Global Estimation of Suspended Particulate Matter From Satellite Ocean Color Imagery.

The suspended particulate matter (SPM) concentration (unit: mg l-1) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance (R rs (λ)) at near-infrared (NIR), red, green, and blue bands (NIR-RGB) as input. The evaluations showed that the NIR-RGB algorithm could predict SPM with the median absolute percentage difference of ∼35%-39% over a wide range from ∼0.01 to >2,000 mg l-1. The uncertainty is smaller (29%-37%) for turbid waters where R rs (671) ≥ 0.0012 sr-1 and slightly higher (41%-44%) for clear waters where R rs (671) < 0.0012 mg l-1. The algorithm was implemented with the global R rs (λ) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS-generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications.

Optimal satellite orbit configuration for global ocean color product coverage.

We develop a methodology to evaluate the current orbital configuration of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 satellites and to study various orbital configurations for the next VIIRS in the Joint Polar Satellite System (JPSS) series from the perspective of maximizing the global daily ocean color retrievals. We focus on the coverage losses due to high sensor-zenith angle and high sun glint contamination and find that two sensors cannot avoid gaps in daily coverage. If JPSS-2 shares the same orbit with SNPP and NOAA-20, then phase shift of around 90° relative to SNPP and NOAA-20 would maximize daily ocean color retrievals.

Destriping algorithm for improved satellite-derived ocean color product imagery.

While modern multi-detector sensors offer a much improved image resolution and signal-to-noise ratio among other performance benefits, the multi-detector arrangement gives rise to striping in satellite imagery due to various sources, which cannot be perfectly corrected by sensor calibration. Recently, Bouali and Ignatov (2014) [J. Atmos. Oceanic Technol., 31, 150-163 (2014)] introduced a new approach to remove relatively small detector performance-related striping from thermal infrared bands for improved sea surface temperature data. We show that this methodology, with appropriately chosen parameters and adjustments, can also be applied to remove striping of a much larger variance from the solar reflective band data. Specifically, we modify and apply this new approach to remove striping from satellite-derived normalized water-leaving radiance spectra nLw(λ) obtained from solar reflective bands. It is important that the destriping approach not be applied to the top-of-atmosphere radiances. The results show a significant improvement in image quality for both nLw(λ) spectra and nLw(λ)-derived ocean biological and biogeochemical products such as chlorophyll-a concentration, and the water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490).

Simulation of inhomogeneous distributions of ultracold atoms in an optical lattice via a massively parallel implementation of nonequilibrium strong-coupling perturbation theory.

We present a nonequilibrium strong-coupling approach to inhomogeneous systems of ultracold atoms in optical lattices. We demonstrate its application to the Mott-insulating phase of a two-dimensional Fermi-Hubbard model in the presence of a trap potential. Since the theory is formulated self-consistently, the numerical implementation relies on a massively parallel evaluation of the self-energy and the Green's function at each lattice site, employing thousands of CPUs. While the computation of the self-energy is straightforward to parallelize, the evaluation of the Green's function requires the inversion of a large sparse 10(d) × 10(d) matrix, with d > 6. As a crucial ingredient, our solution heavily relies on the smallness of the hopping as compared to the interaction strength and yields a widely scalable realization of a rapidly converging iterative algorithm which evaluates all elements of the Green's function. Results are validated by comparing with the homogeneous case via the local-density approximation. These calculations also show that the local-density approximation is valid in nonequilibrium setups without mass transport.

Nonlocal effects on magnetism in the diluted magnetic semiconductor Ga1-xMnxAs.

The magnetic properties of the diluted magnetic semiconductor Ga1-xMnxAs are studied within the dynamical cluster approximation. We use the k x p Hamiltonian to describe the electronic structure of GaAs with spin-orbit coupling and strain effects. We show that nonlocal effects are essential for explaining the experimentally observed transition temperature and saturation magnetization. We also demonstrate that the cluster anisotropy is very strong and induces rotational frustration and a cube-edge direction magnetic anisotropy at low temperature. With this, we explain the temperature-driven spin reorientation in this system.