the northern boundary.

4. Results and discussion First, the two models were run for 10 di!erent years (1985}1994). Each of the years were run separately, starting the model on December 15 the previous year, and ending the run on December 31 the actual year. To ease the analysis, the monthly mean river loads, and the annual light cycles were identical for each year, while the circulation and strati"cation due to varying wind and atmospheric pressure "elds were di!erent. These results will therefore report on the di!erences in primary production due to changed circulation and strati"cation only. The horizontal distribution of the integrated annual primary production have been calculated, and the mean production in each ERSEM box (see Fig. 3) and the integrated mean North Sea (box 1}10) primary production have been found for each year. All numbers are given in Tables 1 (NORWECOM) and 3 (ECOHAM1). In addition the standard deviation, referring to the spatial variability of the mean of each box are given. The last column gives the span: (prod !prod )/prod ]100% .!9 .*/ .%!/ for each box. This number is used as a measure of the interannual variability of the production. 4.1. Results from the NORWECOM model The results from the NORWECOM model varies from 82 to 218 gC m~2 yr~1 (box average) within the North Sea. The highest numbers are found close to the main rivers along the continental coast in the southern North Sea. In the central North Sea the production is generally much lower, while the production is increasing northwards

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Fig. 3. The di!erent ERSEM boxes (1}10).

Table 1 Production statistics for ERSEM boxes with the NORWECOM model. Annual production (gC m~2 yr~1), mean production, standard deviation and the span ((max}min)/mean]100%). All numbers (except the span) are pointwise means covering all grid points within a box. The standard deviation is referencing to the spatial variation of the mean production in a box, and the span to the interannual variability of the annual means of a box Box

85

86

87

88

89

90

91

92

93

94

Mean

S.D.

Span

1 2 3 4 5 6 7 8 9 10

150 136 122 86 93 150 129 197 183 95

174 152 147 103 101 144 132 196 180 113

148 119 148 86 102 133 131 196 188 128

161 140 125 89 99 156 160 211 143 104

180 144 148 92 86 146 152 200 154 111

161 148 150 106 98 170 156 218 173 112

154 130 140 84 95 147 143 212 177 99

163 138 138 85 93 140 130 199 166 107

159 135 158 82 108 144 145 206 158 105

169 139 141 87 97 146 140 204 185 102

162 138 142 90 97 148 142 204 171 108

37 26 10 8 13 37 47 55 35 15

20 24 25 27 22 25 21 11 26 31

Mean

127

139

130

135

137

143

131

132

134

134

134

45

12

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137

due to the in#ow of nutrient rich Atlantic water. Separating the production between diatoms and #agellates, this increase is mainly because of a very high diatom production due to large amounts of silicate in the incoming water. Outside the North Sea in the Faeroe}Shetland channel, the annual productions are comparable to that in the southern North Sea. The highest variability in the production is found in box 10 (Jutland) with a span of 31%, but there are several boxes with almost the same span. Except for the minimum found in box 8 (Belgian/Dutch coast) (11%), all boxes are reporting on a span of at least 20%. The reason for the low span in box 8 is due to the strong in#uence of rivers, and that these inputs are "xed in all runs. On the other hand, the same box (8) has the largest number for the standard deviation (55 gC m~2 yr~1), since the river in#uence is highly variable within the box. The smallest standard deviation is found in the Central North Sea boxes (4 and 5), and along the Norwegian coast (3). In these boxes the production shows a very low spatial variability since there are no nutrient river inputs, and the impact of the Atlantic in#ow water is lower than in the northern boxes (1 and 2) where the standard deviation is much higher. For the temporal variability (the span) there are no signi"cant di!erence between these boxes (1}5). Focusing on the mean North Sea production the variability is much lower. The span is only 12%, almost equal to that found in box 8. This indicates that low production in one area, is compensated with higher production elsewhere, and that it is di$cult to distinguish between years with high and low productivity in the North Sea only due to changes in the wind driven circulation. An example of such a compensation of production is between the central North Sea boxes (4 and 5) in 1993. This year box 4 has its overall minimum, while its neighboring box (5) has its overall maximum. This can probably be explained from a small shift in the modeled circulation. The mean annual North Sea production is shown in Fig. 4. In the summer months the nutrients are almost depleted in the upper layers over large areas, indicating that all available nutrients are consumed by the algae. Since initial "elds and river and atmospheric inputs of nutrients are "xed in all these runs, the year-to-year variations in the modeled North Sea primary production must either be due to di!erences in vertical mixing, changes in the amount of nutrients in the euphotic zone, or due to changes in the in#ow to the North Sea increasing the total amount of available nutrients in the area. We will focus on the last explanation. In the spring of 1990 the highest salinity values ever were found in the North Sea (Ellett and Turrell, 1992; Heath et al., 1991), indicating a large Atlantic in#ow. This was also the year with the highest North Sea primary production according to the model. On the contrary 1985 is found to have the minimum annual production. Focusing on the modeled Atlantic in#ow, we have investigated the #ow through a section going east}west from the Orkney to Utsira on the Norwegian coast (along 59.173 N). The #ow (year vs. month) and a normalized #ow with respect to the average of each month (January to December) during the 10 years is given in Fig. 5. Focusing on the accumulation of the normalized in#ow from January to August (when the main production is over) the minimum #ow is found in 1987, slightly below 1985. These are also the two years with the minimum annual production. In a similar way 1990 is found to have the largest modeled in#ow (and production). The correlation

