3 Thermal Infrared Remote Sensing and Sea Surface Temperature . . .
65
highest filament activities associated with Cape Bojador (26.1
◦ N), Cape Ghir
(30.5
◦ N), and Cape Blanc (21
◦ N).
In the south, Meeuwis and Lutjeharms (1990) also used AVHRR data set to investigate surface thermal characteristics of the Benguela upwelling system, showing
similar permanent feature with seasonal variations depending on the location. The
Benguela upwelling (Fig. 3.4b) extends from the southern tip of South Africa to
the Angola front, with maximum intensity observed off Luderitz (Namibia). Owing
to TIR satellite sensors, Lutjeharms et al. (1991) showed evidence of a complex
structure of filaments exceeding 1000 km in length. Obviously, the spatial extent and
time evolution of these filaments could not have been made using traditional ship
surveys. Similar filaments and eddies are clearly observed in Fig. 3.4a (a MODIS
SST monthly composite) along the coast of South Africa and Namibia with colder
temperature extending several hundreds of km offshore.
In addition to map the spatio-temporal variability of upwelling events through
sequential SST images, TIR data have been extensively used to estimate an upwelling
index consisting in most cases of the temperature difference observed between coastal
water and water further offshore at a given latitude (Nykjaer and Van Camp 1994).
Figure 3.5 illustrates the seasonal cycle of the upwelling index in Northwest Africa
as observed with AVHRR SST for the 1981–1989 period. Upwelling process is
persistent throughout the year between 20
◦ N and 26
◦ N, with maximum intensity
during the summer. South of 20
◦ N, upwelling of lower intensity would mostly occur
in winter, whereas north of 28
◦ N, upwelling cells of significant intensity would take
place during summer and autumn.
A similar scenario was observed using AVHRR SST data for the 1987–2006 period
(Marcello et al. 2011), together with some evidence of an upwelling intensification
during this period along the whole northwest African coast as a result of an increase
in the water temperature offshore with respect to coastal waters. A direct link to
meteorological forcing would expose upwelling systems to higher sensitivity to climate disturbances. Warming is associated with a stronger pressure gradient between
land and ocean, which in turn, would reinforce alongshore geostrophic wind, hence
coastal upwelling (Bakun 1990). The previous observation and this latter theory is
somehow contrasting with another study showing a significant decrease in upwelling
intensity within the Canary upwelling system between 1967 and 2006 as calculated
from wind-derived Ekman transport (Gomez-Gesteira et al. 2008). A similar weakening of the upwelling intensity in the Iberian/Canary system is observed in the
NCEP/NCAR time series resulting from hindcast modeling using observations from
different platforms, including TIR satellite data, over the last 4 decades (Pardo et al.
2011). The same data, on the other hand, would show an enhancement of upwelling in
the Benguela region. The impact of climate change on upwelling systems still relies
on divergent indications. Santos et al. (2005), for example, argued that the variability
of AVHRR-derived SST over 2 decades (1980s and 1990s) in the Canary Current
is better explained by a breakpoint in the upwelling regime intensity as opposed to
a linear long-term trend. Such a debate underlines the importance of maintaining a
long-term continuity of satellite TIR data, and their subsequent combination with
numerical models to get a better understanding of the processes in place.
65
highest filament activities associated with Cape Bojador (26.1
◦ N), Cape Ghir
(30.5
◦ N), and Cape Blanc (21
◦ N).
In the south, Meeuwis and Lutjeharms (1990) also used AVHRR data set to investigate surface thermal characteristics of the Benguela upwelling system, showing
similar permanent feature with seasonal variations depending on the location. The
Benguela upwelling (Fig. 3.4b) extends from the southern tip of South Africa to
the Angola front, with maximum intensity observed off Luderitz (Namibia). Owing
to TIR satellite sensors, Lutjeharms et al. (1991) showed evidence of a complex
structure of filaments exceeding 1000 km in length. Obviously, the spatial extent and
time evolution of these filaments could not have been made using traditional ship
surveys. Similar filaments and eddies are clearly observed in Fig. 3.4a (a MODIS
SST monthly composite) along the coast of South Africa and Namibia with colder
temperature extending several hundreds of km offshore.
In addition to map the spatio-temporal variability of upwelling events through
sequential SST images, TIR data have been extensively used to estimate an upwelling
index consisting in most cases of the temperature difference observed between coastal
water and water further offshore at a given latitude (Nykjaer and Van Camp 1994).
Figure 3.5 illustrates the seasonal cycle of the upwelling index in Northwest Africa
as observed with AVHRR SST for the 1981–1989 period. Upwelling process is
persistent throughout the year between 20
◦ N and 26
◦ N, with maximum intensity
during the summer. South of 20
◦ N, upwelling of lower intensity would mostly occur
in winter, whereas north of 28
◦ N, upwelling cells of significant intensity would take
place during summer and autumn.
A similar scenario was observed using AVHRR SST data for the 1987–2006 period
(Marcello et al. 2011), together with some evidence of an upwelling intensification
during this period along the whole northwest African coast as a result of an increase
in the water temperature offshore with respect to coastal waters. A direct link to
meteorological forcing would expose upwelling systems to higher sensitivity to climate disturbances. Warming is associated with a stronger pressure gradient between
land and ocean, which in turn, would reinforce alongshore geostrophic wind, hence
coastal upwelling (Bakun 1990). The previous observation and this latter theory is
somehow contrasting with another study showing a significant decrease in upwelling
intensity within the Canary upwelling system between 1967 and 2006 as calculated
from wind-derived Ekman transport (Gomez-Gesteira et al. 2008). A similar weakening of the upwelling intensity in the Iberian/Canary system is observed in the
NCEP/NCAR time series resulting from hindcast modeling using observations from
different platforms, including TIR satellite data, over the last 4 decades (Pardo et al.
2011). The same data, on the other hand, would show an enhancement of upwelling in
the Benguela region. The impact of climate change on upwelling systems still relies
on divergent indications. Santos et al. (2005), for example, argued that the variability
of AVHRR-derived SST over 2 decades (1980s and 1990s) in the Canary Current
is better explained by a breakpoint in the upwelling regime intensity as opposed to
a linear long-term trend. Such a debate underlines the importance of maintaining a
long-term continuity of satellite TIR data, and their subsequent combination with
numerical models to get a better understanding of the processes in place.