scholarly journals The Sub-Polar Gyre Index – a community data set for application in fisheries and environment research

2017 ◽  
Vol 9 (1) ◽  
pp. 259-266 ◽  
Author(s):  
Barbara Berx ◽  
Mark R. Payne
Keyword(s):  
Time Series ◽  
North Atlantic Ocean ◽  
Marine Ecosystem ◽  
Principal Component ◽  
Series Length ◽  
Data Set ◽  
The North ◽  
Community Data ◽  
Definition Of ◽  
Index Time Series

Abstract. Scientific interest in the sub-polar gyre of the North Atlantic Ocean has increased in recent years. The sub-polar gyre has contracted and weakened, and changes in circulation pathways have been linked to changes in marine ecosystem productivity. To aid fisheries and environmental scientists, we present here a time series of the Sub-Polar Gyre Index (SPG-I) based on monthly mean maps of sea surface height. The established definition of the SPG-I is applied, and the first EOF (empirical orthogonal function) and PC (principal component) are presented. Sensitivity to the spatial domain and time series length are explored but found not to be important factors in terms of the SPG-I's interpretation. Our time series compares well with indices presented previously. The SPG-I time series is freely available online (http://dx.doi.org/10.7489/1806-1), and we invite the community to access, apply, and publish studies using this index time series.

scholarly journals The Sub-Polar Gyre Index – a community data set for application in fisheries and environment research

2016 ◽  
Author(s):  
Barbara Berx ◽  
Mark R. Payne
Keyword(s):  
Time Series ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
Marine Ecosystem ◽  
Series Length ◽  
Data Set ◽  
The North ◽  
Community Data ◽  
Definition Of ◽  
Index Time Series

Abstract. Scientific interest in the sub-polar gyre of the North Atlantic Ocean has increased in recent years. The sub-polar gyre has contracted and weakened, and changes in circulation pathways have been linked to changes in marine ecosystem productivity. To aid fisheries and environmental scientists, we here present a time series of the Sub-Polar Gyre Index (SPG-I) based on monthly mean maps of sea surface height. The established definition of the SPG-I is applied, and the first EOF and PC are presented. Sensitivity to the spatial domain and time series length are explored, but found not to be important factors. Our time series compares well with indices presented previously. The SPG-I time series is freely available online (doi:10.7489/1806-1) and we invite the community to access, apply and publish studies using this index time series.

scholarly journals MODIS observed increase in duration and spatial extent of sediment plumes in Greenland fjords

2014 ◽  
Vol 8 (4) ◽  
pp. 1161-1176 ◽  
Author(s):  
B. Hudson ◽  
I. Overeem ◽  
D. McGrath ◽  
J. P. M. Syvitski ◽  
A. Mikkelsen ◽  
...  
Keyword(s):  
North Atlantic Ocean ◽  
Regional Scale ◽  
Greenland Ice Sheet ◽  
Sediment Concentration ◽  
Retrieval Algorithm ◽  
Freshwater Flux ◽  
River Plumes ◽  
Data Set ◽  
In Situ Data ◽  
The North

Abstract. The freshwater flux from the Greenland Ice Sheet (GrIS) to the North Atlantic Ocean carries extensive but poorly documented volumes of sediment. We develop a suspended sediment concentration (SSC) retrieval algorithm using a large Greenland specific in situ data set. This algorithm is applied to all cloud-free NASA Moderate Resolution Imaging Spectrometer (MODIS) Terra images from 2000 to 2012 to monitor SSC dynamics at six river plumes in three fjords in southwest Greenland. Melt-season mean plume SSC increased at all but one site, although these trends were primarily not statistically significant. Zones of sediment concentration > 50 mg L−1 expanded in three river plumes, with potential consequences for biological productivity. The high SSC cores of sediment plumes ( > 250 mg L−1 expanded in one-third of study locations. At a regional scale, higher volumes of runoff were associated with higher melt-season mean plume SSC values, but this relationship did not hold for individual rivers. High spatial variability between proximal plumes highlights the complex processes operating in Greenland's glacio–fluvial–fjord systems.

