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  • 2020-2024  (8)
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  • 1
    Publikationsdatum: 2023-07-03
    Beschreibung: For low Earth orbit (LEO) satellites, activities such as precise orbit determination, gravity field retrieval, and thermospheric density estimation from accelerometry require modeled accelerations due to radiation pressure. To overcome inconsistencies and better understand the propagation of modeling errors into estimates, we here suggest to extend the standard analytical LEO radiation pressure model with emphasis on removing systematic errors in time-dependent radiation data products for the Sun and the Earth. Our extended unified model of Earth radiation pressure accelerations is based on hourly CERES SYN1deg data of the Earth’s outgoing radiation combined with angular distribution models. We apply this approach to the GRACE (Gravity Recovery and Climate Experiment) data. Validations with 1 year of calibrated accelerometer measurements suggest that the proposed model extension reduces RMS fits between 5 and 27%, depending on how measurements were calibrated. In contrast, we find little changes when implementing, e.g., thermal reradiation or anisotropic reflection at the satellite’s surface. The refined model can be adopted to any satellite, but insufficient knowledge of geometry and in particular surface properties remains a limitation. In an inverse approach, we therefore parametrize various combinations of possible systematic errors to investigate estimability and understand correlations of remaining inconsistencies. Using GRACE-A accelerometry data, we solve for corrections of material coefficients and CERES fluxes separately over ocean and land. These results are encouraging and suggest that certain physical radiation pressure model parameters could indeed be determined from satellite accelerometry data.
    Beschreibung: Deutsches Zentrum für Luft- und Raumfahrt http://dx.doi.org/10.13039/501100002946
    Beschreibung: ftp://ftp.tugraz.at/outgoing/ITSG/tvgogo/orbits/GRACE/
    Beschreibung: ftp://podaac-ftp.jpl.nasa.gov/allData/grace/L1B/JPL/
    Schlagwort(e): ddc:526 ; Solar radiation pressure ; Earth radiation pressure ; Satellite force models ; Parameter estimation
    Sprache: Englisch
    Materialart: doc-type:article
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2024-02-14
    Beschreibung: Increased Greenland ice sheet melting has an impact on global mean and regional sea level rise and the ocean circulation. In this study, we explore whether Greenland melting signatures found in ocean model simulations are visible in observations from radar altimetry, satellite gravimetry and Argo floats. We have included Greenland freshwater flux (GF) in the global Finite‐Element‐Sea ice‐Ocean Model (FESOM) for the years 1993–2016. The reference run is computed by excluding Greenland freshwater input. These experiments are performed on a low resolution (ca. 24 km) and a high resolution (ca. 6 km) eddy‐permitting mesh. For comparison with the model experiments, we use different observational data, such as Argo floats, satellite observations, and reanalyses. We find that surface GF maps into signatures in temperature and salinity down to about 100 m in the surroundings of Greenland. The simulated melting signatures are particularly visible in steric heights in Baffin Bay and Davis Strait. Here, we find an improvement of the mean square error of up to 30% when including GF. For the Nordic part of the Nordic Seas, however, we find no improvement when including GF. We compare steric heights with reanalysis data and a new setup of the inversion method from gravimetric and altimetric satellite data. We cannot confirm that the GF signatures on variables such as temperature and salinity are visible in the observations on the time scales considered. However, we find that increased model resolution often causes larger improvements than occur due to including the simulated melting effect.
    Beschreibung: Plain Language Summary: In recent years, Greenland's freshwater contribution to the ocean has increased due to the accelerated melting of its ice sheet and glaciers. In this study, we investigate the importance of this melting in reproducing the observed characteristics of the northern part of the North Atlantic Ocean in a numerical ocean model. To do that, we compare the results of two model simulations, one with and one without Greenland melt, with in situ observations or data from satellites. The inclusion of Greenland melt results in a better model representation of the ocean in terms of salinity, temperature, and sea level anomalies, especially in Baffin Bay on the west side of Greenland. We also discuss the role of a higher model resolution on the simulations in reproducing observations. Our study shows that progress in modeling how Greenland melt affects the nearby ocean is best achieved by improving model resolution so that small‐scale processes can be well represented.
    Beschreibung: Key Points: Greenland freshwater flow yields distinct signatures in temperature and salinity within the upper 100 m. Steric heights and sea level anomalies are sensitive to the Greenland freshwater intrusion especially in Baffin Bay. Increasing the spatial model resolution improves the agreement with observations more than if only Greenland meltwater is included.
