Sea-level Oscillations along the Australian Coast

1979 ◽  
Vol 30 (3) ◽  
pp. 295 ◽  
Author(s):  
DG Provis ◽  
R Radok
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Tide Gauges ◽  
Short Term ◽  
Sea Level Oscillations ◽  
Sea Level Variations ◽  
Long Term Variations

Sea level variations along Australia's coast were studied using records from tide gauges. The records were filtered to obtain two sets of time series, the short-term variations with periods between 1 and 20 days and the long-term variations with periods between 20 and 365 days. The coherence of the variations over long distances is noted and their magnitude is discussed with reference to possible causes.

scholarly journals An introduction to causes and consequences of Cretaceous sea-level changes (IGCP 609)

2019 ◽  
Vol 498 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Michael Wagreich ◽  
Benjamin Sames ◽  
Malcolm Hart ◽  
Ismail O. Yilmaz
Keyword(s):  
Sea Level ◽  
Sea Level Changes ◽  
Short Term ◽  
Sea Level Fluctuations ◽  
Groundwater Aquifer ◽  
Sea Level Oscillations ◽  
Short And Long Term ◽  
Geological Timescale ◽  
Land Water

AbstractThe International Geoscience Programme Project IGCP 609 addressed correlation, causes and consequences of short-term sea-level fluctuations during the Cretaceous. Processes causing several ka to several Ma (third- to fourth-order) sea-level oscillations during the Cretaceous are so far poorly understood. IGCP 609 proved the existence of sea-level cycles during potential ice sheet-free greenhouse to hothouse climate phases. These sea-level fluctuations were most probably controlled by aquifer-eustasy that is altering land-water storage owing to groundwater aquifer charge and discharge. The project investigated Cretaceous sea-level cycles in detail in order to differentiate and quantify both short- and long-term records based on orbital cyclicity. High-resolution sea-level records were correlated to the geological timescale resulting in a hierarchy of sea-level cycles in the longer Milankovitch band, especially in the 100 ka, 405 ka, 1.2 Ma and 2.4 Ma range. The relation of sea-level highs and lows to palaeoclimate events, palaeoenvironments and biota was also investigated using multiproxy studies. For a hothouse Earth such as the mid-Cretaceous, humid–arid climate cycles controlling groundwater-related sea-level change were evidenced by stable isotope data, correlation to continental lake-level records and humid–arid weathering cycles.

scholarly journals SEA LEVEL VARIATIONS IN THE GULF OF BOTHNIA

1973 ◽  
Vol 4 (1) ◽  
pp. 41-53 ◽  
Author(s):  
EUGENIE LISITZIN
Keyword(s):  
Baltic Sea ◽  
Sea Level ◽  
Water Volume ◽  
Tide Gauges ◽  
The Baltic Sea ◽  
Land Uplift ◽  
Gulf Of Bothnia ◽  
Sea Level Variations ◽  
The Baltic

An attempt is made to compute the sea level variations in the Gulf of Bothnia, which is isolated by islands and thresholds from the Baltic Sea proper. Observations from tide gauges during the 30-year period 1931–1960 were used. The effect of land uplift was taken into consideration. The maximum annual deviation in water volume from the long-term mean corresponded to 20.74 km3..

scholarly journals Short-Term Sea Level Changes of the Upper Cretaceous Carbonates: Calibration between Palynomorphs Composition, Inorganic Geochemistry, and Stable Isotopes

Minerals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1099
Author(s):  
Ahmed Mansour ◽  
Thomas Gentzis ◽  
Michael Wagreich ◽  
Sameh S. Tahoun ◽  
Ashraf M.T. Elewa
Keyword(s):  
Sea Level ◽  
Late Cretaceous ◽  
Upper Cretaceous ◽  
Freshwater Algae ◽  
Sea Level Changes ◽  
Short Term ◽  
Sea Level Oscillations ◽  
Rising Sea Level ◽  
Southern Tethys

Widespread deposition of pelagic-hemipelagic sediments provide an archive for the Late Cretaceous greenhouse that triggered sea level oscillations. Global distribution of dinoflagellate cysts (dinocysts) exhibited a comparable pattern to the eustatic sea level, and thus, considered reliable indicators for sea level and sequence stratigraphic reconstructions. Highly diverse assemblage of marine palynomorphs along with elemental proxies that relate to carbonates and siliciclastics and bulk carbonate δ13C and δ18O from the Upper Cretaceous Abu Roash A Member were used to reconstruct short-term sea level oscillations in the Abu Gharadig Basin, southern Tethys. Additionally, we investigated the relationship between various palynological, elemental, and isotope geochemistry parameters and their response to sea level changes and examined the link between these sea level changes and Late Cretaceous climate. This multiproxy approach revealed that a long-term sea-level rise, interrupted by minor short-term fall, was prevalent during the Coniacian-earliest Campanian in the southern Tethys, which allowed to divide the studied succession into four complete and two incomplete 3rd order transgressive-regressive sequences. Carbon and oxygen isotopes of bulk hemipelagic carbonates were calibrated with gonyaulacoids and freshwater algae (FWA)-pteridophyte spores and results showed that positive δ13Ccarb trends were consistent, in part, with excess gonyaulacoid dinocysts and reduced FWA-spores, reinforcing a rising sea level and vice versa. A reverse pattern was shown between the δ18Ocarb and gonyaulacoid dinocysts, where negative δ18Ocarb trends were slightly consistent with enhanced gonyaulacoid content, indicating a rising sea level and vice versa. However, stable isotope trends were not in agreement with palynological calibrations at some intervals. Therefore, the isotope records can be used as reliable indicators for reconstructing changes in long-term sea level rather than short-term oscillations.

