ALBERT

Description: Solar heating is an important factor in modelling the upper boundary layer of the ocean. It influences not only the temperature, but also the depth of the mixed layer and must be taken into account in circulation dynamics. The study reported in this paper was designed to reveal the principal features of the global climatology of solar heating in the ocean, with such applications in mind. The meridional, seasonal and diurnal variations of the vertical distribution of solar heating inside the ocean, expressed in terms of I(z), the rate of heat accumulation below depth z, and †(z) = (1/c). dzI(z), the rate of temperature rise, are calculated for given values of cloud cover and seawater turbidity (expressed in terms of Jerlov's water types) using a model that incorporates a new parametrization of I(z)/I(0), which is shown to be more accurate than previous versions. At present there exist no reliable global climatologies of cloud cover and seawater turbidity, so the values of the corresponding parameters are held constant in each computation, which is then repeated using parameter sets covering the full ranges from clear to overcast sky, clear to turbid ocean water. It is found that uncertainty in cloud cover is more important in the mixed layer, and uncertainty in seawater turbidity is more important below. The results presented in this paper are mainly concerned with solar heating below the mixed layer. It is calculated that the annual temperature rise can exceed 1 K and the annual heat accumulation can exceed 100 MJ/m2 below the mixed layer in the tropics. At higher latitudes solar heating produces similar heating rates in summer, but the stored heat is extracted locally in winter when the mixed layer depth exceeds the maximum depth of solar heating, defined here by a daily temperature rise of 1 mK or a heat flux of 86.4 KJ/m2d (=1 W/m2). The sensitivity of the seasonal and meridional variations of the maximum depth of solar heating to cloud cover and seawater turbidity is investigated. The actual change of temperature due to solar heating in the seasonal thermocline at Ocean Weather Station ‘C’ is calculated using Bunker's monthly mean cloud cover and Jerlov's seawater turbidity. Extension of such calculations to the whole of the World Ocean must await the publication of global climatologies of cloud cover and seawater turbidity, which are expected to be derived from satellite observations during the next decade. A solar heating climatology is a prerequisite for computation of the thermal response of the ocean to CO2 pollution of the atmosphere. The implications of the results obtained from the present study are discussed. An early rise in tropical sea surface temperature seems likely, but exact prediction will be hindered by uncertainty in the turbidity of the tropical ocean.

Description: The current status of the Sverdrup theory for the initiation of plankton blooms is examined. A prescription is given for the computation of the Sverdrup critical depth, using recently-published algorithms for mixed-layer primary production and a generalised loss term. Using no further information, the intrinsic rate of increase of phytoplankton biomass in the mixed layer can also be found. This rate, compared against the local frequency of storm occurrence, provides an alternative criterion for the initiation of blooms. The Eulerian (bulk property) methods used to derive these results are contrasted with the Lagrangian Ensemble method. The Lagrangian approach provides one avenue to the elaboration of the Sverdrup criterion to include the effect of processes with characteristic timescales small compared to one day. The incidence of blooms in the apparent absence of vertical stratification is reviewed: it is concluded that these observations do not undermine the basic logic of the Sverdrup theory. However, they do provoke interest in a re-examination of the feedbacks between the physical and biological dynamics in the mixed layer: an example is given. Finally, suggestions are made for further work in this subject area.

Description: According to Sverdrup's (1953) model of the spring bloom, phytoplankton biomass decreases in winter when the mixed layer depth exceeds the critical depth. We have used a one-dimensional mathematical model integrated by the Lagrangian Ensemble method to simulate a population of diatoms during the winter between two growing seasons off the Azores. The model allows us to diagnose the demographic changes in the simulated diatom population from a variety of perspectives. The total population falls to a minimum of 70 million diatoms m-2 at the end of February. The vertical distribution of the population dynamics is first analysed in terms of daily Eulerian averages over 1 m depth intervals. Growth starts in February when the diurnal thermocline becomes shallower than 50 m, but while the mixed layer is still 200 m deep. The natural mortality has a minimum in winter because it is reduced (in the model) with temperature and population density. Eulerian analysis suggests that in winter, diatoms have a life expectancy of more than 3 months, so a significant number will survive the months of December, January and February when there is very little growth. Losses to grazing are negligible in winter. Lagrangian analysis shows how an individual diatom responds to its changing ambient environment caused by variation in depth (due to turbulent mixing) and the diurnal and seasonal changes in the photosynthetically active radiance. The different trajectories followed by the thousands of plankton particles simulated by the model produce diversity in growth rate ranging over several orders of magnitude, so care has to be taken in statistical analysis. The paper ends with a re-assessment of the value of the critical depth and compensation depth as predictors for onset of the spring bloom. The compensation depth was computed by Eulerian averaging over 1 m depth inter-vals each day. For 1 month after the vernal equinox the compensation depth follows the ascent of the mixed layer as it rises from a depth of 100 m to 40 m. Lagrangian analysis reveals that this is due to the photo-adaptation better matching the ambient irradiance experienced by diatoms in the mixed layer compared with those at the same depth in the seasonal thermo-cline. By mid-April the spring bloom has already ad-vanced so far that self shading influences the compensation depth, which then rises into the mixed layer. We conclude that Sverdrup's criterion is not useful for predicting changes in the diatom population simulated by our model.

Description: Understanding the plankton ecosystem in the ocean requires detailed demographic analysis. It is impossible to sample the ocean adequately for such analysis, but progress can be made by analysing data sets generated by mathematical models provided they realistically simulate the ecosystem. The Lagrangian Ensemble method is well suited to demographic studies because it generates large data sets containing complete information on all the families living in the simulated ecosystem. It provides audit trails of individual families for unambiguous analysis of mechanisms responsible for the simulated changes in community and environment. Recent papers based on the Lagrangian Ensemble method are reviewed.

Description: This paper discusses an observing system simulation experiment which reveals the difference in primary production of (i) phytoplankton moving freely in the turbulent mixed layer of the upper ocean and (ii) a sample of the same population held in a bottle at fixed depths. The results indicate the tendency of incubation measurements to overestimate phytoplankton production rates by up to 40%. Differences in primary production depend to a first approximation on the vertical extent of mixing and on water turbidity. A simple model was constructed leading to a non-linear calibration function which relates the difference in primary production to surface irradiance, mixing depth and to the depth of the euphotic zone. This function has been applied to calibrate the production rates simulated at fixed depths, and the corrected values were verified by comparisons with productivities in the turbulent environment. The calibration function was found to be capable of reducing the differences significantly.