    Beschreibung: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Beschreibung: https://doi.org/10.5281/zenodo.6243822
    Schlagwort(e): ddc:551.46 ; ocean modeling ; FESOM ; Greenland freshwater discharge ; ocean reanalysis ; altimetry
    Sprache: Englisch
    Materialart: doc-type:article
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    Publikationsdatum: 2023-03-01
    Beschreibung: Abstract
    Beschreibung: The dataset (Mielke et al, 2023) consists of daily ASCII-files, each containing the spherical harmonic coefficients (SHCs) for atmosphere, hydrology, and ocean bottom pressure. The files that include the AH+O coefficients are provided in the AOD format of the GFZ with the naming convention TYPE_YYYY-MM-DD_X_01.asc and contain header information (30 lines) and four columns with degree (n) order (m) and Stokes coefficients cnm and snm. Coefficients in each file are split up into different subsets, each corresponding to a subdaily time step (i.e., a daily file with 3-hour temporal resolution is split up into 8 subsets). The entire dataset is organized following the folder structure /TYPE/NEST/coeff_aodFormat_XXX/. We provide regional refined (nested), coarse grained (nested, but with a lower resolution version of the regional model), or global model solutions of SHCs for each datatype. Some datasets are available in different spectral resolutions, with d/o up to 179, 180, or 360. In this release all AH+O coefficients have a temporal resolution of 3 hours, except the non-regional refined atmospheric solution, which is given 6-hourly. Currently, the whole data set is provided for June 2007 and some components for the whole year 2007. Additional months and years will be added with newer versions of the dataset or can be provided by the authors on request. For the atmospheric and hydrological background model, regional models with high spatial and temporal resolution are nested into global models: Therefore, global and regional models must be resampled and interpolated on the same regular grid with equivalent time epochs. For the nesting, the global model is interpolated on the same grid resolution as the regional model. Grid points of the global model are than replaced with the data of the regional model of the CORDEX-EU region. A Gaussian filter is applied in a transition zone with a width of 7.5° to reduce an edge effect (Gibbs effect) between the two combined models.
    Beschreibung: Other
    Beschreibung: A deep understanding of mass distribution and mass transport in System Earth is needed to answer central questions in hydrology, oceanography, glaciology, geophysics and climate research. The necessary information is primarily derived from satellite mission data as observed by GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-on) describing the gravity field of the Earth and its temporal variations. The research group (RG) „New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV)”, funded by the German Research Foundation (DFG), develops since May 2019 new analysis methods and modeling approaches to improve GRACE and GRACE-FO mission data analysis and focuses on geophysical applications that benefit from significantly reduced error levels in the time series of monthly gravity fields. Phase 1 lasted from May 2019 till April 2022. After successful evaluation in January 2022 the second phase started in January 2023. The central hypothesis of the research group, slightly updated for phase 2, is: Only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-term consistency of mass transport series can be significantly increased; the science return in various fields of application improved and the potential of future technological sensor developments fully exploited. All groups participating in NEROGRAV have a long-term heritage of expertise in geodetic data acquisition and modeling and will additionally contribute their unique complementary expertise from various neighboring disciplines such as oceanography, hydrology, solid Earth, geophysics and atmospheric and climate sciences. Therefore, it is expected that the second funding phase will not only create significantly improved GRACE/GRACE-FO gravity field models over two decades, but also enable geophysical applications based on this long-term series such as quantifying North Atlantic deep water transports as indicator for variations in the Atlantic Meridional Overturning Circulation (AMOC), assessment of hydrometeorological extreme events or identification of climatic signatures in variations of the terrestrial water storage. Important results and datasets of phase 1 can be found at GFZ Data Services.
    Schlagwort(e): New Refined Observations of Climate Change from Spaceborne Gravity Missions ; NEROGRAV ; Earth Observation Satellites 〉 NASA Earth System Science Pathfinder 〉 GRACE ; EARTH SCIENCE SERVICES 〉 MODELS 〉 ATMOSPHERIC GENERAL CIRCULATION MODELS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 HYDROLOGIC AND TERRESTRIAL WATER CYCLE MODELS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 OCEAN GENERAL CIRCULATION MODELS (OGCM)/REGIONAL OCEAN MODELS
    Materialart: Dataset , Dataset
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
    Publikationsdatum: 2021-12-01
    Print ISSN: 0098-3004
    Digitale ISSN: 1873-7803
    Thema: Geologie und Paläontologie , Informatik
    Publiziert von Elsevier
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
  • 6
    Publikationsdatum: 2024-04-20
    Beschreibung: RECOG - REgional COrrections for GRACE: The dataset contains a monthly global earthquake correction for GRACE-level 3 total water storage anomalies (TWSA) for CSR, GFZ and ITSG solutions. The correction is monthly available from January 2003 to December 2016 and is used to correct for the Sumatra-Andaman (2004) and Tohoku (2011) earthquake by using a method described in Einarsson et al. (2010), where a co- and a post-seismic signal is modeled. The files contain longitude, latitude, time and the correction field of TWSA on an 0.5° grid. In the processing of the data, we included replacing lower degree coefficients, DDK3 filtering, reduced a temporal mean from 2003 to2016 and applied a correction for glacial isostatic adjustment. More information about the computation and application of the earthquake correction can be found in Deggim et al. (2020, in preparation). For more information about the GRACE processing visit following website: https://www.apmg.uni-bonn.de/daten-und-modelle/grace_level3_monthly_solutions, last access 12.08.2020.
