4 resultados para Eulerþs angles

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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The beam attenuation serves as a proxy for particulate matter and is a key parameter in visibility algorithms for the aquatic environment. It is well known, however, that the beam attenuation is a function of the acceptance angle of the transmissometer used to measure it. Here we compare eight different transmissometers with four different acceptance angles using four different deployment strategies and sites, and find that their mean attenuation values differ markedly and in a consistent way with instrument acceptance angle: smaller acceptance angles provide higher beam attenuation values. This difference is due to variations in scattered light collected with different acceptance angles and is neither constant nor easy to parameterize. Variability (in space or time) in the ratios of beam attenuations measured by two different instruments correlates, in most cases, with the particle size parameter (as expected from Mie theory), but this correlation is often weak and can be the opposite of expectations based on particle size changes. We recommended careful consideration of acceptance angle in applications of beam transmission data especially when comparing data from different instruments. (C) 2009 Optical Society of America

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Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI's omission rate can be attributed to a coupling between SEVIRI's low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI's commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring.

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The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

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Addressing the multitude of challenges in marine policy requires an integrated approach that considers the multitude of drivers, pressures, and interests, from several disciplinary angles. Scenarios are needed to harmonise the analyses of different components of the marine system, and to deal with the uncertainty and complexity of the societal and biogeophysical dynamics in the system. This study considers a set of socio-economic scenarios to (1) explore possible futures in relation to marine invasive species, outbreak forming species, and gradual changes in species distribution and productivity; and (2) harmonise the projection modelling performed within associated studies. The exercise demonstrates that developing interdisciplinary scenarios as developed in this study is particularly complicated due to (1) the wide variety in endogeneity or exogeneity of variables in the different analyses involved; (2) the dual role of policy decisions as variables in a scenario or decisions to be evaluated and compared to other decisions; and (3) the substantial difference in time scale between societal and physical drivers.