Can the subtropical North Atlantic permanent thermocline be observed from space?

The analysis of remotely sensed altimeter data and in situ measurements shows that ERS 2 radar can monitor the ocean permanent thermocline from space. The remotely sensed sea level anomaly data account for similar to 2/3 of the temperature variance or vertical displacement of isotherms at a depth of similar to 550 m in the Subtropical North Atlantic Ocean near 32.5 degree N. This depth corresponds closely to the region of maximum temperature gradient in the permanent thermocline where near semi-annual internal vertical displacements reach 200 to 300 m. The gradient of the altimeter sea level anomaly data correlates well with measured ocean currents to a depth of 750 m. It is shown that observations from space can account for similar to 3/4 of the variance of ocean currents measured in situ in the permanent thermocline over a 2-y period. The magnification of the permanent thermocline displacement with respect to the displacement of the sea surface was determined as - x650 and gives a measure of the ratio of barotropic to baroclinic decay scale of geostrophic current with depth. The overall results are used to interpret an eight year altimeter data tie series in the Subtropical North Atlantic at 32.5 degree N which shows a dominant wave or eddy period near 200 days, rather than semi-annual and increases in energy propagating westward in 1995 (west of 25 degree W). The effects of rapid North Atlantic Oscillation climate change on ocean circulation are discussed. The altimeter data for the Atlantic were Fourier analysed. It is shown how the annual and semi-annual components relate to the seasonal maximum cholorophyll-a SeaWiFS signal in tropical and equatorial regions due to the lifting of the thermocline caused by seasonally varying ocean currents forced by wind stress.

Space-borne study of seasonal, multi-year, and decadal phytoplankton dynamics in the Bay of Biscay

Seasonal and inter-annual variations in phytoplankton community abundance in the Bay of Biscay are studied. Preliminarily processed by the National Aeronautics and Space Administration (NASA) to yield normalized water-leaving radiance and the top-of-the-atmosphere solar radiance, Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Coastal Zone Color Scanner (CZCS) data are further supplied to our dedicated retrieval algorithms to infer the sought for parameters. By applying the National Oceanic and Atmospheric Administration's (NOAA's) Advanced Very High Resolution Radiometer (AVHRR) data, the surface reflection coefficient in the only band in the visible spectrum is derived and employed for analysis. Decadal bridged time series of variations of diatom-dominated phytoplankton and green dinoflagellate Lepidodinium chlorophorum within the shelf zone and the coccolithophore Emiliania huxleyi in the pelagic area of the Bay are documented and analysed in terms of impacts of some biogeochemical and geophysical forcing factors.

Identifying four phytoplankton functional types from space: An ecological approach

Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown.

Region-wide changes in marine ecosystem dynamics: state-space models to distinguish trends from step changes

Regime shifts are sudden changes in ecosystem structure that can be detected across several ecosystem components. The concept that regime shifts are common in marine ecosystems has gained popularity in recent years. Many studies have searched for the step-like changes in ecosystem state expected under a simple interpretation of this idea. However, other kinds of change, such as pervasive trends, have often been ignored. We assembled over 300 ecological time series from seven UK marine regions, covering two to three decades. We developed state-space models for the first principal component of the time series in each region, a common measure of ecosystem state. Our models allowed both trends and step changes, possibly in combination. We found trends in three of seven regions and step changes in two of seven regions. Gradual and sudden changes are therefore important trajectories to consider in marine ecosystems.

Space-based lidar measurements of global ocean carbon stocks

Global ocean phytoplankton biomass (C-phyto) and total particulate organic carbon (POC) stocks have largely been characterized from space using passive ocean color measurements. A space-based light detection and ranging (lidar) system can provide valuable complementary observations for C-phyto and POC assessments, with benefits including day-night sampling, observations through absorbing aerosols and thin cloud layers, and capabilities for vertical profiling through the water column. Here we use measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to quantify global C-phyto and POC from retrievals of subsurface particulate backscatter coefficients (b(bp)). CALIOP b(bp) data compare favorably with airborne, ship-based, and passive ocean data and yield global average mixed-layer standing stocks of 0.44 Pg C for C-phyto and 1.9 Pg for POC. CALIOP-based C-phyto and POC data exhibit global distributions and seasonal variations consistent with ocean plankton ecology. Our findings support the use of spaceborne lidar measurements for advancing understanding of global plankton systems.