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Fig. 4. Mean annual production (gC m~2 yr~1) from the NORWECOM model.

between the normalized in#ow the eight "rst months and the annual production is found to be r"0.80. Investigating the seasonal patterns, they are similar for all years with a maximum production in May of around 30 gC m~2 month~1 as a mean for the whole North Sea. This is the same production rate as reported on by Weichart (1980) for the FLEX study in the northern North Sea in the spring of 1976. Between the end of April and the beginning of June the production was about 30 gC m~2. Comparing the di!erent months between the years, there are only small di!erences (10}15%). The exception for this is June 1986 when the production is 30% higher than the mean June production. This single month is the reason for the very high annual production this year, and can be explained from the normalized transports (Fig. 5) in May and June that is approximately 20% above the mean, increasing the amount of available nutrients for production in the North Sea during summer. Also 1988 has some extra production due to large in#ow during summer, and in August 1988 the production is more than 20% above average after a high in#ow in July. Both these years have a high modeled annual production (1986 second highest) and a relatively low accumulated in#ow (1986 sixth). Removing them from the correlation computation gives r"0.89 c Fig. 5. Monthly mean transport (Sverdrup) through the Orkney}Utsira section (upper), and normalized transport with respect to the average of each month (lower).

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139

140

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141

Table 2 Production statistics (gC m~2 yr~1) for di!erent runs of 1987 for individual ERSEM-boxes with the NORWECOM model. 1987-0 is the initial run (1990 rivers). In 1987-1 real 1987 rivers are used and 1987-2 is the results for river runo!s (1987) without any nutrients. The span is de"ned relative to the 10 years means in Table 1 Run/box

1

2

3

4

5

6

7

8

9

10

Mean

1987-0 1987-1 1987-2 Span

148 148 148 1

119 118 119 1

148 149 147 1

86 86 85 1

102 104 93 11

133 133 132 1

131 143 114 21

196 212 157 27

188 204 145 35

128 133 117 15

130 133 121 9

(without 1986) and r"0.92 (without 1986 and 1988). We conclude that there is a strong correlation between the accumulated normalized in#ow and the annual production, and that the in#ow during the summer months has the largest importance. In Fig. 6, the annual production for 1985 (left) and 1990 (right) are given. There are clear di!erences between these two extreme years. In 1990 the production is higher both in the central North Sea and along the Norwegian coast. The increased production due to Atlantic in#ow along the British northeast coast is also going further south, and the model is giving an increased production just inside the English Channel. On the other hand, the production in the German Bight seems higher in 1985 than in 1990. To investigate the e!ect of changing river inputs to the North Sea, we have done two additional runs for one year using real river discharges. The chosen year is 1987, with the largest fresh water inputs (of our data) during the 10 years period. Compared to 1990 the discharges are about 80% higher (main European rivers) in 1987 (90% in the period January } August). In the "rst run the 1987 discharges are used as they are, while in the second one all nutrients are removed from the freshwater. The results are given in Table 2. As expected the dependency of river inputs is negligible in the northern boxes, and are increasing southwards. The near doubling in river nutrients is increasing the production with 7}10% in box 7 (Southern British), 8 (Belgian/Dutch coast) and 9 (German Bight), and the mean North Sea production from 130 to 133 gC m~2 yr~1 (2%), when using the higher loads in 1987 compared to 1990. The e!ect of removing all nutrients from the river water is larger, and the mean North Sea production is decreasing to 121 gC m~2 yr~1 (9% down compared to the run with nutrients). For the most e!ected boxes (8#9) the decrease is approximately 25%. However, it should be noted that even in box 9 the production without any nutrients from the rivers (145 gC m~2 yr~1) is above the minimum of 143 gC m~2 yr~1 found in 1988. Thus, the b Fig. 6. Annual production (gC m~2 yr~1) for 1985 (upper) and 1990 (lower) from the NORWECOM model.