    Schlagwort(e): Binary Object; Binary Object (File Size); Binary Object (Media Type); correction Tohoku; CSR; earthquake; GFZ; GRACE; ITSG; RECOG; Sumatra-Andaman; total water storage anomalies
    Materialart: Dataset
    Format: text/tab-separated-values, 3 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 7
    Publikationsdatum: 2024-04-20
    Beschreibung: The global land water storage (GLWS) data set is produced by assimilating (Eicker at al., 2014) gridded GRACE and GRACE-FO-derived total water storage anomalies (TWSA) into the WaterGAP global hydrological model using the Parallel Data Assimilation Framework (PDAF, Nerger and Hiller, 2013). The resulting data set represents thus an optimal synthesis of GRACE data and all data sets that went into the hydrological model. This synthesis seeks to fit GRACE (-FO) TWSA grids within error bars, and at the same time it solves the horizontal and vertical water balances as represented in the hydrological model, again within error bars. To this end, the uncertainty of the hydrological model simulation is represented via an n-member ensemble, where we take into account the uncertainty of forcing (precipitation and radiation) data as well as the uncertainty of some model calibration parameters. As a result, when no GRACE (-FO) data is available, the GLWS data set represents the mean – or the median additionally provided - of an ensemble where each member is dynamically consistent with the model. It is important to understand that this mean/median depends on the ensemble creation and thus will differ from published WaterGAP standard runs, even if there is no GRACE data within a particular month. It is also important to understand the assimilation-derived GLWS data set does not represent a simple downscaling of the GRACE data, i.e. spatial smoothing of GLWS does not necessarily correspond to GRACE (-FO) TWSA. The monthly level 3 GLWS data represent the total water storage anomaly (TWSA) on 0.5° grids and level 2 GLWS data represent groundwater, soil moisture and surface water. They are provided now for 01/2003 to 12/2019. Additionally, the standard deviation is provided (computed from the ensemble). As default, GLWS is derived from the ensemble mean, here, we additionally provide the ensemble median. The main updates with respect to the release 001 were the use of an updated version of WaterGAP as well as minor bug fixes in the assimilation.
    Schlagwort(e): Data Assimilation; File content; GLWS; GRACE; GRACE-FO; groundwater; netCDF file; netCDF file (File Size); Soil Moisture; surface water; total water storage anomalies; WaterGAP
    Materialart: Dataset
    Format: text/tab-separated-values, 6 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 8
    Publikationsdatum: 2024-04-20
    Beschreibung: TND-IGG RL01: This dataset is the first release of thermospheric neutral densities (TND) processed at the Institute of Geodesy and Geoinformation (IGG), University of Bonn, Germany. TNDs are derived from accelerometer measurements of the satellites GRACE-A, CHAMP and Swarm-C. For GRACE-A and CHAMP we first calibrate the accelerometer data within a precise orbit determination procedure (Vielberg et al., 2018). For Swarm-C we use the calibrated along-track accelerations from ESA (Siemes et al., 2016). In a second step, solar and Earth radiation pressure accelerations according to Vielberg and Kusche (2020) are reduced from the calibrated accelerometer data. The resulting atmospheric drag is then related to the thermospheric neutral density following the direct procedure by Doornbos et al. (2010) with temperature and density of atmospheric constituents from the empirical model NRLMSIS2.0. We apply an accommodation coefficient of 0.93 for GRACE, 0.82 for Swarm and 0.85 for CHAMP. Detailed information about the processing can be found in the ReadMe.txt and in Vielberg et al. (2021, in review). The final thermospheric neutral densities with a temporal resolution of 10 seconds are provided as monthly netCDF files.
    Schlagwort(e): accelerometer; Accelerometer; ACCM; Binary Object; Binary Object (File Size); Binary Object (Media Type); CHAMP; GRACE; mass density; neutral density; satellite data; Swarm; thermopshere
    Materialart: Dataset
    Format: text/tab-separated-values, 3 data points
    Standort Signatur Erwartet Verfügbarkeit
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