944 resultados para least mean-square methods


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The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80x100 m were used as ground-truth to evaluate the simulations. The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of -8.4 K and -8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (-5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R= -0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (-4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.

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A thick Neogene section was recovered in the upper ~300 m of Ocean Drilling Program Hole 1138A, drilled on the Central Kerguelen Plateau in the Indian sector of the Southern Ocean. Sediment lithologies consist primarily of mixed carbonate and biosiliceous clays and oozes, with several thin (1-3 cm) tephra horizons. The tephras are glass rich, well sorted, and dominantly trachytic to rhyolitic in composition. Volcaniclastic material in these horizons is interpreted to have originated from Heard Island, 180 km northwest of Site 1138, and was likely emplaced through both primary ash fall and turbiditic, submarine flows. A Neogene age-depth model for Hole 1138A is constructed primarily from 36 diatom biostratigraphic datums. Nannofossil and planktonic foraminifer biostratigraphy provides supporting age information. Additionally, four high-precision 40Ar-39Ar ages are derived from ash and tephra horizons, and these radiometric ages are in close agreement with the biostratigraphic ages. The integrated age-depth model reveals a reasonably complete lower Miocene to upper Pleistocene section in Hole 1138A, with the exception of a ~1-m.y. hiatus at the Miocene/Pliocene boundary. Another possible hiatus is also identified at the Oligocene/Miocene boundary. High Neogene sedimentation rates and the presence of both calcareous and siliceous microfossils, combined with datable tephra horizons, establish Site 1138 as a suitable target for future drilling legs with paleoceanographic objectives. This report also proposes two new diatom species, Fragilariopsis heardensis and Azpeitia harwoodii, from Pliocene strata of Hole 1138A.

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Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.