scholarly journals A Revised Mid-Pliocene Composite Section for ODP Site 846

2020 ◽  
Author(s):  
Timothy D. Herbert ◽  
Rocio Caballero-Gill ◽  
Joseph B. Novak
Keyword(s):  
Time Series ◽  
Stable Isotopes ◽  
Gamma Ray ◽  
Sea Surface ◽  
Primary Data ◽  
Data Sets ◽  
Late Pliocene ◽  
Stable Isotopic ◽  
Composite Section ◽  
Gamma Ray Attenuation

Abstract. The composite section from ODP Site 846 has provided key data sets for Pliocene stable isotope and paleoclimatic time series. We document here errors in primary data sets for stable isotopes and alkenone-derived sea surface temperature estimates (SST) in the late Pliocene interval containing the M2 glaciation (ca. 3.250–3.3 Ma) by tying high resolution core measurements to a continuous downhole conductivity log. In addition, we provide new stable isotopic and alkenone measurements that correlate well to the revised splices of color reflectance and gamma ray attenuation porosity evaluator data. A new composite splice is proposed, along with composite isotope and alkenone time series that should be integrated into revised Pliocene paleoclimatic stacks.

scholarly journals A revised mid-Pliocene composite section centered on the M2 glacial event for ODP Site 846

2021 ◽  
Vol 17 (3) ◽  
pp. 1385-1394
Author(s):  
Timothy D. Herbert ◽  
Rocio Caballero-Gill ◽  
Joseph B. Novak
Keyword(s):  
Time Series ◽  
Stable Isotopes ◽  
Gamma Ray ◽  
Equatorial Pacific ◽  
Sea Surface ◽  
Published Data ◽  
Data Sets ◽  
Stable Isotopic ◽  
Composite Section ◽  
Gamma Ray Attenuation

Abstract. The composite section from ODP Site 846 has provided key data sets for Pliocene stable isotope and paleoclimatic time series. We document here apparent outliers in previously published data sets for stable isotopes and alkenone-derived sea surface temperature (SST) estimates in the Pliocene interval containing the M2 glaciation (ca. 3.290–3.3 Ma) by tying high-resolution core measurements to a continuous downhole conductivity log. We generate a revised sequence of new stable isotopic and alkenone measurements across the M2 event that correlate well to the revised splices of color reflectance and gamma ray attenuation porosity evaluator data from Site 846, and to a new composite section produced at equatorial Pacific ODP Site 850. A new composite splice for Site 846 is proposed, along with composite isotope and alkenone time series that should be integrated into revised Pliocene paleoclimatic stacks.

EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN

2017 ◽  
Author(s):  
Diaz Juan Navia ◽  
Diaz Juan Navia ◽  
Bolaños Nancy Villegas ◽  
Bolaños Nancy Villegas ◽  
Igor Malikov ◽  
...  
Keyword(s):  
Time Series ◽  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Extreme Values ◽  
Sea Surface ◽  
Absolute Maximum ◽  
Data Set ◽  
Arctic Oscillation Index ◽  
Colombian Pacific

Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.

SEA SURFACE TEMPERATURE PREFERENCES OF DENTOGLOBIGERINA ALTISPIRA DURING THE LATE PLIOCENE

2020 ◽  
Author(s):  
Marci M. Robinson ◽  
◽  
Harry J. Dowsett ◽  
Harry J. Dowsett ◽  
Kevin M. Foley ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Late Pliocene ◽  
Temperature Preferences

Construct Validity

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Construct Validity ◽  
Hypothesis Test ◽  
Secondary Data ◽  
Time Frame ◽  
Primary Data ◽  
Optimal Time ◽  
Intervention Model ◽  
Right Hand ◽  
The Right

Chapter 8 focuses on threats to construct validity arising from the left-hand side time series and the right-hand side intervention model. Construct validity is limited to questions of whether an observed effect can be generalized to alternative cause and effect measures. The “talking out” self-injurious behavior time series, shown in Chapter 5, are examples of primary data. Researchers often have no choice but to use secondary data that were collected by third parties for purposes unrelated to any hypothesis test. Even in those less-than-ideal instances, however, an optimal time series can be constructed by limiting the time frame and otherwise paying attention to regime changes. Threats to construct validity that arise from the right-hand side intervention model, such as fuzzy or unclear onset and responses, are controlled by paying close attention to the underlying theory. Even a minimal theory should specify the onset and duration of an impact.

scholarly journals Interpretation of the Chemical and Physical Time-Series Retrieved from Sentik Glacier, Ladakh Himalaya, India

