260
H.M. Beggs
currently an issue due to the relative coarser horizontal resolution of the global and
regional ocean models (>3 km – Dombrowsky et al., 2009). However, future ultrahigh-resolution regional ocean models may require higher resolution (1 km) SST,
particularly within 50 km of coastlines. In addition to assimilation, regional coastal
models in particular (e.g. Baird et al., 2010) require accurate, ultra high-resolution
(1 km), level 3 or level 4 SST products for validation.
SST in coastal and inland regions have a large variability due to the diurnal cycle
of solar radiation, which enhances surface characteristics of the land and sea and
forces land-air-sea interactions, i.e. land-sea breezes. Typically, coastal ocean modelling systems have a requirement for ultra-high resolution SST data sets (1 km
spatial resolution and < 6 h temporal resolution), with good accuracy (<0.1 ◦ C) and
hourly temporal coverage. 7 Overall, for global, regional and coastal ocean modelling maintenance of high resolution SST is critical as well as the ability to observe
the diurnal cycle (Brassington, 2009).
15.6 Fisheries Management and Protection of Endangered
Species
The prediction of fish habitat using SST (among other data) is currently being
developed and used for fishery management. The near real-time mapping of toppredators’ habitat is being used (e.g. Southern Bluefin Tuna, Hobday and Hartmann,
2006) or proposed (e.g. Atlantic Bluefin Tuna, Druon, 2010) for reducing discard
and preserving the resource and fishery respectively. SST traces efficiently (with
chlorophyll-a data) the biomass-rich oceanic fronts which are used to identify the
feeding habitat of most pelagic species. The monthly accumulation of heat in the
surface layer which can be retrieved from SST may also trace the spawning habitat
of some fish species (Atlantic Bluefin Tuna, Druon, 2010). The potential of using
SST with other satellite and ocean model products for improving scientific knowledge on most fish habitat and fishery management is high with the processing of
both the multi-annual and near-real-time products.
Historically, assessment of the sustainable exploitation of a commercial fish stock
has been largely based on data from the fishing fleet. Recently, international agencies have requested a more ecological approach to managing fisheries and other
marine resources. In the US the “Pelagic Habitat Analysis Module” (PHAM) has
been developed to improve stock assessment by integrating classical fisheries data
with satellite SST and ocean colour maps, outputs from a Global Circulation Model
and statistical algorithms to map habitat of pelagic species (Kiefer et al., 2009).
Such information along with information on recruitment can then be introduced
into existing stock assessment models (Kiefer et al., 2009).
Remotely sensed SST can also be used in management systems to protect endangered marine species, by identifying regions where the species is more likely to
7 http://www.wmo.int/pages/prog/sat/documents/SOG-08_Ocean.doc
H.M. Beggs
currently an issue due to the relative coarser horizontal resolution of the global and
regional ocean models (>3 km – Dombrowsky et al., 2009). However, future ultrahigh-resolution regional ocean models may require higher resolution (1 km) SST,
particularly within 50 km of coastlines. In addition to assimilation, regional coastal
models in particular (e.g. Baird et al., 2010) require accurate, ultra high-resolution
(1 km), level 3 or level 4 SST products for validation.
SST in coastal and inland regions have a large variability due to the diurnal cycle
of solar radiation, which enhances surface characteristics of the land and sea and
forces land-air-sea interactions, i.e. land-sea breezes. Typically, coastal ocean modelling systems have a requirement for ultra-high resolution SST data sets (1 km
spatial resolution and < 6 h temporal resolution), with good accuracy (<0.1 ◦ C) and
hourly temporal coverage. 7 Overall, for global, regional and coastal ocean modelling maintenance of high resolution SST is critical as well as the ability to observe
the diurnal cycle (Brassington, 2009).
15.6 Fisheries Management and Protection of Endangered
Species
The prediction of fish habitat using SST (among other data) is currently being
developed and used for fishery management. The near real-time mapping of toppredators’ habitat is being used (e.g. Southern Bluefin Tuna, Hobday and Hartmann,
2006) or proposed (e.g. Atlantic Bluefin Tuna, Druon, 2010) for reducing discard
and preserving the resource and fishery respectively. SST traces efficiently (with
chlorophyll-a data) the biomass-rich oceanic fronts which are used to identify the
feeding habitat of most pelagic species. The monthly accumulation of heat in the
surface layer which can be retrieved from SST may also trace the spawning habitat
of some fish species (Atlantic Bluefin Tuna, Druon, 2010). The potential of using
SST with other satellite and ocean model products for improving scientific knowledge on most fish habitat and fishery management is high with the processing of
both the multi-annual and near-real-time products.
Historically, assessment of the sustainable exploitation of a commercial fish stock
has been largely based on data from the fishing fleet. Recently, international agencies have requested a more ecological approach to managing fisheries and other
marine resources. In the US the “Pelagic Habitat Analysis Module” (PHAM) has
been developed to improve stock assessment by integrating classical fisheries data
with satellite SST and ocean colour maps, outputs from a Global Circulation Model
and statistical algorithms to map habitat of pelagic species (Kiefer et al., 2009).
Such information along with information on recruitment can then be introduced
into existing stock assessment models (Kiefer et al., 2009).
Remotely sensed SST can also be used in management systems to protect endangered marine species, by identifying regions where the species is more likely to
7 http://www.wmo.int/pages/prog/sat/documents/SOG-08_Ocean.doc