Professor Myles Allen CBE FRS

Abstract:

The along-track scanning radiometer (ATSR) on ERS-1 has delivered a continuous global record of radiometric (skin) sea surface temperature (SST) since August 1991. We present a comprehensive analysis of the large-scale and low-frequency characteristics of the data set using direct comparison with other global SST analyses to develop a quantitative understanding of the various factors contributing to the accuracy of and sources of bias in the first 4 years of the ATSR SST record. Such a global analysis is a necessary complement to direct validation against in situ observations, since large-scale sources of bias may be indistinguishable from instrument noise or sampling uncertainty in individual validation campaigns. No large-scale features attributable to atmospheric contamination through aerosols or water vapor are discernible in the difference between the three-channel, dual-view ATSR SSTs and the National Oceanic and Atmospheric Administration (NOAA) blended analysis of advanced very high resolution radiometer (AVHRR) and in situ SST observations. Features in the difference field can be traced to known deficiencies in the data used in the NOAA operational analysis or tentatively related to skin-bulk temperature differences in certain regions. Atmospheric contamination is, however, evident in the ATSR two-channel SST retrieval (used in daytime and after the failure of the 3.7 /zm channel) compared to the NOAA operational analysis. The Pinatubo aerosol plume is the dominant feature of the difference field in the first year of ATSR operation. In all cases, however, the amplitude of the atmospheric signature is significantly lower in dual-view than in corresponding single-view ATSR SSTs, indicating that the potential remains for unbiased two-channel SST retrieval even in the presence of aerosol. Copyright 1998 by the American Geophysical Union.

Abstract:

In recent years, altimetric measurements of sea surface height (SSH) and infrared radiometric measurements of sea surface temperature (SST) have provided a wealth of information about ocean circulation and atmosphere/ocean interactions. We use SST data from the Along-Track Scanning Radiometer (ATSR) to examine the relationship between SST and SSH anomalies (from temporal means). It is found that zero-lag spatial cross correlations between SST and SSH anomalies are surprisingly strong (∼0.7) in specific geographical locations associated with mesoscale variability. The correlations are seasonal, being strongest in winter months and weakest in summer months. A scale analysis of the correlations suggests that they are mainly due to features with wavelengths ∼600 km, implying that large meanders in ocean fronts and/or mesoscale eddies could be responsible.

Abstract:

Singular spectrum analysis (SSA) provides a robust method of separating an arbitrary signal from "white" (independent, identically distributed) noise. In the presence of "coloured" noise, or any autocorrelated process, high-variance components of the noise can confuse the singular value decomposition, thereby obscuring genuine signals which are, in principle, detectable. A generalization of SSA is presented which yields both an optimal filter to discriminate against an arbitrary coloured noise and an objective method of quantifying uncertainty in signal reconstruction. The algorithm is applied to a simple synthetic signal-separation problem and used to resolve a degeneracy in the SSA of interannual and interdecadal variability of the Earth's global mean temperature. © 1997 Elsevier Science B.V.