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  • 1
    Publication Date: 2018-10-01
    Print ISSN: 0034-4257
    Electronic ISSN: 1879-0704
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Elsevier
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  • 2
  • 3
    Publication Date: 2021-08-10
    Description: EOT20 is the latest in a series of empirical ocean tide (EOT) models derived using residual tidal analysis of multi-mission satellite altimetry at DGFI-TUM. The amplitudes and phases of 17 tidal constituents are provided on a global 0.125∘ grid based on empirical analysis of seven satellite altimetry missions and four extended missions. The EOT20 model shows significant improvements compared to the previous iteration of the global model (EOT11a) throughout the ocean, particularly in the coastal and shelf regions, due to the inclusion of more recent satellite altimetry data as well as more missions, the use of the updated FES2014 tidal model as a reference to estimated residual signals, the inclusion of the ALES retracker and improved coastal representation. In the validation of EOT20 using tide gauges and ocean bottom pressure data, these improvements in the model compared to EOT11a are highlighted with the root sum square (RSS) of the eight major tidal constituents improving by ∼ 1.4 cm for the entire global ocean with the major improvement in RSS (∼ 2.2 cm) occurring in the coastal region. Concerning the other global ocean tidal models, EOT20 shows an improvement of ∼ 0.2 cm in RSS compared to the closest model (FES2014) in the global ocean. Variance reduction analysis was conducted comparing the results of EOT20 with FES2014 and EOT11a using the Jason-2, Jason-3 and SARAL satellite altimetry missions. From this analysis, EOT20 showed a variance reduction for all three satellite altimetry missions with the biggest improvement in variance occurring in the coastal region. These significant improvements, particularly in the coastal region, provide encouragement for the use of the EOT20 model as a tidal correction for satellite altimetry in sea-level research. All ocean and load tide data from the model can be freely accessed at https://doi.org/10.17882/79489 (Hart-Davis et al., 2021). The tide gauges from the TICON dataset used in the validation of the tide model, are available at https://doi.org/10.1594/PANGAEA.896587 (Piccioni et al., 2018a).
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 4
    Publication Date: 2023-03-01
    Description: Abstract
    Description: This data publication represents the main outcomes of WP1.200 of Individual Project IP1 and Deliverable D1.1 of the research unit NEROGRAV. The goal of WP1.200 was the realistic representation of modern ocean tide model uncertainties in the form of empirical Variance-Covariance Matrices (VCMs) for the utilization in satellite gravimetric dealiasing. In the following, we describe the data set generation and format. A more detailed description of the processing strategy of the data set can be found in Abrykosov et al. (2021).
    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: satellite gravimetry ; Stokes coefficients ; Covariance ; empirical VCM ; NEROGRAV ; New Refined Observations of Climate Change from Spaceborne Gravity Missions ; Earth Observation Satellites 〉 NASA Earth System Science Pathfinder 〉 GRACE ; EARTH SCIENCE 〉 OCEANS 〉 MARINE GEOPHYSICS 〉 MARINE GRAVITY FIELD ; EARTH SCIENCE 〉 OCEANS 〉 OCEAN WAVES 〉 GRAVITY WAVES ; EARTH SCIENCE 〉 OCEANS 〉 TIDES 〉 TIDAL COMPONENTS ; EARTH SCIENCE 〉 OCEANS 〉 TIDES 〉 TIDAL HEIGHT
    Type: Dataset , Dataset
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  • 6
    Publication Date: 2024-04-20
    Description: This dataset provides data for four third-degree tidal constituents used in the publication of Sulzbach et al (2022). The tidal constituents provided are the 3M1, 3M3, 3N2 and 3L2 for 134 globally distributed stations. The tide information, such as the nodal modulations of these tides, are taken from Table 1 and Table S2 of Ray (2020). These tidal constants are estimated using the GESLA dataset (Woodworth et al 2014) following the approach presented in Piccioni et al (2019). This record is an add-on to the full TICON dataset (https://doi.org/10.1594/PANGAEA.896587), using exactly the same data format and pre-processing. These steps include using tide gauge data that contains at least ten years of continuous data. Further, the dataset is restricted to only contain open ocean tide gauges by limiting it to a mean surrounding depth of tide gauges to be deeper than 500 meters in a 2-degree radius and excluding stations not native to the ocean domain of the employed tidal model TiME. Duplicate and closely neighbouring tide gauges, found within a 0.2-degree radius, are also removed from the dataset. This resulted in the availability of the four tidal constants for 134 tide gauges. The results are stored in one tab-separated text/ASCII file with 13 columns: 1. Latitude of the tide gauge station 2. Longitude of the tide gauge station 3. Constituent name 4. Amplitude (in cm) 5. Phase (in degrees) 6. Standard deviation of the amplitude (in cm) 7. Standard deviation of the phase (in degrees) 8. Percentage of missing observations 9. Total number of observations analyzed 10. Length of the maximum temporal gap found in the time series in days 11. Date of the first observation 12. Date of the last observation 13. Code that corresponds to the original source of the record TICON is a useful and easy-to-handle data set for tide model validation and allows the users to select the records according to the different criteria most suitable for their purposes. The options span from the choice of a geographical region to the use of single constituents or time periods.
