A joint data record of tropospheric ozone from Aura-TES and MetOp-IASI

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H. Oetjen

2016-08-01

Full Text Available The Tropospheric Emission Spectrometer (TES on Aura and Infrared Atmospheric Sounding Interferometer (IASI on MetOp-A together provide a time series of 10 years of free-tropospheric ozone with an overlap of 3 years. We characterise the differences between TES and IASI ozone measurements and find that IASI's coarser vertical sensitivity leads to a small (< 5 ppb low bias relative to TES for the free troposphere. The TES-IASI differences are not dependent on season or any other factor and hence the measurements from the two instruments can be merged, after correcting for the offset, in order to study decadal-scale changes in tropospheric ozone. We calculate time series of regional monthly mean ozone in the free troposphere over eastern Asia, the western United States (US, and Europe, carefully accounting for differences in spatial sampling between the instruments. We show that free-tropospheric ozone over Europe and the western US has remained relatively constant over the past decade but that, contrary to expectations, ozone over Asia in recent years does not continue the rapid rate of increase observed from 2004 to 2010.

Comparing Simultaneous Stratospheric Aerosol and Ozone Lidar Measurements with SAGE 2 Data after the Mount Pinatubo Eruption

Science.gov (United States)

Yue, G. K.; Poole, L. R.; McCormick, M. P.; Veiga, R. E.; Wang, P.-H.; Rizi, V.; Masci, F.; DAltorio, A.; Visconti, G.

1995-01-01

Stratospheric aerosol and ozone profiles obtained simultaneously from the lidar station at the University of L'Aquila (42.35 deg N, 13.33 deg E, 683 m above sea level) during the first 6 months following the eruption of Mount Pinatubo are compared with corresponding nearby Stratospheric Aerosol and Gas Experiment (SAGE) 2 profiles. The agreement between the two data sets is found to be reasonably good. The temporal change of aerosol profiles obtained by both techniques showed the intrusion and growth of Pinatubo aerosols. In addition, ozone concentration profiles derived from an empirical time-series model based on SAGE 2 ozone data obtained before the Pinatubo eruption are compared with measured profiles. Good agreement is shown in the 1991 profiles, but ozone concentrations measured in January 1992 were reduced relative to time-series model estimates. Possible reasons for the differences between measured and model-based ozone profiles are discussed.

Forecasting and analyzing high O3 time series in educational area through an improved chaotic approach

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Hamid, Nor Zila Abd; Adenan, Nur Hamiza; Noorani, Mohd Salmi Md

2017-08-01

Forecasting and analyzing the ozone (O3) concentration time series is important because the pollutant is harmful to health. This study is a pilot study for forecasting and analyzing the O3 time series in one of Malaysian educational area namely Shah Alam using chaotic approach. Through this approach, the observed hourly scalar time series is reconstructed into a multi-dimensional phase space, which is then used to forecast the future time series through the local linear approximation method. The main purpose is to forecast the high O3 concentrations. The original method performed poorly but the improved method addressed the weakness thereby enabling the high concentrations to be successfully forecast. The correlation coefficient between the observed and forecasted time series through the improved method is 0.9159 and both the mean absolute error and root mean squared error are low. Thus, the improved method is advantageous. The time series analysis by means of the phase space plot and Cao method identified the presence of low-dimensional chaotic dynamics in the observed O3 time series. Results showed that at least seven factors affect the studied O3 time series, which is consistent with the listed factors from the diurnal variations investigation and the sensitivity analysis from past studies. In conclusion, chaotic approach has been successfully forecast and analyzes the O3 time series in educational area of Shah Alam. These findings are expected to help stakeholders such as Ministry of Education and Department of Environment in having a better air pollution management.

Time evolution of tropospheric ozone and its radiative forcing

International Nuclear Information System (INIS)

Berntsen, Terje K.; Isaksen, Ivar S.A.; Myhre, Gunnar; Stordal, Frode

1999-01-01

The overview presents results from studies of ozone concentrations from pre industrial time and up to the end of the 20th century. Different models and also a global 3-D chemistry transport model have been used. Experiments have been performed for 1850, 1900, 1950, 1960, 1970, 1980 and 1990. The radiative forcing increases with increasing ozone levels and has been steadily increasing. It has escalated towards the end of the century. Comparative evaluations with project results and external results are presented. Connections to other greenhouse gases are mentioned

New dynamic NNORSY ozone profile climatology

Science.gov (United States)

Kaifel, A. K.; Felder, M.; Declercq, C.; Lambert, J.-C.

2012-01-01

Climatological ozone profile data are widely used as a-priori information for total ozone using DOAS type retrievals as well as for ozone profile retrieval using optimal estimation, for data assimilation or evaluation of 3-D chemistry-transport models and a lot of other applications in atmospheric sciences and remote sensing. For most applications it is important that the climatology represents not only long term mean values but also the links between ozone and dynamic input parameters. These dynamic input parameters should be easily accessible from auxiliary datasets or easily measureable, and obviously should have a high correlation with ozone. For ozone profile these parameters are mainly total ozone column and temperature profile data. This was the outcome of a user consultation carried out in the framework of developing a new, dynamic ozone profile climatology. The new ozone profile climatology is based on the Neural Network Ozone Retrieval System (NNORSY) widely used for ozone profile retrieval from UV and IR satellite sounder data. NNORSY allows implicit modelling of any non-linear correspondence between input parameters (predictors) and ozone profile target vector. This paper presents the approach, setup and validation of a new family of ozone profile climatologies with static as well as dynamic input parameters (total ozone and temperature profile). The neural network training relies on ozone profile measurement data of well known quality provided by ground based (ozonesondes) and satellite based (SAGE II, HALOE, and POAM-III) measurements over the years 1995-2007. In total, four different combinations (modes) for input parameters (date, geolocation, total ozone column and temperature profile) are available. The geophysical validation spans from pole to pole using independent ozonesonde, lidar and satellite data (ACE-FTS, AURA-MLS) for individual and time series comparisons as well as for analysing the vertical and meridian structure of different modes of

Spatio-temporal observations of the tertiary ozone maximum

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V. F. Sofieva

2009-07-01

Full Text Available We present spatio-temporal distributions of the tertiary ozone maximum (TOM, based on GOMOS (Global Ozone Monitoring by Occultation of Stars ozone measurements in 2002–2006. The tertiary ozone maximum is typically observed in the high-latitude winter mesosphere at an altitude of ~72 km. Although the explanation for this phenomenon has been found recently – low concentrations of odd-hydrogen cause the subsequent decrease in odd-oxygen losses – models have had significant deviations from existing observations until recently. Good coverage of polar night regions by GOMOS data has allowed for the first time to obtain spatial and temporal observational distributions of night-time ozone mixing ratio in the mesosphere.

The distributions obtained from GOMOS data have specific features, which are variable from year to year. In particular, due to a long lifetime of ozone in polar night conditions, the downward transport of polar air by the meridional circulation is clearly observed in the tertiary ozone maximum time series. Although the maximum tertiary ozone mixing ratio is achieved close to the polar night terminator (as predicted by the theory, TOM can be observed also at very high latitudes, not only in the beginning and at the end, but also in the middle of winter. We have compared the observational spatio-temporal distributions of the tertiary ozone maximum with that obtained using WACCM (Whole Atmosphere Community Climate Model and found that the specific features are reproduced satisfactorily by the model.

Since ozone in the mesosphere is very sensitive to HO_x concentrations, energetic particle precipitation can significantly modify the shape of the ozone profiles. In particular, GOMOS observations have shown that the tertiary ozone maximum was temporarily destroyed during the January 2005 and December 2006 solar proton events as a result of the HO_x enhancement from the increased ionization.

Development of a climate record of tropospheric and stratospheric column ozone from satellite remote sensing: evidence of an early recovery of global stratospheric ozone

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J. R. Ziemke

2012-07-01

Full Text Available Ozone data beginning October 2004 from the Aura Ozone Monitoring Instrument (OMI and Aura Microwave Limb Sounder (MLS are used to evaluate the accuracy of the Cloud Slicing technique in effort to develop long data records of tropospheric and stratospheric ozone and for studying their long-term changes. Using this technique, we have produced a 32-yr (1979–2010 long record of tropospheric and stratospheric column ozone from the combined Total Ozone Mapping Spectrometer (TOMS and OMI. Analyses of these time series suggest that the quasi-biennial oscillation (QBO is the dominant source of inter-annual variability of stratospheric ozone and is clearest in the Southern Hemisphere during the Aura time record with related inter-annual changes of 30–40 Dobson Units. Tropospheric ozone for the long record also indicates a QBO signal in the tropics with peak-to-peak changes varying from 2 to 7 DU. The most important result from our study is that global stratospheric ozone indicates signature of a recovery occurring with ozone abundance now approaching the levels of year 1980 and earlier. The negative trends in stratospheric ozone in both hemispheres during the first 15 yr of the record are now positive over the last 15 yr and with nearly equal magnitudes. This turnaround in stratospheric ozone loss is occurring about 20 yr earlier than predicted by many chemistry climate models. This suggests that the Montreal Protocol which was first signed in 1987 as an international agreement to reduce ozone destroying substances is working well and perhaps better than anticipated.

Stratospheric ozone profile and total ozone trends derived from the SAGE I and SAGE II data

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Mccormick, M. P.; Veiga, Robert E.; Chu, William P.

1992-01-01

Global trends in both stratospheric column ozone and as a function of altitude are derived on the basis of SAGE I/II ozone data from the period 1979-1991. A statistical model containing quasi-biennial, seasonal, and semiannual oscillations, a linear component, and a first-order autoregressive noise process was fit to the time series of SAGE I/II monthly zonal mean data. The linear trend in column ozone above 17-km altitude, averaged between 65 deg S and 65 deg N, is -0.30 +/-0.19 percent/yr, or -3.6 percent over the time period February 1979 through April 1991. The data show that the column trend above 17 km is nearly zero in the tropics and increases towards the high latitudes with values of -0.6 percent/yr at 60 deg S and -0.35 percent/yr at 60 deg N. Both these results are in agreement with the recent TOMS results. The profile trend analyses show that the column ozone losses are occurring below 25 km, with most of the loss coming from the region between 17 and 20 km. Negative trend values on the order of -2 percent/yr are found at 17 km in midlatitudes.

GPS Position Time Series @ JPL

Science.gov (United States)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

Fragile ozone layer: a new environmental time bomb

International Nuclear Information System (INIS)

Olivero, J.J.

1975-01-01

The role of ozone as a shield against the harmful effects of ultraviolet radiation on living things is discussed. Studies on the effects of supersonic transport on atmospheric ozone are reviewed. It is pointed out that rockets of the future will deposit large quantities of HCl into the atmosphere; this will be decomposed by ultraviolet radiation to chlorine which will destroy the ozone. The dangers of nuclear weapons tests in reducing ozone in addition to the destructiveness of radioactive fallout are discussed. (U.S.)

Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...

Highly comparative time-series analysis: the empirical structure of time series and their methods.

Science.gov (United States)

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

Extreme events in total ozone: Spatio-temporal analysis from local to global scale

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Rieder, Harald E.; Staehelin, Johannes; Maeder, Jörg A.; Ribatet, Mathieu; di Rocco, Stefania; Jancso, Leonhardt M.; Peter, Thomas; Davison, Anthony C.

2010-05-01

Recently tools from extreme value theory (e.g. Coles, 2001; Ribatet, 2007) have been applied for the first time in the field of stratospheric ozone research, as statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean values) of total ozone data do not address the internal data structure concerning extremes adequately (Rieder et al., 2010a,b). A case study the world's longest total ozone record (Arosa, Switzerland - for details see Staehelin et al., 1998a,b) illustrates that tools based on extreme value theory are appropriate to identify ozone extremes and to describe the tails of the total ozone record. Excursions in the frequency of extreme events reveal "fingerprints" of dynamical factors such as ENSO or NAO, and chemical factors, such as cold Arctic vortex ozone losses, as well as major volcanic eruptions of the 20th century (e.g. Gunung Agung, El Chichón, Mt. Pinatubo). Furthermore, atmospheric loading in ozone depleting substances led to a continuous modification of column ozone in the northern hemisphere also with respect to extreme values (partly again in connection with polar vortex contributions). It is shown that application of extreme value theory allows the identification of many more such fingerprints than conventional time series analysis of annual and seasonal mean values. Especially, the extremal analysis shows the strong influence of dynamics, revealing that even moderate ENSO and NAO events have a discernible effect on total ozone (Rieder et al., 2010b). Overall the extremes concept provides new information on time series properties, variability, trends and the influence of dynamics and chemistry, complementing earlier analyses focusing only on monthly (or annual) mean values. Findings described above could be proven also for the total ozone records of 5 other long-term series (Belsk, Hohenpeissenberg, Hradec Kralove, Potsdam, Uccle) showing that strong influence of atmospheric

Introduction to Time Series Modeling

CERN Document Server

Kitagawa, Genshiro

2010-01-01

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

Estimations of the Global Distribution and Time Series of UV Noontime Irradiance (305, 310, 324, 380 nm, and Erythemal) from TOMS and SeaWiFS Data

Science.gov (United States)

Herman, J.

2004-01-01

The amount of UV irradiance reaching the Earth's surface is estimated from the measured cloud reflectivity, ozone, aerosol amounts, and surface reflectivity time series from 1980 to 1992 and 1997 to 2000 to estimate changes that have occurred over a 21-year period. Recent analysis of the TOMS data shows that there has been an apparent increase in reflectivity (decrease in W) in the Southern Hemisphere that is related to a calibration error in EP-TOMS. Data from the well-calibrated SeaWiFS satellite instrument have been used to correct the EP-TOMS reflectivity and UV time series. After correction, some of the local trend features seen in the N7 time series (1980 to 1992) have been continued in the combined time series, but the overall zonal average and global trends have changed. In addition to correcting the EP-TOMS radiance calibration, the use of SeaWiFS cloud data permits estimation of UV irradiance at higher spatial resolution (1 to 4 km) than is available from TOMS (100 km) under the assumption that ozone is slowly varying over a scale of 100 km. The key results include a continuing decrease in cloud cover over Europe and North America with a corresponding increase in UV and a decrease in UV irradiance near Antarctica.

Modulations of stratospheric ozone by volcanic eruptions

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Blanchette, Christian; Mcconnell, John C.

1994-01-01

We have used a time series of aerosol surface based on the measurements of Hofmann to investigate the modulation of total column ozone caused by the perturbation to gas phase chemistry by the reaction N2O5(gas) + H2O(aero) yields 2HNO3(gas) on the surface of stratospheric aerosols. We have tested a range of values for its reaction probability, gamma = 0.02, 0.13, and 0.26 which we compared to unperturbed homogeneous chemistry. Our analysis spans a period from Jan. 1974 to Oct. 1994. The results suggest that if lower values of gamma are the norm then we would expect larger ozone losses for highly enhanced aerosol content that for larger values of gamma. The ozone layer is more sensitive to the magnitude of the reaction probability under background conditions than during volcanically active periods. For most conditions, the conversion of NO2 to HNO3 is saturated for reaction probability in the range of laboratory measurements, but is only absolutely saturated following major volcanic eruptions when the heterogeneous loss dominates the losses of N2O5. The ozone loss due to this heterogeneous reaction increases with the increasing chlorine load. Total ozone losses calculated are comparable to ozone losses reported from TOMS and Dobson data.

Acute Peritonitis and Nonspecific Resistance Factors in the Administration of Ozonized Perfluorane (Experimental Study

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A. M. Golubev

2008-01-01

Full Text Available Objective: to study the effect of ozonized perfluorane on the natural course of acute of fecal peritonitis and congenital (nonspecific immunity factors during its intraperitoneal administration. Materials and methods. Perfluorane and saline solution were ozonized bubbling with a mixture of ozone and oxygen at a rate of 0.5 l/min and at a preset ozone concentration of 3000 flg/l on a Medozons — BM AOT — H-01-Arz-91 ozonator (OAO «Arzamasskiy Priborostroitelnyi Zavod» for 15 minutes. The concentration of ozone was measured in the solutions on a NF 254/1 spectrophotometer. Experiments were carried out on 200 non-inbred albino male rats in 4 series of experiments. After simulating fecal peritonitis by the procedure developed by S. S. Remennik, the animals were intraperitoneally injected ozonized perfluorane (Series 1, ozonized saline solution (Series 2, perfluorane (Series 3, and saline solution (Series 4 on the basis of 1.5 ml per 100 g of weight. Nine intact rats were used as a control. Results. The congenital immunity parameters (phagocytic block, intracellular and serum bactericidal activities were studied. An association was found between the clinical course and the degree of nonspecific immunity suppression. The ozonized perfluorane was ascertained to have a more significant protective action on nonspecific immunity factors than perfluorane or the ozonized saline solution. The factors under study were significantly decreased when saline solution was administered, and with this there was a mass mortality of Series 4 rats on days 2—14 of the experiment. Conclusion. The therapeutic effect of the ozonized perfluorane is due to the activation of phagocytic mononuclear leukocytes and their increased count, to the antibacterial activity of ozone and the protective action on the nonspecific link of the body’s immunological resistance.

Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing

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I. Cionni

2011-11-01

Full Text Available A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009 with multi-model mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2 Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISS-PUCCINI and of the future by one CCM (CAM3.5. The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs. Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that

Reconstruction of daily erythemal UV radiation values for the last century - The benefit of modelled ozone

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Junk, J.; Feister, U.; Rozanov, E.; Krzyścin, J. W.

2013-05-01

Solar erythemal UV radiation (UVER) is highly relevant for numerous biological processes that affect plants, animals, and human health. Nevertheless, long-term UVER records are scarce. As significant declines in the column ozone concentration were observed in the past and a recovery of the stratospheric ozone layer is anticipated by the middle of the 21st century, there is a strong interest in the temporal variation of UVER time series. Therefore, we combined groundbased measurements of different meteorological variables with modeled ozone data sets to reconstruct time series of daily totals of UVER at the Meteorological Observatory Potsdam, Germany. Artificial neural networks were trained with measured UVER, sunshine duration, the day of year, measured and modeled total column ozone, as well as the minimum solar zenith angle. This allows for the reconstruction of daily totals of UVER for the period from 1901 to 1999. Additionally, analyses of the long-term variations from 1901 until 1999 of the reconstructed, new UVER data set are presented. The time series of monthly and annual totals of UVER provide a long-term meteorological basis for epidemiological investigations in human health and occupational medicine for the region of Potsdam and Berlin. A strong benefit of our ANN-approach is the fact that it can be easily adapted to different geographical locations, as successfully tested in the framework of the COSTAction 726.

Ozone, area social conditions, and mortality in Mexico City

International Nuclear Information System (INIS)

O'Neill, M.S.; Loomis, Dana; Borja-Aburto, V.H.

2004-01-01

We investigated whether the association of daily mortality and ambient ozone differs by age and area social conditions of the region of residence using a time-series analysis. The study setting was metropolitan Mexico City, a high altitude city situated in a valley, with an estimated 20 million inhabitants, large socioeconomic gradients, and ozone levels frequently exceeding international standards. We stratified daily deaths by six census-derived socioeconomic indicators, based on characteristics of the county where decedents lived. We used Poisson regression to model the association between daily mortality and ozone levels (on the day of death and the previous day) in separate models, stratified by area socioeconomic level and age, and controlling for time trends and temperature. Ozone was positively associated with total mortality [0.65% increase per 10 ppb increment, 95% confidence interval (CI): 0.02%, 1.28%] and for mortality among those over age 65 [1.39% increase per 10 ppb increment, 95% CI: 0.51%, 2.28%]. Associations between ozone and all-age mortality did not show any consistent patterns according to socioeconomic gradients. We conclude that elderly people are at higher risk for ozone-associated mortality. Though county-level social indicators in Mexico City were not strong markers of vulnerability to ozone-associated acute mortality in this analysis, complex associations between individual and area-level factors may exist that would require additional data and further analyses to elucidate

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor; Valenzuela, Olga

2017-01-01

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...

Unequivocal detection of ozone recovery in the Antarctic Ozone Hole through significant increases in atmospheric layers with minimum ozone

Science.gov (United States)

de Laat, Jos; van Weele, Michiel; van der A, Ronald

2015-04-01

An important new landmark in present day ozone research is presented through MLS satellite observations of significant ozone increases during the ozone hole season that are attributed unequivocally to declining ozone depleting substances. For many decades the Antarctic ozone hole has been the prime example of both the detrimental effects of human activities on our environment as well as how to construct effective and successful environmental policies. Nowadays atmospheric concentrations of ozone depleting substances are on the decline and first signs of recovery of stratospheric ozone and ozone in the Antarctic ozone hole have been observed. The claimed detection of significant recovery, however, is still subject of debate. In this talk we will discuss first current uncertainties in the assessment of ozone recovery in the Antarctic ozone hole by using multi-variate regression methods, and, secondly present an alternative approach to identify ozone hole recovery unequivocally. Even though multi-variate regression methods help to reduce uncertainties in estimates of ozone recovery, great care has to be taken in their application due to the existence of uncertainties and degrees of freedom in the choice of independent variables. We show that taking all uncertainties into account in the regressions the formal recovery of ozone in the Antarctic ozone hole cannot be established yet, though is likely before the end of the decade (before 2020). Rather than focusing on time and area averages of total ozone columns or ozone profiles, we argue that the time evolution of the probability distribution of vertically resolved ozone in the Antarctic ozone hole contains a better fingerprint for the detection of ozone recovery in the Antarctic ozone hole. The advantages of this method over more tradition methods of trend analyses based on spatio-temporal average ozone are discussed. The 10-year record of MLS satellite measurements of ozone in the Antarctic ozone hole shows a

From Networks to Time Series

Science.gov (United States)

Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

2012-10-01

In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.

Modelling stomatal ozone flux and deposition to grassland communities across Europe

International Nuclear Information System (INIS)

Ashmore, M.R.; Bueker, P.; Emberson, L.D.; Terry, A.C.; Toet, S.

2007-01-01

Regional scale modelling of both ozone deposition and the risk of ozone impacts is poorly developed for grassland communities. This paper presents new predictions of stomatal ozone flux to grasslands at five different locations in Europe, using a mechanistic model of canopy development for productive grasslands to generate time series of leaf area index and soil water potential as inputs to the stomatal component of the DO 3 SE ozone deposition model. The parameterisation of both models was based on Lolium perenne, a dominant species of productive pasture in Europe. The modelled seasonal time course of stomatal ozone flux to both the whole canopy and to upper leaves showed large differences between climatic zones, which depended on the timing of the start of the growing season, the effect of soil water potential, and the frequency of hay cuts. Values of modelled accumulated flux indices and the AOT40 index showed a five-fold difference between locations, but the locations with the highest flux differed depending on the index used; the period contributing to the accumulation of AOT40 did not always coincide with the modelled period of active ozone canopy uptake. Use of a fixed seasonal profile of leaf area index in the flux model produced very different estimates of annual accumulated total canopy and leaf ozone flux when compared with the flux model linked to a simulation of canopy growth. Regional scale model estimates of both the risks of ozone impacts and of total ozone deposition will be inaccurate unless the effects of climate and management in modifying grass canopy growth are incorporated. - Modelled stomatal flux of ozone to productive grasslands in Europe shows different spatial and temporal variation to AOT40, and is modified by management and soil water status

Ozone decay in chemical reactor for ozone-dynamical disintegration of used tyres

International Nuclear Information System (INIS)

Golota, V.I.; Manuilenko, O.V.; Taran, G.V.; Dotsenko, Yu.V.; Pismenetskii, A.S.; Zamuriev, A.A.; Benitskaja, V.A.

2011-01-01

The ozone decay kinetics in the chemical reactor intended for used tyres disintegration is investigated experimentally and theoretically. Ozone was synthesized in barrierless ozonizers based on the streamer discharge. The chemical reactor for tyres disintegration in the ozone-air environment represents the cylindrical chamber, which feeds from the ozonizer by ozone-air mixture with the specified rate of volume flow, and with known ozone concentration. The output of the used mixture, which rate of volume flow is also known, is carried out through the ozone destructor. As a result of ozone decay in the volume and on the reactor walls, and output of the used mixture from the reactor, the ozone concentration in the reactor depends from time. In the paper, the analytical expression for dependence of ozone concentration in the reactor from time and from the parameters of a problem such as the volumetric feed rate, ozone concentration on the input in the reactor, volume flow rate of the used mixture, the volume of the reactor and the area of its internal surface is obtained. It is shown that experimental results coincide with good accuracy with analytical ones.

Human mortality effects of future concentrations of tropospheric ozone

International Nuclear Information System (INIS)

West, J.; Szopa, S.; Hauglustaine, D.A.

2007-01-01

Here we explore the effects of projected future changes in global ozone concentrations on premature human mortality, under three scenarios for 2030. We use daily surface ozone concentrations from a global atmospheric transport and chemistry model, and ozone-mortality relationships from daily time-series studies. The population-weighted annual average 8-h daily maximum ozone is projected to increase, relative to the present, in each of ten world regions under the SRES A2 scenario and the current legislation (CLE) scenario, with the largest growth in tropical regions, while decreases are projected in each region in the maximum feasible reduction (MFR) scenario. Emission reductions in the CLE scenario, relative to A2, are estimated to reduce about 190,000 premature human mortalities globally in 2030, with the most avoided mortalities in Africa. The MFR scenario will avoid about 460,000 premature mortalities relative to A2 in 2030, and 270,000 relative to CLE, with the greatest reductions in South Asia. (authors)

Duality between Time Series and Networks

Science.gov (United States)

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

Long time series

DEFF Research Database (Denmark)

Hisdal, H.; Holmqvist, E.; Hyvärinen, V.

Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...

A Course in Time Series Analysis

CERN Document Server

Peña, Daniel; Tsay, Ruey S

2011-01-01

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a

Development and Implementation of a Near-Real-Time Web Reporting System on Ground-Level Ozone in Europe

DEFF Research Database (Denmark)

Normander, Bo; Haigh, Tim; Christiansen, Jesper S.

2008-01-01

in exchanging data and knowledge. Near-real-time information systems on the Web seem to be a valuable complement to future environmental reporting, and the European Environment Agency is currently investigating the requirements needed to extend the use of near-real-time data, including reporting on air......This article presents the development and results of Ozone Web-a near-real-time Web-based approach to communicate environmental information to policy makers, researchers, and the general public. In Ozone Web, ground-level ozone information from 750 air quality measurement stations across Europe...

Urban Summertime Ozone of China: Peak Ozone Hour and Nighttime Mixing

Science.gov (United States)

Qu, H.; Wang, Y.; Zhang, R.

2017-12-01

We investigate the observed diurnal cycle of summertime ozone in the cities of China using a regional chemical transport model. The simulated daytime ozone is in general agreement with the observations. Model simulations suggest that the ozone peak time and peak concentration are a function of NOx (NO + NO2) and volatile organic compound (VOC) emissions. The differences between simulated and observed ozone peak time and peak concentration in some regions can be applied to understand biases in the emission inventories. For example, the VOCs emissions are underestimated over the Pearl River Delta (PRD) region, and either NOx emissions are underestimated or VOC emissions are overestimated over the Yangtze River Delta (YRD) regions. In contrast to the general good daytime ozone simulations, the simulated nighttime ozone has a large low bias of up to 40 ppbv. Nighttime ozone in urban areas is sensitive to the nocturnal boundary-layer mixing, and enhanced nighttime mixing (from the surface to 200-500 m) is necessary for the model to reproduce the observed level of ozone.

Some current problems in atmospheric ozone chemistry; role of chemical kinetics

Energy Technology Data Exchange (ETDEWEB)

Cox, R.A.

1987-03-01

A review is given on selected aspects of the reaction mechanisms of current interest in the chemistry of atmospheric ozone. Atmospheric ozone is produced and removed by a complex series of elementary gas-phase photochemical reactions involving O/sub x/, HO/sub x/, NO/sub x/, CIO/sub x/ and hydrocarbon species. At the present time there is a good knowledge of the basic processes involved in ozone chemistry in the stratosphere and the troposphere and the kinetics of most of the key reactions are well defined. There are a number of difficulties in the theoretical descriptions of observed ozone behaviour which may be due to uncertainties in the chemistry. Examples are the failure to predict present day ozone in the photochemically controlled region above 35 Km altitude and the large reductions in the ozone column in the Antartic Spring which has been observed in recent years. In the troposphere there is growing evidence that ozone and other trace gases have changed appreciably from pre-industrial concentrations, due to chemical reactions involving man-made pollutants. Quantitative investigation of the mechanisms by which these changes may occur requires a sound laboratory kinetics data base.

Kolmogorov Space in Time Series Data

OpenAIRE

Kanjamapornkul, K.; Pinčák, R.

2016-01-01

We provide the proof that the space of time series data is a Kolmogorov space with $T_{0}$-separation axiom using the loop space of time series data. In our approach we define a cyclic coordinate of intrinsic time scale of time series data after empirical mode decomposition. A spinor field of time series data comes from the rotation of data around price and time axis by defining a new extradimension to time series data. We show that there exist hidden eight dimensions in Kolmogorov space for ...

On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

OpenAIRE

Trottini, Mario; Vigo, Isabel; Belda, Santiago

2015-01-01

Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that ...

Multiple Indicator Stationary Time Series Models.

Science.gov (United States)

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Study of Ozone Layer Variability near St. Petersburg on the Basis of SBUV Satellite Measurements and Numerical Simulation (2000-2014)

Science.gov (United States)

Virolainen, Y. A.; Timofeyev, Y. M.; Smyshlyaev, S. P.; Motsakov, M. A.; Kirner, O.

2017-12-01

A comparison between the numerical simulation results of ozone fields with different experimental data makes it possible to estimate the quality of models for their further use in reliable forecasts of ozone layer evolution. We analyze time series of satellite (SBUV) measurements of the total ozone column (TOC) and the ozone partial columns in two atmospheric layers (0-25 and 25-60 km) and compare them with the results of numerical simulation in the chemistry transport model (CTM) for the low and middle atmosphere and the chemistry climate model EMAC. The daily and monthly average ozone values, short-term periods of ozone depletion, and long-term trends of ozone columns are considered; all data sets relate to St. Petersburg and the period between 2000 and 2014. The statistical parameters (means, standard deviations, variations, medians, asymmetry parameter, etc.) of the ozone time series are quite similar for all datasets. However, the EMAC model systematically underestimates the ozone columns in all layers considered. The corresponding differences between satellite measurements and EMAC numerical simulations are (5 ± 5)% and (7 ± 7)% and (1 ± 4)% for the ozone column in the 0-25 and 25-60 km layers, respectively. The correspondent differences between SBUV measurements and CTM results amount to (0 ± 7)%, (1 ± 9)%, and (-2 ± 8)%. Both models describe the sudden episodes of the ozone minimum well, but the EMAC accuracy is much higher than that of the CTM, which often underestimates the ozone minima. Assessments of the long-term linear trends show that they are close to zero for all datasets for the period under study.

