Difficulties and limitations in the use of ocean colour remote sensing in polar regions:

  • The prevailing low solar elevations: At high latitudes, the Sun zenith angle is often larger than the maximum (generally 70°) for which atmospheric correction algorithms have been developed based on plane-parallel radiative transfer calculations. Consequently, at high latitudes, a large fraction of the ocean surface is undocumented for a large part of the year even though primary production may be significant. Whether or not this is a major problem must be determined, and the quality of standard atmospheric corrections for Sun zenith angle larger than 70° must be assessed.
  • The impact of ice on remotely sensed reflectance: Bélanger et al. (2007) and Wang and Shi (2009) have examined, based on radiative transfer simulations, the effects of the sea ice adjacency and of sub-pixel ice contamination on retrieved seawater reflectance and level-2 ocean products. They found significant impacts over the first several kilometers from the ice-edge and for concentrations of sub-pixel ice floes beyond a few percent. The extent of the problem (i.e. whether it compromises the use of ocean color) in typical polar conditions is unknown.
  • The deep chlorophyll maximum (DCM): A DCM is very often observed both in the Antarctic and Arctic Oceans. In the Arctic Ocean, the thaw-freeze cycle of sea ice and the large export of freshwater to the ocean by large Arctic rivers create pronounced haline stratification within the surface layer. In post-bloom conditions, a deep-chlorophyll maximum is associated with that vertical stratification. Contrary to the DCM observed at lower latitudes (Cullen et al. 1982), the Arctic DCM often corresponds to a maximum in particulate carbon and primary production (e.g. Martin et al. 2010). The statistical relationships between surface chlorophyll and chlorophyll concentration at depth developed for lower latitudes (e.g. Morel and Berthon 1989) are most probably not valid for the polar seas (e.g. Martin et al. 2010). Ignoring the vertical structure of the chlorophyll profile in the Arctic Ocean leads to significant error in the estimation of the areal primary production (Pabi et al. 2008, Hill and Zimmerman 2010).
  • The peculiar phytoplankton photosynthetic parameters: The low irradiance and low seawater temperature prevailing in polar seas are associated with unique bio-optical and photosynthetic parameters reflecting extreme environments (e.g. Rey 1991) that must be accounted for in primary production models. Only few have yet tried to do so (e.g. Arrigo et al. 2008a).
  • The optical complexity of seawater, especially over the Arctic shelves: Because of the important freshwater inputs, the Arctic continental shelves, which occupy 50% of the area, is characterized by high concentrations of CDOM (Matsuoka 2007; Bélanger et al 2008). Also, as a consequence of photoacclimation to low irradiances, phytoplankton cells often contain large amounts of pigments, and the chlorophyll-specific absorption coefficient is therefore particularly low due to pronounced pigment packaging (Cota et al. 2003; Wang et al 2005). Because of those optical peculiarities, standard ocean color algorithms do not work in the Arctic Ocean (Cota et al. 2004, Matsuoka et al. 2007).
  • The persistence of clouds and fog: High latitudes are known to present a heavy cloud cover. In addition, as soon as sea ice melts and open waters become in direct contact with the atmosphere, fog develops near the sea surface. These features limit the usage of ocean color data. Multiple overpasses by satellite over the same region the same day may overcome this problem to some extent. In a recent study, Perrette et al. (2010) tried to monitor ice-edge blooms in the Arctic Ocean, following to some extent the criteria of Arrigo et al. (1998) used in the Antarctic Ocean. Over the assumed 20-day duration of ice-edge conditions for any given pixel, only 50% of the pixels had at least 3 observations. This reflects the difficulty to monitor changes in the Arctic Ocean over short time scales, because of clouds and fog.


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