203 research outputs found

    Remote sensing in the coastal and marine environment. Proceedings of the US North Atlantic Regional Workshop

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    Presentations were grouped in the following categories: (1) a technical orientation of Earth resources remote sensing including data sources and processing; (2) a review of the present status of remote sensing technology applicable to the coastal and marine environment; (3) a description of data and information needs of selected coastal and marine activities; and (4) an outline of plans for marine monitoring systems for the east coast and a concept for an east coast remote sensing facility. Also discussed were user needs and remote sensing potentials in the areas of coastal processes and management, commercial and recreational fisheries, and marine physical processes

    A compilation of digitized satellite imagery of the Gulf Stream (1982, 1983, and 1985)

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    Ninety plots of digitized temperature boundaries from infared satellite images of the Gulf Stream along with corresponding image snapshots were compiled to determine stream width propagation speed. The satellite images are from the years 1982, 1983, and 1985 and are often of consecutive days. In this report, these images and digitized plots are presented.Funding was provided by the Office of Naval Research through contract Number N00014-87-K-0007, and by the National Science Foundation under grant Numbers OCE 87-00601 and OCE 85-10828

    Deep Learning of Sea Surface Temperature Patterns to Identify Ocean Extremes

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    We performed an out-of-distribution (OOD) analysis of ∼12,000,000 semi-independent 128 × 128 pixel2 sea surface temperature (SST) regions, which we define as cutouts, from all nighttime granules in the MODIS R2019 Level-2 public dataset to discover the most complex or extreme phenomena at the ocean’s surface. Our algorithm (ULMO) is a probabilistic autoencoder (PAE), which combines two deep learning modules: (1) an autoencoder, trained on ∼150,000 random cutouts from 2010, to represent any input cutout with a 512-dimensional latent vector akin to a (non-linear) Empirical Orthogonal Function (EOF) analysis; and (2) a normalizing flow, which maps the autoencoder’s latent space distribution onto an isotropic Gaussian manifold. From the latter, we calculated a log-likelihood (LL) value for each cutout and defined outlier cutouts to be those in the lowest 0.1% of the distribution. These exhibit large gradients and patterns characteristic of a highly dynamic ocean surface, and many are located within larger complexes whose unique dynamics warrant future analysis. Without guidance, ULMO consistently locates the outliers where the major western boundary currents separate from the continental margin. Prompted by these results, we began the process of exploring the fundamental patterns learned by ULMO thereby identifying several compelling examples. Future work may find that algorithms such as ULMO hold significant potential/promise to learn and derive other, not-yet-identified behaviors in the ocean from the many archives of satellite-derived SST fields. We see no impediment to applying them to other large remote-sensing datasets for ocean science (e.g., SSH and ocean color)

    Mitigating masked pixels in climate-critical datasets

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    Remote sensing observations of the Earth's surface are frequently stymied by clouds, water vapour, and aerosols in our atmosphere. These degrade or preclude the measurementof quantities critical to scientific and, hence, societal applications. In this study, we train a natural language processing (NLP) algorithm with high-fidelity ocean simulations in order to accurately reconstruct masked or missing data in sea surface temperature (SST)--i.e. one of 54 essential climate variables identified by the Global Climate Observing System. We demonstrate that the Enki model repeatedly outperforms previously adopted inpainting techniques by up to an order-of-magnitude in reconstruction error, while displaying high performance even in circumstances where the majority of pixels are masked. Furthermore, experiments on real infrared sensor data with masking fractions of at least 40% show reconstruction errors of less than the known sensor uncertainty (RMSE < ~0.1K). We attribute Enki's success to the attentive nature of NLP combined with realistic SST model outputs, an approach that may be extended to other remote sensing variables. This study demonstrates that systems built upon Enki--or other advanced systems like it--may therefore yield the optimal solution to accurate estimates of otherwise missing or masked parameters in climate-critical datasets sampling a rapidly changing Earth.Comment: 21 pages, 6 main figure, 3 in Appendix; submitte

    Some observations of the Azores Current and the North Equatorial Current

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    The regions containing the two zonal currents of the subtropical gyre in the eastern North Atlantic, the Azores Current and the North Equatorial Current (NEC), have quite different physical characteristics. Associated with the Azores Current are strong horizontal thermohaline gradients that can be located easily both at the surface and at depth with temperature data alone, thus making satellite IR imagery and expendable bathythermograph profiles suitable for observing it. During winter, the surface expression of the Azores Current is often found to the north of the strongest subsurface gradients. In contrast to the Azores Current and to the central water mass boundary just to the south, the NEC has relatively weak horizontal temperature and salinity gradients, requiring density information in order to identify it. There is no clear surface manifestation found with the NEC. Common to both currents, though, is that each transports O(8 Sv) in the upper 800 m of the ocean near 27°W, with the largest velocities being in the upper 400 m

    Properties of small molecular drug loading and diffusion in a fluorinated PEG hydrogel studied by ^1H molecular diffusion NMR and ^(19)F spin diffusion NMR

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    R_f-PEG (fluoroalkyl double-ended poly(ethylene glycol)) hydrogel is potentially useful as a drug delivery depot due to its advanced properties of sol–gel two-phase coexistence and low surface erosion. In this study, ^1H molecular diffusion nuclear magnetic resonance (NMR) and ^(19)F spin diffusion NMR were used to probe the drug loading and diffusion properties of the R_f-PEG hydrogel for small anticancer drugs, 5-fluorouracil (FU) and its hydrophobic analog, 1,3-dimethyl-5-fluorouracil (DMFU). It was found that FU has a larger apparent diffusion coefficient than that of DMFU, and the diffusion of the latter was more hindered. The result of ^(19)F spin diffusion NMR for the corresponding freeze-dried samples indicates that a larger portion of DMFU resided in the R_f core/IPDU intermediate-layer region (where IPDU refers to isophorone diurethane, as a linker to interconnect the R_f group and the PEG chain) than that of FU while the opposite is true in the PEG–water phase. To understand the experimental data, a diffusion model was proposed to include: (1) hindered diffusion of the drug molecules in the R_f core/IPDU-intermediate-layer region; (2) relatively free diffusion of the drug molecules in the PEG-water phase (or region); and (3) diffusive exchange of the probe molecules between the above two regions. This study also shows that molecular diffusion NMR combined with spin diffusion NMR is useful in studying the drug loading and diffusion properties in hydrogels for the purpose of drug delivery applications

    The role of diurnal cycle in subduction/obduction

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    Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Oceanography 67 (2011): 273-279, doi:10.1007/s10872-011-0025-4.The annual subduction/obduction rate can be calculated in Lagrangian and Eulerian coordinates. In previous studies such calculations were primarily focused on the case with the seasonal cycle only. By extending these calculations to the case including the diurnal cycle of mixed layer depth, the annual subduction/obduction rate can be greatly increased.LLL and FW were supported by National Natural Science Foundation of China under Grant 40906007 and 40890150
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