552
circulation is therefore an important term when calculating a carbon budget
for the MAB continental shelf. By analogy to passive tracers such as salinity,
we also expect there to be inter-annual variability in nutrient and carbon
reservoirs and fluxes in the MAB. Variability on these inter-annual time
scales, and predicted longer term climate change, has important
consequences for ecosystems (Boesch et al. 2000). For localized regions
such as Narragansett Bay, time series studies suggest that climate change
may affect plankton community composition, seasonal succession, and
trophic interactions (Li and Smayda 1998, Smayda 1998), and for dominant
species such as the copepod Calanus finmarchicus, basin-scale variability
has been related to climate indicators observed or implied in both the
Northeast Atlantic (Ottersen et al. 2001) and the Northwest Atlantic (Greene
et al. 2003).
Our understanding of these processes in open shelf waters remains
rudimentary, due in part to our historically limited ability to make
multidisciplinary and multi-scale observations in an environment that is
highly variable in space and time. But this is changing. We are poised to
pursue studies of the coastal ocean through the widespread application of
new observational technologies that allow long-term monitoring and
adaptive sampling of physical, biological and chemical ocean conditions. A
network of Coastal Ocean Observatories is evolving, globally, pioneered in
many respects by the Long-term Ecosystem Observatory (LEO) established
by Rutgers University on the New Jersey coast in the mid 1990s. A 10-km
long electro-optic cable that powers and returns data from two sub-sea nodes
in 15 m of water enables the deployment of vertically profiling temperature,
salinity and bio-optical instruments returning long-term time series in real
time. A concerted effort to acquire data from multiple satellites and the
installation of a surface current radar system completed the backbone of
what has become the Coastal Ocean Observation Laboratory, or the COOL
Room (Glenn and Schofield 2003).
A series of Coastal Predictive Skill Experiments (CPSE) during the
summers of 1999 to 2001 incorporated the LEO data in a coastal ocean
model to deliver an ensemble of 3-day ocean forecasts that could be factored
into the decision-making process for directing ship-based observations so as
to adapt subsurface sampling to the evolving circulation. A re-analysis of the
2001 CPSE forecasts by Wilkin et al. (2004) explored the skill of the
modeling system with respect to a set of subsurface validation mooring data
(temperature and currents) recovered after the real-time experiment
completed. It was found that the model had significant intrinsic predictive
skill, and that this could be improved with the assimilation of sub-surface
observations from ship-based towed-body observations and surface current
data from radar.
Drawing on experience with the CPSE program, and wishing to employ
models as a complement to the burgeoning network of coastal ocean
observatories, we have formulated a number of limited area coastal ocean
JOHN L. WILKIN AND LYON LANEROLLE
circulation is therefore an important term when calculating a carbon budget
for the MAB continental shelf. By analogy to passive tracers such as salinity,
we also expect there to be inter-annual variability in nutrient and carbon
reservoirs and fluxes in the MAB. Variability on these inter-annual time
scales, and predicted longer term climate change, has important
consequences for ecosystems (Boesch et al. 2000). For localized regions
such as Narragansett Bay, time series studies suggest that climate change
may affect plankton community composition, seasonal succession, and
trophic interactions (Li and Smayda 1998, Smayda 1998), and for dominant
species such as the copepod Calanus finmarchicus, basin-scale variability
has been related to climate indicators observed or implied in both the
Northeast Atlantic (Ottersen et al. 2001) and the Northwest Atlantic (Greene
et al. 2003).
Our understanding of these processes in open shelf waters remains
rudimentary, due in part to our historically limited ability to make
multidisciplinary and multi-scale observations in an environment that is
highly variable in space and time. But this is changing. We are poised to
pursue studies of the coastal ocean through the widespread application of
new observational technologies that allow long-term monitoring and
adaptive sampling of physical, biological and chemical ocean conditions. A
network of Coastal Ocean Observatories is evolving, globally, pioneered in
many respects by the Long-term Ecosystem Observatory (LEO) established
by Rutgers University on the New Jersey coast in the mid 1990s. A 10-km
long electro-optic cable that powers and returns data from two sub-sea nodes
in 15 m of water enables the deployment of vertically profiling temperature,
salinity and bio-optical instruments returning long-term time series in real
time. A concerted effort to acquire data from multiple satellites and the
installation of a surface current radar system completed the backbone of
what has become the Coastal Ocean Observation Laboratory, or the COOL
Room (Glenn and Schofield 2003).
A series of Coastal Predictive Skill Experiments (CPSE) during the
summers of 1999 to 2001 incorporated the LEO data in a coastal ocean
model to deliver an ensemble of 3-day ocean forecasts that could be factored
into the decision-making process for directing ship-based observations so as
to adapt subsurface sampling to the evolving circulation. A re-analysis of the
2001 CPSE forecasts by Wilkin et al. (2004) explored the skill of the
modeling system with respect to a set of subsurface validation mooring data
(temperature and currents) recovered after the real-time experiment
completed. It was found that the model had significant intrinsic predictive
skill, and that this could be improved with the assimilation of sub-surface
observations from ship-based towed-body observations and surface current
data from radar.
Drawing on experience with the CPSE program, and wishing to employ
models as a complement to the burgeoning network of coastal ocean
observatories, we have formulated a number of limited area coastal ocean
JOHN L. WILKIN AND LYON LANEROLLE