Time Series Momentum

DEFF Research Database (Denmark)

Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

2012-01-01

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial...... under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor

2016-01-01

This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

Stochastic models for time series

CERN Document Server

Doukhan, Paul

2018-01-01

This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

Science.gov (United States)

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Evaluation of the Ozone Fields in NASA's MERRA-2 Reanalysis

Science.gov (United States)

Wargan, Krzysztof; Labow, Gordon; Frith, Stacey; Pawson, Steven; Livesey, Nathaniel; Partyka, Gary

2017-01-01

We describe and assess the quality of the assimilated ozone product from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) produced at NASAs Global Modeling and Assimilation Office (GMAO) spanning the time period from 1980 to present. MERRA-2 assimilates partial column ozone retrievals from a series of Solar Backscatter Ultraviolet (SBUV) radiometers on NASA and NOAA spacecraft between January 1980 and September 2004; starting in October 2004 retrieved ozone profiles from the Microwave Limb Sounder (MLS) and total column ozone from the Ozone Monitoring Instrument on NASAs EOS Aura satellite are assimilated. We compare the MERRA-2 ozone with independent satellite and ozonesonde data focusing on the representation of the spatial and temporal variability of stratospheric and upper tropospheric ozone and on implications of the change in the observing system from SBUV to EOS Aura. The comparisons show agreement within 10 (standard deviation of the difference) between MERRA-2 profiles and independent satellite data in most of the stratosphere. The agreement improves after 2004 when EOS Aura data are assimilated. The standard deviation of the differences between the lower stratospheric and upper tropospheric MERRA-2 ozone and ozonesondes is 11.2 and 24.5, respectively, with correlations of 0.8 and above, indicative of a realistic representation of the near-tropopause ozone variability in MERRA-2. The agreement improves significantly in the EOS Aura period, however MERRA-2 is biased low in the upper troposphere with respect to the ozonesondes. Caution is recommended when using MERRA-2 ozone for decadal changes and trend studies.

Time Series with Long Memory

OpenAIRE

西埜, 晴久

2004-01-01

The paper investigates an application of long-memory processes to economic time series. We show properties of long-memory processes, which are motivated to model a long-memory phenomenon in economic time series. An FARIMA model is described as an example of long-memory model in statistical terms. The paper explains basic limit theorems and estimation methods for long-memory processes in order to apply long-memory models to economic time series.

Visibility Graph Based Time Series Analysis.

Science.gov (United States)

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Visibility Graph Based Time Series Analysis.

Directory of Open Access Journals (Sweden)

Mutua Stephen

Full Text Available Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Estimated SAGE II ozone mixing ratios in early 1993 and comparisons with Stratospheric Photochemistry, Aerosols and Dynamic Expedition measurements

Science.gov (United States)

Yue, G. K.; Veiga, R. E.; Poole, L. R.; Zawodny, J. M.; Proffitt, M. H.

1994-01-01

An empirical time-series model for estimating ozone mixing ratios based on Stratospheric Aerosols and Gas Experiment II (SAGE II) monthly mean ozone data for the period October 1984 through June 1991 has been developed. The modeling results for ozone mixing ratios in the 10- to 30- km region in early months of 1993 are presented. In situ ozone profiles obtained by a dual-beam UV-absorption ozone photometer during the Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) campaign, May 1-14, 1993, are compared with the model results. With the exception of two profiles at altitudes below 16 km, ozone mixing ratios derived by the model and measured by the ozone photometer are in relatively good agreement within their individual uncertainties. The identified discrepancies in the two profiles are discussed.

Decadal-Scale Responses in Middle and Upper Stratospheric Ozone From SAGE II Version 7 Data

Science.gov (United States)

Remsberg, E. E.

2014-01-01

Stratospheric Aerosol and Gas Experiment (SAGE II) version 7 (v7) ozone profiles are analyzed for their decadal-scale responses in the middle and upper stratosphere for 1991 and 1992-2005 and compared with those from its previous version 6.2 (v6.2). Multiple linear regression (MLR) analysis is applied to time series of its ozone number density vs. altitude data for a range of latitudes and altitudes. The MLR models that are fit to the time series data include a periodic 11 yr term, and it is in-phase with that of the 11 yr, solar UV (Ultraviolet)-flux throughout most of the latitude/ altitude domain of the middle and upper stratosphere. Several regions that have a response that is not quite in-phase are interpreted as being affected by decadal-scale, dynamical forcings. The maximum minus minimum, solar cycle (SClike) responses for the ozone at the low latitudes are similar from the two SAGE II data versions and vary from about 5 to 2.5% from 35 to 50 km, although they are resolved better with v7. SAGE II v7 ozone is also analyzed for 1984-1998, in order to mitigate effects of end-point anomalies that bias its ozone in 1991 and the analyzed results for 1991-2005 or following the Pinatubo eruption. Its SC-like ozone response in the upper stratosphere is of the order of 4%for 1984-1998 vs. 2.5 to 3%for 1991-2005. The SAGE II v7 results are also recompared with the responses in ozone from the Halogen Occultation Experiment (HALOE) that are in terms of mixing ratio vs. pressure for 1991-2005 and then for late 1992- 2005 to avoid any effects following Pinatubo. Shapes of their respective response profiles agree very well for 1992-2005. The associated linear trends of the ozone are not as negative in 1992-2005 as in 1984-1998, in accord with a leveling off of the effects of reactive chlorine on ozone. It is concluded that the SAGE II v7 ozone yields SC-like ozone responses and trends that are of better quality than those from v6.2.

Total ozone changes in the 1987 Antarctic ozone hole

Science.gov (United States)

Krueger, Arlin J.; Schoeberl, Mark R.; Doiron, Scott D.; Sechrist, Frank; Galimore, Reginald

1988-01-01

The development of the Antarctic ozone minimum was observed in 1987 with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) instrument. In the first half of August the near-polar (60 and 70 deg S) ozone levels were similar to those of recent years. By September, however, the ozone at 70 and 80 deg S was clearly lower than any previous year including 1985, the prior record low year. The levels continued to decrease throughout September until October 5 when a new record low of 109 DU was established at a point near the South Pole. This value is 29 DU less than the lowest observed in 1985 and 48 DU less than the 1986 low. The zonal mean total ozone at 60 deg S remained constant throughout the time of ozone hole formation. The ozone decline was punctuated by local minima formed away from the polar night boundary at about 75 deg S. The first of these, on August 15 to 17, formed just east of the Palmer Peninsula and appears to be a mountain wave. The second major minimum formed on September 5 to 7 again downwind of the Palmer Peninsula. This event was larger in scale than the August minimum and initiated the decline of ozone across the polar region. The 1987 ozone hole was nearly circular and pole centered for its entire life. In previous years the hole was perturbed by intrusions of the circumpolar maximum into the polar regions, thus causing the hole to be elliptical. The 1987 hole also remained in place until the end of November, a few days longer than in 1985, and this persistence resulted in the latest time for recovery to normal values yet observed.

Extreme events in total ozone over Arosa: Application of extreme value theory and fingerprints of atmospheric dynamics and chemistry and their effects on mean values and long-term changes

Science.gov (United States)

Rieder, Harald E.; Staehelin, Johannes; Maeder, Jörg A.; Peter, Thomas; Ribatet, Mathieu; Davison, Anthony C.; Stübi, Rene; Weihs, Philipp; Holawe, Franz

2010-05-01

In this study tools from extreme value theory (e.g. Coles, 2001; Ribatet, 2007) are applied for the first time in the field of stratospheric ozone research, as statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean values) of total ozone data do not address the internal data structure concerning extremes adequately. The study illustrates that tools based on extreme value theory are appropriate to identify ozone extremes and to describe the tails of the world's longest total ozone record (Arosa, Switzerland - for details see Staehelin et al., 1998a,b) (Rieder et al., 2010a). A daily moving threshold was implemented for consideration of the seasonal cycle in total ozone. The frequency of days with extreme low (termed ELOs) and extreme high (termed EHOs) total ozone and the influence of those on mean values and trends is analyzed for Arosa total ozone time series. The results show (a) an increase in ELOs and (b) a decrease in EHOs during the last decades and (c) that the overall trend during the 1970s and 1980s in total ozone is strongly dominated by changes in these extreme events. After removing the extremes, the time series shows a strongly reduced trend (reduction by a factor of 2.5 for trend in annual mean). Furthermore, it is shown that the fitted model represents the tails of the total ozone data set with very high accuracy over the entire range (including absolute monthly minima and maxima). Also the frequency distribution of ozone mini-holes (using constant thresholds) can be calculated with high accuracy. Analyzing the tails instead of a small fraction of days below constant thresholds provides deeper insight in time series properties. Excursions in the frequency of extreme events reveal "fingerprints" of dynamical factors such as ENSO or NAO, and chemical factors, such as cold Arctic vortex ozone losses, as well as major volcanic eruptions of the 20th century (e.g. Gunung Agung, El Chich

Network structure of multivariate time series.

Science.gov (United States)

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

Stratospheric ozone measurements at Arosa (Switzerland): history and scientific relevance

Science.gov (United States)

Staehelin, Johannes; Viatte, Pierre; Stübi, Rene; Tummon, Fiona; Peter, Thomas

2018-05-01

Climatic Observatory (LKO) in Arosa (Switzerland), marking the beginning of the world's longest series of total (or column) ozone measurements. They were driven by the recognition that atmospheric ozone is important for human health, as well as by scientific curiosity about what was, at the time, an ill characterised atmospheric trace gas. From around the mid-1950s to the beginning of the 1970s studies of high atmosphere circulation patterns that could improve weather forecasting was justification for studying stratospheric ozone. In the mid-1970s, a paradigm shift occurred when it became clear that the damaging effects of anthropogenic ozone-depleting substances (ODSs), such as long-lived chlorofluorocarbons, needed to be documented. This justified continuing the ground-based measurements of stratospheric ozone. Levels of ODSs peaked around the mid-1990s as a result of a global environmental policy to protect the ozone layer, implemented through the 1987 Montreal Protocol and its subsequent amendments and adjustments. Consequently, chemical destruction of stratospheric ozone started to slow around the mid-1990s. To some extent, this raises the question as to whether continued ozone observation is indeed necessary. In the last decade there has been a tendency to reduce the costs associated with making ozone measurements globally including at Arosa. However, the large natural variability in ozone on diurnal, seasonal, and interannual scales complicates the capacity for demonstrating the success of the Montreal Protocol. Chemistry-climate models also predict a super-recovery of the ozone layer at mid-latitudes in the second half of this century, i.e. an increase of ozone concentrations beyond pre-1970 levels, as a consequence of ongoing climate change. These factors, and identifying potentially unexpected stratospheric responses to climate change, support the continued need to document stratospheric ozone changes. This is particularly valuable at the Arosa site, due

Data mining in time series databases

CERN Document Server

Kandel, Abraham; Bunke, Horst

2004-01-01

Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.

Models for dependent time series

CERN Document Server

Tunnicliffe Wilson, Granville; Haywood, John

2015-01-01

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater

Visual time series analysis

DEFF Research Database (Denmark)

Fischer, Paul; Hilbert, Astrid

2012-01-01

We introduce a platform which supplies an easy-to-handle, interactive, extendable, and fast analysis tool for time series analysis. In contrast to other software suits like Maple, Matlab, or R, which use a command-line-like interface and where the user has to memorize/look-up the appropriate...... commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...... choose between manual and automated parameter selection. The user can dene new transformations and add them to the system. The application contains efficient implementations of advanced and recent techniques for time series analysis including techniques related to extreme value analysis and filtering...

Estimating contribution of wildland fires to ambient ozone levels in National Parks in the Sierra Nevada, California

International Nuclear Information System (INIS)

Preisler, Haiganoush K.; Zhong Shiyuan; Esperanza, Annie; Brown, Timothy J.; Bytnerowicz, Andrzej; Tarnay, Leland

2010-01-01

Data from four continuous ozone and weather monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire. - We have demonstrated that it is possible to produce accurate forecasts of next-day hourly ozone levels in the Sierra Nevada, CA, during fire season.

Estimating contribution of wildland fires to ambient ozone levels in National Parks in the Sierra Nevada, California

Energy Technology Data Exchange (ETDEWEB)

Preisler, Haiganoush K., E-mail: hpreisler@fs.fed.u [USDA Forest Service, Pacific Southwest Research Station, 800 Buchanan St, Albany, CA 94710 (United States); Zhong Shiyuan, E-mail: zhongs@msu.ed [Department of Geography, Michigan State University, 116 Geography Building, East Lansing, MI 48824-1117 (United States); Esperanza, Annie, E-mail: annie_esperanza@nps.go [Sequoia and Kings Canyon National Parks, 47050 Generals Highway Three Rivers, CA 93271 (United States); Brown, Timothy J., E-mail: tim.brown@dri.ed [Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89521-10095 (United States); Bytnerowicz, Andrzej, E-mail: abytnerowicz@fs.fed.u [USDA Forest Service, Pacific Southwest Research Station, 4955 Canyon Crest Drive, Riverside, CA 92507 (United States); Tarnay, Leland, E-mail: Leland_Tarnay@nps.go [Yosemite National Park, El Portal, CA 95318 (United States)

2010-03-15

Data from four continuous ozone and weather monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire. - We have demonstrated that it is possible to produce accurate forecasts of next-day hourly ozone levels in the Sierra Nevada, CA, during fire season.

Contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area, Portugal since the 19th century

International Nuclear Information System (INIS)

Alvim-Ferraz, M.C.M.; Sousa, S.I.V.; Pereira, M.C.; Martins, F.G.

2006-01-01

The main purpose of this study was to evaluate the contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area (Portugal) since the 19th century. The study was based on pre-industrial and recent data series, the results being analyzed according to the atmospheric chemistry. The treatment of ozone and meteorological data was performed by classical statistics and by time-series analysis. It was concluded that in the 19th century the ozone present in the troposphere was not of photochemical origin, being possible to consider the respective concentrations as reference values. For recent data a cycle of 8 h for ozone concentrations could be related to traffic. Compared to the 19th century, the current concentrations were 147% higher (252% higher in May) due to the increased photochemical production associated with the increased anthropogenic emissions. - Compared to the 19th century, the current ozone concentrations are 147% higher at Oporto, Portugal

A Review of Subsequence Time Series Clustering

Directory of Open Access Journals (Sweden)

Seyedjamal Zolhavarieh

2014-01-01

Full Text Available Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

A review of subsequence time series clustering.

Science.gov (United States)

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

A Review of Subsequence Time Series Clustering

Science.gov (United States)

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

Physicochemical patterns of ozone absorption by wood

Science.gov (United States)

Mamleeva, N. A.; Lunin, V. V.

2016-11-01

Results from studying aspen and pine wood ozonation are presented. The effect the concentration of ozone, the reagent residence time, and the content of water in a sample of wood has on ozone consumption rate and ozone demand are analyzed. The residence time is shown to determine the degree of ozone conversion degree and the depth of substrate destruction. The main patterns of ozone absorption by wood with different moisture content are found. Ways of optimizing the ozonation of plant biomass are outlined.

Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...

Adaptive time-variant models for fuzzy-time-series forecasting.

Science.gov (United States)

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

Time Series Analysis and Forecasting by Example

CERN Document Server

Bisgaard, Soren

2011-01-01

An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in

Time series with tailored nonlinearities

Science.gov (United States)

Räth, C.; Laut, I.

2015-10-01

It is demonstrated how to generate time series with tailored nonlinearities by inducing well-defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of an originally linear and uncorrelated Gaussian time series, the observed scaling behavior of the intensity distribution of empirical time series can be reproduced. The power law character of the intensity distributions being typical for, e.g., turbulence and financial data can thus be explained in terms of phase correlations.

Ozone kinetics in low-pressure discharges: vibrationally excited ozone and molecule formation on surfaces

Science.gov (United States)

Marinov, Daniil; Guerra, Vasco; Guaitella, Olivier; Booth, Jean-Paul; Rousseau, Antoine

2013-10-01

A combined experimental and modeling investigation of the ozone kinetics in the afterglow of pulsed direct current discharges in oxygen is carried out. The discharge is generated in a cylindrical silica tube of radius 1 cm, with short pulse durations between 0.5 and 2 ms, pressures in the range 1-5 Torr and discharge currents ˜40-120 mA. Time-resolved absolute concentrations of ground-state atoms and ozone molecules were measured simultaneously in situ, by two-photon absorption laser-induced fluorescence and ultraviolet absorption, respectively. The experiments were complemented by a self-consistent model developed to interpret the results and, in particular, to evaluate the roles of vibrationally excited ozone and of ozone formation on surfaces. It is found that vibrationally excited ozone, O_3^{*} , plays an important role in the ozone kinetics, leading to a decrease in the ozone concentration and an increase in its formation time. In turn, the kinetics of O_3^{*} is strongly coupled with those of atomic oxygen and O2(a 1Δg) metastables. Ozone formation at the wall does not contribute significantly to the total ozone production under the present conditions. Upper limits for the effective heterogeneous recombination probability of O atoms into ozone are established.

Ozone kinetics in low-pressure discharges: vibrationally excited ozone and molecule formation on surfaces

International Nuclear Information System (INIS)

Marinov, Daniil; Guaitella, Olivier; Booth, Jean-Paul; Rousseau, Antoine; Guerra, Vasco

2013-01-01

A combined experimental and modeling investigation of the ozone kinetics in the afterglow of pulsed direct current discharges in oxygen is carried out. The discharge is generated in a cylindrical silica tube of radius 1 cm, with short pulse durations between 0.5 and 2 ms, pressures in the range 1–5 Torr and discharge currents ∼40–120 mA. Time-resolved absolute concentrations of ground-state atoms and ozone molecules were measured simultaneously in situ, by two-photon absorption laser-induced fluorescence and ultraviolet absorption, respectively. The experiments were complemented by a self-consistent model developed to interpret the results and, in particular, to evaluate the roles of vibrationally excited ozone and of ozone formation on surfaces. It is found that vibrationally excited ozone, O 3 * , plays an important role in the ozone kinetics, leading to a decrease in the ozone concentration and an increase in its formation time. In turn, the kinetics of O 3 * is strongly coupled with those of atomic oxygen and O 2 (a 1 Δ g ) metastables. Ozone formation at the wall does not contribute significantly to the total ozone production under the present conditions. Upper limits for the effective heterogeneous recombination probability of O atoms into ozone are established. (paper)

Investigating a high ozone episode in a rural mountain site

International Nuclear Information System (INIS)

Monteiro, A.; Strunk, A.; Carvalho, A.; Tchepel, O.; Miranda, A.I.; Borrego, C.; Saavedra, S.; Rodríguez, A.; Souto, J.; Casares, J.; Friese, E.; Elbern, H.

2012-01-01

A very high ozone episode with observed hourly values above 350 μg m −3 occurred in July 2005 at the Lamas d’Olo air quality monitoring station, located in a mountainous area in the north of Portugal. Aiming to identify the origin and formation of this ozone-rich episode, a statistical analysis and a modelling approach were applied. A cross-spectrum analysis in the frequency domain and a synoptic analysis of the meteorological and air quality time series were performed. In order to go further in this analysis, a numerical modelling approach was applied. The results indicate that the transport of ozone and its precursors is the main responsible for the high ozone concentrations. Together with the local mountain breeze and subsidence conditions, the sea-breeze circulation transporting pollutants from the coastal urban and industrialized areas that reach the site during late afternoon turn out to be the driving forces for the ozone peaks. - Highlights: ► A very high ozone episode occurred in a rural mountain site of Portugal in 2004. ► Data cross-spectrum analysis in the frequency domain was performed. ► A numerical modelling approach was also applied. ► The sea-breeze circulation transported pollutants from the urban and industrialized coast. ► The mountain breeze and subsidence conditions were also driving forces for ozone peaks. - The sea-breeze transporting pollutants from the coast, the mountain breeze and subsidence conditions, were the driving forces for the ozone episode occurred in a rural mountain site.

Computational analysis of ozonation in bubble columns

International Nuclear Information System (INIS)

Quinones-Bolanos, E.; Zhou, H.; Otten, L.

2002-01-01

This paper presents a new computational ozonation model based on the principle of computational fluid dynamics along with the kinetics of ozone decay and microbial inactivation to predict the performance of ozone disinfection in fine bubble columns. The model can be represented using a mixture two-phase flow model to simulate the hydrodynamics of the water flow and using two transport equations to track the concentration profiles of ozone and microorganisms along the height of the column, respectively. The applicability of this model was then demonstrated by comparing the simulated ozone concentrations with experimental measurements obtained from a pilot scale fine bubble column. One distinct advantage of this approach is that it does not require the prerequisite assumptions such as plug flow condition, perfect mixing, tanks-in-series, uniform radial or longitudinal dispersion in predicting the performance of disinfection contactors without carrying out expensive and tedious tracer studies. (author)

Clustering of financial time series

Science.gov (United States)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

The historic surface ozone record, 1896-1975, and its relation to modern measurements

Science.gov (United States)

Galbally, I. E.; Tarasick, D. W.; Stähelin, J.; Wallington, T. J.; Steinbacher, M.; Schultz, M.; Cooper, O. R.

2017-12-01

Tropospheric ozone is a greenhouse gas, a key component of atmospheric chemistry, and is detrimental to human health and plant productivity. The historic surface ozone record 1896-1975 has been constructed from measurements selected for (a) instrumentation whose ozone response can be traced to modern tropospheric ozone measurement standards, (b) samples taken when there is low probability of chemical interference and (c) sampling locations, heights and times when atmospheric mixing will minimise vertical gradients of ozone in the planetary boundary layer above and around the measurement location. Early measurements with the Schönbein filter paper technique cannot be related to modern methods with any degree of confidence. The potassium iodide-arsenite technique used at Montsouris for 1876-1910 is valid for measuring ozone; however, due to the presence of the interfering gases sulfur dioxide, ammonia and nitrogen oxides, the measured ozone concentrations are not representative of the regional atmosphere. The use of these data sets for trend analyses is not recommended. In total, 58 acceptable sets of measurements are currently identified, commencing in Europe in 1896, Greenland in 1932 and globally by the late 1950's. Between 1896 and 1944 there were 21 studies (median duration 5 days) with a median mole fraction of 23 nmol mol-1 (range of study averages 15-62 nmol mol-1). Between 1950 and 1975 there were 37 studies (median duration approx. 21 months) with a median mole fraction of 22 nmol mol-1 (range of study averages 13-49 nmol mol-1), all measured under conditions likely to give ozone mole fractions similar to those in the planetary boundary layer. These time series are matched with modern measurements from the Tropospheric Ozone Assessment Report (TOAR) Ozone Database and used to examine changes between the historic and modern observations. These historic ozone levels are higher than previously accepted for surface ozone in the late 19th early 20th Century

Evaluation of the Ozone Fields in NASA’s MERRA-2 Reanalysis

Science.gov (United States)

Wargan, Krzysztof; Labow, Gordon; Frith, Stacey; Pawson, Steven; Livesey, Nathaniel; Partyka, Gary

2018-01-01

We describe and assess the quality of the assimilated ozone product from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) produced at NASA’s Global Modeling and Assimilation Office (GMAO) spanning the time period from 1980 to present. MERRA-2 assimilates partial column ozone retrievals from a series of Solar Backscatter Ultraviolet (SBUV) radiometers on NASA and NOAA spacecraft between January 1980 and September 2004; starting in October 2004 retrieved ozone profiles from the Microwave Limb Sounder (MLS) and total column ozone from the Ozone Monitoring Instrument on NASA’s EOS Aura satellite are assimilated. We compare the MERRA-2 ozone with independent satellite and ozonesonde data focusing on the representation of the spatial and temporal variability of stratospheric and upper tropospheric ozone and on implications of the change in the observing system from SBUV to EOS Aura. The comparisons show agreement within 10 % (standard deviation of the difference) between MERRA-2 profiles and independent satellite data in most of the stratosphere. The agreement improves after 2004 when EOS Aura data are assimilated. The standard deviation of the differences between the lower stratospheric and upper tropospheric MERRA-2 ozone and ozonesondes is 11.2 % and 24.5 %, respectively, with correlations of 0.8 and above, indicative of a realistic representation of the near-tropopause ozone variability in MERRA-2. The agreement improves significantly in the EOS Aura period, however MERRA-2 is biased low in the upper troposphere with respect to the ozonesondes. Caution is recommended when using MERRA-2 ozone for decadal changes and trend studies. PMID:29527096

Ozone kinetics in low-pressure discharges

Science.gov (United States)

Guerra, Vasco; Marinov, Daniil; Guaitella, Olivier; Rousseau, Antoine

2012-10-01

Ozone kinetics is quite well established at atmospheric pressure, due to the importance of ozone in atmospheric chemistry and to the development of industrial ozone reactors. However, as the pressure is decreased and the dominant three-body reactions lose importance, the main mechanisms involved in the creation and destruction of ozone are still surrounded by important uncertainties. In this work we develop a self-consistent model for a pulsed discharge and its afterglow operating in a Pyrex reactor with inner radius 1 cm, at pressures in the range 1-5 Torr and discharge currents of 40-120 mA. The model couples the electron Boltzmann equation with a system of equations for the time evolution of the heavy particles. The calculations are compared with time-dependent measurements of ozone and atomic oxygen. Parametric studies are performed in order to clarify the role of vibrationally excited ozone in the overall kinetics and to establish the conditions where ozone production on the surface may become important. It is shown that vibrationally excited ozone does play a significant role, by increasing the time constants of ozone formation. Moreover, an upper limit for the ozone formation at the wall in these conditions is set at 10(-4).

A new time-series methodology for estimating relationships between elderly frailty, remaining life expectancy, and ambient air quality.

Science.gov (United States)

Murray, Christian J; Lipfert, Frederick W

2012-01-01

Many publications estimate short-term air pollution-mortality risks, but few estimate the associated changes in life-expectancies. We present a new methodology for analyzing time series of health effects, in which prior frailty is assumed to precede short-term elderly nontraumatic mortality. The model is based on a subpopulation of frail individuals whose entries and exits (deaths) are functions of daily and lagged environmental conditions: ambient temperature/season, airborne particles, and ozone. This frail susceptible population is unknown; its fluctuations cannot be observed but are estimated using maximum-likelihood methods with the Kalman filter. We used an existing 14-y set of daily data to illustrate the model and then tested the assumption of prior frailty with a new generalized model that estimates the portion of the daily death count allocated to nonfrail individuals. In this demonstration dataset, new entries into the high-risk pool are associated with lower ambient temperatures and higher concentrations of particulate matter and ozone. Accounting for these effects on antecedent frailty reduces this at-risk population, yielding frail life expectancies of 5-7 days. Associations between environmental factors and entries to the at-risk pool are about twice as strong as for mortality. Nonfrail elderly deaths are seen to make only small contributions. This new model predicts a small short-lived frail population-at-risk that is stable over a wide range of environmental conditions. The predicted effects of pollution on new entries and deaths are robust and consistent with conventional morbidity/mortality times-series studies. We recommend model verification using other suitable datasets.

Data Mining Smart Energy Time Series

Directory of Open Access Journals (Sweden)

Janina POPEANGA

2015-07-01

Full Text Available With the advent of smart metering technology the amount of energy data will increase significantly and utilities industry will have to face another big challenge - to find relationships within time-series data and even more - to analyze such huge numbers of time series to find useful patterns and trends with fast or even real-time response. This study makes a small review of the literature in the field, trying to demonstrate how essential is the application of data mining techniques in the time series to make the best use of this large quantity of data, despite all the difficulties. Also, the most important Time Series Data Mining techniques are presented, highlighting their applicability in the energy domain.

Predicting chaotic time series

International Nuclear Information System (INIS)

Farmer, J.D.; Sidorowich, J.J.

1987-01-01

We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow

Measuring multiscaling in financial time-series

International Nuclear Information System (INIS)

Buonocore, R.J.; Aste, T.; Di Matteo, T.

2016-01-01

We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analyzing the multi/uni-scaling behavior of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range (2, 5). We discuss the right aggregation horizon to mitigate this bias.

Antarctic ozone loss in 1989-2010: evidence for ozone recovery?

Science.gov (United States)

Kuttippurath, J.; Lefèvre, F.; Pommereau, J.-P.; Roscoe, H. K.; Goutail, F.; Pazmiño, A.; Shanklin, J. D.

2012-04-01

We present a detailed estimation of chemical ozone loss in the Antarctic polar vortex from 1989 to 2010. The analyses include ozone loss estimates for 12 Antarctic ground-based (GB) stations. All GB observations show minimum ozone in the late September-early October period. Among the stations, the lowest minimum ozone values are observed at South Pole and the highest at Dumont d'Urville. The ozone loss starts by mid-June at the vortex edge and then progresses towards the vortex core with time. The loss intensifies in August-September, peaks by the end of September-early October, and recovers thereafter. The average ozone loss in the Antarctic is revealed to be about 33-50% in 1989-1992 in agreement with the increase in halogens during this period, and then stayed at around 48% due to saturation of the loss. The ozone loss in the warmer winters (e.g. 2002, and 2004) is lower (37-46%) and in the colder winters (e.g. 2003, and 2006) is higher (52-55%). Because of small inter-annual variability, the correlation between ozone loss and the volume of polar stratospheric clouds yields ~0.51. The GB ozone and ozone loss values are in good agreement with those found from the space-based observations of the Total Ozone Mapping Spectrometer/Ozone Monitoring Instrument (TOMS/OMI), the Global Ozone Monitoring Experiment (GOME), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Aura Microwave Limb Sounder (MLS), where the differences are within ±5% and are mostly within the error bars of the measurements. The piece-wise linear trends computed from the September-November vortex average GB and TOMS/OMI ozone show about -4 to -5.6 DU (Dobson Unit) yr-1 in 1989-1996 and about +1 DU yr-1 in 1997-2010. The trend during the former period is significant at 95% confidence intervals, but the trend in 1997-2010 is significant only at 85% confidence intervals. Our analyses suggest a period of about 9-10 yr to get the first detectable ozone

Time averaging, ageing and delay analysis of financial time series

Science.gov (United States)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Applied time series analysis

CERN Document Server

Woodward, Wayne A; Elliott, Alan C

2011-01-01

""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

Development and Implementation of a Near-Real-Time Web Reporting System on Ground-Level Ozone in Europe

DEFF Research Database (Denmark)

Normander, Bo; Haigh, Tim; Christiansen, Jesper S.

2008-01-01

in exchanging data and knowledge. Near-real-time information systems on the Web seem to be a valuable complement to future environmental reporting, and the European Environment Agency is currently investigating the requirements needed to extend the use of near-real-time data, including reporting on air......This article presents the development and results of Ozone Web-a near-real-time Web-based approach to communicate environmental information to policy makers, researchers, and the general public. In Ozone Web, ground-level ozone information from 750 air quality measurement stations across Europe...... is collected on an hourly basis, filtered, interpolated, and presented on zoomable maps and graphs. Compared with other environmental information initiatives, the main aspects of this Website is the allowance for user interactivity, free access to data, and high timeliness. Data are published 2 to 3 h after...