scholarly journals Remote detection of water property changes from a time series of oceanographic data

Ocean Science ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 11-18 ◽  
Author(s):  
A. Henry-Edwards ◽  
M. Tomczak
Keyword(s):  
Time Series ◽  
Water Mass ◽  
Synthetic Data ◽  
Data Sets ◽  
The North ◽  
Water Property ◽  
Water Mass Analysis ◽  
Minimization Technique ◽  
Definition Of ◽  
Property Changes

Abstract. A water mass analysis method based on a constrained minimization technique is developed to derive water property changes in water mass formation regions from oceanographic station data taken at significant distance from the formation regions. The method is tested with two synthetic data sets, designed to mirror conditions in the North Atlantic at the Bermuda BATS time series station. The method requires careful definition of constraints before it produces reliable results. It is shown that an analysis of the error fields under different constraint assumptions can identify which properties vary most over the period of the observations. The method reproduces the synthetic data sets extremely well if all properties other than those that are identified as undergoing significant variations are held constant during the minimization.

scholarly journals Fractional Calculus as a Simple Tool for Modeling and Analysis of Long Memory Process in Industry

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 511 ◽  
Author(s):  
Ivo Petráš ◽  
Ján Terpák
Keyword(s):  
Time Series ◽  
Fractional Calculus ◽  
Fractional Order ◽  
Long Memory ◽  
Real Data ◽  
Data Set ◽  
Modeling And Analysis ◽  
Long Memory Process ◽  
Real Process ◽  
Definition Of

This paper deals with the application of the fractional calculus as a tool for mathematical modeling and analysis of real processes, so called fractional-order processes. It is well-known that most real industrial processes are fractional-order ones. The main purpose of the article is to demonstrate a simple and effective method for the treatment of the output of fractional processes in the form of time series. The proposed method is based on fractional-order differentiation/integration using the Grünwald–Letnikov definition of the fractional-order operators. With this simple approach, we observe important properties in the time series and make decisions in real process control. Finally, an illustrative example for a real data set from a steelmaking process is presented.

scholarly journals Towards Reliable Velocities of Permanent GNSS Stations

2016 ◽  
Vol 100 (1) ◽  
pp. 17-26
Author(s):  
Janusz Bogusz ◽  
Anna Klos ◽  
Marta Gruszczynska ◽  
Maciej Gruszczynski
Keyword(s):  
Time Series ◽  
Singular Spectrum Analysis ◽  
Principal Component ◽  
North East ◽  
Temporal Correlations ◽  
The North ◽  
Spatio Temporal ◽  
Permanent Station

Abstract In the modern geodesy the role of the permanent station is growing constantly. The proper treatment of the time series from such station lead to the determination of the reliable velocities. In this paper we focused on some pre-analysis as well as analysis issues, which have to be performed upon the time series of the North, East and Up components and showed the best, in our opinion, methods of determination of periodicities (by means of Singular Spectrum Analysis) and spatio-temporal correlations (Principal Component Analysis), that still exist in the time series despite modelling. Finally, the velocities of the selected European permanent stations with the associated errors determined following power-law assumption in the stochastic part is presented.

Climatic Forecasting of Wind and Waves Using Fuzzy Inference Systems

2017 ◽  
Author(s):  
Christos N. Stefanakos ◽  
Erik Vanem
Keyword(s):  
Time Series ◽  
Fuzzy Inference ◽  
North Atlantic Ocean ◽  
Offshore Structures ◽  
Mean Value ◽  
Initial Time ◽  
The North ◽  
Residual Part ◽  
Time Series Modelling ◽  
Inference Systems

