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  • 1
    Publication Date: 2024-02-14
    Description: 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.
    Description: 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.
    Description: 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.
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: https://doi.org/10.5281/zenodo.6243822
    Keywords: ddc:551.46 ; ocean modeling ; FESOM ; Greenland freshwater discharge ; ocean reanalysis ; altimetry
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-03-01
    Description: Abstract
    Description: 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.
    Description: Other
    Description: 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.
    Keywords: 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
    Type: Dataset , Dataset
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