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

Science.gov (United States)

Sanders, Abram F. J.; Verstraeten, Willem W.; Kooreman, Maurits L.; van Leth, Thomas C.; Beringer, Jason; Joiner, Joanna

2016-01-01

A global, monthly averaged time series of Sun-induced Fluorescence (SiF), spanning January 2007 to June 2015, was derived from Metop-A Global Ozone Monitoring Experiment 2 (GOME-2) spectral measurements. Far-red SiF was retrieved using the filling-in of deep solar Fraunhofer lines and atmospheric absorption bands based on the general methodology described by Joiner et al, AMT, 2013. A Principal Component (PC) analysis of spectra over non-vegetated areas was performed to describe the effects of atmospheric absorption. Our implementation (SiF KNMI) is an independent algorithm and differs from the latest implementation of Joiner et al, AMT, 2013 (SiF NASA, v26), because we used desert reference areas for determining PCs (as opposed to cloudy ocean and some desert) and a wider fit window that covers water vapour and oxygen absorption bands (as opposed to only Fraunhofer lines). As a consequence, more PCs were needed (35 as opposed to 12). The two time series (SiF KNMI and SiF NASA, v26) correlate well (overall R of 0.78) except for tropical rain forests. Sensitivity experiments suggest the strong impact of the water vapour absorption band on retrieved SiF values. Furthermore, we evaluated the SiF time series with Gross Primary Productivity (GPP) derived from twelve flux towers in Australia. Correlations for individual towers range from 0.37 to 0.84. They are particularly high for managed biome types. In the de-seasonalized Australian SiF time series, the break of the Millennium Drought during local summer of 2010/2011 is clearly observed.

Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

ANALYSIS AND CHARACTERIZATION OF OZONE-RICH EPISODES IN NORTHEAST PORTUGAL

Science.gov (United States)

Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.

2009-12-01

Each summer period extremely high ozone levels are registered at the rural background station of Lamas d’Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes. Synoptic patterns anomalies and back trajectories cluster analysis were performed for a period of 76 days where ozone maximum concentrations were above 200 µg.m-3. This analysis was performed for the period between 2004 and 2007. The obtained anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. In addition, a strong wind flow pattern from NE is visible in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, is responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants may be the main contributor to the ozone levels registered at Lamas d’Olo. This is also highlighted by the correlation of the ozone time series with the meteorological parameters analysed in the frequency domain.

Determination of total ozone from DMSP multichannel filter radiometer measurements

International Nuclear Information System (INIS)

Luther, F.M.; Weichel, R.L.

1992-01-01

The multichannel filter radiometer (MFR) infrared sensor was first flown in 1977 on a Defense Meteorological Satellite Program (DMSP) Block 5D series satellite operated by the US Air Force. The first four satellites in this series carried MFR sensors from which total atmospheric column ozone amounts may be derived. The MFR sensor was the first cross-track scanning sensor capable of measuring ozone. MFR sensor infrared measurements are taken day and night. The satellites are in polar sun-synchronous orbits providing daily global coverage. The series of four sensors spans a data period of nearly three years. The MFR sensor measures infrared radiances for 16 channels. Total ozone amounts are determined from sets of radiance measurements using an empirical relationship that is developed using linear regression analysis. Total ozone is modeled as a linear combination of terms involving functions of the MFR radiances for four channels (1, 3, 7 and 16) and the secant of the zenith angle. The MFR scans side to side in discrete steps of 40. The MFR sensor takes infrared radiance measurements at 25 cross-track scanning locations every 32 seconds. The instrument could take a theoretical maximum of 67,500 measurements per day, although typically 35,000 - 45,000 measurements are taken per day

Quantifying memory in complex physiological time-series.

Science.gov (United States)

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

The influence of ozonated time on the degree of depreciation of BOD, COD, TSS and phosphate in hospital liquid waste

International Nuclear Information System (INIS)

Isyuniarto and Andrianto

2009-01-01

The influence of ozonated time towards degree depreciation of Bode, COD, TSS and phosphate in hospital liquid waste was done. This research aim study influence of lime adding and ozone using to reduce of BOD, COD, TSS and phosphate in hospital waste. Added of lime mean for total increase ion OH - , while parameter of ozonization time mean to complete organic compounds oxidation in waste and flock formation. From this research it was found that optimum lime addition was 1.1% (% weight) and ozonization time was 20 minutes. In this condition it was achieved degree of BOD = 18.88 mg/l; COD = 25.68 mg/l, TSS = 80 mg/l and phosphate = 1.52 mg/l. This condition fulfil quality standard decided, that has to BOD = 75 mg/l; COD = 100 mg/l, TSS = 100 mg/l and phosphate = 2.0 mg/l. (author)

Statistical criteria for characterizing irradiance time series.

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2010-10-01

We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.

Ozone-Temperature Diurnal and Longer Term Correlations, in the Lower Thermosphere, Mesosphere and Stratosphere, Based on Measurements from SABER on TIMED

Science.gov (United States)

Huang, Frank T.; Mayr, Hans G.; Russell, James M., III; Mlynczak, Martin G.

2012-01-01

The analysis of mutual ozone-temperature variations can provide useful information on their interdependencies relative to the photochemistry and dynamics governing their behavior. Previous studies have mostly been based on satellite measurements taken at a fixed local time in the stratosphere and lower mesosphere. For these data, it is shown that the zonal mean ozone amounts and temperatures in the lower stratosphere are mostly positively correlated, while they are mostly negatively correlated in the upper stratosphere and in the lower mesosphere. The negative correlation, due to the dependence of photochemical reaction rates on temperature, indicates that ozone photochemistry is more important than dynamics in determining the ozone amounts. In this study, we provide new results by extending the analysis to include diurnal variations over 24 hrs of local time, and to larger spatial regimes, to include the upper mesosphere and lower thermosphere (MLT). The results are based on measurements by the SABER instrument on the TIMED satellite. For mean variations (i.e., averages over local time and longitude) in the MLT, our results show that there is a sharp reversal in the correlation near 80 km altitude, above which the ozone mixing ratio and temperature are mostly positively correlated, while they are mostly negatively correlated below 80 km. This is consistent with the view that above -80 km, effects due to dynamics are more important compared to photochemistry. For diurnal variations, both the ozone and temperature show phase progressions in local time, as a function of altitude and latitude. For temperature, the phase progression is as expected, as they represent migrating tides. For day time ozone, we also find regular phase progression in local time over the whole altitude range of our analysis, 25 to 105 km, at least for low latitudes. This was not previously known, although phase progressions had been noted by us and by others at lower altitudes. For diurnal

Homogenising time series: beliefs, dogmas and facts

Science.gov (United States)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Science.gov (United States)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Multivariate Time Series Decomposition into Oscillation Components.

Science.gov (United States)

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Forecasting Enrollments with Fuzzy Time Series.

Science.gov (United States)

Song, Qiang; Chissom, Brad S.

The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

New Directions: Ozone-initiated reaction products indoors may be more harmful than ozone itself

Science.gov (United States)

Weschler, Charles J.

2004-10-01

Epidemiological studies have found associations between ozone concentrations measured at outdoor monitoring stations and certain adverse health outcomes. As a recent example, Gent et al. (2003, Journal of the American Medical Association 290, 1859-1867) have observed an association between ozone levels and respiratory symptoms as well as the use of maintenance medication by 271 asthmatic children living in Connecticut and the Springfield area of Massachusetts. In another example, Gilliland et al. (2001, Epidemiology 12, 43-54) detected an association between short-term increases in ozone levels and increased absences among 4th grade students from 12 southern California communities during the period from January to June 1996. Although children may spend a significant amount of time outdoors, especially during periods when ozone levels are elevated, they spend a much larger fraction of their time indoors. I hypothesize that exposure to the products of ozone-initiated indoor chemistry is more directly responsible for the health effects observed in the cited epidemiological studies than is exposure to outdoor ozone itself.

Experimental study of ozone synthesis

International Nuclear Information System (INIS)

Garamoon, A A; Elakshar, F F; Nossair, A M; Kotp, E F

2002-01-01

A silent discharge ozonizer has been constructed with a design that enables the study of ozone concentration behaviour as a function of different parameters when oxygen used as a working gas. The behaviour of ozone concentration as a function of discharge current density has four characteristic regions. The concentration is enhanced by more than threefold whenever gas pressure is reduced by a factor of two. The flow rate of the working gas is a more effective parameter on ozone concentration than the gas pressure. When the flow rate is kept constant, and the pressure is decreased by 100%, the ozone concentration increases by only 10%. On the other hand, when the flow rate is decreased by 13%, the ozone concentration increases by 200%, whenever the gas pressure is kept constant. The concentration is nearly doubled when the gap space is increased by four times under the same conditions. The length of the discharge region, the thickness and the dielectric constant of the insulating materials are found to have a considerable effect on the generated ozone concentration. Also, the ozone concentration is ten times less when air is used instead of oxygen as a working gas. A maximum efficiency of 185 g/kWh, is obtained for the present system

Radiative effects of ozone on the climate of a Snowball Earth

Directory of Open Access Journals (Sweden)

J. Yang

2012-12-01

Full Text Available Some geochemical and geological evidence has been interpreted to suggest that the concentration of atmospheric oxygen was only 1–10 % of the present level in the time interval from 750 to 580 million years ago when several nearly global glaciations or Snowball Earth events occurred. This low concentration of oxygen would have been accompanied by a lower ozone concentration than exists at present. Since ozone is a greenhouse gas, this change in ozone concentration would alter surface temperature, and thereby could have an important influence on the climate of the Snowball Earth. Previous works that have focused either on initiation or deglaciation of the proposed Snowball Earth has not taken the radiative effects of ozone changes into account. We address this issue herein by performing a series of simulations using an atmospheric general circulation model with various ozone concentrations.

Our simulation results demonstrate that, as ozone concentration is uniformly reduced from 100 % to 50 %, surface temperature decreases by approximately 0.8 K at the Equator, with the largest decreases located in the middle latitudes reaching as high as 2.5 K. When ozone concentration is reduced and its vertical and horizontal distribution is simultaneously modulated, surface temperature decreases by 0.4–1.0 K at the Equator and by 4–7 K in polar regions. These results here have uncertainties, depending on model parameterizations of cloud, surface snow albedo, and relevant feedback processes, while they are qualitatively consistent with radiative-convective model results that do not involve such parameterizations and feedbacks. These results suggest that ozone variations could have had a moderate impact on the climate during the Neoproterozoic glaciations.

National Plan for Stratospheric Ozone Monitoring and Early Detection of Change, 1981-1986

International Nuclear Information System (INIS)

1982-02-01

A transition from reliance on a ground-based, geographically-biased ozone observing network operated by cooperating nations to a combined satellite and ground-based monitoring program that will provide global coverage of the vertical distribution of stratospheric ozone, as well as total ozone overburden is discussed. The strategy, instrumentation, and monitoring products to be prepared during this transition period are also discussed. Global atmospheric monitoring for protection of the ultraviolet shielding properties of atmospheric ozone is considered. The operational satellite ozone vertical profile monitoring system to be flown on the NOAA Tiros N operational satellite series to carry on ozone measurements initiated on the NASA R D satellites is also considered

Temporally resolved ozone distribution of a time modulated RF atmospheric pressure argon plasma jet: flow, chemical reaction, and transient vortex

International Nuclear Information System (INIS)

Zhang, S; Sobota, A; Van Veldhuizen, E M; Bruggeman, P J

2015-01-01

The ozone density distribution in the effluent of a time modulated RF atmospheric pressure plasma jet (APPJ) is investigated by time and spatially resolved by UV absorption spectroscopy. The plasma jet is operated with an averaged dissipated power of 6.5 W and gas flow rate 2 slm argon  +2% O 2 . The modulation frequency of the RF power is 50 Hz with a duty cycle of 50%. To investigate the production and destruction mechanism of ozone in the plasma effluent, the atomic oxygen and gas temperature is also obtained by TALIF and Rayleigh scattering, respectively. A temporal increase in ozone density is observed close to the quartz tube exit when the plasma is switched off due to the decrease in O density and gas temperature. Ozone absorption at different axial positions indicates that the ozone distribution is dominated by the convection induced by the gas flow and allows estimating the on-axis local gas velocity in the jet effluent. Transient vortex structures occurring during the switch on and off of the RF power also significantly affect the ozone density in the far effluent. (paper)

Forecasting Cryptocurrencies Financial Time Series

DEFF Research Database (Denmark)

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...

Forecasting Cryptocurrencies Financial Time Series

OpenAIRE

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...

Reconstruction and analysis of erythemal UV radiation time series from Hradec Králové (Czech Republic) over the past 50 years

Science.gov (United States)

Čížková, Klára; Láska, Kamil; Metelka, Ladislav; Staněk, Martin

2018-02-01

This paper evaluates the variability of erythemal ultraviolet (EUV) radiation from Hradec Králové (Czech Republic) in the period 1964-2013. The EUV radiation time series was reconstructed using a radiative transfer model and additional empirical relationships, with the final root mean square error of 9.9 %. The reconstructed time series documented the increase in EUV radiation doses in the 1980s and the 1990s (up to 15 % per decade), which was linked to the steep decline in total ozone (10 % per decade). The changes in cloud cover were the major factor affecting the EUV radiation doses especially in the 1960s, 1970s, and at the beginning of the new millennium. The mean annual EUV radiation doses in the decade 2004-2013 declined by 5 %. The factors affecting the EUV radiation doses differed also according to the chosen integration period (daily, monthly, and annually): solar zenith angle was the most important for daily doses, cloud cover, and surface UV albedo for their monthly means, and the annual means of EUV radiation doses were most influenced by total ozone column. The number of days with very high EUV radiation doses increased by 22 % per decade, the increase was statistically significant in all seasons except autumn. The occurrence of the days with very high EUV doses was influenced mostly by low total ozone column (82 % of days), clear-sky or partly cloudy conditions (74 % of days) and by increased surface albedo (19 % of days). The principal component analysis documented that the occurrence of days with very high EUV radiation doses was much affected by the positive phase of North Atlantic Oscillation with an Azores High promontory reaching over central Europe. In the stratosphere, a strong Arctic circumpolar vortex and the meridional inflow of ozone-poor air from the southwest were favorable for the occurrence of days with very high EUV radiation doses. This is the first analysis of the relationship between the high EUV radiation doses and macroscale

High ozone levels in the northeast of Portugal: Analysis and characterization

Science.gov (United States)

Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A. I.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.

2010-03-01

Each summer period extremely high ozone levels are registered at the rural background station of Lamas d'Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes at this site. Synoptic patterns anomalies and back trajectories cluster analysis were performed, for the period between 2004 and 2007, considering 76 days when ozone maximum hourly concentrations were above 200 μg m -3. The obtained atmospheric anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. A strong wind flow pattern from NE is observable in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal during summer. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, are responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants is the main contributor to the ozone levels registered at Lamas d'Olo. This is also highlighted by the correlation of the ozone time-series with the meteorological parameters analysed in the frequency domain.

Ozone time scale decomposition and trend assessment from surface observations in National Parks of the United States

Science.gov (United States)

Mao, H.; McGlynn, D. F.; Wu, Z.; Sive, B. C.

2017-12-01

A time scale decomposition technique, the Ensemble Empirical Mode Decomposition (EEMD), has been employed to decompose the time scales in long-term ozone measurement data at 24 US National Park Service sites. Time scales of interest include the annual cycle, variability by large scale climate oscillations, and the long-term trend. The implementation of policy regulations was found to have had a greater effect on sites nearest to urban regions. Ozone daily mean values increased until around the late 1990s followed by decreasing trends during the ensuing decades for sites in the East, southern California, and northwestern Washington. Sites in the Midwest did not experience a reversal of trends from positive to negative until the mid- to late 2000s. The magnitude of the annual amplitude decreased for nine sites and increased for three sites. Stronger decreases in the annual amplitude occurred in the East, with more sites in the East experiencing decreases in annual amplitude than in the West. The date of annual ozone peaks and minimums has changed for 12 sites in total, but those with a shift in peak date did not necessarily have a shift in the trough date. There appeared to be a link between peak dates occurring earlier and a decrease in the annual amplitude. This is likely related to a decrease in ozone titration due to NOx emission reductions. Furthermore, it was found that the shift in the Pacific Decadal Oscillation (PDO) regime from positive to negative in 1998-1999 resulting in an increase in occurrences of La Niña-like conditions had the effect of directing more polluted air masses from East Asia to higher latitudes over North America. This change in PDO regime was likely one main factor causing the increase in ozone concentrations on all time scales at an Alaskan site DENA-HQ.

Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

Time Series Analysis Forecasting and Control

CERN Document Server

Box, George E P; Reinsel, Gregory C

2011-01-01

A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl

Costationarity of Locally Stationary Time Series Using costat

OpenAIRE

Cardinali, Alessandro; Nason, Guy P.

2013-01-01

This article describes the R package costat. This package enables a user to (i) perform a test for time series stationarity; (ii) compute and plot time-localized autocovariances, and (iii) to determine and explore any costationary relationship between two locally stationary time series. Two locally stationary time series are said to be costationary if there exists two time-varying combination functions such that the linear combination of the two series with the functions produces another time...

Detecting nonlinear structure in time series

International Nuclear Information System (INIS)

Theiler, J.

1991-01-01

We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a time series. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of ''surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against the null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs

Ozone Transport Aloft Drives Surface Ozone Maxima Across the Mojave Desert

Science.gov (United States)

VanCuren, R. A.

2014-12-01

A persistent layer of polluted air in the lower free troposphere over the Mojave Desert (California and Nevada) drives spring and summer surface ozone maxima as deep afternoon mixing delivers ozone and ozone precursors to surface measurement sites 200 km or more downwind of the mountains that separate the deserts from the heavily populated coastal areas of California. Pollutants in this elevated layer derive from California source regions (the Los Angeles megacity region and the intensive agricultural region of the San Joaquin Valley), and from long-range transport from Asia. Recognition of this poorly studied persistent layer explains and expands the significance of previously published reports of ozone and other pollutants observed in and over the Mojave Desert, resolves an apparent paradox in the timing of ozone peaks due to transport from the upwind basins, and provides a new perspective on the long-range downwind impacts of megacity pollution plumes.

Introduction to time series and forecasting

CERN Document Server

Brockwell, Peter J

2016-01-01

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space mod...

Evidence for midwinter chemical ozone destruction over Antartica

Energy Technology Data Exchange (ETDEWEB)

Voemel, H. [Univ. of Colorado, Boulder, CO (United States); Hoffmann, D.J.; Oltmans, S.J.; Harris, J.M. [NOAA Climate Monitoring and Diagnostics Laboratory, Boulder, CO (United States)

1995-09-01

Two ozone profiles on June 15 and June 19, obtained over McMurdo, Antartica, showed a strong depletion in stratospheric ozone, and a simultaneous profile of water vapor on June 19 showed the first clear signs of dehydration. The observation of Polar Stratospheric Clouds (PSCs) beginning with the first sounding showing ozone depletion, the indication of rehydration layers, which could be a sign for recent dehydration, and trajectory calculations indicate that the observed low ozone was not the result of transport from lower latitudes. during this time the vortex was strongly distorted, transporting PSC processed air well into sunlit latitudes where photochemical ozone destruction may have occurred. The correlation of ozone depletion and dehydration indicates that water ice PSCs provided the dominant surface for chlorine activation. An analysis of the time when the observed air masses could have formed type II PSCs for the first time limits the time scale for the observed ozone destruction to about 4 days.

Total Ozone Data From a European Network 1951-1957

Science.gov (United States)

Brönnimann, S.; Brönnimann, S.; Farmer, S.

2001-12-01

Soon after its foundation in 1948, the International Ozone Commission (IOC) established a total ozone network in Europe, together with the Gassiot Committee of the Royal Socitey, UNESCO, the London Meteorological Office and national services. The network was built-up in 1950 with Dobson spectrophotometers equipped with photomultipliers, which were calibrated in Oxford before shipping to the stations. In 1957, some of the stations became part of the network of the IGY, and these data can be found today at the WOUDC. The earlier data were compiled and archived in Oxford by the secretary of the IOC, Charles Normand, but have never been published and only rarely appeared in the scientific literature [Normand, QJRMS 67 (1951) 474 and QJRMS 69 (1953) 39]. The copies of the data sheets stored at UK Met Office [MO/19/3/9 Part I] comprise daily values from the following stations/time periods: Aarhus (DK, 6/52-12/59, Dobson #41), Aldergrove (UK, 6/52-4/57, #35?), Arosa (CH, 6/52-12/58 #15), Cagliari/Elmas (IT, 12/54-5/59, #48), Camborne (UK, 1/52-12/59, #32), Eskdalemuir (UK, 9/57-12/59, #35), Hemsby (UK, 6/52-9/55), Lerwick (UK, 6/52-12/59, #7), Magny les Hameaux (FR, 1/55-9/57, #49?), Messina (IT, 7/54-6/58, #46), Oxford (UK, 6/52-12/59, #1), Paris/Montsouris (FR, 10/57-8/58, #49), Reykjavik (IS, 6/52-10/59, #50), Rome/Vigna di Valle (IT, 4/54-12/59 #47), Santa Maria/Azores (ES, 2/53-7/56, #13), Spitzbergen (NO, 11/50-7/58, #8), Tromsoe (NO, 6/52-5/59, #14), Uccle (BE, 6/52-12/58, #40), and Uppsala (SE, 6/52-12/58, #30). These data could be useful to supplement the currently available total ozone measurement series. Together with existing meteorological data, they enable us to study the relation between atmospheric circulation and total ozone in a chemically largely unperturbed time period. The daily values from 1951 to 1957 have now been digitized. Using appropriate statistical methods, the quality of each series will be addressed. The data will be homogenized and re

Balance of the tropospheric ozone and its relation to stratospheric intrusions indicated by cosmogenic radionuclides. Technical progress report, November 1, 1980-June 30, 1981

International Nuclear Information System (INIS)

Reiter, R.; Kanter, H.J.; Sladkovic, R.; Jaeger, H.; Munzert, K.H.

1981-06-01

The balance of the tropospheric ozone is studied with regard to sources and sinks. The influx of stratospheric ozone through stratospheric intrusions and photochemical production under pure air conditions is discussed. The 4-year measuring series (1977-1980) of the ozone concentration measured at 3 different levels are evaluated, the influence of meteorological parameters is examined. The time variation of the ozone layer between 1000 and 3000 m ASL is investigated as a function of different ozone sources. First results show that stratospheric ozone arriving at the troposphere penetrates only in a few rare cases to the ground layer below 1500 m ASL. Most of the time, the variation of ozone concentration in this layer is determined by photochemical processes which are, in turn, controlled by meteorological parameters. The upper boundary of the photochemically active layer is found at about 500 m above ground. Variability of the concentration of stratospheric aerosol and its optical properties after the volcanic eruptions in the year 1980 are discussed on the basis on lidar backscattering measurements

Long-term Measurements of Summer-time Ozone at the Walnut Grove Tower - Understanding Trends in the Boundary Layer

Science.gov (United States)

Mahmud, A.; Di, P.; Mims, D.; Avise, J.; DaMassa, J.; Kaduwela, A. P.

2015-12-01

low wind condition) and positively correlated with ambient temperature (i.e. ozone was high under high temperature condition) during ~40% and ~50% of the time, respectively. A modeling exercise for Jun - Sep of 2012 shows that CMAQ captures the observed evolution and vertical mixing of ozone throughout the day quite well in the boundary layer.

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.

Co-Mitigation of Ozone and PM2.5 Pollution over the Beijing-Tianjin-Hebei Region

Science.gov (United States)

Liu, J.; Xiang, S.; Yi, K.; Tao, W.

2017-12-01

With the rapid industrialization and urbanization, emissions of air pollutants in China were increasing rapidly during the past few decades, causing severe particulate matter and ozone pollution in many megacities. Facing these knotty environmental problems, China has released a series of pollution control policies to mitigate air pollution emissions and optimize energy supplement structure. Consequently, fine particulate matters (PM2.5) decrease recently. However, the concentrations of ambient ozone have been increasing, especially during summer time and over megacities. In this study, we focus on the opposite trends of ozone and PM2.5 over the Beijing-Tianjin-Hebei region. We use the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) to simulate and analyze the best emission reduction strategies, and adopt the Empirical Kinetics Modeling Approach (EKMA) to depict the influences of mitigating NOx and VOCs. We also incorporate the abatement costs for NOx and VOCs in our analysis to explore the most cost-effective mitigation strategies for both ozone and PM2.5.

Frontiers in Time Series and Financial Econometrics

OpenAIRE

Ling, S.; McAleer, M.J.; Tong, H.

2015-01-01

__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contrib...

Error analysis of Dobson spectrophotometer measurements of the total ozone content

Science.gov (United States)

Holland, A. C.; Thomas, R. W. L.

1975-01-01

A study of techniques for measuring atmospheric ozone is reported. This study represents the second phase of a program designed to improve techniques for the measurement of atmospheric ozone. This phase of the program studied the sensitivity of Dobson direct sun measurements and the ozone amounts inferred from those measurements to variation in the atmospheric temperature profile. The study used the plane - parallel Monte-Carlo model developed and tested under the initial phase of this program, and a series of standard model atmospheres.

Scale-dependent intrinsic entropies of complex time series.

Science.gov (United States)

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...

An Energy-Based Similarity Measure for Time Series

Directory of Open Access Journals (Sweden)

Pierre Brunagel

2007-11-01

Full Text Available A new similarity measure, called SimilB, for time series analysis, based on the cross-ΨB-energy operator (2004, is introduced. ΨB is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED or the Pearson correlation coefficient (CC, SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of ΨB are presented. Particularly, we show that ΨB as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.

Long-memory processes in ozone and temperature variations at the region 60° S–60° N

Directory of Open Access Journals (Sweden)

C. Varotsos

2006-01-01

Full Text Available Global column ozone and tropospheric temperature observations made by ground-based (1964–2004 and satellite-borne (1978–2004 instrumentation are analyzed. Ozone and temperature fluctuations in small time-intervals are found to be positively correlated to those in larger time-intervals in a power-law fashion. For temperature, the exponent of this dependence is larger in the mid-latitudes than in the tropics at long time scales, while for ozone, the exponent is larger in tropics than in the mid-latitudes. In general, greater persistence could be a result of either stronger positive feedbacks or larger inertia. Therefore, the increased slope of the power distribution of temperature in mid-latitudes at long time scales compared to the slope in the tropics could be connected to the poleward increase in climate sensitivity predicted by the global climate models. The detrended fluctuation analysis of model and observed time series provides a helpful tool for visualizing errors in the treatment of long-range correlations, whose correct modeling would greatly enhance confidence in long-term climate and atmospheric chemistry modeling.

Detecting chaos in irregularly sampled time series.

Science.gov (United States)

Kulp, C W

2013-09-01

Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a time series' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other time series characterization algorithms, requires that the time series be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled time series. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled time series. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.

Building Chaotic Model From Incomplete Time Series

Science.gov (United States)

Siek, Michael; Solomatine, Dimitri

2010-05-01

This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual

The interaction of ozone and nitrogen dioxide in the stratosphere of East Antarctica

Science.gov (United States)

Bruchkouski, Ilya; Krasouski, Aliaksandr; Dziomin, Victar; Svetashev, Alexander

2016-04-01

calculated from the observed time series, demonstrating that changes in nitrogen dioxide content cause subsequent changes in the ozone layer. Attempt to explain this phenomenon as influence upper atmosphere on ozone layer is under discussed.

Multivariate Time Series Search

Data.gov (United States)

National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

Analysing Stable Time Series

National Research Council Canada - National Science Library

Adler, Robert

1997-01-01

We describe how to take a stable, ARMA, time series through the various stages of model identification, parameter estimation, and diagnostic checking, and accompany the discussion with a goodly number...

Neural Network Models for Time Series Forecasts

OpenAIRE

Tim Hill; Marcus O'Connor; William Remus

1996-01-01

Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...

Time Series Observations in the North Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Shenoy, D.M.; Naik, H.; Kurian, S.; Naqvi, S.W.A.; Khare, N.

Ocean and the ongoing time series study (Candolim Time Series; CaTS) off Goa. In addition, this article also focuses on the new time series initiative in the Arabian Sea and the Bay of Bengal under Sustained Indian Ocean Biogeochemistry and Ecosystem...

Geometric noise reduction for multivariate time series.

Science.gov (United States)

Mera, M Eugenia; Morán, Manuel

2006-03-01

We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.

BRITS: Bidirectional Recurrent Imputation for Time Series

OpenAIRE

Cao, Wei; Wang, Dong; Li, Jian; Zhou, Hao; Li, Lei; Li, Yitan

2018-01-01

Time series are widely used as signals in many classification/regression tasks. It is ubiquitous that time series contains many missing values. Given multiple correlated time series data, how to fill in missing values and to predict their class labels? Existing imputation methods often impose strong assumptions of the underlying data generating process, such as linear dynamics in the state space. In this paper, we propose BRITS, a novel method based on recurrent neural networks for missing va...

Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Studies on time series applications in environmental sciences

CERN Document Server

Bărbulescu, Alina

2016-01-01

Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code. .

Global Population Density Grid Time Series Estimates

Data.gov (United States)

National Aeronautics and Space Administration — Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's...

Prediction and Geometry of Chaotic Time Series

National Research Council Canada - National Science Library

Leonardi, Mary

1997-01-01

This thesis examines the topic of chaotic time series. An overview of chaos, dynamical systems, and traditional approaches to time series analysis is provided, followed by an examination of state space reconstruction...

Tropical Tropospheric Ozone from SHADOZ (Southern Hemisphere ADditional Ozonesondes) Network: A Project for Satellite Research, Process Studies, Education

Science.gov (United States)

Thompson, Anne M.; Witte, Jacquelyn C.; Oltmans, Samuel J.; Schmidlin, Francis J.; Coetzee, G. J. R.; Hoegger, Bruno; Kirchhoff, V. W. J. H.; Ogawa, Toshihiro; Kawakami, Shuji; Posny, Francoise

2002-01-01

The first climatological overview of total, stratospheric and tropospheric ozone in the southern hemisphere tropical and subtropics is based on ozone sounding data from 10 sites comprising the Southern Hemisphere Additional OZonesondes (SHADOZ) network. The period covered is 1998-2000. Observations were made over: Ascension Island; Nairobi, Kenya; Irene, South Africa; Reunion Island; Watukosek, Java; Fiji; Tahiti; American Samoa; San Cristobal, Galapagos; Natal, Brazil. Campaign data were collected on a trans-Atlantic oceanographic cruise and during SAFARI-2000 in Zambia. The ozone data, with simultaneous temperature profiles to approx. 7 hPa and relative humidity to approx. 200 hPa, reside at: . SHADOZ ozone time-series and profiles give a perspective on tropical total, stratospheric and tropospheric ozone. Prominent features are highly variable tropospheric ozone and a zonal wave-one pattern in total (and tropospheric) column ozone. Total, stratospheric and tropospheric column ozone amounts peak between August and November and are lowest between March and May. Tropospheric ozone variability over the Indian and Pacific Ocean displays influences of the Indian Ocean Dipole and convective mixing. Pollution transport from Africa and South America is a seasonal feature. Tropospheric ozone seasonality over the Atlantic Basin shows effects of regional subsidence and recirculation as well as biomass burning. Dynamical and chemical influences appear to be of comparable magnitude though model studies are needed to quantify this.

Changing Conditions in the Arctic: An Analysis of 45 years of Tropospheric Ozone Measurements at Barrow Observatory

Science.gov (United States)

McClure-Begley, A.; Petropavlovskikh, I. V.; Crepinsek, S.; Jefferson, A.; Emmons, L. K.; Oltmans, S. J.