Wind and wave climatic simulations are of great interest in a number of different applications, including the design and operation of ships and offshore structures, marine energy generation, aquaculture and coastal installations. In a climate change perspective, projections of such simulations to a future climate are of great importance for risk management and adaptation purposes. This work investigates the applicability of FIS/ANFIS models for climatic simulations of wind and wave data. The models are coupled with a nonstationary time series modelling, which decomposes the initial time series into a seasonal mean value and a residual part multiplied by a seasonal standard deviation. In this way, the nonstationary character is first removed before starting the fuzzy forecasting procedure. Then, the FIS/ANFIS models are applied to the stationary residual part providing us with more unbiased climatic estimates. Two long-term datasets for an area in the North Atlantic Ocean are used in the present study, namely NORA10 (57 years) and ExWaCli (30 years in the present and 30 years in the future). Two distinct experiments have been performed to simulate future values of the time series in a climatic scale. The assessment of the simulations by means of the actual values kept for comparison purposes gives very good results.

scholarly journals An update on multivariate return periods in hydrology

2016 ◽  
Vol 373 ◽  
pp. 175-178 ◽  
Author(s):  
Benedikt Gräler ◽  
Andrea Petroselli ◽  
Salvatore Grimaldi ◽  
Bernard De Baets ◽  
Niko Verhoest
Keyword(s):  
Time Series ◽  
Return Period ◽  
Simulated Data ◽  
Time Span ◽  
Return Periods ◽  
Data Set ◽  
Univariate Case ◽  
Definition Of ◽  
Selection Of

Abstract. Many hydrological studies are devoted to the identification of events that are expected to occur on average within a certain time span. While this topic is well established in the univariate case, recent advances focus on a multivariate characterization of events based on copulas. Following a previous study, we show how the definition of the survival Kendall return period fits into the set of multivariate return periods.Moreover, we preliminary investigate the ability of the multivariate return period definitions to select maximal events from a time series. Starting from a rich simulated data set, we show how similar the selection of events from a data set is. It can be deduced from the study and theoretically underpinned that the strength of correlation in the sample influences the differences between the selection of maximal events.

scholarly journals Detecting quasi-oscillations in the monthly precipitation regimes of the Iberian Peninsula

2003 ◽  
Vol 21 (3) ◽  
pp. 819-832 ◽  
Author(s):  
L. Morala ◽  
A. Serrano ◽  
J. A. Garcia
Keyword(s):  
Time Series ◽  
High Pressure ◽  
Iberian Peninsula ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
Singular Spectrum Analysis ◽  
Monthly Precipitation ◽  
The North ◽  
Precipitation Regimes ◽  
The North Atlantic

Abstract. A spectral analysis of the time series corresponding to the main monthly precipitation regimes of the Iberian Peninsula was performed using two methods, the Multi-Taper Method and Monte Carlo Singular Spectrum Analysis. The Multi-Taper Method gave a preliminary view of the presence of signals in some of the time series. Monte Carlo Singular Spectrum Analysis discriminated between potential oscillations and noise. From the results of the two methods it is concluded that there exist three significant quasi-oscillations at the 95% level of confidence: a 5.0 year quasi-oscillation and a long-term trend in the Atlantic pattern of March, a 3.2 year quasi-oscillation in the Cantabrian pattern of January, and a 4.0 year quasi-oscillation in the Catalonian pattern of February. These quasi-oscillations might be related to climatic variations with similar periodicities over the North Atlantic Ocean. The possible simultaneity of high values of precipitation generated by the significant quasi-oscillations and high sea–level pressures was studied by means of composite maps. It was found that high values of precipitation generated by the oscillations of the Atlantic patterns of January and March exist simultaneously with a specific high pressure structure over the North Atlantic Ocean, that allow cyclonic perturbations to cross the Iberian Peninsula. During the non-wet years, this high pressure structure moves northwards, keeping the track of the low pressure centers to the north, far from the Iberian Peninsula. On the other hand, high values of precipitation generated by the oscillation of the Cantabrian pattern of January exist simultaneously with a high pressure structure over the Galicia region and the Cantabrian Sea, that allow a northerly flow over the region. Also, a positive trend in the NAO index for March has been found, starting in the sixties, which is not evident for other winter months. This trend agrees with the decreasing trend found in the March Atlantic pattern.Key words. Meteorology and atmospheric dynamics (climatology; precipitation) Oceanography: general (climate and interannual variability)

scholarly journals Prevalence of the Chloroflexi-Related SAR202 Bacterioplankton Cluster throughout the Mesopelagic Zone and Deep Ocean