142

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model indicates that the natural variability due to the wind driven circulation can be higher than the total contribution from the rivers also in these areas. 4.2. Results from the ECOHAM1 model Net primary production varies from 97 to 224 gC m~2 yr~1 within the North Sea (box averages). The highest numbers are found close to the main rivers along the British coast (max 412 gC m~2 yr~1) and continental coast (max 767 gC m~2 yr~1) in the southern North Sea. In the central North Sea the production is low (about 100 gC m~2 yr~1), while the production increases northwards up to 125 gC m~2 yr~1 due to nutrient rich in#ow of Atlantic water. The highest variability in the production is found at the northern boundary and in the Southern Bight with a span around 18}24% and up to 58% in box 8. The exceptional box 8 is discussed in detail later. The minimum is found in box 4 (12%) and box 6 (13%), while most boxes have a span between 16 and 25%. The standard deviations increase from values below 20 gC m~2 yr~1 in deep waters to values above 50 up to 133 gC m~2 yr~1 in shallow waters, where the horizontal gradients are more intensive than in the central and northern North Sea. Focusing on the mean North Sea production the variability is much lower. The span is only 18%, almost equal to that found in box 2 and 3. This indicates that low production in one area is compensated with higher production elsewhere, and that it is di$cult to distinguish between years with high and low productivity in the North Sea only due to changes in the wind driven circulation. An example of such a comparison of production is between the northern North Sea boxes 2 and 3 in 1992. This year box 2 has its overall minimum, while its neighboring box 3 has its overall maximum. This can be explained from a shift in the modeled circulation and strati"cation. The mean annual production is shown in Fig. 7. The initial "elds and the river inputs are "xed in all runs. Therefore, the year-to-year variations in the simulated production must either be due to di!erences in the transports and/or the vertical strati"cation and mixing. To separate both e!ects, an additional scenario without horizontal transports but everything else unchanged was simulated. About 71% of the net primary production is determined in the ECOHAM simulation by the vertical mixing alone. The year 1990 accounts for the minimum production in the fully three-dimensional simulation as in the simulation without transports for most of the North Sea boxes. Additional, the bottom remineralization is highest in 1986 and 25% above the minimum remineralization in 1990. Thus, the production amount is determined by the strati"cation/mixing and modulated by the transports. The seasonal cycle show a maximum production in May of around 30 gC m~2 month~1 as a mean for the whole North Sea. This is in good agreement with the production rate reported by Weichart (1980), see above. Comparing the di!erent May months between the di!erent years, there are only small di!erences varying between 27 and 34 gC m~2 yr~1. Investigating the accumulated production until the end of May, the year 1990 show the minimum production rate of 46.5 gC m~2, while 1986 show the maximum of 74.7 gC m~2. In 1990 the production is low due to the mixing

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143

Fig. 7. Mean annual production (gC m~2 yr~1) for the ECOHAM1 model. Note that the results are overlaid the NORWECOM model domain for a better comparison.

and strati"cation regime, which limits production in April. The monthly mean production is 13 gC m~2 month~1 compared to 32 gC m~2 month~1 in 1985 or 1986. We conclude that annual production is determined by the strati"cation regime especially during early spring, and that the transports modulates the production in ECOHAM1. In Fig. 8, the annual production for 1985 (left) and 1990 (right) are given. The maximum production occurs in 1986 a little above the value of 1985. And this year is presented in the "gure to be in correspondence with the NORWECOM presentation. There are clear di!erences between these two extreme years. In 1985 the production is higher in all boxes of the North Sea. The area with production between 100 and 125 gC m~2 yr~1 is smaller compared to 1990. The production of the minimum year 1990 is in all boxes below the mean box values. The mean primary production for box 8 (o! The Netherlands) is 126 gC m~2 yr~1. This annual mean value is too low compared with observations and the yearly production decreased continually during the 10 years. This is an e!ect of the suspended matter attenuation. The SPM forcing data are derived from observations for the ERSEM boxes, and due to the large boxes there is no o!shore gradient resulting in a strong light attenuation over the whole box. This has to be improved in further model activities (Table 3).