2017-12-01

In order to understand the impact of climate on local bio-systems, understanding the changes to the atmospheric composition and processes in the Arctic boundary layer and free troposphere is imperative. In the Arctic, many conditions influence tropospheric ozone variability such as: seasonal halogen caused depletion events, long range transport of pollutants from mid-northern latitudes, compounds released from wildfires, and different meteorological conditions. The Barrow station in Utqiagvik, Alaska has collected continuous measurements of ground-level ozone since 1973. This unique long-term time series allows for analysis of the influence of a rapidly changing climate on ozone conditions in this region. Specifically, this study analyzes the frequency of enhanced ozone episodes over time and provides in depth analysis of periods of positive deviations from the expected conditions. To discern the contribution of different pollutant sources to observed ozone variability, co-located measurements of aerosols, carbon monoxide, and meteorological conditions are used. In addition, the NCAR Mozart-4/MOPITT Chemical Forecast model and NOAA Hysplit back-trajectory analysis provide information on transport patterns to the Arctic and confirmation of the emission sources that influenced the observed conditions. These anthropogenic influences on ozone variability in and below the boundary layer are essential for developing an understanding of the interaction of climate change and the bio-systems in the Arctic.

Sensor-Generated Time Series Events: A Definition Language

Science.gov (United States)

Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

2012-01-01

There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

A two-dimensional model study of past trends in global ozone

International Nuclear Information System (INIS)

Wuebbles, D.J.; Kinnison, D.E.

1988-08-01

Emissions and atmospheric concentrations of several trace gases important to atmospheric chemistry are known to have increased substantially over recent decades. Solar flux variations and the atmospheric nuclear test series are also likely to have affected stratospheric ozone. In this study, the LLNL two-dimensional chemical-radiative-transport model of the troposphere and stratosphere has been applied to an analysis of the effects that these natural and anthropogenic influences may have had on global ozone concentrations over the last three decades. In general, model determined species distributions and the derived ozone trends agree well with published analyses of land-based and satellite-based observations. Also, the total ozone and ozone distribution trends derived from CFC and other trace gas effects have a different response with latitude than the derived trends from solar flux variations, thus providing a ''signature'' for anthropogenic effects on ozone. 24 refs., 5 figs

Correlation and multifractality in climatological time series

International Nuclear Information System (INIS)

Pedron, I T

2010-01-01

Climate can be described by statistical analysis of mean values of atmospheric variables over a period. It is possible to detect correlations in climatological time series and to classify its behavior. In this work the Hurst exponent, which can characterize correlation and persistence in time series, is obtained by using the Detrended Fluctuation Analysis (DFA) method. Data series of temperature, precipitation, humidity, solar radiation, wind speed, maximum squall, atmospheric pressure and randomic series are studied. Furthermore, the multifractality of such series is analyzed applying the Multifractal Detrended Fluctuation Analysis (MF-DFA) method. The results indicate presence of correlation (persistent character) in all climatological series and multifractality as well. A larger set of data, and longer, could provide better results indicating the universality of the exponents.

Time Series Forecasting with Missing Values

Directory of Open Access Journals (Sweden)

Shin-Fu Wu

2015-11-01

Full Text Available Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM. We employ the input patterns with the temporal information which is defined as local time index (LTI. Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.

Reconstruction of ensembles of coupled time-delay systems from time series.

Science.gov (United States)

Sysoev, I V; Prokhorov, M D; Ponomarenko, V I; Bezruchko, B P

2014-06-01

We propose a method to recover from time series the parameters of coupled time-delay systems and the architecture of couplings between them. The method is based on a reconstruction of model delay-differential equations and estimation of statistical significance of couplings. It can be applied to networks composed of nonidentical nodes with an arbitrary number of unidirectional and bidirectional couplings. We test our method on chaotic and periodic time series produced by model equations of ensembles of diffusively coupled time-delay systems in the presence of noise, and apply it to experimental time series obtained from electronic oscillators with delayed feedback coupled by resistors.

The analysis of time series: an introduction

National Research Council Canada - National Science Library

Chatfield, Christopher

1989-01-01

.... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...

Nitrous Oxides Ozone Destructiveness Under Different Climate Scenarios

Science.gov (United States)

Kanter, David R.; McDermid, Sonali P.

2016-01-01

Nitrous oxide (N2O) is an important greenhouse gas and ozone depleting substance as well as a key component of the nitrogen cascade. While emissions scenarios indicating the range of N2O's potential future contributions to radiative forcing are widely available, the impact of these emissions scenarios on future stratospheric ozone depletion is less clear. This is because N2O's ozone destructiveness is partially dependent on tropospheric warming, which affects ozone depletion rates in the stratosphere. Consequently, in order to understand the possible range of stratospheric ozone depletion that N2O could cause over the 21st century, it is important to decouple the greenhouse gas emissions scenarios and compare different emissions trajectories for individual substances (e.g. business-as-usual carbon dioxide (CO2) emissions versus low emissions of N2O). This study is the first to follow such an approach, running a series of experiments using the NASA Goddard Institute for Space Sciences ModelE2 atmospheric sub-model. We anticipate our results to show that stratospheric ozone depletion will be highest in a scenario where CO2 emissions reductions are prioritized over N2O reductions, as this would constrain ozone recovery while doing little to limit stratospheric NOx levels (the breakdown product of N2O that destroys stratospheric ozone). This could not only delay the recovery of the stratospheric ozone layer, but might also prevent a return to pre-1980 global average ozone concentrations, a key goal of the international ozone regime. Accordingly, we think this will highlight the importance of reducing emissions of all major greenhouse gas emissions, including N2O, and not just a singular policy focus on CO2.

Time series modeling in traffic safety research.

Science.gov (United States)

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

Seasonal Changes in Tropospheric Ozone Concentrations over South Korea and Its Link to Ozone Precursors

Science.gov (United States)

Jung, H. C.; Moon, B. K.; Wie, J.

2017-12-01

Concentration of tropospheric ozone over South Korea has steadily been on the rise in the last decades, mainly due to rapid industrializing and urbanizing in the Eastern Asia. To identify the characteristics of tropospheric ozone in South Korea, we fitted a sine function to the surface ozone concentration data from 2005 to 2014. Based on fitted sine curves, we analyzed the shifts in the dates on which ozone concentration reached its peak in the calendar year. Ozone monitoring sites can be classified into type types: where the highest annual ozone concentration kept occurring sooner (Esites) and those that kept occurring later (Lsites). The seasonal analysis shows that the surface ozone had increased more rapidly in Esites than in Lsites in the past decade during springtime and vice-versa during summertime. We tried to find the reason for the different seasonal trends with the relationship between ozone and ozone precursors. As a result, it was found that the changes in the ground-level ozone concentration in the spring and summer times are considerably influenced by changes in nitrogen dioxide concentration, and this is closely linked to the destruction (production) process of ozone by nitrogen dioxide in spring (summer). The link between tropospheric ozone and nitrogen dioxide discussed in this study will have to be thoroughly examined through climate-chemistry modeling in the future. Acknowledgements This research was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program."

Time series prediction: statistical and neural techniques

Science.gov (United States)

Zahirniak, Daniel R.; DeSimio, Martin P.

1996-03-01

In this paper we compare the performance of nonlinear neural network techniques to those of linear filtering techniques in the prediction of time series. Specifically, we compare the results of using the nonlinear systems, known as multilayer perceptron and radial basis function neural networks, with the results obtained using the conventional linear Wiener filter, Kalman filter and Widrow-Hoff adaptive filter in predicting future values of stationary and non- stationary time series. Our results indicate the performance of each type of system is heavily dependent upon the form of the time series being predicted and the size of the system used. In particular, the linear filters perform adequately for linear or near linear processes while the nonlinear systems perform better for nonlinear processes. Since the linear systems take much less time to be developed, they should be tried prior to using the nonlinear systems when the linearity properties of the time series process are unknown.

Effectiveness of Multivariate Time Series Classification Using Shapelets

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

Time-series-analysis techniques applied to nuclear-material accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.; Downing, D.J.

1982-05-01

This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother

Clinical and epidemiological rounds. Time series

Directory of Open Access Journals (Sweden)

León-Álvarez, Alba Luz

2016-07-01

Full Text Available Analysis of time series is a technique that implicates the study of individuals or groups observed in successive moments in time. This type of analysis allows the study of potential causal relationships between different variables that change over time and relate to each other. It is the most important technique to make inferences about the future, predicting, on the basis or what has happened in the past and it is applied in different disciplines of knowledge. Here we discuss different components of time series, the analysis technique and specific examples in health research.

Effects of ozone-vegetation coupling on surface ozone air quality via biogeochemical and meteorological feedbacks

Science.gov (United States)

Sadiq, Mehliyar; Tai, Amos P. K.; Lombardozzi, Danica; Martin, Maria Val

2017-02-01

Tropospheric ozone is one of the most hazardous air pollutants as it harms both human health and plant productivity. Foliage uptake of ozone via dry deposition damages photosynthesis and causes stomatal closure. These foliage changes could lead to a cascade of biogeochemical and biogeophysical effects that not only modulate the carbon cycle, regional hydrometeorology and climate, but also cause feedbacks onto surface ozone concentration itself. In this study, we implement a semi-empirical parameterization of ozone damage on vegetation in the Community Earth System Model to enable online ozone-vegetation coupling, so that for the first time ecosystem structure and ozone concentration can coevolve in fully coupled land-atmosphere simulations. With ozone-vegetation coupling, present-day surface ozone is simulated to be higher by up to 4-6 ppbv over Europe, North America and China. Reduced dry deposition velocity following ozone damage contributes to ˜ 40-100 % of those increases, constituting a significant positive biogeochemical feedback on ozone air quality. Enhanced biogenic isoprene emission is found to contribute to most of the remaining increases, and is driven mainly by higher vegetation temperature that results from lower transpiration rate. This isoprene-driven pathway represents an indirect, positive meteorological feedback. The reduction in both dry deposition and transpiration is mostly associated with reduced stomatal conductance following ozone damage, whereas the modification of photosynthesis and further changes in ecosystem productivity are found to play a smaller role in contributing to the ozone-vegetation feedbacks. Our results highlight the need to consider two-way ozone-vegetation coupling in Earth system models to derive a more complete understanding and yield more reliable future predictions of ozone air quality.

Ambient Ozone Pollution and Daily Mortality: A Nationwide Study in 272 Chinese Cities.

Science.gov (United States)

Yin, Peng; Chen, Renjie; Wang, Lijun; Meng, Xia; Liu, Cong; Niu, Yue; Lin, Zhijing; Liu, Yunning; Liu, Jiangmei; Qi, Jinlei; You, Jinling; Zhou, Maigeng; Kan, Haidong

2017-11-21

Few large multicity studies have been conducted in developing countries to address the acute health effects of atmospheric ozone pollution. We explored the associations between ozone and daily cause-specific mortality in China. We performed a nationwide time-series analysis in 272 representative Chinese cities between 2013 and 2015. We used distributed lag models and over-dispersed generalized linear models to estimate the cumulative effects of ozone (lagged over 0-3 d) on mortality in each city, and we used hierarchical Bayesian models to combine the city-specific estimates. Regional, seasonal, and demographic heterogeneity were evaluated by meta-regression. At the national-average level, a 10-μg/m 3 increase in 8-h maximum ozone concentration was associated with 0.24% [95% posterior interval (PI): 0.13%, 0.35%], 0.27% (95% PI: 0.10%, 0.44%), 0.60% (95% PI: 0.08%, 1.11%), 0.24% (95% PI: 0.02%, 0.46%), and 0.29% (95% PI: 0.07%, 0.50%) higher daily mortality from all nonaccidental causes, cardiovascular diseases, hypertension, coronary diseases, and stroke, respectively. Associations between ozone and daily mortality due to respiratory and chronic obstructive pulmonary disease specifically were positive but imprecise and nonsignificant. There were no statistically significant differences in associations between ozone and nonaccidental mortality according to region, season, age, sex, or educational attainment. Our findings provide robust evidence of higher nonaccidental and cardiovascular mortality in association with short-term exposure to ambient ozone in China. https://doi.org/10.1289/EHP1849.

Integer-valued time series

NARCIS (Netherlands)

van den Akker, R.

2007-01-01

This thesis adresses statistical problems in econometrics. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis discusses semiparametric estimation in copula models and develops semiparametric lower bounds for a large class of

Robust Forecasting of Non-Stationary Time Series

NARCIS (Netherlands)

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable

Measurement of Ozone Production Sensor

Directory of Open Access Journals (Sweden)

M. Cazorla

2010-05-01

Full Text Available A new ambient air monitor, the Measurement of Ozone Production Sensor (MOPS, measures directly the rate of ozone production in the atmosphere. The sensor consists of two 11.3 L environmental chambers made of UV-transmitting Teflon film, a unit to convert NO₂ to O₃, and a modified ozone monitor. In the sample chamber, flowing ambient air is exposed to the sunlight so that ozone is produced just as it is in the atmosphere. In the second chamber, called the reference chamber, a UV-blocking film over the Teflon film prevents ozone formation but allows other processes to occur as they do in the sample chamber. The air flows that exit the two chambers are sampled by an ozone monitor operating in differential mode so that the difference between the two ozone signals, divided by the exposure time in the chambers, gives the ozone production rate. High-efficiency conversion of NO₂ to O₃ prior to detection in the ozone monitor accounts for differences in the NO_x photostationary state that can occur in the two chambers. The MOPS measures the ozone production rate, but with the addition of NO to the sampled air flow, the MOPS can be used to study the sensitivity of ozone production to NO. Preliminary studies with the MOPS on the campus of the Pennsylvania State University show the potential of this new technique.

Tropospheric ozone seasonal and long-term variability as seen by lidar and surface measurements at the JPL-Table Mountain Facility, California

Directory of Open Access Journals (Sweden)

M. J. Granados-Muñoz

2016-07-01

Full Text Available A combined surface and tropospheric ozone climatology and interannual variability study was performed for the first time using co-located ozone photometer measurements (2013–2015 and tropospheric ozone differential absorption lidar measurements (2000–2015 at the Jet Propulsion Laboratory Table Mountain Facility (TMF; elev. 2285 m, in California. The surface time series were investigated both in terms of seasonal and diurnal variability. The observed surface ozone is typical of high-elevation remote sites, with small amplitude of the seasonal and diurnal cycles, and high ozone values, compared to neighboring lower altitude stations representative of urban boundary layer conditions. The ozone mixing ratio ranges from 45 ppbv in the winter morning hours to 65 ppbv in the spring and summer afternoon hours. At the time of the lidar measurements (early night, the seasonal cycle observed at the surface is similar to that observed by lidar between 3.5 and 9 km. Above 9 km, the local tropopause height variation with time and season impacts significantly the ozone lidar observations. The frequent tropopause folds found in the vicinity of TMF (27 % of the time, mostly in winter and spring produce a dual-peak vertical structure in ozone within the fold layer, characterized by higher-than-average values in the bottom half of the fold (12–14 km, and lower-than-averaged values in the top half of the fold (14–18 km. This structure is consistent with the expected origin of the air parcels within the fold, i.e., mid-latitude stratospheric air folding down below the upper tropospheric sub-tropical air. The influence of the tropopause folds extends down to 5 km, increasing the ozone content in the troposphere. No significant signature of interannual variability could be observed on the 2000–2015 de-seasonalized lidar time series, with only a statistically non-significant positive anomaly during the years 2003–2007. Our trend analysis

PHOTOCHEMICAL AIR POLLUTION IN THE NORTH OF PORTUGAL: A HIGH TROPOSHERIC OZONE EPISODE

Science.gov (United States)

Monteiro, A.; Carvalho, A.; Tchepel, O.; Ferreira, J.; Martins, H.; Miranda, A.; Borrego, C.; Saavedra, S.; Rodríguez, A.; Souto, J. A.

2009-12-01

Very high concentrations of ozone are continuously measured at the monitoring station at Lamas d’Olo, located at the North of Portugal,. A particular high photochemical episode occurred between 11 and 13 of July 2005, registering ozone hourly maximum values above 350 µg.m-3. This ozone-rich episode is investigated in this paper, in order to identify its origin and formation. Besides the analysis of both meteorological and air quality monitoring datasets, a numerical modelling approach, based on MM5-CAMx system, was used to simulate the dispersion and transport (horizontal and vertical) of the photochemical pollutants and its precursors. A cross spectrum analysis of the meteorological and air quality time series was performed, in the frequency domain, to establish the relationships between ozone data measured at Lamas d’Olo with air quality data from neighbourhood stations and meteorological parameters. Results point out different behaviour/contribution between the analysed sites. Moreover, different contributions of the u and v wind component on the ozone concentration fluctuations were found suggesting the presence a mountain breeze circulation and a north synoptic transport. The preliminary modelling results pointed out that the vertical transport of pollutants are responsible for the measured high concentrations, combined with particular meteorological conditions, related to the planetary boundary layer (PBL) development. The pollutants transported and existent at high vertical levels are captured/trapped when the PBL height reaches its daily maximum, and extremely high ozone ground level concentrations are consequently measured.

Characterizing time series via complexity-entropy curves

Science.gov (United States)

Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

Ozone sonde cell current measurements and implications for observations of near-zero ozone concentrations in the tropical upper troposphere

Directory of Open Access Journals (Sweden)

H. Vömel

2010-04-01

Full Text Available Laboratory measurements of the Electrochemical Concentration Cell (ECC ozone sonde cell current using ozone free air as well as defined amounts of ozone reveal that background current measurements during sonde preparation are neither constant as a function of time, nor constant as a function of ozone concentration. Using a background current, measured at a defined timed after exposure to high ozone may often overestimate the real background, leading to artificially low ozone concentrations in the upper tropical troposphere, and may frequently lead to operator dependent uncertainties. Based on these laboratory measurements an improved cell current to partial pressure conversion is proposed, which removes operator dependent variability in the background reading and possible artifacts in this measurement. Data from the Central Equatorial Pacific Experiment (CEPEX have been reprocessed using the improved background treatment based on these laboratory measurements. In the reprocessed data set near-zero ozone events no longer occur. At Samoa, Fiji, Tahiti, and San Cristóbal, nearly all near-zero ozone concentrations occur in soundings with larger background currents. To a large extent, these events are no longer observed in the reprocessed data set using the improved background treatment.

Complex network approach to fractional time series

Energy Technology Data Exchange (ETDEWEB)

Manshour, Pouya [Physics Department, Persian Gulf University, Bushehr 75169 (Iran, Islamic Republic of)

2015-10-15

In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacency matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2008-01-01

An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

Science.gov (United States)

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

Science.gov (United States)

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

The foundations of modern time series analysis

CERN Document Server

Mills, Terence C

2011-01-01

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

Time series clustering in large data sets

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2011-01-01

Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.

Caffeine degradation in water by gamma irradiation, ozonation and ozonation/gamma irradiation

Directory of Open Access Journals (Sweden)

Torun Murat

2014-03-01

Full Text Available Aqueous solutions of caffeine were treated with ozone and gamma irradiation. The amounts of remaining caffeine were determined after solid phase extraction as a function of absorbed dose and ozonation time. In addition to this, some important parameters such as inorganic ions, chemical oxygen demand (COD dissolved oxygen and total acidity changes were followed. Caffeine (50 ppm is found to be completely decomposed at 3.0 kGy and 1.2 kGy doses in the absence of H2O2 and in 1.20 mM H2O2 solutions, respectively. In the case of gamma irradiation after ozonation, 50 ppm caffeine was removed at 0.2 kGy when the solution was ozonized for 100 s at a rate of 10 g O3 h-1 in 400 mL 50 ppm paracetamol solution.

Ozone depletion following future volcanic eruptions

Science.gov (United States)

Eric Klobas, J.; Wilmouth, David M.; Weisenstein, Debra K.; Anderson, James G.; Salawitch, Ross J.

2017-07-01

While explosive volcanic eruptions cause ozone loss in the current atmosphere due to an enhancement in the availability of reactive chlorine following the stratospheric injection of sulfur, future eruptions are expected to increase total column ozone as halogen loading approaches preindustrial levels. The timing of this shift in the impact of major volcanic eruptions on the thickness of the ozone layer is poorly known. Modeling four possible climate futures, we show that scenarios with the smallest increase in greenhouse gas concentrations lead to the greatest risk to ozone from heterogeneous chemical processing following future eruptions. We also show that the presence in the stratosphere of bromine from natural, very short-lived biogenic compounds is critically important for determining whether future eruptions will lead to ozone depletion. If volcanic eruptions inject hydrogen halides into the stratosphere, an effect not considered in current ozone assessments, potentially profound reductions in column ozone would result.

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

Science.gov (United States)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Lag space estimation in time series modelling

DEFF Research Database (Denmark)

Goutte, Cyril

1997-01-01

The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer...

Time-series prediction and applications a machine intelligence approach

CERN Document Server

Konar, Amit

2017-01-01

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...

Ozone and limonene in indoor air: a source of submicron particle exposure.

Science.gov (United States)

Wainman, T; Zhang, J; Weschler, C J; Lioy, P J

2000-12-01

Little information currently exists regarding the occurrence of secondary organic aerosol formation in indoor air. Smog chamber studies have demonstrated that high aerosol yields result from the reaction of ozone with terpenes, both of which commonly occur in indoor air. However, smog chambers are typically static systems, whereas indoor environments are dynamic. We conducted a series of experiments to investigate the potential for secondary aerosol in indoor air as a result of the reaction of ozone with d-limonene, a compound commonly used in air fresheners. A dynamic chamber design was used in which a smaller chamber was nested inside a larger one, with air exchange occurring between the two. The inner chamber was used to represent a model indoor environment and was operated at an air exchange rate below 1 exchange/hr, while the outer chamber was operated at a high air exchange rate of approximately 45 exchanges/hr. Limonene was introduced into the inner chamber either by the evaporation of reagent-grade d-limonene or by inserting a lemon-scented, solid air freshener. A series of ozone injections were made into the inner chamber during the course of each experiment, and an optical particle counter was used to measure the particle concentration. Measurable particle formation and growth occurred almost exclusively in the 0.1-0.2 microm and 0.2-0.3 microm size fractions in all of the experiments. Particle formation in the 0.1-0.2 microm size range occurred as soon as ozone was introduced, but the formation of particles in the 0.2-0.3 microm size range did not occur until at least the second ozone injection occurred. The results of this study show a clear potential for significant particle concentrations to be produced in indoor environments as a result of secondary particle formation via the ozone-limonene reaction. Because people spend the majority of their time indoors, secondary particles formed in indoor environments may make a significant contribution to

A Time Series Forecasting Method

Directory of Open Access Journals (Sweden)

Wang Zhao-Yu

2017-01-01

Full Text Available This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is removed from the cluster it currently belongs to and added to the most similar cluster. During the clustering process, weights are learned for each cluster. Given a series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. To estimate the value at time t + 1, we find the k nearest neighbors of the input pattern and use these k neighbors to decide the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.

Stochastic nature of series of waiting times

Science.gov (United States)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2time distribution. We find that the logarithmic difference of waiting times series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

Efficient Approximate OLAP Querying Over Time Series

DEFF Research Database (Denmark)

Perera, Kasun Baruhupolage Don Kasun Sanjeewa; Hahmann, Martin; Lehner, Wolfgang

2016-01-01

The ongoing trend for data gathering not only produces larger volumes of data, but also increases the variety of recorded data types. Out of these, especially time series, e.g. various sensor readings, have attracted attention in the domains of business intelligence and decision making. As OLAP...... queries play a major role in these domains, it is desirable to also execute them on time series data. While this is not a problem on the conceptual level, it can become a bottleneck with regards to query run-time. In general, processing OLAP queries gets more computationally intensive as the volume...... of data grows. This is a particular problem when querying time series data, which generally contains multiple measures recorded at fine time granularities. Usually, this issue is addressed either by scaling up hardware or by employing workload based query optimization techniques. However, these solutions...

Multi-model assessment of stratospheric ozone return dates and ozone recovery in CCMVal-2 models

Directory of Open Access Journals (Sweden)

V. Eyring

2010-10-01

Full Text Available Projections of stratospheric ozone from a suite of chemistry-climate models (CCMs have been analyzed. In addition to a reference simulation where anthropogenic halogenated ozone depleting substances (ODSs and greenhouse gases (GHGs vary with time, sensitivity simulations with either ODS or GHG concentrations fixed at 1960 levels were performed to disaggregate the drivers of projected ozone changes. These simulations were also used to assess the two distinct milestones of ozone returning to historical values (ozone return dates and ozone no longer being influenced by ODSs (full ozone recovery. The date of ozone returning to historical values does not indicate complete recovery from ODSs in most cases, because GHG-induced changes accelerate or decelerate ozone changes in many regions. In the upper stratosphere where CO₂-induced stratospheric cooling increases ozone, full ozone recovery is projected to not likely have occurred by 2100 even though ozone returns to its 1980 or even 1960 levels well before (~2025 and 2040, respectively. In contrast, in the tropical lower stratosphere ozone decreases continuously from 1960 to 2100 due to projected increases in tropical upwelling, while by around 2040 it is already very likely that full recovery from the effects of ODSs has occurred, although ODS concentrations are still elevated by this date. In the midlatitude lower stratosphere the evolution differs from that in the tropics, and rather than a steady decrease in ozone, first a decrease in ozone is simulated from 1960 to 2000, which is then followed by a steady increase through the 21st century. Ozone in the midlatitude lower stratosphere returns to 1980 levels by ~2045 in the Northern Hemisphere (NH and by ~2055 in the Southern Hemisphere (SH, and full ozone recovery is likely reached by 2100 in both hemispheres. Overall, in all regions except the tropical lower stratosphere, full ozone recovery from ODSs occurs significantly later than the

A Dynamic Fuzzy Cluster Algorithm for Time Series

Directory of Open Access Journals (Sweden)

Min Ji

2013-01-01

clustering time series by introducing the definition of key point and improving FCM algorithm. The proposed algorithm works by determining those time series whose class labels are vague and further partitions them into different clusters over time. The main advantage of this approach compared with other existing algorithms is that the property of some time series belonging to different clusters over time can be partially revealed. Results from simulation-based experiments on geographical data demonstrate the excellent performance and the desired results have been obtained. The proposed algorithm can be applied to solve other clustering problems in data mining.

Ozone concentrations in the Brazilian Amazonia during BASE-A

International Nuclear Information System (INIS)

Setzer, A.W.; Kirchhoff, V.W.J.H.; Pereira, M.C.

1991-01-01

During the Biomass Burning Airborne and Spaceborne Experiment--Amazonia, thermal images of fires were made with the Advanced Very High Resolution Radiometer (AVHRR) on board meteorological NOAA series satellites. The results of ozone measurements made on board the Brazilian Institute for Space Research (INPE) airplane during September of 1989 are presented and analyzed in relation to the temporal and geographical location of fires detected before and during the sampling. Results show that on a synoptic scale, concentrations of ozone rise sharply in regions of more intense burning

50 years of monitoring of the ozone layer in the Czech Republic - results and challenges

Science.gov (United States)

Vanicek, Karel; Skrivankova, Pavla; Metelka, Ladislav; Stanek, Martin

2010-05-01

Long-term observations of total ozone (TOZ) and vertical ozone profiles, the basic parameters of the ozone layer, have been performed at the Solar and Ozone Observatory (SOO) Hradec Kralove and at the Aerological Department (AD) Praha of the Czech Hydrometeorological Institute (CHMI) since 1961 and 1992 respectively. The Dobson and Brewer spectrophotometers regularly calibrated towards the international references and electro-chemical ECC ozone sondes are used for the measurements. The observations contribute to the global GAW and NDACC ozone monitoring systems. Up to now analyses of the data give the basic findings given bellow and documented in the presentation. Some of them have important implication to the international ozone monitoring infrastructure, as well. - The decrease of TOZ by about 5-7 % in the winter-spring months towards the pre ozone-hole period have occurred since the mid eighties. This is in good agreement by the magnitude and time with depletion of the ozone layer due to chemical destruction of ozone in the NH mid-latitudes. - Significant depletion 3-5 % of TOZ has been identified also in the summer season since the early nineties. As this can not be attributed to the man-made chemical processes a change in the UT/LS dynamics over Central Europe is the most probable reason. - Aerological measurements taken at AD show that the summer reduction of TOZ very well coincides with a change of UT/LS temperature that persists for about two decades over the Czech territory. Therefore it has a long-term character that can be regarded as a climate shift in UT/LS and need to be further investigated. - 15 years of unique simultaneous Dobson/Brewer observations of TOZ performed at SOO show systematic seasonal deviations between both data sets that exceed instrumental accuracy of measurements. The differences are mostly caused by different wavelengths and their ozone absorption coefficients used by both instruments. As the Brewer observations are being

A novel weight determination method for time series data aggregation

Science.gov (United States)

Xu, Paiheng; Zhang, Rong; Deng, Yong

2017-09-01

Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.

Foundations of Sequence-to-Sequence Modeling for Time Series

OpenAIRE

Kuznetsov, Vitaly; Mariet, Zelda

2018-01-01

The availability of large amounts of time series data, paired with the performance of deep-learning algorithms on a broad class of problems, has recently led to significant interest in the use of sequence-to-sequence models for time series forecasting. We provide the first theoretical analysis of this time series forecasting framework. We include a comparison of sequence-to-sequence modeling to classical time series models, and as such our theory can serve as a quantitative guide for practiti...

Climate Prediction Center (CPC) Global Precipitation Time Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal...

Climate Prediction Center (CPC) Global Temperature Time Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global temperature time series provides time series charts using station based observations of daily temperature. These charts provide information about the...

MBBR evaluation for oil refinery wastewater treatment, with post-ozonation and BAC, for wastewater reuse.

Science.gov (United States)

Schneider, E E; Cerqueira, A C F P; Dezotti, M

2011-01-01

This work evaluated the performance of a Moving Bed Biofilm Reactor (MBBR) in the treatment of an oil refinery wastewater. Also, it investigated the possibility of reuse of the MBBR effluent, after ozonation in series with a biological activated carbon (BAC) column. The best performance of the MBBR was achieved with a hydraulic retention time (HRT) of 6 hours, employing a bed to bioreactor volume ratio (V(B)/V(R)) of 0.6. COD and N-NH₄(+) MBBR effluent concentrations ranged from 40 to 75 mg L⁻¹ (removal efficiency of 69-89%) and 2 to 6 mg L⁻¹ (removal efficiency of 45-86%), respectively. Ozonation carried out for 15 min with an ozone concentration of 5 mg L⁻¹ was able to improve the treated wastewater biodegradability. The treatment performance of the BAC columns was practically the same for ozonated and non ozonated MBBR effluents. The dissolved organic carbon (DOC) content of the columns of the activated carbon columns (CAG) was in the range of 2.1-3.8 mg L⁻¹, and the corresponding DOC removal efficiencies were comprised between 52 and 75%. The effluent obtained at the end of the proposed treatment presented a quality, which meet the requirements for water reuse in the oil refinery.

Recurrent Neural Network Applications for Astronomical Time Series

Science.gov (United States)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

Ozonation for source treatment of pharmaceuticals in hospital wastewater - ozone lifetime and required ozone dose

DEFF Research Database (Denmark)

Hansen, Kamilla Marie Speht; Spiliotopoulou, Aikaterini; Chhetri, Ravi Kumar

2016-01-01

Ozonation aimed at removing pharmaceuticals was studied in an effluent from an experimental pilot system using staged moving bed biofilm reactor (MBBR) tanks for the optimal biological treatment of wastewater from a medical care unit of Aarhus University Hospital. Dissolved organic carbon (DOC......) and pH in samples varied considerably, and the effect of these two parameters on ozone lifetime and the efficiency of ozone in removing pharmaceuticals were determined. The pH in the effluent varied from 5.0 to 9.0 resulting in approximately a doubling of the required ozone dose at the highest p......H for each pharmaceutical. DOC varied from 6 to 20 mg-DOC/L. The ozone required for removing each pharmaceutical, varied linearly with DOC and thus, ozone doses normalized to DOC (specific ozone dose) agreed between water samples (typically within 15%). At neutral pH the specific ozone dose required...