2004 ◽  
Vol 70 (5) ◽  
pp. 2836-2842 ◽  
Author(s):  
R. M. Morris ◽  
M. S. Rappé ◽  
E. Urbach ◽  
S. A. Connon ◽  
S. J. Giovannoni
Keyword(s):  
Time Series ◽  
Pacific Ocean ◽  
16S Rrna ◽  
Atlantic Ocean ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
The North ◽  
The North Atlantic

ABSTRACT Since their initial discovery in samples from the north Atlantic Ocean, 16S rRNA genes related to the environmental gene clone cluster known as SAR202 have been recovered from pelagic freshwater, marine sediment, soil, and deep subsurface terrestrial environments. Together, these clones form a major, monophyletic subgroup of the phylum Chloroflexi. While members of this diverse group are consistently identified in the marine environment, there are currently no cultured representatives, and very little is known about their distribution or abundance in the world's oceans. In this study, published and newly identified SAR202-related 16S rRNA gene sequences were used to further resolve the phylogeny of this cluster and to design taxon-specific oligonucleotide probes for fluorescence in situ hybridization. Direct cell counts from the Bermuda Atlantic time series study site in the north Atlantic Ocean, the Hawaii ocean time series site in the central Pacific Ocean, and along the Newport hydroline in eastern Pacific coastal waters showed that SAR202 cluster cells were most abundant below the deep chlorophyll maximum and that they persisted to 3,600 m in the Atlantic Ocean and to 4,000 m in the Pacific Ocean, the deepest samples used in this study. On average, members of the SAR202 group accounted for 10.2% (±5.7%) of all DNA-containing bacterioplankton between 500 and 4,000 m.

Holocene Mg/Ca, alkenones, and light stable isotope measurements on the outer North Iceland shelf (MD99-2269): A comparison with other multi-proxy data and sub-division of the Holocene

The Holocene ◽  
2016 ◽  
Vol 27 (1) ◽  
pp. 52-62 ◽  
Author(s):  
Greta B Kristjánsdóttir ◽  
Matthias Moros ◽  
John T Andrews ◽  
Anne E Jennings
Keyword(s):  
Bottom Water ◽  
Environmental Changes ◽  
Singular Spectrum Analysis ◽  
Principal Component ◽  
Sea Ice Extent ◽  
Data Set ◽  
Bottom Water Temperature ◽  
Near Surface ◽  
The Holocene ◽  
The North

To evaluate whether proxies that record surface, near-surface, and bottom water conditions from the North Iceland shelf have similar trends and periodicities, we examine Holocene century-scale paleoceanographic records from core MD99-2269. This core site lies close to the boundary between Atlantic and Arctic/Polar waters, and in an area frequently influenced by drift ice. The proxies are stable δ13C and δ18O values on planktonic and benthic foraminifera, alkenone-based sea-surface temperatures (SST°C), and foraminiferal Mg/Ca SST°C and bottom water temperature (BWT°C) estimates. These data were converted to equi-spaced 60-year time-series; significant trends were extracted using Singular Spectrum Analysis, which accounted for between 50% and 70% of the variance. In order to evaluate within-site ocean climate variability, a comparison between these data and previously published proxies from MD99-2269 was carried out on a standardized data set of 14 proxies covering the interval 400–9200 cal. yr BP. Principal component (PC) analysis indicated that the first two PC axes accounted for 57% of the variability with high loadings primarily defining ‘nutrient’ and ‘temperature’ proxies. Fuzzy k-mean clustering of the 14 climate proxies indicated major environmental changes at ~6350 and ~3450 cal. yr BP, which define local early-, middle-, and late-Holocene climatic shifts. Our results indicate that the major control on the combined proxy signal is the Holocene decrease in June insolation, but regional changes in such factors as sea-ice extent and salinity are required to explain the threefold division of the Holocene.

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