SEASONAL DYNAMICS AND BIOLOGICAL PRODUCTIVITY IN THE ARABIAN SEA EUPHOTIC ZONE AS SIMULATED BY A 3-DIMENSIONAL ECOSYSTEM MODEL

A nitrogen-based, seven-component ecosystem model of Fasham [1993] typ e has been coupled to a three-dimensional quasi-geostrophic ocean gene ral circulation model and applied to a simulation of the seasonal vari ability of physical and ecosystem variables in the northwestern Indian Ocean. The comparison of the solution with available data (seasonal c hanges in surface chlorophyll at certain key positions from the climat ological coastal zone color scanner (CZCS) database, satellite-derived annual primary production, and data from cruises) has highlighted man y agreements but also some disagreements between the model and observa tions. In particular, the model produces an entrainment bloom in May-J une in the central Arabian Sea for which there is no evidence in the C ZCS data and does not reproduce the observed August-September bloom in the northern Arabian Sea. In the latter case an analysis showed that zooplankton grazing control prevents the development of the model bloo m. A comparison of our solution with the results obtained by McCreary et al. [1996] using a 2.5-layer physical-ecosystem model showed that, despite numerous differences between the models, the period and locati on for most blooms in these solutions coincide closely. The model repr oduced the differences in primary productivity between the northeast a nd southwest monsoon periods and showed that the model phytoplankton i n the main upwelling areas were only seriously nutrient limited during the spring intermonsoon period. For large parts of the year the model predicts that phytoplankton production is closely coupled to zooplank ton grazing with blooms only occurring when there are rapid changes in phytoplankton growth rate due either to the entrainment of nitrate in to the mixed layer or decreased light limitation when the mixed layer is shallowing thereby allowing the phytoplankton to escape from grazin g control. The predicted particle flux from the euphotic zone was of t he order of 40% of the primary production and lagged the latter quanti ty by 8-10 days. This time lag meant that the correlation between dail y values of the two quantities was low, and this may partly explain th e difficulties of finding good correlations between observations of th ese two quantities.