519 resultados para Egypt, Remote Sensing, GIS, Red Sea


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To settle debate on the timing of sea level fluctuations during marine isotope stage (MIS) 3, we present records of d18O ruber (sea level proxy) and magnetic susceptibility from the same samples within the single sediment archive (i.e., "coregistered") of central Red Sea core GeoTü-KL11. Core-scanning X-ray fluorescence and environmental magnetic data establish the suitability of magnetic susceptibility as a proxy for eolian dust content in Red Sea sediments. The eolian dust data record similar variability as Greenland d18O ice during early to middle MIS 3, in agreement with previous observations that regional Arabian Sea climate fluctuated with a timing similar to that of Greenland climate variations. In contrast, the sea level record fluctuates with a timing similar to that of Antarctic-style climate variations. The coregistered nature of the two records in core KL11 unambiguously reveals a distinct offset in the phase relationship between sea level and eolian dust fluctuations. The results confirm that sea level rises, indicated by shifts in Red Sea d18O ruber to lighter values, occurred during cold episodes in Greenland during early to middle MIS 3. This indicates that the amplitudes of the reconstructed MIS 3 sea level fluctuations would not be reduced by inclusion of regional climate fluctuations in the Red Sea sea level method. Our analysis comprehensively supports our earlier conclusions of large-amplitude sea level variations during MIS 3 with a timing that is strongly similar to Antarctic-style climate variations.

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In this study we investigated the relations between community calcification of an entire coral reef in the northern Red Sea and annual changes in temperature, aragonite saturation and nutrient loading over a two year period. Summer (April-October) and winter (November-March) average calcification rates varied between 60 ± 20 and 30 ± 20 mmol·m-2·d-1, respectively. In general, calcification increased with temperature and aragonite saturation state of reef water with an apparent effect of nutrients, which is in agreement with most laboratory studies and in situ measurements of single coral growth rates. The calcification rates we measured in the reef correlated remarkably well with precipitation rates of inorganic aragonite calculated for the same temperature and degree of saturation ranges using empirical equations from the literature. This is a very significant finding considering that only a minute portion of reef calcification is inorganic. Hence, these relations could be used to predict the response of coral reefs to ocean acidification and warming.

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This dataset provides an inventory of thermo-erosional landforms and streams in three lowland areas underlain by ice-rich permafrost of the Yedoma-type Ice Complex at the Siberian Laptev Sea coast. It consists of two shapefiles per study region: one shapefile for the digitized thermo-erosional landforms and streams, one for the study area extent. Thermo-erosional landforms were manually digitized from topographic maps and satellite data as line features and subsequently analyzed in a Geographic Information System (GIS) using ArcGIS 10.0. The mapping included in particular thermo-erosional gullies and valleys as well as streams and rivers, since development of all of these features potentially involved thermo-erosional processes. For the Cape Mamontov Klyk site, data from Grosse et al. [2006], which had been digitized from 1:100000 topographic map sheets, were clipped to the Ice Complex extent of Cape Mamontov Klyk, which excludes the hill range in the southwest with outcropping bedrock and rocky slope debris, coastal barrens, and a large sandy floodplain area in the southeast. The mapped features (streams, intermittent streams) were then visually compared with panchromatic Landsat-7 ETM+ satellite data (4 August 2000, 15 m spatial resolution) and panchromatic Hexagon data (14 July 1975, 10 m spatial resolution). Smaller valleys and gullies not captured in the maps were subsequently digitized from the satellite data. The criterion for the mapping of linear features as thermo-erosional valleys and gullies was their clear incision into the surface with visible slopes. Thermo-erosional features of the Lena Delta site were mapped on the basis of a Landsat-7 ETM+ image mosaic (2000 and 2001, 30 m ground resolution) [Schneider et al., 2009] and a Hexagon satellite image mosaic (1975, 10 m ground resolution) [G. Grosse, unpublished data] of the Lena River Delta within the extent of the Lena Delta Ice Complex [Morgenstern et al., 2011]. For the Buor Khaya Peninsula, data from Arcos [2012], which had been digitized based on RapidEye satellite data (8 August 2010, 6.5 m ground resolution), were completed for smaller thermo-erosional features using the same RapidEye scene as a mapping basis. The spatial resolution, acquisition date, time of the day, and viewing geometry of the satellite data used may have influenced the identification of thermo-erosional landforms in the images. For Cape Mamontov Klyk and the Lena Delta, thermo-erosional features were digitized using both Hexagon and Landsat data; Hexagon provided higher resolution and Landsat provided the modern extent of features. Allowance of up to decameters was made for the lateral expansion of features between Hexagon and Landsat acquisitions (between 1975 and 2000).

