Improving the Use of Satellite Ocean Color Data in Arctic Coastal Ecosystems
Arctic Research Initiative
2007 Funded Project
If the Arctic warms over the next century as predicted, thawing and erosion of previously permafrosted land will increase the flux of nutrients into coastal Arctic waters. Warming will also reduce seasonal sea ice cover and thus greatly increase marine light levels. Arctic phytoplankton will perceive these changes as strong perturbations in their basic material and energetic resources. Because phytoplankton assemblage dynamics directly shape marine food webs, fisheries, and ecosystems, a solid understanding of how phytoplankton respond to such acute perturbations is a prerequisite for predicting and understanding how climate change affects Arctic ecosystems. The coastal Arctic is a challenging region to sample and study, but satellites can provide synoptic monitoring of coastal Arctic ecosystems over broad spatiotemporal scales. Proxies for phytoplankton biomass and productivity can be computed from satellite ocean color data, as can relevant environmental properties like particle load and the concentration of colored dissolved organic matter. Yet, basic problems with using ocean color data from the Arctic remain unresolved. "Standard" bio-optical algorithms are not robust there due to fundamental optical differences between Arctic waters and those at lower latitudes. These differences are poorly understood and they hinder our ability to use these otherwise valuable sensors to monitor and track climate-driven change along the Arctic coastal margin.
The goal of this research is to make ocean color data a more robust component of Arctic observational networks. Our research combines field observations in the eastern Chukchi Sea with a computer modeling study, to examine how ocean color algorithms in the Arctic can be improved by better addressing some of the basic optical differences in Arctic waters. This joint modeling- observational approach will provide guidance for determining what measurements or regions should be given the highest priority in Arctic observation systems to better ground-truth the ocean color data that are being currently collected. This study will also evaluate the use of alternate bio-optical algorithms for the Arctic, which have been proposed in the past but which have not been examined in detail because the optical field observations needed to evaluate them have been lacking.