144

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145

Table 3 Production statistics for ERSEM boxes with the ECOHAM1 model. Annual production (gC m~2 yr~1), mean production, standard deviation and the span ((max-min)/mean]100%). All numbers (except the span) are point wise means covering all grid points within a box. The standard deviation is referencing to the spatial variation of the mean production in a box, and the span to the interannual variability of the annual means of a box Box

85

86

87

88

89

90

91

92

93

94

Mean

S.D.

Span

1 2 3 4 5 6 7 8 9 10

106 111 123 115 129 141 128 168 244 157

124 120 124 117 131 140 123 157 234 165

118 111 117 108 128 139 123 149 228 151

110 111 118 104 110 132 106 115 208 136

104 109 129 108 108 122 101 105 218 143

97 109 116 103 102 125 101 94 203 140

100 108 122 111 116 130 115 126 232 161

100 101 137 107 109 123 110 113 235 150

107 112 129 114 119 138 115 121 239 156

103 110 128 106 115 133 110 109 212 154

107 110 124 109 117 132 113 126 225 151

15 16 16 15 15 20 61 52 133 22

25 16 16 12 24 13 23 58 18 18

Mean

133

135

129

119

118

112

123

120

127

121

124

29

18

Table 4 Production statistics (gC m~2 yr~1) for two di!erent runs of 1987 for individual ERSEM-boxes with the ECOHAM1 model. 1987-0 is the run with NSTF rivers loads. In run 1987-2 the results for a simulation without any river loads is presented. The span is de"ned relative to the 10 years means in Table 3 Run/box

1

2

3

4

5

6

7

8

9

10

Mean

1987-0 1987-2 Span

118 118 0

111 111 0

117 117 0

108 107 1

128 124 3

139 139 0

123 106 15

149 132 13

228 161 30

151 147 3

129 120 7

To investigate the e!ect of changing river inputs to the North Sea, we have done one additional run with ECOHAM1 using no river loads. The results are given in Table 4. As expected the dependency of river inputs is negligible in the northern boxes, and are increasing southwards. The e!ect from removing all nutrients from the river water is decreasing the production with 11}29% in box 7, 8 and 9, and the mean North Sea production is decreasing from 129 to 120 gC m~2 yr~1 (7% down compared to the run with nutrients). However, unlike the results from NORWECOM, the production in box 9 without any nutrients from the rivers (161 gC m~2 yr~1) is below the minimum of 203 gC m~2 yr~1 found in 1990. Thus, this model indicates b Fig. 8. Annual production (gC m~2 yr~1) for 1985 (upper) and 1990 (lower) from the ECOHAM model. Note that the results are overlaid the NORWECOM model domain for a better comparison.

146

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that the natural variability due to the wind driven circulation is not higher than the total contribution from the rivers in this area. 4.3. Model to model intercomparison The mean North Sea production is about 8% higher in NORWECOM than in ECOHAM1 (134 compared to 124 gC m~2 yr~1), but both models are well within previous estimates from the literature. The interannual variability as de"ned by the span, is comparable in both models (12 and 18%), and both models suggest that the variability locally (averaged over the individual ERSEM boxes) generally is higher than for the overall North Sea production, thus indicating that high production in one area are likely to be compensated by low production in another. Both models also have a peak production in May of about 30 gC m~2, with a low interannual variability. The main di!erence between the two models is the south/north gradient of the production. In ECOHAM1 there is a general increase in the production southwards towards the continental coast, while NORWECOM also gives very high production in the northern boxes. However, since this increase is mainly caused by a high diatom production due to high silicate values in the in#owing Atlantic water, it is di$cult to compare with ECOHAM1 that does not distinguish between diatoms and #agellates, and has phosphate as the only limiting nutrient. The best agreement between the annual mean primary production is found in the central North Sea (boxes 3 Norway, 4 Northern Central, 5 Southern Central and 6 Northern British). In the southern North Sea, there seems to be a shift in production with ECOHAM1 having the higher production in the German boxes (9 and 10), and NORWECOM having higher production in box 7 (Southern British) and 8 (Belgian/Dutch coast). To get a better view of the di!erence between the production in the individual boxes, the mean annual productions and standard deviation (with respect to the mean in time) is shown in Fig. 9. The correlation between di!erent years for the two models are generally low, even negative. The highest correlation is found in box 5 (Southern Central) with r"0.35, while the lowest is found in box 7 (Southern British) with r"!0.80. Also the correlation between the annual means are negative (r"!0.49). These low correlations are probably due to the di!erence in the hydrodynamic forcing for the primary production in the two models. While the production in NORWECOM is determined by the Atlantic in#ow, the production in ECOHAM1 is determined by the strati"cation and only modulated by the transports. The hydrodynamic forcing of the two models, especially the transports for selected sections were investigated in a model intercomparison by Smith et al. (1996). The forcing for the annual Atlantic in#ow in NORWECOM is 1.13 Sv compared to 0.42 Sv in the forcing for ECOHAM1. Even in summer NORWECOM has twice (0.96 Sv) the in#ow of ECOHAM1 (0.41 Sv). For the shallow continental coast the transports are equal, for example the German Bight section show 0.2 Sv in NORWECOM and 0.18 Sv in ECOHAM1 for the long-term annual mean. For this part of the North Sea