scholarly journals Long-Term, Seasonal and Short-Term Fluctuations in the Water Level of the Southern Baltic Sea

2014 ◽  
Vol 33 (3) ◽  
pp. 181-197 ◽  
Author(s):  
Tomasz Wolski ◽  
Bernard Wiśniewski
Keyword(s):  
Baltic Sea ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauges ◽  
Short Term ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Solar Tide ◽  
Southern Baltic

Abstract Aim of this work are analyses of oscillations sea levels in the Southern Baltic on a scale of short-term changes, seasonal and long-term (age). The study was based on observational data in different periods time for tide gauges station of the Polish coast. On the example of some storm situations presents the part of the baric wave and the wind in the formation of extreme sea levels. The primary cause of the annual variability of sea levels was the characteristics of the annual and semi-annual oscillations (the annual and semi-annual solar tide). In the work also determined the rate of long-term sea-level rise for the Polish coast.

scholarly journals Overlapping sea level time series measured using different technologies: an example from the REDMAR Spanish network

2014 ◽  
Vol 14 (3) ◽  
pp. 589-610 ◽  
Author(s):  
B. Pérez ◽  
A. Payo ◽  
D. López ◽  
P. L. Woodworth ◽  
E. Alvarez Fanjul
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Tide Gauge ◽  
Sampling Strategies ◽  
Tide Gauges ◽  
Sea Levels ◽  
Tsunami Detection ◽  
The Impact

Abstract. This paper addresses the problems of overlapping sea level time series measured using different technologies and sometimes from different locations inside a harbour. The renovation of the Spanish REDMAR (RED de MAReógrafos) sea level network is taken here as an example of the difficulties encountered: up to seventeen old tide gauge stations have been replaced by radar tide gauges all around the Spanish coast, in order to fulfil the new international requirements on tsunami detection. Overlapping periods between old and new stations have allowed the comparison of records in different frequency ranges and the determination of the impact of this change of instrumentation on the long-term sea level products such as tides, surges and mean sea levels. The differences encountered are generally within the values expected, taking into account the characteristics of the different sensors, the different sampling strategies and sometimes the different locations inside the harbours. However, our analysis has also revealed in some cases the presence of significant scale errors that, overlapping with datum differences and uncertainties, as well as with hardware problems in many new radar gauges, may hinder the generation of coherent and continuous sea level time series. Comparisons with nearby stations have been combined with comparisons with altimetry time series close to each station in order to better determine the sources of error and to guarantee the precise relationships between the sea level time series from the old and the new tide gauges.

scholarly journals Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1151
Author(s):  
Carolina Gijón ◽  
Matías Toril ◽  
Salvador Luna-Ramírez ◽  
María Luisa Marí-Altozano ◽  
José María Ruiz-Avilés
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Analysis ◽  
Data Traffic ◽  
Medium Term ◽  
Short Term ◽  
Traffic Forecasting ◽  
Series Analysis ◽  
Radio Planning

Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.

Application of singular spectrum analysis in reconstruction of the annual signal from GRACE

2020 ◽  
Vol 14 (3) ◽  
pp. 295-302
Author(s):  
Chuandong Zhu ◽  
Wei Zhan ◽  
Jinzhao Liu ◽  
Ming Chen
Keyword(s):  
Time Series ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Mixture Effect ◽  
Singular Spectrum ◽  
Grace Data ◽  
Terrestrial Water ◽  
Annual Signal ◽  
Long Term Variations

AbstractThe mixture effect of the long-term variations is a main challenge in single channel singular spectrum analysis (SSA) for the reconstruction of the annual signal from GRACE data. In this paper, a nonlinear long-term variations deduction method is used to improve the accuracy of annual signal reconstructed from GRACE data using SSA. Our method can identify and eliminate the nonlinear long-term variations of the equivalent water height time series recovered from GRACE. Therefore the mixture effect of the long-term variations can be avoided in the annual modes of SSA. For the global terrestrial water recovered from GRACE, the peak to peak value of the annual signal is between 1.4 cm and 126.9 cm, with an average of 11.7 cm. After the long-term and the annual term have been deducted, the standard deviation of residual time series is between 0.9 cm and 9.9 cm, with an average of 2.1 cm. Compared with the traditional least squares fitting method, our method can reflect the dynamic change of the annual signal in global terrestrial water, more accurately with an uncertainty of between 0.3 cm and 2.9 cm.

scholarly journals An Efficient Prediction Model for Water Discharge in Schoharie Creek, NY

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Katerina G. Tsakiri ◽  
Antonios E. Marsellos ◽  
Igor G. Zurbenko
Keyword(s):  
New York ◽  
Time Series ◽  
Water Discharge ◽  
Winter Period ◽  
Statistical Methodology ◽  
Summer Period ◽  
Short Term ◽  
Efficient Prediction ◽  
Climatic Time Series

Flooding normally occurs during periods of excessive precipitation or thawing in the winter period (ice jam). Flooding is typically accompanied by an increase in river discharge. This paper presents a statistical model for the prediction and explanation of the water discharge time series using an example from the Schoharie Creek, New York (one of the principal tributaries of the Mohawk River). It is developed with a view to wider application in similar water basins. In this study a statistical methodology for the decomposition of the time series is used. The Kolmogorov-Zurbenko filter is used for the decomposition of the hydrological and climatic time series into the seasonal and the long and the short term component. We analyze the time series of the water discharge by using a summer and a winter model. The explanation of the water discharge has been improved up to 81%. The results show that as water discharge increases in the long term then the water table replenishes, and in the seasonal term it depletes. In the short term, the groundwater drops during the winter period, and it rises during the summer period. This methodology can be applied for the prediction of the water discharge at multiple sites.

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