Influence of salinity on the interannual heat storage trends in the Atlantic estimated from altimeters and Pilot Research Moored Array in the Tropical Atlantic data

Changes in the oceanic heat storage (HS) can reveal important evidences of climate variability related to ocean heat fluxes. Specifically, long-term variations in HS are a powerful indicator of climate change as HS represents the balance between the net surface energy flux and the poleward heat transported by the ocean currents. HS is estimated from sea surface height anomaly measured from the altimeters TOPEX/Poseidon and Jason 1 from 1993 to 2006. To characterize and validate the altimeter-based HS in the Atlantic, we used the data from the Pilot Research Moored Array in the Tropical Atlantic (PIRATA) array. Correlations and rms differences are used as statistical figures of merit to compare the HS estimates. The correlations range from 0.50 to 0.87 in the buoys located at the equator and at the southern part of the array. In that region the rms differences range between 0.40 and 0.51 x 10(9) Jm(-2). These results are encouraging and indicate that the altimeter has the precision necessary to capture the interannual trends in HS in the Atlantic. Albeit relatively small, salinity changes can also have an effect on the sea surface height anomaly. To account for this effect, NCEP/GODAS reanalysis data are used to estimate the haline contraction. To understand which dynamical processes are involved in the HS variability, the total signal is decomposed into nonpropagating basin-scale and seasonal (HS(l)) planetary waves, mesoscale eddies, and small-scale residual components. In general, HS(l) is the dominant signal in the tropical region. Results show a warming trend of HS(l) in the past 13 years almost all over the Atlantic basin with the most prominent slopes found at high latitudes. Positive interannual trends are found in the halosteric component at high latitudes of the South Atlantic and near the Labrador Sea. This could be an indication that the salinity anomaly increased in the upper layers during this period. The dynamics of the South Atlantic subtropical gyre could also be subject to low-frequency changes caused by a trend in the halosteric component on each side of the South Atlantic Current.

A complexity measure for selective matching of signals by the brain.

We have previously derived a theoretical measure of neural complexity (CN) in an attempt to characterize functional connectivity in the brain. CN measures the amount and heterogeneity of statistical correlations within a neural system in terms of the mutual information between subsets of its units. CN was initially used to characterize the functional connectivity of a neural system isolated from the environment. In the present paper, we introduce a related statistical measure, matching complexity (CM), which reflects the change in CN that occurs after a neural system receives signals from the environment. CM measures how well the ensemble of intrinsic correlations within a neural system fits the statistical structure of the sensory input. We show that CM is low when the intrinsic connectivity of a simulated cortical area is randomly organized. Conversely, CM is high when the intrinsic connectivity is modified so as to differentially amplify those intrinsic correlations that happen to be enhanced by sensory input. When the input is represented by an individual stimulus, a positive value of CM indicates that the limited mutual information between sensory sheets sampling the stimulus and the rest of the brain triggers a large increase in the mutual information between many functionally specialized subsets within the brain. In this way, a complex brain can deal with context and go "beyond the information given."