Combination of ozonation and photocatalysis for pharmaceutical wastewater treatment

Science.gov (United States)

Ratnawati, Enjarlis, Slamet

2017-11-01

The chemical oxygen demand (COD) and phenol removal from pharmaceutical wastewater were investigated using configuration of two circulation batch reactors in a series with ozonation and photocatalytic processes. The ozonation is conducted with O3/granulated activated carbon (O3/GAC), whereas photocatalysis with TiO2 that immobilized on pumice stone (PS-TiO2). The effect of circulation flow rate (10; 12; 15 L/min) and the amount PS-TiO2 (200 g, 250 g, 300 g) were examined. Wastewater of 20 L was circulated pass through the pipe that injected with O3 by the ozone generator, and subsequently flow through two GAC columns, and finally, go through photoreactor that contains photocatalyst PS-TiO2 which equipped with mercury lamp as a photon source. At a time interval, COD and phenol concentration were measured to assess the performance of the process. FESEM imaging confirmed that TiO2 was successfully impregnated on PS, as corroborated by EDX spectra. Meanwhile, degradation process indicated that the combined ozonation and photocatalytic processes (O3/GAC-TiO2) is more efficient compared to the ozonation and photocatalysis alone. For combination process with the circulation flow rate of 10 L/min and 300 g of PS-TiO2,the influent COD of around 1000 ppm are effectively degraded to a final effluent COD of 290 ppm (71% removal) and initial phenol concentration of 4.75 ppm down to 0 ppm for 4 h which this condition fulfill the discharge standards quality. Therefore, this portable prototype reactor is effective that can be used in the pharmaceutical wastewater treatment. For the future, this process condition will be developed for orientation on the industrial applications (portable equipment) since pharmaceutical industries produce wastewater relatively in the small amount.

Transition Icons for Time-Series Visualization and Exploratory Analysis.

Science.gov (United States)

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

Science.gov (United States)

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Variational data assimilation for the optimized ozone initial state and the short-time forecasting

Directory of Open Access Journals (Sweden)

S.-Y. Park

2016-03-01

Full Text Available In this study, we apply the four-dimensional variational (4D-Var data assimilation to optimize initial ozone state and to improve the predictability of air quality. The numerical modeling systems used for simulations of atmospheric condition and chemical formation are the Weather Research and Forecasting (WRF model and the Community Multiscale Air Quality (CMAQ model. The study area covers the capital region of South Korea, where the surface measurement sites are relatively evenly distributed. The 4D-Var code previously developed for the CMAQ model is modified to consider background error in matrix form, and various numerical tests are conducted. The results are evaluated with an idealized covariance function for the appropriateness of the modified codes. The background error is then constructed using the NMC method with long-term modeling results, and the characteristics of the spatial correlation scale related to local circulation are analyzed. The background error is applied in the 4D-Var research, and a surface observational assimilation is conducted to optimize the initial concentration of ozone. The statistical results for the 12 h assimilation periods and the 120 observatory sites show a 49.4 % decrease in the root mean squared error (RMSE, and a 59.9 % increase in the index of agreement (IOA. The temporal variation of spatial distribution of the analysis increments indicates that the optimized initial state of ozone concentration is transported to inland areas by the clockwise-rotating local circulation during the assimilation windows. To investigate the predictability of ozone concentration after the assimilation window, a short-time forecasting is carried out. The ratios of the RMSE (root mean squared error with assimilation versus that without assimilation are 8 and 13 % for the +24 and +12 h, respectively. Such a significant improvement in the forecast accuracy is obtained solely by using the optimized initial state. The potential

Mathematical foundations of time series analysis a concise introduction

CERN Document Server

Beran, Jan

2017-01-01

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.

Time series analysis in the social sciences the fundamentals

CERN Document Server

Shin, Youseop

2017-01-01

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re

Data imputation analysis for Cosmic Rays time series

Science.gov (United States)

Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

The impact of free convection on late morning ozone decreases on an Alpine foreland mountain summit

Directory of Open Access Journals (Sweden)

J.-C. Mayer

2008-10-01

Full Text Available Exceptional patterns in the diurnal course of ozone mixing ratio at a mountain top site (998 m a.s.l. were observed during a field experiment (September 2005. They manifested themselves as strong and sudden decreases of ozone mixing ratio with a subsequent return to previous levels. The evaluation of corresponding long-term time series (2000–2005 revealed that such events occur mainly during summer, and affect the mountain top site on about 18% of the summer days. Combining (a surface layer measurements at mountain summit and at the foot of the mountain, (b in-situ (tethered balloon and remote sensing (SODAR-RASS measurements within the atmospheric boundary layer, the origin of these events of sudden ozone decrease could be attributed to free convection. The free convection was triggered by a rather frequently occurring wind speed minimum around the location of the mountain.

Algorithm for Compressing Time-Series Data

Science.gov (United States)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Modeling of Volatility with Non-linear Time Series Model

OpenAIRE

Kim Song Yon; Kim Mun Chol

2013-01-01

In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.

Layered Ensemble Architecture for Time Series Forecasting.

Science.gov (United States)

Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

2016-01-01

Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

Investigating Dry Deposition of Ozone to Vegetation

Science.gov (United States)

Silva, Sam J.; Heald, Colette L.

2018-01-01

Atmospheric ozone loss through dry deposition to vegetation is a critically important process for both air quality and ecosystem health. The majority of atmospheric chemistry models calculate dry deposition using a resistance-in-series parameterization by Wesely (1989), which is dependent on many environmental variables and lookup table values. The uncertainties contained within this parameterization have not been fully explored, ultimately challenging our ability to understand global scale biosphere-atmosphere interactions. In this work, we evaluate the GEOS-Chem model simulation of ozone dry deposition using a globally distributed suite of observations. We find that simulated daytime deposition velocities generally reproduce the magnitude of observations to within a factor of 1.4. When correctly accounting for differences in land class between the observations and model, these biases improve, most substantially over the grasses and shrubs land class. These biases do not impact the global ozone burden substantially; however, they do lead to local absolute changes of up to 4 ppbv and relative changes of 15% in summer surface concentrations. We use MERRA meteorology from 1979 to 2008 to assess that the interannual variability in simulated annual mean ozone dry deposition due to model input meteorology is small (generally less than 5% over vegetated surfaces). Sensitivity experiments indicate that the simulation is most sensitive to the stomatal and ground surface resistances, as well as leaf area index. To improve ozone dry deposition models, more measurements are necessary over rainforests and various crop types, alongside constraints on individual depositional pathways and other in-canopy ozone loss processes.

Global long-term ozone trends derived from different observed and modelled data sets

Science.gov (United States)

Coldewey-Egbers, M.; Loyola, D.; Zimmer, W.; van Roozendael, M.; Lerot, C.; Dameris, M.; Garny, H.; Braesicke, P.; Koukouli, M.; Balis, D.

2012-04-01

The long-term behaviour of stratospheric ozone amounts during the past three decades is investigated on a global scale using different observed and modelled data sets. Three European satellite sensors GOME/ERS-2, SCIAMACHY/ENVISAT, and GOME-2/METOP are combined and a merged global monthly mean total ozone product has been prepared using an inter-satellite calibration approach. The data set covers the 16-years period from June 1995 to June 2011 and it exhibits an excellent long-term stability, which is required for such trend studies. A multiple linear least-squares regression algorithm using different explanatory variables is applied to the time series and statistically significant positive trends are detected in the northern mid latitudes and subtropics. Global trends are also estimated using a second satellite-based Merged Ozone Data set (MOD) provided by NASA. For few selected geographical regions ozone trends are additionally calculated using well-maintained measurements of individual Dobson/Brewer ground-based instruments. A reasonable agreement in the spatial patterns of the trends is found amongst the European satellite, the NASA satellite, and the ground-based observations. Furthermore, two long-term simulations obtained with the Chemistry-Climate Models E39C-A provided by German Aerospace Center and UMUKCA-UCAM provided by University of Cambridge are analysed.

Long-term meteorologically independent trend analysis of ozone air quality at an urban site in the greater Houston area.

Science.gov (United States)

Botlaguduru, Venkata S V; Kommalapati, Raghava R; Huque, Ziaul

2018-04-19

The Houston-Galveston-Brazoria (HGB) area of Texas has a history of ozone exceedances and is currently classified under moderate nonattainment status for the 2008 8-hr ozone standard of 75 ppb. The HGB area is characterized by intense solar radiation, high temperature, and humidity, which influence day-to-day variations in ozone concentrations. Long-term air quality trends independent of meteorological influence need to be constructed for ascertaining the effectiveness of air quality management in this area. The Kolmogorov-Zurbenko (KZ) filter technique used to separate different scales of motion in a time series, is applied in the current study for maximum daily 8-hr (MDA8) ozone concentrations at an urban site (EPA AQS Site ID: 48-201-0024, Aldine) in the HGB area. This site located within 10 miles of downtown Houston and the George Bush Intercontinental Airport, was selected for developing long-term meteorologically independent MDA8 ozone trends for the years 1990-2016. Results from this study indicate a consistent decrease in meteorologically independent MDA8 ozone between 2000-2016. This pattern could be partially attributed to a reduction in underlying NO X emissions, particularly that of lowering nitrogen dioxide (NO 2 ) levels, and a decrease in the release of highly reactive volatile organic compounds (HRVOC). Results also suggest solar radiation to be most strongly correlated to ozone, with temperature being the secondary meteorological control variable. Relative humidity and wind speed have tertiary influence at this site. This study observed that meteorological variability accounts for a high of 61% variability in baseline ozone (low-frequency component, sum of long-term and seasonal components), while 64% of the change in long-term MDA8 ozone post-2000 could be attributed to NO X emissions reduction. Long-term MDA8 ozone trend component was estimated to be decreasing at a linear rate of 0.412 ± 0.007 ppb/yr for the years 2000-2016, and 0.155�

Stratospheric ozone chemistry in the Antarctic: what determines the lowest ozone values reached and their recovery?

Directory of Open Access Journals (Sweden)

J.-U. Grooß

2011-12-01

Full Text Available Balloon-borne observations of ozone from the South Pole Station have been reported to reach ozone mixing ratios below the detection limit of about 10 ppbv at the 70 hPa level by late September. After reaching a minimum, ozone mixing ratios increase to above 1 ppmv on the 70 hPa level by late December. While the basic mechanisms causing the ozone hole have been known for more than 20 yr, the detailed chemical processes determining how low the local concentration can fall, and how it recovers from the minimum have not been explored so far. Both of these aspects are investigated here by analysing results from the Chemical Lagrangian Model of the Stratosphere (CLaMS. As ozone falls below about 0.5 ppmv, a balance is maintained by gas phase production of both HCl and HOCl followed by heterogeneous reaction between these two compounds in these simulations. Thereafter, a very rapid, irreversible chlorine deactivation into HCl can occur, either when ozone drops to values low enough for gas phase HCl production to exceed chlorine activation processes or when temperatures increase above the polar stratospheric cloud (PSC threshold. As a consequence, the timing and mixing ratio of the minimum ozone depends sensitively on model parameters, including the ozone initialisation. The subsequent ozone increase between October and December is linked mainly to photochemical ozone production, caused by oxygen photolysis and by the oxidation of carbon monoxide and methane.

A window-based time series feature extraction method.

Science.gov (United States)

Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

2017-10-01

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of Ozone (O₃ and Erythemal UV (EUV measured by TOMS in the equatorial African belt

Directory of Open Access Journals (Sweden)

Øyvind Frette

2010-03-01

Full Text Available We presented time series of total ozone column amounts (TOCAs and erythemal UV (EUV doses derived from measurements by TOMS (Total Ozone Mapping Spectrometer instruments on board the Nimbus-7 (N7 and the Earth Probe (EP satellites for three locations within the equatorial African belt for the period 1979 to 2000. The locations were Dar-es-Salaam (6.8° S, 39.26° E in Tanzania, Kampala (0.19° N, 32.34° E in Uganda, and Serrekunda (13.28° N, 16.34° W in Gambia. Equatorial Africa has high levels of UV radiation, and because ozone shields UV radiation from reaching the Earth’s surface, there is a need to monitor TOCAs and EUV doses. In this paper we investigated the trend of TOCAs and EUV doses, the effects of annual and solar cycles on TOCAs, as well as the link between lightning and ozone production in the equatorial African belt. We also compared clear-sky simulated EUV doses with the corresponding EUV doses derived from TOMS measurements. The TOCAs were found to vary in the ranges 243 DU − 289 DU, 231 DU − 286 DU, and 236 DU − 296 DU, with mean values of 266.9 DU, 260.9 DU, and 267.8 DU for Dar-es-Salaam, Kampala and Serrekunda, respectively. Daily TOCA time series indicated that Kampala had the lowest TOCA values, which we attributed to the altitude effect. There were two annual ozone peaks in Dar-es-Salaam and Kampala, and one annual ozone peak in Serrekunda. The yearly TOCA averages showed an oscillation within a five-year period. We also found that the EUV doses were stable at all three locations for the period 1979−2000, and that Kampala and Dar-es-Salaam were mostly cloudy throughout the year, whereas Serrekunda was mostly free from clouds. It was also found that clouds were among the major factors determining the level of EUV reaching the Earth´s surface. Finally, we noted that during rainy seasons, horizontal advection effects augmented by lightning activity may be responsible for enhanced ozone production in the tropics.

Ozone profiles at Juelich, FRG, during 1988 and 1989

International Nuclear Information System (INIS)

Smit, H.G.J.; Straeter, W.; Loup, H.; Kley, D.

1989-12-01

Ozone soundings were performed regular at Juelich, FRG (50deg 41' N, 6deg 24' E). This report, the first one of an intended series, contains information on technical aspects and presents vertical profiles obtained during 1988 and 1989. (orig.) [de

Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales

Science.gov (United States)

Razavi, Saman; Vogel, Richard

2018-02-01

Prewhitening, the process of eliminating or reducing short-term stochastic persistence to enable detection of deterministic change, has been extensively applied to time series analysis of a range of geophysical variables. Despite the controversy around its utility, methodologies for prewhitening time series continue to be a critical feature of a variety of analyses including: trend detection of hydroclimatic variables and reconstruction of climate and/or hydrology through proxy records such as tree rings. With a focus on the latter, this paper presents a generalized approach to exploring the impact of a wide range of stochastic structures of short- and long-term persistence on the variability of hydroclimatic time series. Through this approach, we examine the impact of prewhitening on the inferred variability of time series across time scales. We document how a focus on prewhitened, residual time series can be misleading, as it can drastically distort (or remove) the structure of variability across time scales. Through examples with actual data, we show how such loss of information in prewhitened time series of tree rings (so-called "residual chronologies") can lead to the underestimation of extreme conditions in climate and hydrology, particularly droughts, reconstructed for centuries preceding the historical period.

Oxidation kinetics of hazelnut oil treated with ozone

Directory of Open Access Journals (Sweden)

H. Uzun

2018-01-01

Full Text Available The present study investigates the oxidation kinetics of hazelnut oil ozonated in different treatment periods (1, 5, 60 and 180 min. The kinetic rate constant (k was taken as the inverse of oxidation onset time (To observing a linear relationship from the plot of lnTo to isothermal temperatures (373, 383, 393, and 403 K carried out at differential scanning calorimetry. Kinetic parameters, activation energy (Ea, activation enthalpy (ΔH‡ and entropy (ΔS‡ were calculated based on the Arrhenius equation and activated complex theory. k values showed an exponential rise with the increase of ozone treatment time. The increase in k correlated well with the increase in the peroxide and free fatty acid values of all samples. Ea and ∆H‡ of the ozone treated oils showed a reducing trend and reflected an increased oxidation sensitivity after ozone treatment. Consistently, an increase in ∆S‡ indicated a faster oxidation reaction with an increase in ozone exposure time. However, no significant difference was observed in k, Ea, ΔH‡, ΔS‡ (p < 0.05 as a function of storage period, after the hazelnut oil was treated with ozone for 1 min.

Oxidation kinetics of hazelnut oil treated with ozone

International Nuclear Information System (INIS)

Uzun, H.; Ibanoglu, E.

2017-01-01

The present study investigates the oxidation kinetics of hazelnut oil ozonated in different treatment periods (1, 5, 60 and 180 min). The kinetic rate constant (k) was taken as the inverse of oxidation onset time (To) observing a linear relationship from the plot of ln To to isothermal temperatures (373, 383, 393, and 403 K) carried out at differential scanning calorimetry. Kinetic parameters, activation energy (Ea), activation enthalpy (ΔH‡) and entropy (ΔS‡) were calculated based on the Arrhenius equation and activated complex theory. k values showed an exponential rise with the increase of ozone treatment time. The increase in k correlated well with the increase in the peroxide and free fatty acid values of all samples. Ea and ΔH‡ of the ozone treated oils showed a reducing trend and reflected an increased oxidation sensitivity after ozone treatment. Consistently, an increase in ΔS‡ indicated a faster oxidation reaction with an increase in ozone exposure time. However, no significant difference was observed in k, Ea, ΔH‡, ΔS‡ (p < 0.05) as a function of storage period, after the hazelnut oil was treated with ozone for 1 min. [es

Multi sensor reanalysis of total ozone

Directory of Open Access Journals (Sweden)

R. J. van der A

2010-11-01

Full Text Available A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR, has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe, SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16, GOME (ERS-2, SCIAMACHY (Envisat, OMI (EOS-Aura, and GOME-2 (Metop-A have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend, and effective ozone temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric transport and uses parameterisations for gas-phase and ozone hole chemistry. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 1× 1 1/2° with a sample frequency of 6 h for the complete time period (1978–2008. The Observation-minus-Analysis (OmA statistics show that the bias of the MSR analyses is less than 1% with an RMS standard deviation of about 2% as compared to the corrected satellite observations used.

Modelling horizontal and vertical concentration profiles of ozone and oxides of nitrogen within high-latitude urban areas

International Nuclear Information System (INIS)

Nicholson, J.P.; Weston, K.J.

2001-01-01

Urban ozone concentrations are determined by the balance between ozone destruction, chemical production and supply through advection and turbulent down-mixing from higher levels. At high latitudes, low levels of solar insolation and high horizontal advection speeds reduce the photochemical production and the spatial ozone concentration patterns are largely determined by the reaction of ozone with nitric oxide and dry deposition to the surface. A Lagrangian column model has been developed to simulate the mean (monthly and annual) three-dimensional structure in ozone and nitrogen oxides (NO x ) concentrations in the boundary-layer within and immediately around an urban area. The short-time-scale photochemical processes of ozone and NO x , as well as emissions and deposition to the ground, are simulated. The model has a horizontal resolution of 1x1km and high resolution in the vertical. It has been applied over a 100x100km domain containing the city of Edinburgh (at latitude 56 o N) to simulate the city-scale processes of pollutants. Results are presented, using averaged wind-flow frequencies and appropriate stability conditions, to show the extent of the depletion of ozone by city emissions. The long-term average spatial patterns in the surface ozone and NO x concentrations over the model domain are reproduced quantitatively. The model shows the average surface ozone concentrations in the urban area to be lower than the surrounding rural areas by typically 50% and that the areas experiencing a 20% ozone depletion are generally restricted to within the urban area. The depletion of the ozone concentration to less than 50% of the rural surface values extends only 20m vertically above the urban area. A series of monitoring sites for ozone, nitric oxide and nitrogen dioxide on a north-south transect through the city - from an urban, through a semi-rural, to a remote rural location - allows the comparison of modelled with observed data for the mean diurnal cycle of ozone

Statistical evaluation of the impact of shale gas activities on ozone pollution in North Texas.

Science.gov (United States)

Ahmadi, Mahdi; John, Kuruvilla

2015-12-01

Over the past decade, substantial growth in shale gas exploration and production across the US has changed the country's energy outlook. Beyond its economic benefits, the negative impacts of shale gas development on air and water are less well known. In this study the relationship between shale gas activities and ground-level ozone pollution was statistically evaluated. The Dallas-Fort Worth (DFW) area in north-central Texas was selected as the study region. The Barnett Shale, which is one the most productive and fastest growing shale gas fields in the US, is located in the western half of DFW. Hourly meteorological and ozone data were acquired for fourteen years from monitoring stations established and operated by the Texas Commission on Environmental Quality (TCEQ). The area was divided into two regions, the shale gas region (SGR) and the non-shale gas (NSGR) region, according to the number of gas wells in close proximity to each monitoring site. The study period was also divided into 2000-2006 and 2007-2013 because the western half of DFW has experienced significant growth in shale gas activities since 2007. An evaluation of the raw ozone data showed that, while the overall trend in the ozone concentration was down over the entire region, the monitoring sites in the NSGR showed an additional reduction of 4% in the annual number of ozone exceedance days than those in the SGR. Directional analysis of ozone showed that the winds blowing from areas with high shale gas activities contributed to higher ozone downwind. KZ-filtering method and linear regression techniques were used to remove the effects of meteorological variations on ozone and to construct long-term and short-term meteorologically adjusted (M.A.) ozone time series. The mean value of all M.A. ozone components was 8% higher in the sites located within the SGR than in the NSGR. These findings may be useful for understanding the overall impact of shale gas activities on the local and regional ozone

DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

Ozone Gardens for the Citizen Scientist

Science.gov (United States)

Pippin, Margaret; Reilly, Gay; Rodjom, Abbey; Malick, Emily

2016-01-01

NASA Langley partnered with the Virginia Living Museum and two schools to create ozone bio-indicator gardens for citizen scientists of all ages. The garden at the Marshall Learning Center is part of a community vegetable garden designed to teach young children where food comes from and pollution in their area, since most of the children have asthma. The Mt. Carmel garden is located at a K-8 school. Different ozone sensitive and ozone tolerant species are growing and being monitored for leaf injury. In addition, CairClip ozone monitors were placed in the gardens and data are compared to ozone levels at the NASA Langley Chemistry and Physics Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, VA. Leaf observations and plant measurements are made two to three times a week throughout the growing season.

Degradation of 4-chlorophenol by ozonation, γ radiation as well as ozonation combined with γ radiation

International Nuclear Information System (INIS)

Hu, J.; Wang, J.L.

2005-01-01

The radiolysis of aqueous 4-chlorophenol (4-CP) by gamma radiation in the presence of air and ozone was investigated. The 4-CP degradation, release of chloride ion, UV absorption spectrum, total organic carbon (TOC) and adsorbable organic halogens (AOX) was measured. Under the conditions of synergistic effect of ozone and radiation a complete degradation of 100 mg/L 4-CP was obtained at a dose of 6 kGy, without ozone the 4-chlorophenol was completely decomposed at 15 kGy. The total organic carbon (TOC) was reduced by 26% when ionizing radiation (at 15 kGy) combined with ozonation, and by 17% without ozone, respectively. Analysis of intermediate products resulting from synergistic effect of ozone and radiation of 4-CP was performed by using the GC/MS method. Some primary influencing factors such as irradiation time and initial 4-CP concentration were also discussed. The results showed that the degradation of 4-chlorophenol could described by first-order reaction kinetic model. There is potential for combination of irradiation with ozonation, which can remarkably reduce the irradiation dose increase the degradation efficiency of 4-CP.

Variable Selection in Time Series Forecasting Using Random Forests

Directory of Open Access Journals (Sweden)

Hristos Tyralis

2017-10-01

Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

Ozone Layer Protection

Science.gov (United States)

... and Research Centers Contact Us Share Ozone Layer Protection The stratospheric ozone layer is Earth’s “sunscreen” – protecting ... GreenChill Partnership Responsible Appliance Disposal (RAD) Program Ozone Protection vs. Ozone Pollution This website addresses stratospheric ozone ...

Trend time-series modeling and forecasting with neural networks.

Science.gov (United States)

Qi, Min; Zhang, G Peter

2008-05-01

Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.

Segmentation of Nonstationary Time Series with Geometric Clustering

DEFF Research Database (Denmark)

Bocharov, Alexei; Thiesson, Bo

2013-01-01

We introduce a non-parametric method for segmentation in regimeswitching time-series models. The approach is based on spectral clustering of target-regressor tuples and derives a switching regression tree, where regime switches are modeled by oblique splits. Such models can be learned efficiently...... from data, where clustering is used to propose one single split candidate at each split level. We use the class of ART time series models to serve as illustration, but because of the non-parametric nature of our segmentation approach, it readily generalizes to a wide range of time-series models that go...

Non-parametric characterization of long-term rainfall time series

Science.gov (United States)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

The statistical study of rainfall time series is one of the approaches for efficient hydrological system design. Identifying, and characterizing long-term rainfall time series could aid in improving hydrological systems forecasting. In the present study, eventual statistics was applied for the long-term (1851-2006) rainfall time series under seven meteorological regions of India. Linear trend analysis was carried out using Mann-Kendall test for the observed rainfall series. The observed trend using the above-mentioned approach has been ascertained using the innovative trend analysis method. Innovative trend analysis has been found to be a strong tool to detect the general trend of rainfall time series. Sequential Mann-Kendall test has also been carried out to examine nonlinear trends of the series. The partial sum of cumulative deviation test is also found to be suitable to detect the nonlinear trend. Innovative trend analysis, sequential Mann-Kendall test and partial cumulative deviation test have potential to detect the general as well as nonlinear trend for the rainfall time series. Annual rainfall analysis suggests that the maximum changes in mean rainfall is 11.53% for West Peninsular India, whereas the maximum fall in mean rainfall is 7.8% for the North Mountainous Indian region. The innovative trend analysis method is also capable of finding the number of change point available in the time series. Additionally, we have performed von Neumann ratio test and cumulative deviation test to estimate the departure from homogeneity. Singular spectrum analysis has been applied in this study to evaluate the order of departure from homogeneity in the rainfall time series. Monsoon season (JS) of North Mountainous India and West Peninsular India zones has higher departure from homogeneity and singular spectrum analysis shows the results to be in coherence with the same.

Time Series Decomposition into Oscillation Components and Phase Estimation.

Science.gov (United States)

Matsuda, Takeru; Komaki, Fumiyasu

2017-02-01

Many time series are naturally considered as a superposition of several oscillation components. For example, electroencephalogram (EEG) time series include oscillation components such as alpha, beta, and gamma. We propose a method for decomposing time series into such oscillation components using state-space models. Based on the concept of random frequency modulation, gaussian linear state-space models for oscillation components are developed. In this model, the frequency of an oscillator fluctuates by noise. Time series decomposition is accomplished by this model like the Bayesian seasonal adjustment method. Since the model parameters are estimated from data by the empirical Bayes' method, the amplitudes and the frequencies of oscillation components are determined in a data-driven manner. Also, the appropriate number of oscillation components is determined with the Akaike information criterion (AIC). In this way, the proposed method provides a natural decomposition of the given time series into oscillation components. In neuroscience, the phase of neural time series plays an important role in neural information processing. The proposed method can be used to estimate the phase of each oscillation component and has several advantages over a conventional method based on the Hilbert transform. Thus, the proposed method enables an investigation of the phase dynamics of time series. Numerical results show that the proposed method succeeds in extracting intermittent oscillations like ripples and detecting the phase reset phenomena. We apply the proposed method to real data from various fields such as astronomy, ecology, tidology, and neuroscience.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

Multi-Scale Dissemination of Time Series Data

DEFF Research Database (Denmark)

Guo, Qingsong; Zhou, Yongluan; Su, Li

2013-01-01

In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber......, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time...

Optimization of Industrial Ozone Generation with Pulsed Power

Science.gov (United States)

Lopez, Jose; Guerrero, Daniel; Freilich, Alfred; Ramoino, Luca; Seton Hall University Team; Degremont Technologies-Ozonia Team

2013-09-01

Ozone (O3) is widely used for applications ranging from various industrial chemical synthesis processes to large-scale water treatment. The consequent surge in world-wide demand has brought about the requirement for ozone generation at the rate of several hundreds grams per kilowatt hour (g/kWh). For many years, ozone has been generated by means of dielectric barrier discharges (DBD), where a high-energy electric field between two electrodes separated by a dielectric and gap containing pure oxygen or air produce various microplasmas. The resultant microplasmas provide sufficient energy to dissociate the oxygen molecules while allowing the proper energetics channels for the formation of ozone. This presentation will review the current power schemes used for large-scale ozone generation and explore the use of high-voltage nanosecond pulses with reduced electric fields. The created microplasmas in a high reduced electric field are expected to be more efficient for ozone generation. This is confirmed with the current results of this work which observed that the efficiency of ozone generation increases by over eight time when the rise time and pulse duration are shortened. Department of Physics, South Orange, NJ, USA.

Comparative study of ozonized olive oil and ozonized sunflower oil

Directory of Open Access Journals (Sweden)

Díaz Maritza F.

2006-01-01

Full Text Available In this study the ozonized olive and sunflower oils are chemical and microbiologically compared. These oils were introduced into a reactor with bubbling ozone gas in a water bath at room temperature until they were solidified. The peroxide, acidity and iodine values along with antimicrobial activity were determined. Ozonization effects on the fatty acid composition of these oils were analyzed using Gas-Liquid Chromatographic Technique. An increase in peroxidation and acidity values was observed in both oils but they were higher in ozonized sunflower oil. Iodine value was zero in ozonized olive oil whereas in ozonized sunflower was 8.8 g Iodine per 100 g. The antimicrobial activity was similar for both ozonized oils except for Minimum Bactericidal Concentrations of Pseudomona aeruginosa. Composition of fatty acids in both ozonized oils showed gradual decrease in unsaturated fatty acids (C18:1, C18:2 with gradual increase in ozone doses.

RADON CONCENTRATION TIME SERIES MODELING AND APPLICATION DISCUSSION.

Science.gov (United States)

Stránský, V; Thinová, L

2017-11-01

In the year 2010 a continual radon measurement was established at Mladeč Caves in the Czech Republic using a continual radon monitor RADIM3A. In order to model radon time series in the years 2010-15, the Box-Jenkins Methodology, often used in econometrics, was applied. Because of the behavior of radon concentrations (RCs), a seasonal integrated, autoregressive moving averages model with exogenous variables (SARIMAX) has been chosen to model the measured time series. This model uses the time series seasonality, previously acquired values and delayed atmospheric parameters, to forecast RC. The developed model for RC time series is called regARIMA(5,1,3). Model residuals could be retrospectively compared with seismic evidence of local or global earthquakes, which occurred during the RCs measurement. This technique enables us to asses if continuously measured RC could serve an earthquake precursor. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Similarity estimators for irregular and age uncertain time series

Science.gov (United States)

Rehfeld, K.; Kurths, J.

2013-09-01

Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many datasets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age uncertain time series. We compare the Gaussian-kernel based cross correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60-55% (in the linear case) to 53-42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity

Similarity estimators for irregular and age-uncertain time series

Science.gov (United States)

Rehfeld, K.; Kurths, J.

