TY - JOUR
T1 - Average seasonal changes in chlorophyll a in Icelandic waters
AU - Gudmundsson, Kristinn
AU - Heath, Mike R.
AU - Clarke, Elizabeth D.
AU - Marine Laboratory, Aberdeen, Scotland (Funder)
AU - Marine Research Institute, Reykjavik, Iceland (Funder)
PY - 2009/8
Y1 - 2009/8
N2 - The standard algorithms used to derive sea surface chlorophyll a concentration from remotely sensed ocean colour data are based almost entirely on the measurements of surface water samples collected in open sea (case 1) waters which cover ~60% of the worlds oceans, where strong correlations between reflectance and chlorophyll concentration have been found. However, satellite
chlorophyll data for waters outside the defined case 1 areas, but derived using standard calibrations, are frequently used without reference to local in situ measurements and despite well-known factors likely to lead to inaccuracy. In Icelandic waters, multiannual
averages of 8-d composites of SeaWiFS chlorophyll concentration accounted for just 20% of the variance in a multiannual dataset of in situ chlorophyll a measurements. Nevertheless, applying penalized regression spline methodology to model the spatial and temporal patterns of in situ measurements, using satellite chlorophyll as one of the predictor variables, improved the correlation
considerably. Day number, representing seasonal variation, accounted for substantial deviation between SeaWiFS and in situ estimates of surface chlorophyll. The final model, using bottom depth and bearing to the sampling location as well as the two variables mentioned above, explained 49% of the variance in the fitting dataset.
AB - The standard algorithms used to derive sea surface chlorophyll a concentration from remotely sensed ocean colour data are based almost entirely on the measurements of surface water samples collected in open sea (case 1) waters which cover ~60% of the worlds oceans, where strong correlations between reflectance and chlorophyll concentration have been found. However, satellite
chlorophyll data for waters outside the defined case 1 areas, but derived using standard calibrations, are frequently used without reference to local in situ measurements and despite well-known factors likely to lead to inaccuracy. In Icelandic waters, multiannual
averages of 8-d composites of SeaWiFS chlorophyll concentration accounted for just 20% of the variance in a multiannual dataset of in situ chlorophyll a measurements. Nevertheless, applying penalized regression spline methodology to model the spatial and temporal patterns of in situ measurements, using satellite chlorophyll as one of the predictor variables, improved the correlation
considerably. Day number, representing seasonal variation, accounted for substantial deviation between SeaWiFS and in situ estimates of surface chlorophyll. The final model, using bottom depth and bearing to the sampling location as well as the two variables mentioned above, explained 49% of the variance in the fitting dataset.
KW - chlorophyll a
KW - modelling
KW - north atlantic
KW - remote sensing
KW - seasonal
KW - subarctic
KW - mathematics
KW - marine science
U2 - 10.1093/icesjms/fsp208
DO - 10.1093/icesjms/fsp208
M3 - Article
SN - 1054-3139
VL - 66
SP - 2133
EP - 2140
JO - ICES Journal of Marine Science
JF - ICES Journal of Marine Science
IS - 10
ER -