37 resultados para Data acquisition

em Publishing Network for Geoscientific


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During the SINOPS project, an optimal state of the art simulation of the marine silicon cycle is attempted employing a biogeochemical ocean general circulation model (BOGCM) through three particular time steps relevant for global (paleo-) climate. In order to tune the model optimally, results of the simulations are compared to a comprehensive data set of 'real' observations. SINOPS' scientific data management ensures that data structure becomes homogeneous throughout the project. Practical work routine comprises systematic progress from data acquisition, through preparation, processing, quality check and archiving, up to the presentation of data to the scientific community. Meta-information and analytical data are mapped by an n-dimensional catalogue in order to itemize the analytical value and to serve as an unambiguous identifier. In practice, data management is carried out by means of the online-accessible information system PANGAEA, which offers a tool set comprising a data warehouse, Graphical Information System (GIS), 2-D plot, cross-section plot, etc. and whose multidimensional data model promotes scientific data mining. Besides scientific and technical aspects, this alliance between scientific project team and data management crew serves to integrate the participants and allows them to gain mutual respect and appreciation.

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IBAMar (http://www.ba.ieo.es/ibamar) is a regional database that puts together all physical and biochemical data obtained by multiparametric probes (CTDs equipped with different sensors), during the cruises managed by the Balearic Center of the Spanish Institute of Oceanography (COB-IEO). It has been recently extended to include data obtained with classical hydro casts using oceanographic Niskin or Nansen bottles. The result is a database that includes a main core of hydrographic data: temperature (T), salinity (S), dissolved oxygen (DO), fluorescence and turbidity; complemented by bio-chemical data: dissolved inorganic nutrients (phosphate, nitrate, nitrite and silicate) and chlorophyll-a. In IBAMar Database, different technologies and methodologies were used by different teams along the four decades of data sampling in the COB-IEO. Despite of this fact, data have been reprocessed using the same protocols, and a standard QC has been applied to each variable. Therefore it provides a regional database of homogeneous, good quality data. Data acquisition and quality control (QC): 94% of the data are CTDs Sbe911 and Sbe25. S and DO were calibrated on board using water samples, whenever a Rossetta was available (70% of the cases). All CTD data from Seabird CTDs were reviewed and post processed with the software provided by Sea-Bird Electronics. Data were averaged to get 1 dbar vertical resolution. General sampling methodology and pre processing are described in https://ibamardatabase.wordpress.com/home/). Manual QC include visual checks of metadata, duplicate data and outliers. Automatic QC include range check of variables by area (north of Balearic Islands, south of BI and Alboran Sea) and depth (27 standard levels), check for spikes and check for density inversions. Nutrients QC includes a preliminary control and a range check on the observed level of the data to detect outliers around objectively analyzed data fields. A quality flag is assigned as an integer number, depending on the result of the QC check.

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For the production of the orthophoto map Vernagtferner 1979, scale I: 10000, photographs of the flight "Hintereisferner 1979" were used, which have been found to be very suitable for differential rectification. Control points were determined before the flight took place. The processing of nine stereopairs was carried out on an analytical plotter. Simultaneously with the on-line plotting of the contour lines the reference data for the computation of the profiles for the differential rectification were recorded. The orthophoto map was covered by four aerial photographs. A smooth data transfer was ensured because the same computer was used for the data acquisition and the differential rectification. Two printing originals were prepared, one for the outline drawings with contour lines and another for the orthophoto. The print was done in black for the two copies. The data acquisition, the computation of the scanning profiles for the othoprojector and the procedure of the differential rectification are described. The reason for the use of on-line drawn contour lines is explained. Further applications, also for digital contour lines, are introduced. Possibilities for the achievement of high photo quality during the reproduction are discussed.

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This study focuses on the present-day surface elevation of the Greenland and Antarctic ice sheets. Based on 3 years of CryoSat-2 data acquisition we derived new elevation models (DEMs) as well as elevation change maps and volume change estimates for both ice sheets. Here we present the new DEMs and their corresponding error maps. The accuracy of the derived DEMs for Greenland and Antarctica is similar to those of previous DEMs obtained by satellite-based laser and radar altimeters. Comparisons with ICESat data show that 80% of the CryoSat-2 DEMs have an uncertainty of less than 3 m ± 15 m. The surface elevation change rates between January 2011 and January 2014 are presented for both ice sheets. We compared our results to elevation change rates obtained from ICESat data covering the time period from 2003 to 2009. The comparison reveals that in West Antarctica the volume loss has increased by a factor of 3. It also shows an anomalous thickening in Dronning Maud Land, East Antarctica which represents a known large-scale accumulation event. This anomaly partly compensates for the observed increased volume loss of the Antarctic Peninsula and West Antarctica. For Greenland we find a volume loss increased by a factor of 2.5 compared to the ICESat period with large negative elevation changes concentrated at the west and southeast coasts. The combined volume change of Greenland and Antarctica for the observation period is estimated to be -503 ± 107 km**3/yr. Greenland contributes nearly 75% to the total volume change with -375 ± 24 km**3/yr.

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This dataset presents hydro-sedimentary data within the Bossons glacier proglacial area. Bossons glacier is rapidly retreating and its proglacial area is deglaciated for ~ 30 years. It is an intriguing location to study periglacial, proglacial and subglacial erosion processes which requires estimating Total Dissolved Solid (TDS) and Total Suspended Solid (TSS) concentrations, and discharge. Measurements were performed at three distinct locations within Bosson glacier watershed : Bossons downstream (BDS), Bossons upstream (BUS) and Crosette (CRO). The latter is located at the glacier termini whereas BDS and BUS stations are farther downstream from the glacier, at 1.5 and 1.15 km, respectively .