2014-01-01

Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many data sets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age-uncertain time series. We compare the Gaussian-kernel-based cross-correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case, coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60-55% (in the linear case) to 53-42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity

Artificially ionized region as a source of ozone in the stratosphere

International Nuclear Information System (INIS)

Gurevich, Aleksandr V; Litvak, Aleksandr G; Vikharev, A L; Ivanov, O A; Borisov, Nikolai D; Sergeichev, Konstantin F

2000-01-01

A set of physical and chemical processes occurring in a microwave stratospheric discharge of nanosecond duration is discussed in connection with the effect they may have locally on the ozone layer in the artificially ionized region (AIR) in the stratosphere. The AIR, to be created at altitudes of 18 - 20 km by the microwave breakdown of air with ground-produced powerful electromagnetic wave beams, is planned for use in the natural physical experiment aimed at active monitoring of the ozone layer (its internal state and a set of plasma-chemical and photochemical processes) by controllably generating a considerable amount of ozone in the stratosphere. Results of relevant theoretical studies are presented, as are those of a large series of laboratory experiments performed under conditions similar to those prevailing in the stratosphere. Discharge regimes securing the efficient growth of ozone concentration are identified and studied in detail. It is demonstrated that such a stratospheric ozonizer is about as efficient as the best ground-based ozonizers used at present. For typical stratospheric conditions (low pressures and temperatures T ∼ 200 - 220 K), it is shown that the intense generation of ozone in a microwave breakdown effected by groups of short nanosecond pulses does not virtually increase the density of nitrogen oxides - gases that play a vital role in catalytic ozone-decomposing reactions. The possibility of effectively producing ozone in prebreakdown electric fields is established experimentally. It is demonstrated that due to its long lifetime, ozone produced locally at altitudes of 18 - 20 km may spread widely under the action of winds and turbulent diffusion, thus leading to an additional - artificial - ozonization of the stratosphere. (reviews of topical problems)

Extreme events in total ozone over the Northern mid-latitudes: an analysis based on long-term data sets from five European ground-based stations

Energy Technology Data Exchange (ETDEWEB)

Rieder, Harald E. (Inst. for Atmospheric and Climate Science, ETH Zurich, Zurich (Switzerland)), e-mail: hr2302@columbia.edu; Jancso, Leonhardt M. (Inst. for Atmospheric and Climate Science, ETH Zurich, Zurich (Switzerland); Inst. for Meteorology and Geophysics, Univ. of Innsbruck, Innsbruck (Austria)); Di Rocco, Stefania (Inst. for Atmospheric and Climate Science, ETH Zurich, Zurich (Switzerland); Dept. of Geography, Univ. of Zurich, Zurich (Switzerland)) (and others)

2011-11-15

We apply methods from extreme value theory to identify extreme events in high (termed EHOs) and low (termed ELOs) total ozone and to describe the distribution tails (i.e. very high and very low values) of five long-term European ground-based total ozone time series. The influence of these extreme events on observed mean values, long-term trends and changes is analysed. The results show a decrease in EHOs and an increase in ELOs during the last decades, and establish that the observed downward trend in column ozone during the 1970-1990s is strongly dominated by changes in the frequency of extreme events. Furthermore, it is shown that clear 'fingerprints' of atmospheric dynamics (NAO, ENSO) and chemistry [ozone depleting substances (ODSs), polar vortex ozone loss] can be found in the frequency distribution of ozone extremes, even if no attribution is possible from standard metrics (e.g. annual mean values). The analysis complements earlier analysis for the world's longest total ozone record at Arosa, Switzerland, confirming and revealing the strong influence of atmospheric dynamics on observed ozone changes. The results provide clear evidence that in addition to ODS, volcanic eruptions and strong/moderate ENSO and NAO events had significant influence on column ozone in the European sector

Sterilization of Microorganisms by Ozone and Ultrasound

Science.gov (United States)

Krasnyj, V. V.; Klosovskij, A. V.; Panasko, T. A.; Shvets, O. M.; Semenova, O. T.; Taran, V. S.; Tereshin, V. I.

2008-03-01

The results of recent experimental methods of sterilization of microorganisms with the use of ozone and ultrasound are presented. The main aim was to optimize the process of sterilization in water solution taking into account the ozone concentration, the power of ultrasonic emitter and the temperature of water. In the present work, the ultrasonic cavitation with simultaneous ozone generation has been used. The high ozone concentration in water solution was achieved by two-barrier glow discharge generated at atmospheric pressure and a cooling thermo-electric module. Such a sterilizer consists of ozone generator in a shape of flat electrodes covered with dielectric material and a high-voltage pulsed power supply of 250 W. The sterilization camera was equipped with ultrasonic source operated at 100 W. The experiments on the inactivation of bacteria of the Bacillus Cereus type were carried out in the distilled water saturated by ozone. The ozone concentration in the aqueous solution was 10 mg/1, whereas the ozone concentration at the output of ozone generator was 30 mg/1. The complete inactivation of spores took 15 min. Selection of the temperature of water, the ozone concentrations and ultrasonic power allowed to determine the time necessary for destroying the row of microorganisms.

Robust Forecasting of Non-Stationary Time Series

OpenAIRE

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...

The behaviour of PM10 and ozone in Malaysia through non-linear dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Sapini, Muhamad Luqman [Pusat Pengajian Matematik, Fakulti Sains Komputer & Matematik Universiti Teknologi MARA Kampus Seremban, 70300 Negeri Sembilan (Malaysia); Rahim, Nurul Zahirah binti Abd [Pengajian Matematik, Fakulti Sains Komputer & Matematik Universiti Teknologi MARA Kampus Jasin, 77000 Melaka (Malaysia); Noorani, Mohd Salmi Md. [Pusat Pengajian Sains Matematik, Fakulti Sains & Teknologi Universiti Kebangsaan Malaysia, 43650 Selangor (Malaysia)

2015-10-22

Prediction of ozone (O3) and PM10 is very important as both these air pollutants affect human health, human activities and more. Short-term forecasting of air quality is needed as preventive measures and effective action can be taken. Therefore, if it is detected that the ozone data is of a chaotic dynamical systems, a model using the nonlinear dynamic from chaos theory data can be made and thus forecasts for the short term would be more accurate. This study uses two methods, namely the 0-1 Test and Lyapunov Exponent. In addition, the effect of noise reduction on the analysis of time series data will be seen by using two smoothing methods: Rectangular methods and Triangle methods. At the end of the study, recommendations were made to get better results in the future.

Tropospheric Ozone Pollution from Space: New Views from the TOMS (Total Ozone Mapping Spectrometer) Instrument

Science.gov (United States)

Thompson, Anne M.; Hudson, Robert D.; Frolov, Alexander D.; Witte, Jacquelyn C.; Kucsera, Tom L.; Einaudi, Franco (Technical Monitor)

2000-01-01

New products from the TOMS (Total Ozone Mapping Spectrometer) >satellite instrument can resolve pollution events in tropical and mid-latitudes, Over the past several years, we have developed tropospheric ozone data sets by two methods. The modified-residual technique [Hudson and Thompson, 1998; Thompson and Hudson, 1999] uses v. 7 TOMS total ozone and is applicable to tropical regimes in which the wave-one pattern in total ozone is observed. The TOMSdirect method [Hudson et at., 2000] represents a new algorithm that uses TOMS radiances to extract tropospheric ozone in regions of constant stratospheric ozone and tropospheric ozone displaying high mixing ratios and variability characteristic of pollution, Absorbing aerosols (dust and smoke; Herman et at., 1997 Hsu et al., 1999), a standard TOMS product, provide transport and/or source marker information to interpret tropospheric ozone. For the Nimbus 7/TOMS observing period (1979-1992), modified-residual TTO (tropical tropospheric ozone) appears as two maps/month at I-degree latitude 2-degree longitude resolution at a homepage and digital data are available (20S to 20N) by ftp at http://metosrv2. umd.edu/tropo/ 14y_data.d. Preliminary modified-residual TTO data from the operational Earth-Probe/TOMS (1996- present) are posted in near-real-time at the same website. Analyses with the new tropospheric ozone and aerosol data are illustrated by the following (I)Signals in tropical tropospheric ozone column and smoke amount during ENSO (El Nino-Southern Oscillation) events, e.g. 1982-1983 and the intense ENSO induced biomass fires of 1997-1998 over the Indonesian region [Thompson et a[, 2000a, Thompson and Hudson, 1999]. (2) Trends in tropospheric ozone and smoke aerosols in various tropical regions (Atlantic, Pacific, Africa, Brazil). No significant trends were found for ozone from1980-1990 [Thompson and Hudson, 19991 although smoke aerosols increased during the period [Hsu et al.,1999]. (3) Temporal and spatial offsets

Secondary organic aerosol formation by limonene ozonolysis: Parameterizing multi-generational chemistry in ozone- and residence time-limited indoor environments

Science.gov (United States)

Waring, Michael S.

2016-11-01

Terpene ozonolysis reactions can be a strong source of secondary organic aerosol (SOA) indoors. SOA formation can be parameterized and predicted using the aerosol mass fraction (AMF), also known as the SOA yield, which quantifies the mass ratio of generated SOA to oxidized terpene. Limonene is a monoterpene that is at sufficient concentrations such that it reacts meaningfully with ozone indoors. It has two unsaturated bonds, and the magnitude of the limonene ozonolysis AMF varies by a factor of ∼4 depending on whether one or both of its unsaturated bonds are ozonated, which depends on whether ozone is in excess compared to limonene as well as the available time for reactions indoors. Hence, this study developed a framework to predict the limonene AMF as a function of the ozone [O3] and limonene [lim] concentrations and the air exchange rate (AER, h-1), which is the inverse of the residence time. Empirical AMF data were used to calculate a mixing coefficient, β, that would yield a 'resultant AMF' as the combination of the AMFs due to ozonolysis of one or both of limonene's unsaturated bonds, within the volatility basis set (VBS) organic aerosol framework. Then, β was regressed against predictors of log10([O3]/[lim]) and AER (R2 = 0.74). The β increased as the log10([O3]/[lim]) increased and as AER decreased, having the physical meaning of driving the resultant AMF to the upper AMF condition when both unsaturated bonds of limonene are ozonated. Modeling demonstrates that using the correct resultant AMF to simulate SOA formation owing to limonene ozonolysis is crucial for accurate indoor prediction.

Time Series Econometrics for the 21st Century

Science.gov (United States)

Hansen, Bruce E.

2017-01-01

The field of econometrics largely started with time series analysis because many early datasets were time-series macroeconomic data. As the field developed, more cross-sectional and longitudinal datasets were collected, which today dominate the majority of academic empirical research. In nonacademic (private sector, central bank, and governmental)…

Effectiveness of firefly algorithm based neural network in time series ...

African Journals Online (AJOL)

Effectiveness of firefly algorithm based neural network in time series forecasting. ... In the experiments, three well known time series were used to evaluate the performance. Results obtained were compared with ... Keywords: Time series, Artificial Neural Network, Firefly Algorithm, Particle Swarm Optimization, Overfitting ...

Investigation of In-Package Ozonation: The Effectiveness of Ozone to Inactive Salmonella enteritidis on Raw, Shell Eggs

Directory of Open Access Journals (Sweden)

Austin Donner

2011-01-01

Full Text Available Food production, handling, and distribution practices pose a constant threat to the quality and safety of food products. The objective of this research is to evaluate an innovative in-package ozonation process to reduce Salmonella enteritidis on raw, shell eggs. Previous research has shown that in-package ozonation eliminates contaminants from outside sources, reduces pathogens, and extends shelf life. In this study, raw, shell eggs were inoculated with Salmonella enteritidis and exposed to ozonation treatment. Microbial recoveries were then tested to determine bacterial reductions. Measurements included: relative humidity (34 percent at 5oC, surface temperatures (oC, ozone concentrations, bacterial reductions of Salmonella enteritidis, and quality assessment of eggs (Haugh Unit [HU], color, pH, and weight. After a 24-hour storage period, all treated samples indicated 3 log10 reductions on average (previous research has achieved up to 6log10. These results show effective in-package ozonation treatment reducing Salmonella enteritidis on raw, shell eggs without significant effect on measured egg quality over time. Benefits of in-package ozonation include no heating, low power requirements (less or equal to 50 Watts, short treatment time (seconds to minutes, and adaptability into existing processes. Given its ability to ensure the safety and longevity of food products, this technology has great potential for utilization in the food processing industry.

Ozone's impact on public health: Contributions from indoor exposures to ozone and products of ozone-initiated chemistry

DEFF Research Database (Denmark)

Weschler, Charles J.

2006-01-01

OBJECTIVES: The associations between ozone concentrations measured outdoors and both morbidity and mortality may be partially due to indoor exposures to ozone and ozone-initiated oxidation products. In this article I examine the contributions of such indoor exposures to overall ozone-related heal...

Time Series Analysis of Insar Data: Methods and Trends

Science.gov (United States)

Osmanoglu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cano-Cabral, Enrique

2015-01-01

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

Ground Level Ozone Regional Background Characteristics In North-west Pacific Rim

Science.gov (United States)

Chiang, C.; Fan, J.; Chang, J. S.

2007-12-01

Understanding the ground level ozone regional background characteristics is essential in understanding the contribution of long-range transport of pollutants from Asia Mainland to air quality in downwind areas. In order to understand this characteristic in north-west Pacific Rim, we conducted a coupled study using ozone observation from regional background stations and 3-D regional-scale chemical transport model simulations. We used O3, CO, wind speed and wind direction data from two regional background stations and ¡§other stations¡¨ over a ten year period and organized several numerical experiments to simulate one spring month in 2003 to obtain a deeper understanding. The so called ¡§other stations¡¨ had actually been named as background stations under various governmental auspices. But we found them to be often under strong influence of local pollution sources with strong diurnal or slightly longer time variations. We found that the Yonagunijima station (24.74 N, 123.02 E) and Heng-Chuen station (21.96 N,120.78 E), about a distance of 400 km apart, have almost the same ozone time series pattern. For these two stations in 2003, correlation coefficients (R2) for annual observed ozone concentration is about 0.64, in the springtime it is about 0.7, and in a one-month period at simulation days it is about 0.76. These two stations have very little small scale variations in all the variables studied. All variations are associated with large scale circulation changes. This is especially so at Yonagunijima station. Using a 3-D regional-scale chemical transport model for East Asia region including contribution from Asia continental outflow and neighboring island pollution areas we found that the Yonagunijima and HengChuen station are indeed free of pollutants from all neighboring areas keeping in mind that pollutants from Taiwan area is never far away. Ozone concentrations in these two stations are dominated by synoptic scale weather patterns, with diffused

Ozone modeling within plasmas for ozone sensor applications

OpenAIRE

Arshak, Khalil; Forde, Edward; Guiney, Ivor

2007-01-01

peer-reviewed Ozone (03) is potentially hazardous to human health and accurate prediction and measurement of this gas is essential in addressing its associated health risks. This paper presents theory to predict the levels of ozone concentration emittedfrom a dielectric barrier discharge (DBD) plasma for ozone sensing applications. This is done by postulating the kinetic model for ozone generation, with a DBD plasma at atmospheric pressure in air, in the form of a set of rate equations....

Interpretation of a compositional time series

Science.gov (United States)

Tolosana-Delgado, R.; van den Boogaart, K. G.

2012-04-01

Common methods for multivariate time series analysis use linear operations, from the definition of a time-lagged covariance/correlation to the prediction of new outcomes. However, when the time series response is a composition (a vector of positive components showing the relative importance of a set of parts in a total, like percentages and proportions), then linear operations are afflicted of several problems. For instance, it has been long recognised that (auto/cross-)correlations between raw percentages are spurious, more dependent on which other components are being considered than on any natural link between the components of interest. Also, a long-term forecast of a composition in models with a linear trend will ultimately predict negative components. In general terms, compositional data should not be treated in a raw scale, but after a log-ratio transformation (Aitchison, 1986: The statistical analysis of compositional data. Chapman and Hill). This is so because the information conveyed by a compositional data is relative, as stated in their definition. The principle of working in coordinates allows to apply any sort of multivariate analysis to a log-ratio transformed composition, as long as this transformation is invertible. This principle is of full application to time series analysis. We will discuss how results (both auto/cross-correlation functions and predictions) can be back-transformed, viewed and interpreted in a meaningful way. One view is to use the exhaustive set of all possible pairwise log-ratios, which allows to express the results into D(D - 1)/2 separate, interpretable sets of one-dimensional models showing the behaviour of each possible pairwise log-ratios. Another view is the interpretation of estimated coefficients or correlations back-transformed in terms of compositions. These two views are compatible and complementary. These issues are illustrated with time series of seasonal precipitation patterns at different rain gauges of the USA

Capturing Structure Implicitly from Time-Series having Limited Data

OpenAIRE

Emaasit, Daniel; Johnson, Matthew

2018-01-01

Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of scientific discovery. Moreover, the available limited data are quite noisy. This presents a major challenge when estimating time-series models that are robust to overfitting and have well-calibrated uncertainty estimates. Most of the current literature in these fields involve visualizing the time-series for noticeabl...

Drift-corrected Odin-OSIRIS ozone product: algorithm and updated stratospheric ozone trends

Directory of Open Access Journals (Sweden)

A. E. Bourassa

2018-01-01

Full Text Available A small long-term drift in the Optical Spectrograph and Infrared Imager System (OSIRIS stratospheric ozone product, manifested mostly since 2012, is quantified and attributed to a changing bias in the limb pointing knowledge of the instrument. A correction to this pointing drift using a predictable shape in the measured limb radiance profile is implemented and applied within the OSIRIS retrieval algorithm. This new data product, version 5.10, displays substantially better both long- and short-term agreement with Microwave Limb Sounder (MLS ozone throughout the stratosphere due to the pointing correction. Previously reported stratospheric ozone trends over the time period 1984–2013, which were derived by merging the altitude–number density ozone profile measurements from the Stratospheric Aerosol and Gas Experiment (SAGE II satellite instrument (1984–2005 and from OSIRIS (2002–2013, are recalculated using the new OSIRIS version 5.10 product and extended to 2017. These results still show statistically significant positive trends throughout the upper stratosphere since 1997, but at weaker levels that are more closely in line with estimates from other data records.

Self-affinity in the dengue fever time series

Science.gov (United States)

Azevedo, S. M.; Saba, H.; Miranda, J. G. V.; Filho, A. S. Nascimento; Moret, M. A.

2016-06-01

Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

The DMSP/MFR total ozone and radiance data base

International Nuclear Information System (INIS)

Ellis, J.S.; Lovill, J.E.; Luther, F.M.; Sullivan, T.J.; Taylor, S.S.; Weichel, R.L.

1992-01-01

The radiance measurements by the multichannel filter radiometer (MFR), a scanning instrument carried on the Defense Meteorological Satellite Program (DMSP) Block 5D series of satellites (flight models F1, F2, F3 and F4), were used to calculate the total column ozone globally for the period March 1977 through February 1980. These data were then calibrated and mapped to earth coordinates at LLNL. Total column ozone was derived from these calibrated radiance data and placed both the ozone and calibrated radiance data into a computer data base called SOAC (Satellite Ozone Analysis Center) using the FRAMIS database manager. The uncalibrated radiance data tapes were initially sent on to the National Climate Center, Asheville, North Carolina and then to the Satellite Data Services Branch /EDS/NOAA in Suitland, Maryland where they were archived. Copies of the data base containing the total ozone and the calibrated radiance data reside both at LLNL and at the National Space Science Data Center, NASA Goddard Space Flight Center, Greenbelt, Maryland. This report describes the entries into the data base in sufficient detail so that the data base might be useful to others. The characteristics of the MFR sensor are briefly discussed and a complete index to the data base tapes is given

Modelling the Ozone-Based Treatments for Inactivation of Microorganisms

Directory of Open Access Journals (Sweden)

Agnieszka Joanna Brodowska

2017-10-01

Full Text Available The paper presents the development of a model for ozone treatment in a dynamic bed of different microorganisms (Bacillus subtilis, B. cereus, B. pumilus, Escherichia coli, Pseudomonas fluorescens, Aspergillus niger, Eupenicillium cinnamopurpureum on a heterogeneous matrix (juniper berries, cardamom seeds initially treated with numerous ozone doses during various contact times was studied. Taking into account various microorganism susceptibility to ozone, it was of great importance to develop a sufficiently effective ozone dose to preserve food products using different strains based on the microbial model. For this purpose, we have chosen the Weibull model to describe the survival curves of different microorganisms. Based on the results of microorganism survival modelling after ozone treatment and considering the least susceptible strains to ozone, we selected the critical ones. Among tested strains, those from genus Bacillus were recognized as the most critical strains. In particular, B. subtilis and B. pumilus possessed the highest resistance to ozone treatment because the time needed to achieve the lowest level of its survival was the longest (up to 17.04 min and 16.89 min for B. pumilus reduction on juniper berry and cardamom seed matrix, respectively. Ozone treatment allow inactivate microorganisms to achieving lower survival rates by ozone dose (20.0 g O3/m3 O2, with a flow rate of 0.4 L/min and contact time (up to 20 min. The results demonstrated that a linear correlation between parameters p and k in Weibull distribution, providing an opportunity to calculate a fitted equation of the process.

Modelling the Ozone-Based Treatments for Inactivation of Microorganisms

Science.gov (United States)

Brodowska, Agnieszka Joanna; Nowak, Agnieszka; Kondratiuk-Janyska, Alina; Piątkowski, Marcin; Śmigielski, Krzysztof

2017-01-01

The paper presents the development of a model for ozone treatment in a dynamic bed of different microorganisms (Bacillus subtilis, B. cereus, B. pumilus, Escherichia coli, Pseudomonas fluorescens, Aspergillus niger, Eupenicillium cinnamopurpureum) on a heterogeneous matrix (juniper berries, cardamom seeds) initially treated with numerous ozone doses during various contact times was studied. Taking into account various microorganism susceptibility to ozone, it was of great importance to develop a sufficiently effective ozone dose to preserve food products using different strains based on the microbial model. For this purpose, we have chosen the Weibull model to describe the survival curves of different microorganisms. Based on the results of microorganism survival modelling after ozone treatment and considering the least susceptible strains to ozone, we selected the critical ones. Among tested strains, those from genus Bacillus were recognized as the most critical strains. In particular, B. subtilis and B. pumilus possessed the highest resistance to ozone treatment because the time needed to achieve the lowest level of its survival was the longest (up to 17.04 min and 16.89 min for B. pumilus reduction on juniper berry and cardamom seed matrix, respectively). Ozone treatment allow inactivate microorganisms to achieving lower survival rates by ozone dose (20.0 g O3/m3 O2, with a flow rate of 0.4 L/min) and contact time (up to 20 min). The results demonstrated that a linear correlation between parameters p and k in Weibull distribution, providing an opportunity to calculate a fitted equation of the process. PMID:28991199

Reevaluation of Stratospheric Ozone Trends From SAGE II Data Using a Simultaneous Temporal and Spatial Analysis

Science.gov (United States)

Damadeo, R. P.; Zawodny, J. M.; Thomason, L. W.

2014-01-01

This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for potential diurnal ozone variation. Results show biases, introduced by the way data is prepared for use with traditional methods, can be as high as 10%. Derived long-term changes show declines in ozone similar to other studies but very different trends in the presumed recovery period, with differences up to 2% per decade. The regression model allows for a variable turnaround time and reveals a hemispheric asymmetry in derived trends in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

On the plurality of times: disunified time and the A-series | Nefdt ...

African Journals Online (AJOL)

Then, I attempt to show that disunified time is a problem for a semantics based on the A-series since A-truthmakers are hard to come by in a universe of temporally disconnected time-series. Finally, I provide a novel argument showing that presentists should be particularly fearful of such a universe. South African Journal of ...

Impacts from a fossil fuel power plant on ozone levels in Memphis, Tennessee

International Nuclear Information System (INIS)

Mueller, S.F.; Bailey, E.M.

1998-01-01

The Tennessee Valley Authority (TVA) Allen power plant is located on the Mississippi River in the southwest corner of Memphis, Tennessee. Allen has three coal-fired cyclone boilers with a rated capacity of 272 MW each. It is a Phase 2 plant under Title IV of the Clean Air Act and is the largest single source of NO x in the Memphis area. TVA plans to reduce Allen NOx emissions through a combination of burning low-sulfur coal (which has the benefit of reducing NO x emissions while also reducing SO 2 emissions) and installing gas re-burn technology. A modeling study using the SAI, Inc., UAM-V photochemical model was conducted to examine the potential impacts of NO x reductions on ozone levels in the Memphis area. A series of four model simulations were made in which different Allen emissions scenarios were examined. The focus period of the photochemical modeling was 11--14 July 1995 when measurements in and near Memphis indicated peak hourly ozone levels of 135--140 ppb. This analysis primarily examined computed impacts within 50 km of Memphis. Allen was computed to contribute as much as 20--30 ppb to ground ozone levels 20-50 km downwind using its NO x emission rate before Title IV compliance. After compliance it was computed to contribute only about 10--20 ppb. At the same time, maximum daily ozone reductions due to Allen NO x titration of ozone were between 30 and 60 ppb. These benefits will be reduced by 30--50% after Title IV compliance, and are expected to occur within 30 km of the plant. More model grid cells indicated dis-benefits (net ground-level ozone increases) than benefits on three of the four episode days using the Title IV compliance emission rate. Significant ozone dis-benefits were expected because of the well-documented NO titration of ozone within plumes having a high ratio of NO to volatile organic compounds

Time-series modeling of long-term weight self-monitoring data.

Science.gov (United States)

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

Time series prediction of apple scab using meteorological ...

African Journals Online (AJOL)

A new prediction model for the early warning of apple scab is proposed in this study. The method is based on artificial intelligence and time series prediction. The infection period of apple scab was evaluated as the time series prediction model instead of summation of wetness duration. Also, the relations of different ...

Is the ozone climate penalty robust in Europe?

International Nuclear Information System (INIS)

Colette, Augustin; Bessagnet, Bertrand; Meleux, Frédérik; Rouïl, Laurence; Andersson, Camilla; Engardt, Magnuz; Langner, Joakim; Baklanov, Alexander; Brandt, Jørgen; Christensen, Jesper H; Geels, Camilla; Hedegaard, Gitte B; Doherty, Ruth; Giannakopoulos, Christos; Katragkou, Eleni; Lei, Hang; Manders, Astrid; Melas, Dimitris; Sofiev, Mikhail; Soares, Joana

2015-01-01

Ozone air pollution is identified as one of the main threats bearing upon human health and ecosystems, with 25 000 deaths in 2005 attributed to surface ozone in Europe (IIASA 2013 TSAP Report #10). In addition, there is a concern that climate change could negate ozone pollution mitigation strategies, making them insufficient over the long run and jeopardising chances to meet the long term objective set by the European Union Directive of 2008 (Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008) (60 ppbv, daily maximum). This effect has been termed the ozone climate penalty. One way of assessing this climate penalty is by driving chemistry-transport models with future climate projections while holding the ozone precursor emissions constant (although the climate penalty may also be influenced by changes in emission of precursors). Here we present an analysis of the robustness of the climate penalty in Europe across time periods and scenarios by analysing the databases underlying 11 articles published on the topic since 2007, i.e. a total of 25 model projections. This substantial body of literature has never been explored to assess the uncertainty and robustness of the climate ozone penalty because of the use of different scenarios, time periods and ozone metrics. Despite the variability of model design and setup in this database of 25 model projection, the present meta-analysis demonstrates the significance and robustness of the impact of climate change on European surface ozone with a latitudinal gradient from a penalty bearing upon large parts of continental Europe and a benefit over the North Atlantic region of the domain. Future climate scenarios present a penalty for summertime (JJA) surface ozone by the end of the century (2071–2100) of at most 5 ppbv. Over European land surfaces, the 95% confidence interval of JJA ozone change is [0.44; 0.64] and [0.99; 1.50] ppbv for the 2041–2070 and 2071–2100 time windows, respectively

Is the ozone climate penalty robust in Europe?

Science.gov (United States)

Colette, Augustin; Andersson, Camilla; Baklanov, Alexander; Bessagnet, Bertrand; Brandt, Jørgen; Christensen, Jesper H.; Doherty, Ruth; Engardt, Magnuz; Geels, Camilla; Giannakopoulos, Christos; Hedegaard, Gitte B.; Katragkou, Eleni; Langner, Joakim; Lei, Hang; Manders, Astrid; Melas, Dimitris; Meleux, Frédérik; Rouïl, Laurence; Sofiev, Mikhail; Soares, Joana; Stevenson, David S.; Tombrou-Tzella, Maria; Varotsos, Konstantinos V.; Young, Paul

2015-08-01

Ozone air pollution is identified as one of the main threats bearing upon human health and ecosystems, with 25 000 deaths in 2005 attributed to surface ozone in Europe (IIASA 2013 TSAP Report #10). In addition, there is a concern that climate change could negate ozone pollution mitigation strategies, making them insufficient over the long run and jeopardising chances to meet the long term objective set by the European Union Directive of 2008 (Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008) (60 ppbv, daily maximum). This effect has been termed the ozone climate penalty. One way of assessing this climate penalty is by driving chemistry-transport models with future climate projections while holding the ozone precursor emissions constant (although the climate penalty may also be influenced by changes in emission of precursors). Here we present an analysis of the robustness of the climate penalty in Europe across time periods and scenarios by analysing the databases underlying 11 articles published on the topic since 2007, i.e. a total of 25 model projections. This substantial body of literature has never been explored to assess the uncertainty and robustness of the climate ozone penalty because of the use of different scenarios, time periods and ozone metrics. Despite the variability of model design and setup in this database of 25 model projection, the present meta-analysis demonstrates the significance and robustness of the impact of climate change on European surface ozone with a latitudinal gradient from a penalty bearing upon large parts of continental Europe and a benefit over the North Atlantic region of the domain. Future climate scenarios present a penalty for summertime (JJA) surface ozone by the end of the century (2071-2100) of at most 5 ppbv. Over European land surfaces, the 95% confidence interval of JJA ozone change is [0.44; 0.64] and [0.99; 1.50] ppbv for the 2041-2070 and 2071-2100 time windows, respectively.

Characterization of time series via Rényi complexity-entropy curves

Science.gov (United States)

Jauregui, M.; Zunino, L.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2018-05-01

One of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the Shannon entropy and the statistical complexity. Recently, this idea has been generalized by considering the Tsallis monoparametric generalization of the Shannon entropy, yielding complexity-entropy curves. These curves have proven to enhance the discrimination among different time series related to stochastic and chaotic processes of numerical and experimental nature. Here we further explore these complexity-entropy curves in the context of the Rényi entropy, which is another monoparametric generalization of the Shannon entropy. By combining the Rényi entropy with the proper generalization of the statistical complexity, we associate a parametric curve (the Rényi complexity-entropy curve) with a given time series. We explore this approach in a series of numerical and experimental applications, demonstrating the usefulness of this new technique for time series analysis. We show that the Rényi complexity-entropy curves enable the differentiation among time series of chaotic, stochastic, and periodic nature. In particular, time series of stochastic nature are associated with curves displaying positive curvature in a neighborhood of their initial points, whereas curves related to chaotic phenomena have a negative curvature; finally, periodic time series are represented by vertical straight lines.

Quantifying Selection with Pool-Seq Time Series Data.

Science.gov (United States)

Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

2017-11-01

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Transformation-cost time-series method for analyzing irregularly sampled data.

