The great 2012 Arctic Ocean summer cyclone enhanced biological productivity on the shelves

Abstract

[1] A coupled biophysical model is used to examine the impact of the great Arctic cyclone of early August 2012 on the marine planktonic ecosystem in the Pacific sector of the Arctic Ocean (PSA). Model results indicate that the cyclone influences the marine planktonic ecosystem by enhancing productivity on the shelves of the Chukchi, East Siberian, and Laptev seas during the storm. Although the cyclone's passage in the PSA lasted only a few days, the simulated biological effects on the shelves last 1 month or longer. At some locations on the shelves, primary productivity (PP) increases by up to 90% and phytoplankton biomass by up to 40% in the wake of the cyclone. The increase in zooplankton biomass is up to 18% on 31 August and remains 10% on 15 September, more than 1 month after the storm. In the central PSA, however, model simulations indicate a decrease in PP and plankton biomass. The biological gain on the shelves and loss in the central PSA are linked to two factors. (1) The cyclone enhances mixing in the upper ocean, which increases nutrient availability in the surface waters of the shelves; enhanced mixing in the central PSA does not increase productivity because nutrients there are mostly depleted through summer draw down by the time of the cyclone's passage. (2) The cyclone also induces divergence, resulting from the cyclone's low-pressure system that drives cyclonic sea ice and upper ocean circulation, which transports more plankton biomass onto the shelves from the central PSA. The simulated biological gain on the shelves is greater than the loss in the central PSA, and therefore, the production on average over the entire PSA is increased by the cyclone. Because the gain on the shelves is offset by the loss in the central PSA, the average increase over the entire PSA is moderate and lasts only about 10 days. The generally positive impact of cyclones on the marine ecosystem in the Arctic, particularly on the shelves, is likely to grow with increasing summer cyclone activity if the Arctic continues to warm and the ice cover continues to shrink.

The influence of sea ice and snow cover and nutrient availability on the formation of massive under-ice phytoplankton blooms in the Chukchi Sea

“…BIOMAS is a coupled biophysical model (Zhang et al, 2010a(Zhang et al, , 2014) that has three model elements: a sea ice model, an ocean circulation model, and a pelagic biological model. The pelagic biological model is an 11-component marine pelagic ecosystem model that includes two phytoplankton components (diatoms and flagellates), three zooplankton components (microzooplankton, copepods, and predator zooplankton), dissolved organic nitrogen, detrital particulate organic nitrogen, particulate organic silica, nitrate, ammonium, and silicate (see Fig.…”

“…The pelagic biological model is an 11-component marine pelagic ecosystem model that includes two phytoplankton components (diatoms and flagellates), three zooplankton components (microzooplankton, copepods, and predator zooplankton), dissolved organic nitrogen, detrital particulate organic nitrogen, particulate organic silica, nitrate, ammonium, and silicate (see Fig. 3 in Zhang et al, 2014; also see Kishi et al, 2007). Values of key biological parameters used in the model are listed in Zhang et al (2010a).…”

“…The global model's outputs of ocean velocity, temperature, salinity, and sea surface height are used as open boundary conditions for the southern boundaries of the BIOMAS domain along 391N. In addition, the nitrate and silicate along the open boundaries (which are far away from the Arctic Ocean) are restored to monthly climatology data from the World Ocean Atlas 2005 (Garcia et al, 2006) by the same method as Zhang et al (2014).…”

“…6e and f). The discrepancies may be linked to model overestimation or underestimation of light and nutrient distributions and to model uncertainties in parameters such as phytoplankton photoinhibition and photochemical reaction coefficients and zooplankton grazing and mortality rates (also see Zhang et al, 2010aZhang et al, , 2014. The discrepancies may be also linked to the fact that the model results are monthly mean values, while the satellite data are monthly composite values.…”

Wind-driven interannual variability of sea ice algal production in the western Arctic Chukchi Borderland

“…A previous modeling analysis indicated that plankton productivity over the Chukchi, East Siberian, and Laptev shelves was enhanced by vertical mixing with nutrient replenishment and lateral plankton transport from the western Arctic basin during the cyclone storm (Zhang et al, 2014). It is assumed that synoptic cyclone activities have both positive and negative contributions to ice algal production.…”