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A wide variety of environmental records is necessary for analysing and understanding the complex Late Quaternary dynamics of permafrost-dominated Arctic landscapes. A NE Siberian periglacial key region was studied in detail using sediment records, remote sensing data, and terrain modelling, all incorporated in a geographical information system (GIS). The study area consists of the Bykovsky Peninsula and the adjacent Khorogor Valley in the Kharaulakh Ridge situated a few kilometres southeast of the Lena Delta. In this study a comprehensive cryolithological database containing information from 176 sites was compiled. The information from these sites is based on the review of previously published borehole data, outcrop profiles, surface samples, and our own field data. These archives cover depositional records of three periods: from Pliocene to Early Pleistocene, the Late Pleistocene and the Holocene. The main sediment sequences on the Bykovsky Peninsula consist of up to 50 m thick ice-rich permafrost deposits (Ice Complex) that were accumulated during the Late Pleistocene. They were formed as a result of nival processes around extensive snowfields in the Kharaulakh Ridge, slope processes in these mountains (such as in the Khorogor Valley), and alluvial/proluvial sedimentation in a flat accumulation plain dominated by polygonal tundra in the mountain foreland (Bykovsky Peninsula). During the early to middle Holocene warming, a general landscape transformation occurred from an extensive Late Pleistocene accumulation plain to a strongly thermokarst-dominated relief dissected by numerous depressions. Thermokarst subsidence had an enormous influence on the periglacial hydrological patterns, the sediment deposition, and on the composition and distribution of habitats. Climate deterioration, lake drainage, and talik refreezing occurred during the middle to late Holocene. The investigated region was reached by the post-glacial sea level rise during the middle Holocene, triggering thermo-abrasion of ice-rich coasts and the marine inundation of thermokarst depressions.

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An integrated instrument package for measuring and understanding the surface radiation budget of sea ice is presented, along with results from its first deployment. The setup simultaneously measures broadband fluxes of upwelling and downwelling terrestrial and solar radiation (four components separately), spectral fluxes of incident and reflected solar radiation, and supporting data such as air temperature and humidity, surface temperature, and location (GPS), in addition to photographing the sky and observed surface during each measurement. The instruments are mounted on a small sled, allowing measurements of the radiation budget to be made at many locations in the study area to see the effect of small-scale surface processes on the large-scale radiation budget. Such observations have many applications, from calibration and validation of remote sensing products to improving our understanding of surface processes that affect atmosphere-snow-ice interactions and drive feedbacks, ultimately leading to the potential to improve climate modelling of ice-covered regions of the ocean. The photographs, spectral data, and other observations allow for improved analysis of the broadband data. An example of this is shown by using the observations made during a partly cloudy day, which show erratic variations due to passing clouds, and creating a careful estimate of what the radiation budget along the observed line would have been under uniform sky conditions, clear or overcast. Other data from the setup's first deployment, in June 2011 on fast ice near Point Barrow, Alaska, are also shown; these illustrate the rapid changes of the radiation budget during a cold period that led to refreezing and new snow well into the melt season.

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A study of the polarimetric backscattering response of newly formed sea ice types under a large assortment of surface coverage was conducted using a ship-based C-band polarimetric radar system. Polarimetric backscattering results and physical data for 40 stations during the fall freeze-up of 2003, 2006, and 2007 are presented. Analysis of the copolarized correlation coefficient showed its sensitivity to both sea ice thickness and surface coverage and resulted in a statistically significant separation of ice thickness into two regimes: ice less than 6 cm thick and ice greater than 8 cm thick. A case study quantified the backscatter of a layer of snow infiltrated frost flowers on new sea ice, showing that the presence of the old frost flowers can enhance the backscatter by more than 6 dB. Finally, a statistical analysis of a series of temporal-spatial measurements over a visually homogeneous frost-flower-covered ice floe identified temperature as a significant, but not exclusive, factor in the backscattering measurements.

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The properties of snow on East Antarctic sea ice off Wilkes Land were examined during the Sea Ice Physics and Ecosystem Experiment (SIPEX) in late winter of 2007, focusing on the interaction with sea ice. This observation includes 11 transect lines for the measurement of ice thickness, freeboard, and snow depth, 50 snow pits on 13 ice floes, and diurnal variation of surface heat flux on three ice floes. The detailed profiling of topography along the transects and the d18O, salinity, and density datasets of snow made it possible to examine the snow-sea-ice interaction quantitatively for the first time in this area. In general, the snow displayed significant heterogeneity in types, thickness (mean: 0.14 +- 0.13 m), and density (325 +- 38 kg/m**3), as reported in other East Antarctic regions. High salinity was confined to the lowest 0.1 m. Salinity and d18O data within this layer revealed that saline water originated from the surface brine of sea ice in 20% of the total sites and from seawater in 80%. From the vertical profiles of snow density, bulk thermal conductivity of snow was estimated as 0.15 W/K/m on average, only half of the value used for numerical sea-ice models. Although the upward heat flux within snow estimated with this value was significantly lower than that within ice, it turned out that a higher value of thermal conductivity (0.3 to 0.4 W/K/m) is preferable for estimating ice growth amount in current numerical models. Diurnal measurements showed that upward conductive heat flux within the snow and net long-wave radiation at the surface seem to play important roles in the formation of snow ice from slush. The detailed surface topography allowed us to compare the air-ice drag coefficients of ice and snow surfaces under neutral conditions, and to examine the possibility of the retrieval of ice thickness distribution from satellite remote sensing. It was found that overall snow cover works to enhance the surface roughness of sea ice rather than moderate it, and increases the drag coefficient by about 10%. As for thickness retrieval, mean ice thickness had a higher correlation with ice surface roughness than mean freeboard or surface elevation, which indicates the potential usefulness of satellite L-band SAR in estimating the ice thickness distribution in the seasonal sea-ice zone.

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The effects of changing ice and atmospheric conditions on the upwelling of deep nutrient-laden waters and biological productivity in the coastal Beaufort Sea were quantified using a unique combination of in situ and remote-sensing approaches. Repeated instances of ice ablation and upwelling during fall 2007 and summer 2008 multiplied the production of ice algae, phytoplankton, zooplankton and benthos by 2 to 6 fold. Strong wind forcing failed to induce upward shifts in the biological productivity of stratified waters off the shelf.

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Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.