1984 ◽  
Vol 30 (104) ◽  
pp. 66-76 ◽  
Author(s):  
Paul A. Mayewski ◽  
W. Berry Lyons ◽  
N. Ahmad ◽  
Gordon Smith ◽  
M. Pourchet
Keyword(s):  
Time Series ◽  
Chemical Species ◽  
Data Sets ◽  
Reactive Iron ◽  
Physical Time ◽  
Ladakh Himalaya ◽  
Data Density ◽  
Mass Circulation ◽  
The Himalaya ◽  
Analysis Of Time Series

AbstractSpectral analysis of time series of a c. 17 ± 0.3 year core, calibrated for total ß activity recovered from Sentik Glacier (4908m) Ladakh, Himalaya, yields several recognizable periodicities including subannual, annual, and multi-annual. The time-series, include both chemical data (chloride, sodium, reactive iron, reactive silicate, reactive phosphate, ammonium, δD, δ(18O) and pH) and physical data (density, debris and ice-band locations, and microparticles in size grades 0.50 to 12.70 μm). Source areas for chemical species investigated and general air-mass circulation defined from chemical and physical time-series are discussed to demonstrate the potential of such studies in the development of paleometeorological data sets from remote high-alpine glacierized sites such as the Himalaya.

scholarly journals An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks

2021 ◽  
Author(s):  
Cong Gao ◽  
Ping Yang ◽  
Yanping Chen ◽  
Zhongmin Wang ◽  
Yue Wang
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Estimation Method ◽  
Feature Representation ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Data Sets ◽  
Edge Node

AbstractWith large deployment of wireless sensor networks, anomaly detection for sensor data is becoming increasingly important in various fields. As a vital data form of sensor data, time series has three main types of anomaly: point anomaly, pattern anomaly, and sequence anomaly. In production environments, the analysis of pattern anomaly is the most rewarding one. However, the traditional processing model cloud computing is crippled in front of large amount of widely distributed data. This paper presents an edge-cloud collaboration architecture for pattern anomaly detection of time series. A task migration algorithm is developed to alleviate the problem of backlogged detection tasks at edge node. Besides, the detection tasks related to long-term correlation and short-term correlation in time series are allocated to cloud and edge node, respectively. A multi-dimensional feature representation scheme is devised to conduct efficient dimension reduction. Two key components of the feature representation trend identification and feature point extraction are elaborated. Based on the result of feature representation, pattern anomaly detection is performed with an improved kernel density estimation method. Finally, extensive experiments are conducted with synthetic data sets and real-world data sets.

scholarly journals Gamma-Ray Attenuation to Evaluate Soil Porosity: An Analysis of Methods

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Luiz F. Pires ◽  
André B. Pereira
Keyword(s):  
Gamma Ray ◽  
Particle Density ◽  
Pore Space ◽  
Physical Property ◽  
Soil Bulk Density ◽  
Soil Porosity ◽  
Porous System ◽  
Soil Pore Space ◽  
Gamma Ray Attenuation ◽  
Dry Soil

Soil porosity (ϕ) is of a great deal for environmental studies due to the fact that water infiltrates and suffers redistribution in the soil pore space. Many physical and biochemical processes related to environmental quality occur in the soil porous system. Representative determinations ofϕare necessary due to the importance of this physical property in several fields of natural sciences. In the current work, two methods to evaluateϕwere analyzed by means of gamma-ray attenuation technique. The first method uses the soil attenuation approach through dry soil and saturated samples, whereas the second one utilizes the same approach but taking into account dry soil samples to assess soil bulk density and soil particle density to determineϕ. The results obtained point out a good correlation between both methods. However, whenϕis obtained through soil water content at saturation and a 4 mm collimator is used to collimate the gamma-ray beam the first method also shows good correlations with the traditional one.

scholarly journals A Hypothesis Test for the Goodness-of-Fit of the Marginal Distribution of a Time Series with Application to Stablecoin Data

2021 ◽  
Vol 5 (1) ◽  
pp. 10
Author(s):  
Mark Levene
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Marginal Distribution ◽  
Hypothesis Test ◽  
Data Sets ◽  
Test Statistic ◽  
Sample Test ◽  
Kolmogorov Smirnov ◽  
Heavy Tailed ◽  
Jensen Shannon Divergence

A bootstrap-based hypothesis test of the goodness-of-fit for the marginal distribution of a time series is presented. Two metrics, the empirical survival Jensen–Shannon divergence (ESJS) and the Kolmogorov–Smirnov two-sample test statistic (KS2), are compared on four data sets—three stablecoin time series and a Bitcoin time series. We demonstrate that, after applying first-order differencing, all the data sets fit heavy-tailed α-stable distributions with 1<α<2 at the 95% confidence level. Moreover, ESJS is more powerful than KS2 on these data sets, since the widths of the derived confidence intervals for KS2 are, proportionately, much larger than those of ESJS.

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