Science.gov (United States)

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations-with associated costs-to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

Transformation-cost time-series method for analyzing irregularly sampled data

Science.gov (United States)

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G. Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations—with associated costs—to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

A multidisciplinary database for geophysical time series management

Science.gov (United States)

Montalto, P.; Aliotta, M.; Cassisi, C.; Prestifilippo, M.; Cannata, A.

2013-12-01

The variables collected by a sensor network constitute a heterogeneous data source that needs to be properly organized in order to be used in research and geophysical monitoring. With the time series term we refer to a set of observations of a given phenomenon acquired sequentially in time. When the time intervals are equally spaced one speaks of period or sampling frequency. Our work describes in detail a possible methodology for storage and management of time series using a specific data structure. We designed a framework, hereinafter called TSDSystem (Time Series Database System), in order to acquire time series from different data sources and standardize them within a relational database. The operation of standardization provides the ability to perform operations, such as query and visualization, of many measures synchronizing them using a common time scale. The proposed architecture follows a multiple layer paradigm (Loaders layer, Database layer and Business Logic layer). Each layer is specialized in performing particular operations for the reorganization and archiving of data from different sources such as ASCII, Excel, ODBC (Open DataBase Connectivity), file accessible from the Internet (web pages, XML). In particular, the loader layer performs a security check of the working status of each running software through an heartbeat system, in order to automate the discovery of acquisition issues and other warning conditions. Although our system has to manage huge amounts of data, performance is guaranteed by using a smart partitioning table strategy, that keeps balanced the percentage of data stored in each database table. TSDSystem also contains modules for the visualization of acquired data, that provide the possibility to query different time series on a specified time range, or follow the realtime signal acquisition, according to a data access policy from the users.

Evaluation of tropospheric and stratospheric ozone trends over Western Europe from ground-based FTIR network observations

Directory of Open Access Journals (Sweden)

C. Vigouroux

2008-12-01

Full Text Available Within the European project UFTIR (Time series of Upper Free Troposphere observations from an European ground-based FTIR network, six ground-based stations in Western Europe, from 79° N to 28° N, all equipped with Fourier Transform infrared (FTIR instruments and part of the Network for the Detection of Atmospheric Composition Change (NDACC, have joined their efforts to evaluate the trends of several direct and indirect greenhouse gases over the period 1995–2004. The retrievals of CO, CH₄, C₂H₆, N₂O, CHClF₂, and O₃ have been optimized. Using the optimal estimation method, some vertical information can be obtained in addition to total column amounts. A bootstrap resampling method has been implemented to determine annual partial and total column trends for the target gases. The present work focuses on the ozone results. The retrieved time series of partial and total ozone columns are validated with ground-based correlative data (Brewer, Dobson, UV-Vis, ozonesondes, and Lidar. The observed total column ozone trends are in agreement with previous studies: 1 no total column ozone trend is seen at the lowest latitude station Izaña (28° N; 2 slightly positive total column trends are seen at the two mid-latitude stations Zugspitze and Jungfraujoch (47° N, only one of them being significant; 3 the highest latitude stations Harestua (60° N, Kiruna (68° N and Ny-Ålesund (79° N show significant positive total column trends. Following the vertical information contained in the ozone FTIR retrievals, we provide partial columns trends for the layers: ground-10 km, 10–18 km, 18–27 km, and 27–42 km, which helps to distinguish the contributions from dynamical and chemical changes on the total column ozone trends. We obtain no statistically significant trends in the ground-10 km layer for five out of the six ground-based stations. We find significant positive trends for the lowermost

Ozone decomposition

Directory of Open Access Journals (Sweden)

Batakliev Todor

2014-06-01

Full Text Available Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers. Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates

Modeling financial time series with S-plus

CERN Document Server

Zivot, Eric

2003-01-01

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics This is the first book to show the power of S-PLUS for the analysis of time series data It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department at the University of Washington, and is co-director of the nascent Professional Master's Program in Computational Finance He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the He...

Application of Time Series Analysis in Determination of Lag Time in Jahanbin Basin

Directory of Open Access Journals (Sweden)

Seied Yahya Mirzaee

2005-11-01

    One of the important issues that have significant role in study of hydrology of basin is determination of lag time. Lag time has significant role in hydrological studies. Quantity of rainfall related lag time depends on several factors, such as permeability, vegetation cover, catchments slope, rainfall intensity, storm duration and type of rain. Determination of lag time is important parameter in many projects such as dam design and also water resource studies. Lag time of basin could be calculated using various methods. One of these methods is time series analysis of spectral density. The analysis is based on fouries series. The time series is approximated with Sinuous and Cosines functions. In this method harmonically significant quantities with individual frequencies are presented. Spectral density under multiple time series could be used to obtain basin lag time for annual runoff and short-term rainfall fluctuation. A long lag time could be due to snowmelt as well as melting ice due to rainfalls in freezing days. In this research the lag time of Jahanbin basin has been determined using spectral density method. The catchments is subjected to both rainfall and snowfall. For short term rainfall fluctuation with a return period  2, 3, 4 months, the lag times were found 0.18, 0.5 and 0.083 month, respectively.

Modeling Time Series Data for Supervised Learning

Science.gov (United States)

Baydogan, Mustafa Gokce

2012-01-01

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

Empirical method to measure stochasticity and multifractality in nonlinear time series

Science.gov (United States)

Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

2013-12-01

An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

The chemical and biological characteristics of coke-oven wastewater by ozonation

International Nuclear Information System (INIS)

Chang, E.-E.; Hsing, H.-J.; Chiang, P.-C.; Chen, M.-Y.; Shyng, J.-Y.

2008-01-01

A bench-scale bubble column reactor was used to investigate the biological and chemical characteristics of coke-oven wastewater after ozonation treatment through the examination of selected parameters. Color and thiocyanate could be removed almost entirely; however, organic matter and cyanide could not, due to the inadequate oxidation ability of ozone to remove ozonated byproducts under given experimental conditions. The removal of cyanide and total organic carbon were pH-dependent and were found to be efficient under neutral to alkaline conditions. The removal rate for thiocyanate was about five times that of cyanide. The ozone consumption ratio approached to about 1 at the early stage of ozonation (time TOC ) increased to 30%, indicating that easily degraded pollutants were degraded almost entirely. The effect of ozonation on the subsequent biological treatment unit (i.e., activated sludge process) was determined by observing the ratio of 5-day biological oxygen demand to chemical oxygen demand (BOD 5 /COD) and the specific oxygen utilization rate (SOUR). The results indicated that the contribution of ozonation to inhibition reduction was very significant but limited to the enhancement of biodegradation. The operation for ozonation of coke-oven wastewater was feasible under neutral condition and short ozone contact time in order to achieve better performance and cost savings

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Clinical time series prediction: towards a hierarchical dynamical system framework

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

Turbulencelike Behavior of Seismic Time Series

International Nuclear Information System (INIS)

Manshour, P.; Saberi, S.; Sahimi, Muhammad; Peinke, J.; Pacheco, Amalio F.; Rahimi Tabar, M. Reza

2009-01-01

We report on a stochastic analysis of Earth's vertical velocity time series by using methods originally developed for complex hierarchical systems and, in particular, for turbulent flows. Analysis of the fluctuations of the detrended increments of the series reveals a pronounced transition in their probability density function from Gaussian to non-Gaussian. The transition occurs 5-10 hours prior to a moderate or large earthquake, hence representing a new and reliable precursor for detecting such earthquakes

Characterizing time series: when Granger causality triggers complex networks

Science.gov (United States)

Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong

2012-08-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.

Characterizing time series: when Granger causality triggers complex networks

International Nuclear Information System (INIS)

Ge Tian; Cui Yindong; Lin Wei; Liu Chong; Kurths, Jürgen

2012-01-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length. (paper)

Multivariate time series analysis with R and financial applications

CERN Document Server

Tsay, Ruey S

2013-01-01

Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl

Measurements of spatial population synchrony: influence of time series transformations.

Science.gov (United States)

Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël

2015-09-01

Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.

Ozone pollution and ozone biomonitoring in European cities Part II. Ozone-induced plant injury and its relationship with descriptors of ozone pollution

DEFF Research Database (Denmark)

Klumpp, A.; Ansel, W.; Klumpp, G.

2006-01-01

within local networks were relatively small, but seasonal and inter-annual differences were strong due to the variability of meteorological conditions and related ozone concentrations. The 2001 data revealed a significant relationship between foliar injury degree and various descriptors of ozone...... pollution such as mean value, AOT20 and AOT40. Examining individual sites of the local monitoring networks separately, however, yielded noticeable differences. Some sites showed no association between ozone pollution and ozone-induced effects, whereas others featured almost linear relationships...

Stochastic time series analysis of hydrology data for water resources

Science.gov (United States)

Sathish, S.; Khadar Babu, S. K.

2017-11-01

The prediction to current publication of stochastic time series analysis in hydrology and seasonal stage. The different statistical tests for predicting the hydrology time series on Thomas-Fiering model. The hydrology time series of flood flow have accept a great deal of consideration worldwide. The concentration of stochastic process areas of time series analysis method are expanding with develop concerns about seasonal periods and global warming. The recent trend by the researchers for testing seasonal periods in the hydrologic flowseries using stochastic process on Thomas-Fiering model. The present article proposed to predict the seasonal periods in hydrology using Thomas-Fiering model.

Representativeness of single lidar stations for zonally averaged ozone profiles, their trends and attribution to proxies

Directory of Open Access Journals (Sweden)

C. Zerefos

2018-05-01

Full Text Available This paper is focusing on the representativeness of single lidar stations for zonally averaged ozone profile variations over the middle and upper stratosphere. From the lower to the upper stratosphere, ozone profiles from single or grouped lidar stations correlate well with zonal means calculated from the Solar Backscatter Ultraviolet Radiometer (SBUV satellite overpasses. The best representativeness with significant correlation coefficients is found within ±15° of latitude circles north or south of any lidar station. This paper also includes a multivariate linear regression (MLR analysis on the relative importance of proxy time series for explaining variations in the vertical ozone profiles. Studied proxies represent variability due to influences outside of the earth system (solar cycle and within the earth system, i.e. dynamic processes (the Quasi Biennial Oscillation, QBO; the Arctic Oscillation, AO; the Antarctic Oscillation, AAO; the El Niño Southern Oscillation, ENSO, those due to volcanic aerosol (aerosol optical depth, AOD, tropopause height changes (including global warming and those influences due to anthropogenic contributions to atmospheric chemistry (equivalent effective stratospheric chlorine, EESC. Ozone trends are estimated, with and without removal of proxies, from the total available 1980 to 2015 SBUV record. Except for the chemistry related proxy (EESC and its orthogonal function, the removal of the other proxies does not alter the significance of the estimated long-term trends. At heights above 15 hPa an inflection point between 1997 and 1999 marks the end of significant negative ozone trends, followed by a recent period between 1998 and 2015 with positive ozone trends. At heights between 15 and 40 hPa the pre-1998 negative ozone trends tend to become less significant as we move towards 2015, below which the lower stratosphere ozone decline continues in agreement with findings of recent literature.

Representativeness of single lidar stations for zonally averaged ozone profiles, their trends and attribution to proxies

Science.gov (United States)

Zerefos, Christos; Kapsomenakis, John; Eleftheratos, Kostas; Tourpali, Kleareti; Petropavlovskikh, Irina; Hubert, Daan; Godin-Beekmann, Sophie; Steinbrecht, Wolfgang; Frith, Stacey; Sofieva, Viktoria; Hassler, Birgit

2018-05-01

This paper is focusing on the representativeness of single lidar stations for zonally averaged ozone profile variations over the middle and upper stratosphere. From the lower to the upper stratosphere, ozone profiles from single or grouped lidar stations correlate well with zonal means calculated from the Solar Backscatter Ultraviolet Radiometer (SBUV) satellite overpasses. The best representativeness with significant correlation coefficients is found within ±15° of latitude circles north or south of any lidar station. This paper also includes a multivariate linear regression (MLR) analysis on the relative importance of proxy time series for explaining variations in the vertical ozone profiles. Studied proxies represent variability due to influences outside of the earth system (solar cycle) and within the earth system, i.e. dynamic processes (the Quasi Biennial Oscillation, QBO; the Arctic Oscillation, AO; the Antarctic Oscillation, AAO; the El Niño Southern Oscillation, ENSO), those due to volcanic aerosol (aerosol optical depth, AOD), tropopause height changes (including global warming) and those influences due to anthropogenic contributions to atmospheric chemistry (equivalent effective stratospheric chlorine, EESC). Ozone trends are estimated, with and without removal of proxies, from the total available 1980 to 2015 SBUV record. Except for the chemistry related proxy (EESC) and its orthogonal function, the removal of the other proxies does not alter the significance of the estimated long-term trends. At heights above 15 hPa an inflection point between 1997 and 1999 marks the end of significant negative ozone trends, followed by a recent period between 1998 and 2015 with positive ozone trends. At heights between 15 and 40 hPa the pre-1998 negative ozone trends tend to become less significant as we move towards 2015, below which the lower stratosphere ozone decline continues in agreement with findings of recent literature.

Neural network versus classical time series forecasting models

Science.gov (United States)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

Nonlinear time series analysis of the human electrocardiogram

International Nuclear Information System (INIS)

Perc, Matjaz

2005-01-01

We analyse the human electrocardiogram with simple nonlinear time series analysis methods that are appropriate for graduate as well as undergraduate courses. In particular, attention is devoted to the notions of determinism and stationarity in physiological data. We emphasize that methods of nonlinear time series analysis can be successfully applied only if the studied data set originates from a deterministic stationary system. After positively establishing the presence of determinism and stationarity in the studied electrocardiogram, we calculate the maximal Lyapunov exponent, thus providing interesting insights into the dynamics of the human heart. Moreover, to facilitate interest and enable the integration of nonlinear time series analysis methods into the curriculum at an early stage of the educational process, we also provide user-friendly programs for each implemented method

Reconciliation of Halogen-Induced Ozone Loss with the Total-Column Ozone Record

Science.gov (United States)

Shepherd, T. G.; Plummer, D. A.; Scinocca, J. F.; Hegglin, M. I.; Fioletov, V. E.; Reader, M. C.; Remsberg, E.; von Clarmann, T.; Wang, H. J.

2014-01-01

The observed depletion of the ozone layer from the 1980s onwards is attributed to halogen source gases emitted by human activities. However, the precision of this attribution is complicated by year-to-year variations in meteorology, that is, dynamical variability, and by changes in tropospheric ozone concentrations. As such, key aspects of the total-column ozone record, which combines changes in both tropospheric and stratospheric ozone, remain unexplained, such as the apparent absence of a decline in total-column ozone levels before 1980, and of any long-term decline in total-column ozone levels in the tropics. Here we use a chemistry-climate model to estimate changes in halogen-induced ozone loss between 1960 and 2010; the model is constrained by observed meteorology to remove the eects of dynamical variability, and driven by emissions of tropospheric ozone precursors to separate out changes in tropospheric ozone. We show that halogen-induced ozone loss closely followed stratospheric halogen loading over the studied period. Pronounced enhancements in ozone loss were apparent in both hemispheres following the volcanic eruptions of El Chichon and, in particular, Mount Pinatubo, which significantly enhanced stratospheric aerosol loads. We further show that approximately 40% of the long-term non-volcanic ozone loss occurred before 1980, and that long-term ozone loss also occurred in the tropical stratosphere. Finally, we show that halogeninduced ozone loss has declined by over 10% since stratospheric halogen loading peaked in the late 1990s, indicating that the recovery of the ozone layer is well underway.

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

Science.gov (United States)

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Hidden Markov Models for Time Series An Introduction Using R

CERN Document Server

Zucchini, Walter

2009-01-01

Illustrates the flexibility of HMMs as general-purpose models for time series data. This work presents an overview of HMMs for analyzing time series data, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts and categorical observations.

Constructing ordinal partition transition networks from multivariate time series.

Science.gov (United States)

Zhang, Jiayang; Zhou, Jie; Tang, Ming; Guo, Heng; Small, Michael; Zou, Yong

2017-08-10

A growing number of algorithms have been proposed to map a scalar time series into ordinal partition transition networks. However, most observable phenomena in the empirical sciences are of a multivariate nature. We construct ordinal partition transition networks for multivariate time series. This approach yields weighted directed networks representing the pattern transition properties of time series in velocity space, which hence provides dynamic insights of the underling system. Furthermore, we propose a measure of entropy to characterize ordinal partition transition dynamics, which is sensitive to capturing the possible local geometric changes of phase space trajectories. We demonstrate the applicability of pattern transition networks to capture phase coherence to non-coherence transitions, and to characterize paths to phase synchronizations. Therefore, we conclude that the ordinal partition transition network approach provides complementary insight to the traditional symbolic analysis of nonlinear multivariate time series.

Permutation entropy of finite-length white-noise time series.

Science.gov (United States)

Little, Douglas J; Kane, Deb M

2016-08-01

Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a time series. While the PE of white noise is well understood in the long time-series limit, analysis in the general case is currently lacking. Here the expectation value and variance of white-noise PE are derived as functions of the number of ordinal pattern trials, N, and the embedding dimension, D. It is demonstrated that the probability distribution of the white-noise PE converges to a χ^{2} distribution with D!-1 degrees of freedom as N becomes large. It is further demonstrated that the PE variance for an arbitrary time series can be estimated as the variance of a related metric, the Kullback-Leibler entropy (KLE), allowing the qualitative N≫D! condition to be recast as a quantitative estimate of the N required to achieve a desired PE calculation precision. Application of this theory to statistical inference is demonstrated in the case of an experimentally obtained noise series, where the probability of obtaining the observed PE value was calculated assuming a white-noise time series. Standard statistical inference can be used to draw conclusions whether the white-noise null hypothesis can be accepted or rejected. This methodology can be applied to other null hypotheses, such as discriminating whether two time series are generated from different complex system states.

Multiresolution analysis of Bursa Malaysia KLCI time series

Science.gov (United States)

Ismail, Mohd Tahir; Dghais, Amel Abdoullah Ahmed

2017-05-01

In general, a time series is simply a sequence of numbers collected at regular intervals over a period. Financial time series data processing is concerned with the theory and practice of processing asset price over time, such as currency, commodity data, and stock market data. The primary aim of this study is to understand the fundamental characteristics of selected financial time series by using the time as well as the frequency domain analysis. After that prediction can be executed for the desired system for in sample forecasting. In this study, multiresolution analysis which the assist of discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transform (MODWT) will be used to pinpoint special characteristics of Bursa Malaysia KLCI (Kuala Lumpur Composite Index) daily closing prices and return values. In addition, further case study discussions include the modeling of Bursa Malaysia KLCI using linear ARIMA with wavelets to address how multiresolution approach improves fitting and forecasting results.

Modelling bursty time series

International Nuclear Information System (INIS)

Vajna, Szabolcs; Kertész, János; Tóth, Bálint

2013-01-01

Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty time series due to the non-trivial dynamics of the task list. The model is characterized by a priority distribution as an input parameter, which describes the choice procedure from the list. We give exact results on the asymptotic behaviour of the model and we show that the interevent time distribution is power-law decaying for any kind of input distributions that remain normalizable in the infinite list limit, with exponents tunable between 1 and 2. The model satisfies a scaling law between the exponents of interevent time distribution (β) and autocorrelation function (α): α + β = 2. This law is general for renewal processes with power-law decaying interevent time distribution. We conclude that slowly decaying autocorrelation function indicates long-range dependence only if the scaling law is violated. (paper)

Application of Ozone MBBR Process in Refinery Wastewater Treatment

Science.gov (United States)

Lin, Wang

2018-01-01

Moving Bed Biofilm Reactor (MBBR) is a kind of sewage treatment technology based on fluidized bed. At the same time, it can also be regarded as an efficient new reactor between active sludge method and the biological membrane method. The application of ozone MBBR process in refinery wastewater treatment is mainly studied. The key point is to design the ozone +MBBR combined process based on MBBR process. The ozone +MBBR process is used to analyze the treatment of concentrated water COD discharged from the refinery wastewater treatment plant. The experimental results show that the average removal rate of COD is 46.0%~67.3% in the treatment of reverse osmosis concentrated water by ozone MBBR process, and the effluent can meet the relevant standard requirements. Compared with the traditional process, the ozone MBBR process is more flexible. The investment of this process is mainly ozone generator, blower and so on. The prices of these items are relatively inexpensive, and these costs can be offset by the excess investment in traditional activated sludge processes. At the same time, ozone MBBR process has obvious advantages in water quality, stability and other aspects.

Timing calibration and spectral cleaning of LOFAR time series data

NARCIS (Netherlands)

Corstanje, A.; Buitink, S.; Enriquez, J. E.; Falcke, H.; Horandel, J. R.; Krause, M.; Nelles, A.; Rachen, J. P.; Schellart, P.; Scholten, O.; ter Veen, S.; Thoudam, S.; Trinh, T. N. G.

We describe a method for spectral cleaning and timing calibration of short time series data of the voltage in individual radio interferometer receivers. It makes use of phase differences in fast Fourier transform (FFT) spectra across antenna pairs. For strong, localized terrestrial sources these are

Time series momentum and contrarian effects in the Chinese stock market

Science.gov (United States)

Shi, Huai-Long; Zhou, Wei-Xing

2017-10-01

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. The performances of the time series momentum and contrarian strategies are highly dependent on the look-back and holding periods and firm-specific characteristics.

Two-phase ozonation of chlorinated organics

International Nuclear Information System (INIS)

Bhattacharyya, D.; Freshour, A.; West, D.

1995-01-01

In the last few years the amount of research being conducted in the field of single-phase ozonation has grown extensively. However, traditional aqueous-phase ozonation systems are limited by a lack of selective oxidation potential, low ozone solubility in water, and slow intermediate decomposition rates. Furthermore, ozone may decompose before it can be utilized for pollutant destruction since ozone can be highly unstable in aqueous solutions. Naturally occurring compounds such as NaHCO 3 also affect ozone reactions by inhibiting the formation of OH-free radicals. To compensate for these factors, excess ozone is typically supplied to a reactor. Since ozone generation requires considerable electric power consumption (16 - 24 kWh/kg of O 3 ), attempts to enhance the ozone utilization rate and stability should lead to more efficient application of this process to hazardous waste treatment. To improve the process, ozonation may be more efficiently carried out in a two-phase system consisting of an inert solvent (saturated with O 3 ) contacted with an aqueous phase containing pollutants. The non-aqueous phase must meet the following criteria: (1) non-toxic, (2) very low vapor pressure, (3) high density (for ease of separation), (4) complete insolubility in water, (5) reusability, (6) selective pollutant extractability, (7) high oxidant solubility, and (8) extended O 3 stability. Previously published studies (1) have indicated that a number of fluorinated hydrocarbon compounds fit these criteria. For this project, FC40 (a product of 3M Co.) was chosen due to its low vapor pressure (3 mm Hg) and high specific gravity (1.9). The primary advantages of the FC40 solvent are that it is non-toxic, reusable, has an ozone solubility 10 times that of water, and that 85 % of the ozone remains in the solvent even after 2 hours. This novel two-phase process has been utilized to study the rapid destruction of organic chlorine compounds and organic mixtures

Characterizing interdependencies of multiple time series theory and applications

CERN Document Server

Hosoya, Yuzo; Takimoto, Taro; Kinoshita, Ryo

2017-01-01

This book introduces academic researchers and professionals to the basic concepts and methods for characterizing interdependencies of multiple time series in the frequency domain. Detecting causal directions between a pair of time series and the extent of their effects, as well as testing the non existence of a feedback relation between them, have constituted major focal points in multiple time series analysis since Granger introduced the celebrated definition of causality in view of prediction improvement. Causality analysis has since been widely applied in many disciplines. Although most analyses are conducted from the perspective of the time domain, a frequency domain method introduced in this book sheds new light on another aspect that disentangles the interdependencies between multiple time series in terms of long-term or short-term effects, quantitatively characterizing them. The frequency domain method includes the Granger noncausality test as a special case. Chapters 2 and 3 of the book introduce an i...

A perturbative approach for enhancing the performance of time series forecasting.

Science.gov (United States)

de Mattos Neto, Paulo S G; Ferreira, Tiago A E; Lima, Aranildo R; Vasconcelos, Germano C; Cavalcanti, George D C

2017-04-01

This paper proposes a method to perform time series prediction based on perturbation theory. The approach is based on continuously adjusting an initial forecasting model to asymptotically approximate a desired time series model. First, a predictive model generates an initial forecasting for a time series. Second, a residual time series is calculated as the difference between the original time series and the initial forecasting. If that residual series is not white noise, then it can be used to improve the accuracy of the initial model and a new predictive model is adjusted using residual series. The whole process is repeated until convergence or the residual series becomes white noise. The output of the method is then given by summing up the outputs of all trained predictive models in a perturbative sense. To test the method, an experimental investigation was conducted on six real world time series. A comparison was made with six other methods experimented and ten other results found in the literature. Results show that not only the performance of the initial model is significantly improved but also the proposed method outperforms the other results previously published. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drunk driving detection based on classification of multivariate time series.

Science.gov (United States)

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Evaluation of scaling invariance embedded in short time series.

Directory of Open Access Journals (Sweden)

Xue Pan

Full Text Available Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2. Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03 and sharp confidential interval (standard deviation ≤0.05. Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Evaluation of scaling invariance embedded in short time series.

Science.gov (United States)

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2). Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03) and sharp confidential interval (standard deviation ≤0.05). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

Science.gov (United States)

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

CONTRIBUTION TO INDOOR OZONE LEVELS OF AN OZONE GENERATOR

Science.gov (United States)

This report gives results of a study of a commonly used commercially available ozone generator, undertaken to determine its impact on indoor ozone levels. xperiment were conducted in a typical mechanically ventilated office and in a test house. he generated ozone and the in-room ...

Geomechanical time series and its singularity spectrum analysis

Czech Academy of Sciences Publication Activity Database

Lyubushin, Alexei A.; Kaláb, Zdeněk; Lednická, Markéta

2012-01-01

Roč. 47, č. 1 (2012), s. 69-77 ISSN 1217-8977 R&D Projects: GA ČR GA105/09/0089 Institutional research plan: CEZ:AV0Z30860518 Keywords : geomechanical time series * singularity spectrum * time series segmentation * laser distance meter Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 0.347, year: 2012 http://www.akademiai.com/content/88v4027758382225/fulltext.pdf

Intercomparison of ozone measurements between Lidar and ECC-sondes

Energy Technology Data Exchange (ETDEWEB)

Grabbe, G.C. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Boesenberg, J. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Dier, H. [Meteorologisches Obs., Lindenberg (Germany); Goersdorf, U. [Meteorologisches Obs., Lindenberg (Germany); Matthias, V. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Peters, G. [Meteorologisches Obs., Lindenberg (Germany); Schaberl, T. [Hamburg Univ. (Germany). Meteorologisches Inst.; Senff, C. [Hamburg Univ. (Germany). Meteorologisches Inst.

1996-02-01

An intercomparison experiment for measurements of ozone vertical profiles in the lower troposphere was performed using a ground-based ozone DIAL (DIfferential Absorption Lidar) and ECC-sondes (Electrochemical Concentration Cell) attached to tethered as well as free flying balloons, which took place in June of 1994. The tethered balloon was used for ozone soundings in the planetary boundary layer up to an altitude of 500 m, while in the free troposphere free flying balloons were used. For the time series of up to 90 min obtained with the tethersondes both averages and standard deviations are compared. The mean difference for all measurements amounted to 3.5 {mu}g/m{sup 3} only, corresponding to 3.5%. For the instantaneous profiles compared to the free flying sondes the differences were only marginally larger, with a mean value of 3.6 {mu}g/m{sup 3} corresponding to 4.1%. With two exceptions all averages for a single profile stayed below 7 {mu}g/m{sup 3}. Larger individual excursions were observed. In some cases, in particular in regions of steep aerosol gradients at layer boundaries, most probably the lidar values cause the deviation, while in other cases the ECC-sonde is suspected to yield erroneous results. For the measured standard deviation those retrieved from DIAL measurements are generally larger than measured by the ECC-sondes, especially in regions of inhomogeneous aerosol distribution. For the measurements reported here, this is attributed to residual errors in the aerosol correction of the DIAL measurements. The general agreement found in this intercomparison is regarded as excellent, DIAL is proven to be a very valuable tool for detailed studies of the ozone distribution in the lower troposphere. (orig.)

Development of Compact Ozonizer with High Ozone Output by Pulsed Power

Science.gov (United States)

Tanaka, Fumiaki; Ueda, Satoru; Kouno, Kanako; Sakugawa, Takashi; Akiyama, Hidenori; Kinoshita, Youhei

Conventional ozonizer with a high ozone output using silent or surface discharges needs a cooling system and a dielectric barrier, and therefore becomes a large machine. A compact ozonizer without the cooling system and the dielectric barrier has been developed by using a pulsed power generated discharge. The wire to plane electrodes made of metal have been used. However, the ozone output was low. Here, a compact and high repetition rate pulsed power generator is used as an electric source of a compact ozonizer. The ozone output of 6.1 g/h and the ozone yield of 86 g/kWh are achieved at 500 pulses per second, input average power of 280 W and an air flow rate of 20 L/min.

Ozone decomposition kinetics on alumina: effects of ozone partial pressure, relative humidity and repeated oxidation cycles

Directory of Open Access Journals (Sweden)

R. C. Sullivan

2004-01-01

Full Text Available The room temperature kinetics of gas-phase ozone loss via heterogeneous interactions with thin alumina films has been studied in real-time using 254nm absorption spectroscopy to monitor ozone concentrations. The films were prepared from dispersions of fine alumina powder in methanol and their surface areas were determined by an in situ procedure using adsorption of krypton at 77K. The alumina was found to lose reactivity with increasing ozone exposure. However, some of the lost reactivity could be recovered over timescales of days in an environment free of water, ozone and carbon dioxide. From multiple exposures of ozone to the same film, it was found that the number of active sites is large, greater than 1.4x1014 active sites per cm2 of surface area or comparable to the total number of surface sites. The films maintain some reactivity at this point, which is consistent with there being some degree of active site regeneration during the experiment and with ozone loss being catalytic to some degree. The initial uptake coefficients on fresh films were found to be inversely dependent on the ozone concentration, varying from roughly 10-6 for ozone concentrations of 1014 molecules/cm3 to 10-5 at 1013 molecules/cm3. The initial uptake coefficients were not dependent on the relative humidity, up to 75%, within the precision of the experiment. The reaction mechanism is discussed, as well as the implications these results have for assessing the effect of mineral dust on atmospheric oxidant levels.

Pseudo-random bit generator based on lag time series

Science.gov (United States)

García-Martínez, M.; Campos-Cantón, E.

2014-12-01

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Non-linear forecasting in high-frequency financial time series

Science.gov (United States)

Strozzi, F.; Zaldívar, J. M.

2005-08-01

A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.

Analysis of JET ELMy time series

International Nuclear Information System (INIS)

Zvejnieks, G.; Kuzovkov, V.N.

