Baroclinic Rossby waves as inferred from temperature fluctuations in the Eastern Pacific

Monthly mean values of temperature from both hydrographic and XBT casts are used to compute isotherm displacements at weather station November (30N, 140W) and at six 2-degree squares between Hawaii and the weather station. A composite spectrum computed from all the isotherms in the six 2-degree squares shows significantly higher potential energy in the frequency range below the theoretical cut-off frequency (corresponding period about five months) for baroclinic Rossby waves...

Trends in Atlantic equatorial current variability

Approximately twice-monthly expendable bathythermograph (XBT) sections between Europe and Brazil, are used to characterize trends in the equatorial geostrophic surface currents orthogonal to the sections between September, 1980 and May, 1984. Using mean temperature-salinity relationships the upper layer temperature profiles are converted to density and used to compute 0/300 db dynamic height. Applying a second derivative method, at and near the equator, geostrophic surface currents are computed along each quasimeridional XBT section and time/space series of the equatorial currents are developed using spline interpolations in both time and space. Equatorial currents are mapped as time series of dynamic height and geostrophic current

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided

Computing Ocean Surface Currents from GOCI Ocean Color Satellite Imagery Over the Bohai Sea, Yellow Sea, East China Sea and Sea of Japan

One of the significant challenges in physical oceanography is getting an adequate space/time description of the ocean surface currents. One possible solution is the maximum cross-correlation (MCC) which we apply to hourly ocean color (OC) images from the Geostationary Ocean Color Imager (GOCI) over a 5-year long time period. Since GOCI provided a large number of MCC image pairs to process we introduce a new MCC search strategy to improve the computational efficiency of the MCC method saving 95.9% of the processing time. We also used a MCC current overlap method to increase the total spatial coverage of the currents, proving a 25.6% increase. A 5-year mean and seasonal time-average flows were computed for capturing the major currents in the area of interest (AOI). The mean flows investigate that the Kuroshio path, support the triple-branch pattern of the Tsushima Warm Current (TC) and reveal the origin of the TC. The evolution of the Kuroshio warm-core ring near the east coast of Japan is revealed by three monthly MCC composites. We capture the evolution of the Kuroshio meander over seasonal, monthly and weekly time scales. Three successive weekly MCC composite maps demonstrate how a large anticyclonic eddy, to the south of the Kuroshio meander, influences its formation and evolution in time and space. The unique ability to view short space/time scale changes in these strong current systems is a major benefit of the application of the MCC method to the high spatial resolution and rapid refresh GOCI data.</p

A comparison of sea surface temperatures from microwave remote sensing of the Labrador Sea with in situ measurements and model simulations

As one of the few places in the ocean where winter cooling and mixing creates conditions where water from the surface can penetrate into the deep ocean the Labrador Sea is an area of interest to people studying climate change in the ocean. Persistent cloud cover over this area makes it impossible to use infrared satellite imagery to relate space/time changes in sea surface temperature (SST) to changes in surface currents and air-sea interaction. Using passive microwave SSTs from the Advanced Microwave Scanning Radiometer (AMSR-E), we plot space/time changes in SST in the Labrador Sea and relate these changes to both simultaneous in situ measurements of temperature and numerical model SSTs. A direct comparison between the microwave SSTs, infrared SSTs, and in situ temperatures measured from profiling floats reveals that the microwave SSTs are a good representation of space/time changes in infrared SST and in ocean temperatures down to 10 m below the sea surface. Comparisons between the microwave SSTs and time series of temperatures at depths below 50 m reveal that winter/spring surface cooling makes the SST similar to temperatures at these deeper depths in the convection region of the central Labrador Sea. Detailed comparison of the annual cycle between the microwave SSTs and the model SST and 10 m currents reveals overall good agreement and some interesting differences

Direction of Arrival Estimation and Sensor Array Error Calibration Based on Blind Signal Separation

We consider estimating the direction of arrival (DOA) in the presence of sensor array error. In the proposed method, a blind signal separation method, the Joint Approximation and Diagonalization of Eigenmatrices (JADE) algorithm, is implemented to separate the signal vector and the mixing matrix consisting of the array manifold matrix and the sensor array error matrix. Based on a new mixing matrix and the reconstruction of the array output vector of each individual signal, we propose a novel DOA estimation method and sensor array error calibration procedure. This method is independent of array phase errors and performs well against difference of SNR of signals. Numerical simulations verify the effectiveness of the proposed method

Unsupervised Learning of Generalized Gamma Mixture Model with Application in Statistical Modeling of High-Resolution SAR Images

International audienceThe accurate statistical modeling of synthetic aperture radar (SAR) images is a crucial problem in the context of effective SAR image processing, interpretation and application. In this paper a semi-parametric approach is designed within the framework of finite mixture models based on the generalized Gamma distribution (GΓD) in view of its flexibility and compact form. Specifically, we develop a generalized Gamma mixture model (GΓMM) to implement an effective statistical analysis of high-resolution SAR images and prove the identifiability of such mixtures. A low-complexity unsupervised estimation method is derived by combining the proposed histogram-based expectation-conditional maximization (ECM) algorithm and the Figueiredo-Jain algorithm. This results in a numerical maximum likelihood (ML) estimator that can simultaneously determine the ML estimates of component parameters and the optimal number of mixture components. Finally, the state-of-the-art performance of this proposed method is verified by experiments with a wide range of high-resolution SAR images. Index Terms Synthetic aperture radar (SAR) images, finite mixture model, generalized Gamma distribution, expectation-conditional maximization (ECM) algorithm, minimum message length (MML), probability density function estimation , unsupervised learning

Origin of the Pseudogap in High-Temperature Cuprate Superconductors

Cuprate high-temperature superconductors exhibit a pseudogap in the normal state that decreases monotonically with increasing hole doping and closes at x \approx 0.19 holes per planar CuO2 while the superconducting doping range is 0.05 < x < 0.27 with optimal Tc at x \approx 0.16. Using ab initio quantum calculations at the level that leads to accurate band gaps, we found that four-Cu-site plaquettes are created in the vicinity of dopants. At x \approx 0.05 the plaquettes percolate, so that the Cu dx2y2/O p{\sigma} orbitals inside the plaquettes now form a band of states along the percolating swath. This leads to metallic conductivity and below Tc to superconductivity. Plaquettes disconnected from the percolating swath are found to have degenerate states at the Fermi level that split and lead to the pseudogap. The pseudogap can be calculated by simply counting the spatial distribution of isolated plaquettes, leading to an excellent fit to experiment. This provides strong evidence in favor of inhomogeneous plaquettes in cuprates.Comment: 24 pages (4 pages main text plus 20 pages supplement