Phytoplankton spring blooms in the Arctic have increased in magnitude and extent over the past two decades, particularly in open waters near the sea ice edge. We develop an idealized model of phytoplankton dynamics that takes into account the role of sea ice meltwater flux and its impact on surface mixed layer depth. Satellite observations feature a characteristic peak in phytoplankton concentration at around 100 km from the ice edge. This peak, as well as the overall structure of the plankton distribution is captured by the model dynamics. In the model, the characteristic spatial scale emerges from a balance of exponential growth near the ice edge, horizontal advection, and increased decay with distance from the ice as the mixed layer deepens. Observations and data further agree in that meltwater impacts plankton concentrations up to 1000 km from the ice edge. The results suggest that reduced meltwater input under future sea ice retreat may suppress spring phytoplankton blooms in the region.

The data used in this study consists of 3 main components:

(1) Near-surface chl-a concentration data for the years 2011–2019. This consists of monthly Level 3 products from three sensors: MODIS Aqua (NASA Ocean Biology Processing Group, GSFC 2021), MODIS Terra (NASA Ocean Biology Processing Group, GSFC 2022), and VIIRS-SPNN (NASA Ocean Biology Processing Group, GSFC 2017), all at 9 km resolution. Note that VIIRS-SPNN only came online in late 2011 and so only covers the spring seasons 2012--2019.

Files: "Chla_Modis_Aqua.zip", "Chla_Modis_Terra.zip","Chla_VIIRS_SNPP.zip"

(2)  Version 1 of the monthly Level 3 Soil Moisture and Ocean Salinity (SMOS) Arctic Sea Surface Salinity (SSS) product provided by LOCEAN (Supply et al. 2020) at 25 km resolution. This product spans from June 2010 to November 2019 and covers the Arctic region north of 60◦N. Since we are interested in the spring bloom period (April–June) we limit our study period to years 2011–2019.

File: "SSS_SMOS.zip"

(3) Sea Ice Concentration (SIC) for Fram Strait spanning the years 2011 to 2019 from SMMR-SSM/I data processed with the NASA Team algorithm (Cavalieri et al. 1996) at 25 km resolution. 

File: "SIC_NASATeam.zip"

The focus of this study is how chl-a and SSS vary with distance from the sea ice edge. To compute this dependence, we determine the distance to the sea ice edge (defined as the SIC = 50 % contour) for each grid box on all monthly distribution maps. We then calculate the values of chl-a and SSS at each location and bin the data as a function of distance from the ice edge. Finally, we average over the years 2011-2019 to get the decadal-mean monthly curves for April, May, and June as functions of distance from the sea ice edge. The SIC contours for 15%, 50%, and 75% run in approximately straight and parallel lines from the northeast (near Svalbard) to the southwest. This enables us to consider how chl-a and SSS vary in the direction perpendicular to the ice edge by averaging the data in the direction parallel to the ice edge.