2005-01-01

Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)

Generation of ozone foam and its application for disinfection

Science.gov (United States)

Hiragaki, Keisuke; Ishimaru, Tomiya; Nakanishi, Masaru; Muraki, Ryouji; Nieda, Masanori; Yamabe, Chobei

2015-07-01

Generated ozone foam was applied to the disinfection of Pseudomonas fluorescens. The effect of disinfection has been confirmed experimentally and new equipment for the disinfection of hands using this ozone foam has been put on the market for the practical use. The ozone foam was produced in the foam generator after mixing the water including surfactant (30 mL/min) and air including ozone (1000 ppm = 2.14 g/m3 ~ 1600 ppm = 3.4 g/m3, 300 mL/min). The liquid-to-gas ratio is 100 L/m3. The concentration of dissolved ozone in the thin liquid films of the bubbles was about 3 mg/L which was measured by the chemical method of the KI absorption and titration of sodium thiosulfate solution. The disinfection test samples were prepared using the PET disk on which Pseudomonas fluorescens of its number of more than 108 were attached. Test sample was inserted into ozone foam set on the glass plate for one to 6 min. The survival rate log (N/N0 decreased with time and its value of about-2.6 (i.e., ~1/400) was obtained at 6 min (2 min × 3 times repeated). It was also confirmed that the ozone foam was useful for the disinfection of hands. For more effective disinfection (in case of taking a long time for foam melting), the ozone foam was broken by force and changed into ozone water by which the survival rate decreased ×4 (i.e., N/N0 = 1/10 000) at 4 ~ 6 min. Contribution to the topical issue "The 14th International Symposium on High Pressure Low Temperature Plasma Chemistry (HAKONE XIV)", edited by Nicolas Gherardi, Ronny Brandenburg and Lars Stollenwark

The Statistical Analysis of Time Series

CERN Document Server

Anderson, T W

2011-01-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

Analysis of time series and size of equivalent sample

International Nuclear Information System (INIS)

Bernal, Nestor; Molina, Alicia; Pabon, Daniel; Martinez, Jorge

2004-01-01

In a meteorological context, a first approach to the modeling of time series is to use models of autoregressive type. This allows one to take into account the meteorological persistence or temporal behavior, thereby identifying the memory of the analyzed process. This article seeks to pre-sent the concept of the size of an equivalent sample, which helps to identify in the data series sub periods with a similar structure. Moreover, in this article we examine the alternative of adjusting the variance of the series, keeping in mind its temporal structure, as well as an adjustment to the covariance of two time series. This article presents two examples, the first one corresponding to seven simulated series with autoregressive structure of first order, and the second corresponding to seven meteorological series of anomalies of the air temperature at the surface in two Colombian regions

Cooling tower water conditioning study. [using ozone

Science.gov (United States)

Humphrey, M. F.; French, K. R.

1979-01-01

Successful elimination of cooling tower treatment chemicals was demonstrated. Three towers functioned for long periods of time with ozone as the only treatment for the water. The water in the systems was reused as much as 30 times (cycles of concentration) without deleterious effects to the heat exchangers. Actual system blow-down was eliminated and the only makeup water added was that required to replace the evaporation and mist entrainment losses. Minimum water savings alone are approximately 75.1 1/kg/year. Cost estimates indicate that a savings of 55 percent was obtained on the systems using ozone. A major problem experienced in the use of ozone for cooling tower applications was the difficulty of accurate concentration measurements. The ability to control the operational characteristics relies on easily and accurately determined concentration levels. Present methods of detection are subject to inaccuracies because of interfering materials and the rapid destruction of the ozone.

Secondary maxima in ozone profiles

Directory of Open Access Journals (Sweden)

R. Lemoine

2004-01-01

Full Text Available Ozone profiles from balloon soundings as well as SAGEII ozone profiles were used to detect anomalous large ozone concentrations of ozone in the lower stratosphere. These secondary ozone maxima are found to be the result of differential advection of ozone-poor and ozone-rich air associated with Rossby wave breaking events. The frequency and intensity of secondary ozone maxima and their geographical distribution is presented. The occurrence and amplitude of ozone secondary maxima is connected to ozone variability and trend at Uccle and account for a large part of the total ozone and lower stratospheric ozone variability.

Transport aloft drives peak ozone in the Mojave Desert

Science.gov (United States)

VanCuren, Richard

2015-05-01

Transport of anthropogenic pollution eastward out of the Los Angeles megacity region in California has been periodically observed to reach the Colorado River and the Colorado Plateau region beyond. In the 1980s, anthropogenic halocarbon tracers measured in and near the Las Angeles urban area and at a mountain-top site near the Colorado River, 400 km downwind, were shown to have a correlated seven-day cycle explainable by transport from the urban area with a time lag of 1-2 days. Recent short term springtime intensive studies using aircraft observations and regional modeling of long range transport of ozone from the Southern California megacity region showed frequent and persistent ozone impacts at surface sites across the Colorado Plateau and Southern Rocky Mountain region, at distances up to 1500 km, also with time lags of 1-2 days. However, the timing of ozone peaks at low altitude monitoring sites within the Mojave Desert, at distances from 100 to 400 km from the South Coast and San Joaquin Valley ozone source regions, does not show the expected time-lag behavior seen in the larger transport studies. This discrepancy is explained by recognizing ozone transport across the Mojave Desert to occur in a persistent layer of polluted air in the lower free troposphere with a base level at approximately 1 km MSL. This layer impacts elevated downwind sites directly, but only influences low altitude surface ozone maxima through deep afternoon mixing. Pollutants in this elevated layer derive from California source regions (the Los Angeles megacity region and the intensive agricultural region of the San Joaquin Valley), from long-range transport from Asia, and stratospheric down-mixing. Recognition of the role of afternoon mixing during spring and summer over the Mojave explains and expands the significance of previously published reports of ozone and other pollutants observed in and over the Mojave Desert, and resolves an apparent paradox in the timing of ozone peaks due to

Treatability study of the effluent containing reactive blue 21 dye by ozonation and the mass transfer study of ozone

Science.gov (United States)

Velpula, Priyadarshini; Ghuge, Santosh; Saroha, Anil K.

2018-04-01

Ozonation is a chemical treatment process in which ozone reacts with the pollutants present in the effluent by infusion of ozone into the effluent. This study includes the effect of various parameters such as inlet ozone dose, pH of solution and initial concentration of dye on decolorization of dye in terms CRE. The maximum CRE of 98.62% with the reaction rate constant of 0.26 min-1 is achieved in 18 minutes of reaction time at inlet ozone dose of 11.5 g/m3, solution pH of 11 and 30 mg/L of initial concentration of dye. The presence of radical scavenger (Tertiary Butyl Alcohol) suppressed the CRE from 98.62% to 95.4% at high pH values indicates that the indirect mechanism dominates due to the presence of hydroxyl radicals which are formed by the decomposition of ozone. The diffusive and convective mass transfer coefficients of ozone are calculated as 1.78 × 10-5 cm2/sec and 0.075 min-1. It is observed that the fraction of resistance offered by liquid is very much high compared to gas phase indicates that the ozonation is a liquid phase mass transfer controlled operation.

Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

Energy Technology Data Exchange (ETDEWEB)

Simmhan, Yogesh; Noor, Muhammad Usman

2013-10-09

Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

Decolorization of malachite green, decolorization kinetics and stoichiometry of ozone-malachite green and removal of antibacterial activity with ozonation processes

International Nuclear Information System (INIS)

Kusvuran, Erdal; Gulnaz, Osman; Samil, Ali; Yildirim, Ozlem

2011-01-01

This study aimed to identify degradation intermediates and to investigate the stoichiometry of decolorization and degradation, decolorization kinetics, and removal of antibacterial activity of malachite green (MG) using ozonization processes. The decolorization of MG was optimal at an acidic pH value of 3 based on molecular ozone attack on MG molecules. The stoichiometric ratio of decolorization between ozone and MG was calculated to be 7.0 with a regression coefficient of 0.995, whereas the ratio for degradation was calculated as 13.1 with a regression coefficient of 0.998. With MG concentrations in the range of 0.30-1.82 mM, the concentration of decolorized MG increased with higher initial concentrations of MG, whereas the ozonolytic decolorization rates of MG, decreased with increasing initial concentration. The pseudo-first-order degradation rate constants (k') decreased with the initial concentration and ranged from 0.769 to 0.223 min -1 . Twelve different intermediates were produced during the ozonation of MG with ozonation times between 5 min and 30 min and were identified by GC-MS. Although 86% of MG in the reaction mixture was removed by ozonation after 10 min, the decrease of antibacterial activity was very low (10%) for Bacillus subtilis and Staphylococcus epidermidis because the degradation intermediates, phenol and benzoic acid, also have antibacterial activity. The antibacterial activity of both MG and its intermediates were removed successfully with ozonation times above 26 min.

Decolorization of malachite green, decolorization kinetics and stoichiometry of ozone-malachite green and removal of antibacterial activity with ozonation processes

Energy Technology Data Exchange (ETDEWEB)

Kusvuran, Erdal, E-mail: erdalkusvuran@yahoo.com [Chemistry Department, Arts and Sciences Faculty, Cukurova University, 01330 Balcali, Adana (Turkey); Gulnaz, Osman [Biology Department, Arts and Sciences Faculty, Cukurova University, 01330 Balcali, Adana (Turkey); Samil, Ali [Chemistry Department, Arts and Sciences Faculty, Sutcu Imam University, 46100 Kahramanmaras (Turkey); Yildirim, Ozlem [Chemistry Department, Arts and Sciences Faculty, Cukurova University, 01330 Balcali, Adana (Turkey)

2011-02-15

This study aimed to identify degradation intermediates and to investigate the stoichiometry of decolorization and degradation, decolorization kinetics, and removal of antibacterial activity of malachite green (MG) using ozonization processes. The decolorization of MG was optimal at an acidic pH value of 3 based on molecular ozone attack on MG molecules. The stoichiometric ratio of decolorization between ozone and MG was calculated to be 7.0 with a regression coefficient of 0.995, whereas the ratio for degradation was calculated as 13.1 with a regression coefficient of 0.998. With MG concentrations in the range of 0.30-1.82 mM, the concentration of decolorized MG increased with higher initial concentrations of MG, whereas the ozonolytic decolorization rates of MG, decreased with increasing initial concentration. The pseudo-first-order degradation rate constants (k') decreased with the initial concentration and ranged from 0.769 to 0.223 min{sup -1}. Twelve different intermediates were produced during the ozonation of MG with ozonation times between 5 min and 30 min and were identified by GC-MS. Although 86% of MG in the reaction mixture was removed by ozonation after 10 min, the decrease of antibacterial activity was very low (10%) for Bacillus subtilis and Staphylococcus epidermidis because the degradation intermediates, phenol and benzoic acid, also have antibacterial activity. The antibacterial activity of both MG and its intermediates were removed successfully with ozonation times above 26 min.

Forecasting with nonlinear time series models

DEFF Research Database (Denmark)

Kock, Anders Bredahl; Teräsvirta, Timo

In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econo- metrics are presented and some of their properties discussed. This in- cludes two models based on universal approximators: the Kolmogorov- Gabor polynomial model...... applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic...... and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently...

The stratospheric ozone and the ozone layer

International Nuclear Information System (INIS)

Zea Mazo, Jorge Anibal; Leon Aristizabal Gloria Esperanza; Eslava Ramirez Jesus Antonio

2000-01-01

An overview is presented of the principal characteristics of the stratospheric ozone in the Earth's atmosphere, with particular emphasis on the tropics and the ozone hole over the poles. Some effects produced in the atmosphere as a consequence of the different human activities will be described, and some data on stratospheric ozone will be shown. We point out the existence of a nucleus of least ozone in the tropics, stretching from South America to central Africa, with annual mean values less than 240 DU, a value lower than in the middle latitudes and close to the mean values at the South Pole. The existence of such a minimum is confirmed by mean values from measurements made on satellites or with earthbound instruments, for different sectors in Colombia, like Medellin, Bogota and Leticia

Nonparametric factor analysis of time series

OpenAIRE

Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

1998-01-01

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

Time Series Outlier Detection Based on Sliding Window Prediction

Directory of Open Access Journals (Sweden)

Yufeng Yu

2014-01-01

Full Text Available In order to detect outliers in hydrological time series data for improving data quality and decision-making quality related to design, operation, and management of water resources, this research develops a time series outlier detection method for hydrologic data that can be used to identify data that deviate from historical patterns. The method first built a forecasting model on the history data and then used it to predict future values. Anomalies are assumed to take place if the observed values fall outside a given prediction confidence interval (PCI, which can be calculated by the predicted value and confidence coefficient. The use of PCI as threshold is mainly on the fact that it considers the uncertainty in the data series parameters in the forecasting model to address the suitable threshold selection problem. The method performs fast, incremental evaluation of data as it becomes available, scales to large quantities of data, and requires no preclassification of anomalies. Experiments with different hydrologic real-world time series showed that the proposed methods are fast and correctly identify abnormal data and can be used for hydrologic time series analysis.

Metagenomics meets time series analysis: unraveling microbial community dynamics

NARCIS (Netherlands)

Faust, K.; Lahti, L.M.; Gonze, D.; Vos, de W.M.; Raes, J.

2015-01-01

The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the world's oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic

Time series forecasting based on deep extreme learning machine

NARCIS (Netherlands)

Guo, Xuqi; Pang, Y.; Yan, Gaowei; Qiao, Tiezhu; Yang, Guang-Hong; Yang, Dan

2017-01-01

Multi-layer Artificial Neural Networks (ANN) has caught widespread attention as a new method for time series forecasting due to the ability of approximating any nonlinear function. In this paper, a new local time series prediction model is established with the nearest neighbor domain theory, in

Effects of Low Ozone Concentrations and Short Exposure Times on the Mortality of Immature Stages of the Indian Meal Moth, Plodia Interpunctella (Lepidoptera: Pyralidae

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Keivanloo Ensieh

2014-07-01

Full Text Available In Iran, the Indian meal moth, Plodia interpunctella (Hübner, is one of the most important pests of such stored products as date fruits and pistachio nuts. Ozone was applied as a gas at four concentrations (0, 2, 3, and 5 ppm for four different periods (30, 60, 90, and 120 min on the immature stages of P. interpunctella. The results indicated that by increasing the concentration and exposure time, the rate of mortality increased for all tested stages. This study showed that 12-day-old larvae were more susceptible than other stages when exposed to 5 ppm ozone for 120 min. The next in order of susceptibility were pupae, then 5-day-old larvae, and 17-dayold larvae had the highest sensitivity to ozonation. At the highest concentration of ozone, for the longest time, the least mortality rate was recorded for one-day-old eggs. According to the results, a reduction in the population density of P. interpunctella in laboratory experiments is promising. However, validation studies will be necessary to fully determine the potential of ozone as a replacement for the current post harvest chemical control of P. interpunctella on either pistachio nuts or date fruits.

False-nearest-neighbors algorithm and noise-corrupted time series

International Nuclear Information System (INIS)

Rhodes, C.; Morari, M.

1997-01-01

The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented. copyright 1997 The American Physical Society

Global Ozone Distribution relevant to Human Health: Metrics and present day levels from the Tropospheric Ozone Assessment Report (TOAR)

Science.gov (United States)

Fleming, Z. L.; Doherty, R. M.; von Schneidemesser, E.; Cooper, O. R.; Malley, C.; Colette, A.; Xu, X.; Pinto, J. P.; Simpson, D.; Schultz, M. G.; Hamad, S.; Moola, R.; Solberg, S.; Feng, Z.

2017-12-01

Using stations from the TOAR surface ozone database, this study quantifies present-day global and regional distributions of five ozone metrics relevant for both short-term and long-term human exposure. These metrics were explored at ozone monitoring sites globally, and re-classified for this project as urban or non-urban using population densities and night-time lights. National surface ozone limit values are usually related to an annual number of exceedances of daily maximum 8-hour running mean (MDA8), with many countries not even having any ozone limit values. A discussion and comparison of exceedances in the different ozone metrics, their locations and the seasonality of exceedances provides clues as to the regions that potentially have more serious ozone health implications. Present day ozone levels (2010-2014) have been compared globally and show definite geographical differences (see Figure showing the annual 4th highest MDA8 for present day ozone for all non-urban stations). Higher ozone levels are seen in western compared to eastern US, and between southern and northern Europe, and generally higher levels in east Asia. The metrics reflective of peak concentrations show highest values in western North America, southern Europe and East Asia. A number of the metrics show similar distributions of North-South gradients, most prominent across Europe and Japan. The interquartile range of the regional ozone metrics was largest in East Asia, higher for urban stations in Asia but higher for non-urban stations in Europe and North America. With over 3000 monitoring stations included in this analysis and despite the higher densities of monitoring stations in Europe, north America and East Asia, this study provides the most comprehensive global picture to date of surface ozone levels in terms of health-relevant metrics.

The roles of ozone and zeolite on reactive dye degradation in electrical discharge reactors.

Science.gov (United States)

Peternel, L; Kusic, H; Koprivanac, N; Locke, B R

2006-05-01

In this study high voltage pulsed corona electrical discharge advanced oxidation processes (AOPs) were applied to bleach and degrade C.I. Reactive Green 8 and C.I. Reactive Red 45 organic dyes in water solutions. Two types of hybrid gas/liquid high voltage electrical discharge (corona) reactors, known as hybrid series and hybrid parallel were studied. The difference between these reactors relates to electrode configuration, which affects the amounts of ozone, hydrogen peroxide and hydroxyl radicals produced. Experiments were conducted using dye concentrations of 20 mgl(-1) and 75 mgl(-1), with and without NH4ZSM5 zeolite addition in order to determine possible effects of added solid particles to total process efficiency. The role of ozone in combination with zeolites was assessed through comparative direct ozonation experiments with ozone supplied by an ozone generator. UV/VIS spectrophotometric measurements and measurements of total organic carbon (TOC) were used for the determination of decolorization and mineralization rates.

Ozone impact minimization through coordinated scheduling of turnaround operations from multiple olefin plants in an ozone nonattainment area

Science.gov (United States)

Ge, Sijie; Wang, Sujing; Xu, Qiang; Ho, Thomas

2018-03-01

Turnaround operations (start-up and shutdown) are critical operations in olefin plants, which emit large quantities of VOCs, NOx and CO. The emission has great potentials to impact the ozone level in ozone nonattainment areas. This study demonstrates a novel practice to minimize the ozone impact through coordinated scheduling of turnaround operations from multiple olefin plants located in Houston, Texas, an ozone nonattainment area. The study considered two olefin plants scheduled to conduct turnaround operations: one start-up and one shutdown, simultaneously on the same day within a five-hour window. Through dynamic simulations of the turnaround operations using ASPEN Plus Dynamics and air quality simulations using CAMx, the study predicts the ozone impact from the combined effect of the two turnaround operations under different starting-time scenarios. The simulations predict that the ozone impact from planned turnaround operations ranges from a maximum of 11.4 ppb to a minimum of 1.4 ppb. Hence, a reduction of up to 10.0 ppb can be achieved on a single day based on the selected two simulation days. This study demonstrates a cost-effective and environmentally benign ozone control practice for relevant stakeholders, including environmental agencies, regional plant operators, and local communities.

CauseMap: fast inference of causality from complex time series.

Science.gov (United States)

Maher, M Cyrus; Hernandez, Ryan D

2015-01-01

Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data. Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM), a method for establishing causality from long time series data (≳25 observations). Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens' Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement CCM in Julia, a

CauseMap: fast inference of causality from complex time series

Directory of Open Access Journals (Sweden)

M. Cyrus Maher

2015-03-01

Full Text Available Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data.Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM, a method for establishing causality from long time series data (≳25 observations. Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens’ Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement

Time domain series system definition and gear set reliability modeling

International Nuclear Information System (INIS)

Xie, Liyang; Wu, Ningxiang; Qian, Wenxue

2016-01-01

Time-dependent multi-configuration is a typical feature for mechanical systems such as gear trains and chain drives. As a series system, a gear train is distinct from a traditional series system, such as a chain, in load transmission path, system-component relationship, system functioning manner, as well as time-dependent system configuration. Firstly, the present paper defines time-domain series system to which the traditional series system reliability model is not adequate. Then, system specific reliability modeling technique is proposed for gear sets, including component (tooth) and subsystem (tooth-pair) load history description, material priori/posterior strength expression, time-dependent and system specific load-strength interference analysis, as well as statistically dependent failure events treatment. Consequently, several system reliability models are developed for gear sets with different tooth numbers in the scenario of tooth root material ultimate tensile strength failure. The application of the models is discussed in the last part, and the differences between the system specific reliability model and the traditional series system reliability model are illustrated by virtue of several numerical examples. - Highlights: • A new type of series system, i.e. time-domain multi-configuration series system is defined, that is of great significance to reliability modeling. • Multi-level statistical analysis based reliability modeling method is presented for gear transmission system. • Several system specific reliability models are established for gear set reliability estimation. • The differences between the traditional series system reliability model and the new model are illustrated.

Track Irregularity Time Series Analysis and Trend Forecasting

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Jia Chaolong

2012-01-01

Full Text Available The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM (1,1 is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.

Solar dynamics influence on the atmospheric ozone

International Nuclear Information System (INIS)

Gogosheva, T.; Grigorieva, V.; Mendeva, B.; Krastev, D.; Petkov, B.

2007-01-01

A response of the atmospheric ozone to the solar dynamics has been studied using the total ozone content data, taken from the satellite experiments GOME on ERS-2 and TOMS-EP together with data obtained from the ground-based spectrophotometer Photon operating in Stara Zagora, Bulgaria during the period 1999-2005. We also use data from surface ozone observations performed in Sofia, Bulgaria. The solar activity was characterized by the sunspot daily numbers W, the solar radio flux at 10.7 cm (F10.7) and the MgII wing-to-core ratio solar index. The impact of the solar activity on the total ozone has been investigated analysing the ozone response to sharp changes of these parameters. Some of the examined cases showed a positive correlation between the ozone and the solar parameters, however, a negative correlation in other cases was found. There were some cases when the sharp increases of the solar activity did not provoke any ozone changes. The solar radiation changes during an eclipse can be considered a particular case of the solar dynamics as this event causes a sharp change of irradiance within a comparatively short time interval. The results of both - the total and surface ozone measurements carried out during the eclipses on 11 August 1999, 31 May 2003 and 29 March 2006 are presented. It was found that the atmospheric ozone behavior shows strong response to the fast solar radiation changes which take place during solar eclipse. (authors)

PRESEE: an MDL/MML algorithm to time-series stream segmenting.

Science.gov (United States)

Xu, Kaikuo; Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie

2013-01-01

Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream.

Time-varying surrogate data to assess nonlinearity in nonstationary time series: application to heart rate variability.

Science.gov (United States)

Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico

2009-03-01

We propose a method to extend to time-varying (TV) systems the procedure for generating typical surrogate time series, in order to test the presence of nonlinear dynamics in potentially nonstationary signals. The method is based on fitting a TV autoregressive (AR) model to the original series and then regressing the model coefficients with random replacements of the model residuals to generate TV AR surrogate series. The proposed surrogate series were used in combination with a TV sample entropy (SE) discriminating statistic to assess nonlinearity in both simulated and experimental time series, in comparison with traditional time-invariant (TIV) surrogates combined with the TIV SE discriminating statistic. Analysis of simulated time series showed that using TIV surrogates, linear nonstationary time series may be erroneously regarded as nonlinear and weak TV nonlinearities may remain unrevealed, while the use of TV AR surrogates markedly increases the probability of a correct interpretation. Application to short (500 beats) heart rate variability (HRV) time series recorded at rest (R), after head-up tilt (T), and during paced breathing (PB) showed: 1) modifications of the SE statistic that were well interpretable with the known cardiovascular physiology; 2) significant contribution of nonlinear dynamics to HRV in all conditions, with significant increase during PB at 0.2 Hz respiration rate; and 3) a disagreement between TV AR surrogates and TIV surrogates in about a quarter of the series, suggesting that nonstationarity may affect HRV recordings and bias the outcome of the traditional surrogate-based nonlinearity test.

Local normalization: Uncovering correlations in non-stationary financial time series

Science.gov (United States)

Schäfer, Rudi; Guhr, Thomas

2010-09-01

The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility, while preserving cross-correlations. We test this method in a Monte Carlo simulation, and apply it to empirical data for the S&P 500 stocks.

Ozone generation by nuclear irradiation of oxygen and oxygen-sulfur hexafluoride mixtures

International Nuclear Information System (INIS)

Elsayed-Ali, H.E.; Miley, G.H.

1984-01-01

A series of experimental measurements of 0/sub 3/ yield in nuclear induced 0/sub 2/ and 0/sub 2/-SF/sub 6/ discharges has been accomplished. The discharges were formed by irradiation with high-energy (MeV) He and Li ions created by neutron-induced nuclear reactions in Boron-10. Two experimental apparatus were utilized for this study; a flowing gas and a static in-core apparatus. In the former, 0/sub 2/ and 0/sub 2/-SF/sub 6/ mixtures were allowed to flow inside the irradiation cell for a known period of time. The irradiated mixture was then transported outside the reactor shielding where ozone concentrations were determined by measuring its absorption at 253.7nm. This set-up was used to study continuous irradiation with irradiation times varying from 0.1 to 0.7 seconds at dose rates of 10/sup 18/ - 10/sup 20/ eV g/sup -1/s/sup -1/. An in-core static system was utilized to monitor ozone buildup for continuous irradiation and to study yields when the reactor was pulsed giving a peak dose rate of 10/sup 24/ eV g/sup -1/s/sup -1/

Earth's ozone layer

International Nuclear Information System (INIS)

Lasa, J.

1991-01-01

The paper contain the actual results of investigations of the influence of the human activity on the Earth's ozone layer. History of the ozone measurements and of the changes in its concentrations within the last few years are given. The influence of the trace gases on both local and global ozone concentrations are discussed. The probable changes of the ozone concentrations are presented on the basis of the modelling investigations. The effect of a decrease in global ozone concentration on human health and on biosphere are also presented. (author). 33 refs, 36 figs, 5 tabs

Fuzzy time-series based on Fibonacci sequence for stock price forecasting

Science.gov (United States)

Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

2007-07-01

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

On the compatibility of Brewer total column ozone measurements in two adjacent valleys (Arosa and Davos in the Swiss Alps

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R. Stübi

2017-11-01

Full Text Available The Arosa site is well known in the ozone community for its continuous total ozone column observations that have been recorded since 1926. Originally based on Dobson sun spectrophotometers, the site has been gradually complemented by three automatic Brewer instruments, in operation since 1998. To secure the long-term ozone monitoring in this Alpine region and to benefit from synergies with the World Radiation Center, the feasibility of moving this activity to the nearby site at Davos (aerial distance of 13 km has been explored. Concerns about a possible rupture of the 90-year-long record has motivated a careful comparison of the two sites, since great attention to the data continuity and quality has always been central to the operations of the observatory at Arosa. To this end, one element of the Arosa Brewer triad has been set up at the Davos site since November 2011 to realize a campaign of parallel measurements and to study the deviations between the three Brewer instruments. The analysis of the coincident measurement shows that the differences between Arosa and Davos remain within the range of the long-term stability of the Brewer instruments. A nonsignificant seasonal cycle is observed, which could possibly be induced by a stray-light bias and the altitude difference between the two sites. These differences are shown to be lower than the short-term variability of the time series and the overall uncertainty from individual Brewer instruments and therefore are not statistically significant. It is therefore concluded that the world's longest time series of the total ozone column obtained at Arosa site could be safely extended and continued with measurements taken from instruments located at the nearby Davos site without introducing a bias to this unique record.

Ozone disintegration kinetics in the reactor for tyres decomposition

International Nuclear Information System (INIS)

Golota, V.I.; Manujlenko, O.V.; Taran, G.V.; Pis'menetskij, A.S.; Zamuriev, A.A.

2010-01-01

The results of theoretical and experimental research of ozone disintegration kinetics in the chemical reactor which is developed for decomposition of tyres in the ozone-air environment are presented. Analytical expression for dependence of ozone concentration in the reactor from time and from parameters of the task, such as volume speed of ozone-air mixture feed on a reactor input, concentration of ozone on the input to the reactor, volume speed of output of the used mixture, reactor size, and square of its internal surface is obtained. It is shown that at the same speed of ozone-air mixture pro rolling through the reactor, with growth of ozone concentration on the input, value of stationary concentration in the reactor grows, remaining always less than concentration on the input. It is also shown that at the same ozone concentration on the input, with growth of speed of ozone-air mixture pro rolling through the reactor, value of stationary ozone concentration in the reactor also grows, remaining always less than ozone concentration on the input. The ozone disintegration kinetics in the reactor in a wide range of speed of ozone-air mixture pro rolling through the reactor (0.15, 0.30, 0.45, 0.60 m3/hour) and various ozone concentration on the input (5, 10, 15, 20 g/m3) is experimentally studied. It is shown that experimental results with good accuracy coincide with the theoretical. Direct experiment showed the essential influence of the internal surface of the reactor on the ozone disintegration kinetics.

Percutaneous intradiscal ozone (O3)-injection: an experimental study in canines

International Nuclear Information System (INIS)

Yu Zhijian; He Xiaofeng; Chen Yong; Zeng Qingle; Liu Chihong; Zhao Zhongqing; Lu Yong; Li Yanhao

2002-01-01

Objective: To evaluate the influence of ozone on normal nucleus pulpous and the safety of intradiscal ozone-injection for the treatment of herniated lumbar disc. Methods: Ozone was injected into selected lumbar discs (3 ml) and the para-spinal space (7 ml) with 20 G Chiba needle under fluoroscopy in five canines. The ozone concentration was 30 μg/ml and 50 μg/ml respectively. Two discs were selected for each concentration. Total 20 discs were injected. Three of the canines were given one-time ozone-injection and were sacrificed for pathology one week, one month and two months respectively after the procedure, and the other two canines were given two-time ozone-injection and were sacrificed one month and two months respectively after the procedure. The specimens including nucleus pulpous, end-plate, spinal cord, nerve root, and greater psoas muscle were observed macroscopically and microscopically. Results: No serious behavior abnormalities were observed in all animals. The atrophy of nucleus pulpous could be observed one month after ozone-injection due to significant reduction of water and extensive proliferation of collagenous fiber. The influence on the atrophy of nucleus pulpous demonstrated no apparent difference between the selected two concentrations of ozone, but was more apparent with two-time injection than that with one-time injection. The end-plates increased slightly or moderately in thickness in 16 simples and a few of fibers in greater psoas muscle suffered slight atrophy in 5 samples. Conclusion: It is suggested that percutaneous intradiscal ozone-injection is a safe method, and can cause gradual atrophy of nucleus pulpous. This study provides the evidence of the feasibility and value of this procedure's application in clinics

Ozonation control and effects of ozone on water quality in recirculating aquaculture systems

DEFF Research Database (Denmark)

Spiliotopoulou, Aikaterini; Rojas-Tirado, Paula Andrea; Chetri, Ravi K.

2018-01-01

To address the undesired effect of chemotherapeutants in aquaculture, ozone has been suggested as an alternative to improve water quality. To ensure safe and robust treatment, it is vital to define the ozone demand and ozone kinetics of the specific water matrix to avoid ozone overdose. Different...... ozone dosages were applied to water in freshwater recirculating aquaculture systems (RAS). Experiments were performed to investigate ozone kinetics and demand, and to evaluate the effects on the water quality, particularly in relation to fluorescent organic matter. This study aimed at predicting...... a suitable ozone dosage for water treatment based on daily ozone demand via laboratory studies. These ozone dosages will be eventually applied and maintained at these levels in pilot-scale RAS to verify predictions. Selected water quality parameters were measured, including natural fluorescence and organic...

Parameterizing unconditional skewness in models for financial time series