    Keywords: GESLA; tidal height; Tides
    Type: Dataset
    Format: application/zip, 1.5 MBytes
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  • 7
    Publication Date: 2024-04-20
    Description: The TIdal CONstants (TICON) dataset was first published in Piccioni et al (2019). This dataset provided estimations of 40 tidal constituents from 1,145 tide gauge records. These tide gauge records were taken from the GESLA-2 database (Woodworth et al 2017). The dataset has served the community well as it was used for the validation of global ocean tide models in several studies (e.g. Hart-Davis et al 2021; Sulzbach et al 2021). Since this, a more recent database has been produced, GESLA-3 (Haigh et al 2022), which significantly increases the number of tide gauge records to 5,119 tide gauges. This has led to the need for an update to the TICON dataset in order to account for the increased number of observations as well as the increased time-series records of the already existing tide gauges. This need has resulted in the development of the TICON-3 dataset, which is presented here. Following the same approach as described in Piccioni et al (2019), least-squares harmonic analysis was conducted on every individual tide gauge of the GESLA-3 database. Additional processing was done to remove any tide gauges with insufficient data (at least 70% of valid measurements) as well as the removal of tide gauges with less than 1 years worth of valid measurements. This has resulted in the availability of 3,471 tide gauges within the TICON-3 dataset, a significant increase of 2,323 tide gauges relative to the previous TICON version. A further addition to the TICON dataset is based on gauge type information newly provided by the GESLA-3 database, which has also been included as the final column of the TICON-3 dataset. These gauge types are either 'Coastal', 'River' and 'Lake'. Distinguishing between these tide gauge types is vital based on the applications where the data is used and it is, therefore, important that users select the appropriate gauge type.
    Keywords: GESLA-3; tidal height; Tides
    Type: Dataset
    Format: application/zip, 2.7 MBytes
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  • 8
    Publication Date: 2024-04-20
    Description: Ocean tides, the sea surface fluctuations caused by the gravitational attraction of the Moon and the Sun, are one of the most important oceanographic processes. They have intrigued scientists for centuries, with the development of tide gauges in the early 1800s providing valuable insights into the physical mechanisms behind tide-induced sea-level changes. Since then, tide gauges continue to be developed and deployed globally and continue to be of value to tidal studies as well as for other coastal processes such as storm surges and sea-level rise. The temporal changes in the ocean surface due to tides can be decomposed into a number of harmonic constants called tidal constants or constituents. Accurate knowledge of these tidal constants is vital in providing precise estimations of the full ocean tidal signal. In this regard, a dataset of TIdal CONstants (TICON) has been derived at DGFI-TUM using tide gauges from the ​​Global Extreme Sea Level Analysis (GESLA, www.gesla.org; Haigh et al 2021) database. These tidal constants are derived through least-squares-based harmonic analysis of sea level time series. By default, TICON provides the amplitude, phase and their respective standard deviation for all constituents within the database. Additional information about the tide gauge data used to derive these constituents is also provided, such as the temporal range, data gaps and data sources. More details about the processing techniques as well as the validation of the techniques used can be found in Piccioni et al (2019).
    Type: Dataset
    Format: 3 datasets
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