5 Mesoscale Dynamics in the Canary Islands Area . . .
99
wakes and of both cyclonic and anticyclonic eddies. RS images derived from sensors
operating in the visible and thermal infrared parts of the spectrum provide indications
of the systematic presence of mesoscale eddies and warm regions in the lee of nearly
all islands (Van Camp et al. 1991; Pacheco and Hernández-Guerra 1999; Barton et al.
2000), but so far the most studied and best documented features, by means of both
in-situ and RS observations, are those found south of Gran Canaria island (Arístegui
et al. 1997; Barton et al. 1998; Basterretxea et al. 2002; Sangrà et al. 2005).
Previous investigations such as those mentioned above, focusing mainly on the
analysis of the mesoscale features found south of Gran Canaria, concluded that the
island-induced eddies of this region are recurrent oceanographic structures, which—
in combination with other features originating from the coastal zone, like upwelling
filaments and eddies—contribute significantly and in different ways to the variability
of the observed physical and biological field south of the Archipelago (Arístegui et al.
1997). The main purpose of this work is to provide an additional description of the
mesoscale variability around the Canary Islands, covering in detail an entire seasonal
cycle.
This will be done using a combination of RS data with complementary specificities, taking into account that earlier work in the region has already shown the
correlation existing between the signature of mesoscale features in satellite data and
concurrent in situ observations, and validating their use to assess oceanographic processes of the whole area (Arístegui et al. 1994; Barton et al. 1998; Tejera et al. 2002).
The main advantages and drawbacks of the RS techniques used in the present work
will be briefly reviewed. Further, the results of an altimeter data time series analysis
will be given, together with a detailed account of the mesoscale variability in the
region, as obtained through the combined analysis of altimeter and multi-spectral
radiometer data.
5.2 Remote Sensing Data and Mesoscale Variability
Chlorophyll-a (Chl-a), Brightness Temperature (BT) and Sea Surface Temperature
(SST) data, gathered by multi-spectral radiometers operating in the visible and infrared spectrum, have all been used in this work, in combination with Sea Level
Anomaly (SLA) data from altimeter radars operating in the microwave spectrum.
Both BT and SST can be obtained from thermal infrared sensors, but unlike for SST,
the atmospheric signal is not removed for BT.
Algorithms used to remove atmospheric effects increase the noise level and reduce
the temperature gradients in the data (La Violette and Holyer 1988). This sometimes
renders BT images preferable to SST images, when observing mesoscale features. A
description of how these geophysical parameters are derived from RS measurements
is out of the scope of this work and can be found in a vast literature on the subject
(see e.g. Robinson 2004). However, in relation to the retrieval of information on
mesoscale phenomena in the Canary Islands area, it is worth examining the sampling performance of different sensors and the main characteristics of their derived
parameters.
99
wakes and of both cyclonic and anticyclonic eddies. RS images derived from sensors
operating in the visible and thermal infrared parts of the spectrum provide indications
of the systematic presence of mesoscale eddies and warm regions in the lee of nearly
all islands (Van Camp et al. 1991; Pacheco and Hernández-Guerra 1999; Barton et al.
2000), but so far the most studied and best documented features, by means of both
in-situ and RS observations, are those found south of Gran Canaria island (Arístegui
et al. 1997; Barton et al. 1998; Basterretxea et al. 2002; Sangrà et al. 2005).
Previous investigations such as those mentioned above, focusing mainly on the
analysis of the mesoscale features found south of Gran Canaria, concluded that the
island-induced eddies of this region are recurrent oceanographic structures, which—
in combination with other features originating from the coastal zone, like upwelling
filaments and eddies—contribute significantly and in different ways to the variability
of the observed physical and biological field south of the Archipelago (Arístegui et al.
1997). The main purpose of this work is to provide an additional description of the
mesoscale variability around the Canary Islands, covering in detail an entire seasonal
cycle.
This will be done using a combination of RS data with complementary specificities, taking into account that earlier work in the region has already shown the
correlation existing between the signature of mesoscale features in satellite data and
concurrent in situ observations, and validating their use to assess oceanographic processes of the whole area (Arístegui et al. 1994; Barton et al. 1998; Tejera et al. 2002).
The main advantages and drawbacks of the RS techniques used in the present work
will be briefly reviewed. Further, the results of an altimeter data time series analysis
will be given, together with a detailed account of the mesoscale variability in the
region, as obtained through the combined analysis of altimeter and multi-spectral
radiometer data.
5.2 Remote Sensing Data and Mesoscale Variability
Chlorophyll-a (Chl-a), Brightness Temperature (BT) and Sea Surface Temperature
(SST) data, gathered by multi-spectral radiometers operating in the visible and infrared spectrum, have all been used in this work, in combination with Sea Level
Anomaly (SLA) data from altimeter radars operating in the microwave spectrum.
Both BT and SST can be obtained from thermal infrared sensors, but unlike for SST,
the atmospheric signal is not removed for BT.
Algorithms used to remove atmospheric effects increase the noise level and reduce
the temperature gradients in the data (La Violette and Holyer 1988). This sometimes
renders BT images preferable to SST images, when observing mesoscale features. A
description of how these geophysical parameters are derived from RS measurements
is out of the scope of this work and can be found in a vast literature on the subject
(see e.g. Robinson 2004). However, in relation to the retrieval of information on
mesoscale phenomena in the Canary Islands area, it is worth examining the sampling performance of different sensors and the main characteristics of their derived
parameters.