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147

Fig. 9. Annual mean production and standard deviation for each individual ERSEM box. The standard deviation is referring to the mean production over the 10 years period.

the bottom remineralization is important, which is not included in the NORWECOM model. Focusing on the interannual variability, NORWECOM has a larger span in most boxes. In boxes 1 and 8 ECOHAM1 has a larger span, while in two boxes (5 and 7) the span is almost equal. An interesting observation is that ECOHAM1 shows the largest interannual variability in box 8 (Belgian/Dutch coast), the same box where NORWECOM has the lowest variability, and that the high span values for ECOHAM1 is mainly due to the exceptional year 1990, that gave the 10 year minimum for this model. In NORWECOM, however, 1990 gave the 10 year maximum production due to a very high Atlantic in#ow. The spatial variability (standard deviation) within the boxes, also indicates di!erences in the horizontal gradients between the models. NORWECOM has the largest numbers in the northern areas (box 1, 2 and 6), while ECOHAM1 gives a signi"cant larger spatial variability in the German bight (box 9). For the whole North Sea, NORWECOM also shows a larger spatial variability. NORWECOM seems to be most dependent on the river inputs. For the whole North Sea the dependency measured in terms of the span is comparable (9}7%). However, comparing the two runs 1987-0 and 1987-2 we note that both models give a decrease in the mean North Sea production of 9 gC m~2 yr~1. Focusing on the spatial di!erences, NORWECOM has a larger o!shore signal in box 5 and downstream in box 10. For the boxes where the river in#uence are most signi"cant (7 and 9), the dependencies are comparable, while the exceptional box 8 has already been discussed in the ECOHAM results.

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5. Conclusions In this paper the interannual variability of the North Sea primary production have been studied by using two state of the art ecological models. Previous studies of primary production in the North Sea have mainly focused on general estimates of the production. To our knowledge this is the "rst study of this kind, where threedimensional coupled biophysical models have been used for long-term modeling and a discussion of spatial and temporal variability in this area. Despite their di!erences, the two models agree on an annual mean primary production, its variability and the timing and size of the peak production. The integrated in#uence of the river inputs seems also to be equal, even if there are spatial di!erences. While the interannual variability in the primary production in NORWECOM can be explained to a large extent from the Atlantic in#ow, and thereby an increase in nutrients, the production in ECOHAM1 is determined mainly by the strati"cation regime and modulated by the transports. The di!erence in results, also seen in the low correlation between the production in the di!erent years, is due to the use of two di!erent physical models. This resulting di!erence in physical forcing of the biological models, explains why a conclusion from one of the models not necessarily is true for the other, and why a di!erent triggering of the modeled primary production in the North Sea is found. A further validation, including estimates for uncertainties, would need a proper aggregation of the existing data for primary production. This is essential for a proper validation of the production variability. However, based on the present work, and previous validation studies where the models are compared to data for primary production in the North Sea (Skogen et al., 1995; Moll, 1998; OSPAR, 1998), we conclude that both models give estimates for the North Sea primary production that compare well to literature, and that the high variability of the forcing generates a considerable variability in the primary production. Both models presented include the necessary model set-ups to couple the biological dynamics with the underlying physics. The main conclusion is that changes in the physical conditions and forcing, results in a large variability in the primary production in the North Sea. A three-dimensional circulation model is therefore essential for primary production studies in this area, including both a realistic horizontal advection and exchange with the Atlantic, and a proper simulation of the vertical density structures.

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