Analysis Of Daily Time Series Research Articles

Black-Box: snapshots of daily life Time series analysis in a depressed elderly patient

Black-Box: snapshots of daily life Time series analysis in a depressed elderly patient

Crop Leaf Area Index Observations With a Wireless Sensor Network and Its Potential for Validating Remote Sensing Products

The collection of ground measurements for validating remotely sensed crop leaf area index (LAI) is labor and time intensive. This paper presents an automatic measuring system that was designed based on a wireless sensor network (WSN). The corn LAI was continuously observed from June 25 to August 24, 2012. Approximately, 42 in situ WSN measurement nodes were used in a 4 ×4 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> area in the Heihe watershed of northwest China. The data were analyzed in three ways: 1) a comparison with LAI-2000, 2) a daily and 5-day aggregated time series analysis, and 3) a comparison with a Moderate Resolution Imaging Spectroradiometer (MODIS) LAI using both a ground LAINet LAI and a scaled-up LAI through inversion of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) data. The preliminary results indicated that the measured LAI values from the LAINet were correlated with the values derived from LAI-2000 (R2 from 0.27 to 0.96 with an average of 0.42). When compared with the daily crop LAI growth trajectory, the performance of the measurement system was improved by using the data that were aggregated over a 5-day window. When compared with MODIS LAI, we found that the spatial aggregation values of the ground LAINet observations and the scaled-up ASTER LAI were identical or similar to the MODIS LAI values over time. With its low-cost and low-energy consumption, the proposed WSN observation system is a promising method for collecting ground crop LAI in flexible time and space for validating the remote sensing land products.

Complexity–entropy analysis of daily stream flow time series in the continental United States

Complexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy $${\cal H}_S$$ versus Jensen–Shannon complexity $${\cal C}_{JS}$$ that has been introduced in nonlinear dynamics analysis to classify signals according to their degrees of randomness and complexity. In this study, we explore the applicability of CECP in hydrological studies by analyzing 80 daily stream flow time series recorded in the continental United States during a period of 75 years, surrogate sequences simulated by autoregressive models (with independent or long-range memory innovations), Theiler amplitude adjusted Fourier transform and Theiler phase randomization, and a set of signals drawn from nonlinear dynamic systems. The effect of seasonality, and the relationships between the CECP quantifiers and several physical and statistical properties of the observed time series are also studied. The results point out that: (1) the CECP can discriminate chaotic and stochastic signals in presence of moderate observational noise; (2) the signal classification depends on the sampling frequency and aggregation time scales; (3) both chaotic and stochastic systems can be compatible with the daily stream flow dynamics, when the focus is on the information content, thus setting these results in the context of the debate on observational equivalence; (4) the empirical relationships between $${\mathcal H}_S$$ and $${\mathcal C}_{JS}$$ and Hurst parameter H, base flow index, basin drainage area and stream flow quantiles highlight that the CECP quantifiers can be considered as proxies of the long-term low-frequency groundwater processes rather than proxies of the short-term high-frequency surface processes; (6) the joint application of linear and nonlinear diagnostics allows for a more comprehensive characterization of the stream flow time series.

Effect of airborne Alternaria conidia, ozone exposure, PM10 and weather on emergency visits for asthma in school-age children in Kolkata city, India

Alternaria is one of the important allergenic fungal spores having special role in childhood asthma. Aerodynamic particle of <10 μm diameter (PM10) and ozone exacerbate respiratory conditions including asthma. There is no documentation determining the role of airborne concentration of Alternaria conidia, pollutants like PM10 and ozone and weather on school-age (5–18 years) children causing life-threatening episodes requiring emergency hospitalization for asthma in the megacity of Kolkata, Eastern India. We examined the relationship of daily hospitalization for asthma in school-age children and daily concentration of outdoor Alternaria conidia, ozone, PM10 and weather parameters in the atmosphere of Kolkata during 2010 using nonparametric generalized additive model (GAM). After a baseline survey (2008–2009), asthma hospitalization data for school-age children (based on case history and symptom-medication) were collected from two important city hospitals near study area in 2010. Daily Alternaria concentration was recorded using Burkard volumetric sampler. Its allergenic potential was confirmed by skin reactivity. Ozone and PM10 concentration data were collected from West Bengal Pollution Control Board. The daily time series analyses of data were performed using GAM. There are two peak seasons of asthma hospitalization, one in spring-early summer (end of March to mid April) and other in autumn (mid September–October). In GAM analyses, Alternaria conidia, ozone and PM10 were found to be significant both in spline and LOcal regrESSion smoothing method. Airborne Alternaria conidia, ozone and PM10 in the city of Kolkata are found to have effect on school-age children with asthma and appear responsible for severe attacks leading to hospitalization.

Ordinal pattern and statistical complexity analysis of daily stream flow time series

When calculating the Bandt and Pompe ordinal pattern distribution from given time series at depth D, some of the D! patterns might not appear. This could be a pure finite size effect (missing patterns) or due to dynamical properties of the observed system (forbidden patterns). For pure noise, no forbidden patterns occur, contrary to deterministic chaotic maps. We investigate long time series of river runoff for missing patterns and calculate two global properties of their pattern distributions: the Permutation Entropy and the Permutation Statistical Complexity. This is compared to purely stochastic but long-range correlated processes, the k-noise (noise with power spectrum f −k ), where k is a parameter determining the strength of the correlations. Although these processes closely resemble runoff series in their correlation behavior, the ordinal pattern statistics reveals qualitative differences, which can be phrased in terms of missing patterns behavior or the temporal asymmetry of the observed series. For the latter, an index is developed in the paper, which may be used to quantify the asymmetry of natural processes as opposed to artificially generated data.

The risk of dying on days of higher air pollution among the socially disadvantaged elderly

Rationale The estimated mortality rate associated with ambient air pollution based on general population studies may not be applicable to certain subgroups. Objective The objective of the present study was to determine the influence of age, education, employment status and income on the risk of mortality associated with ambient air pollution. Methods Daily time-series analyses tested the association between daily air pollution and daily mortality in seven Chilean urban centers during the period January 1997–December 2007. Results were adjusted for long-term trends, day-of-the week and humidex. Results Interquartile increases in particulate matter (PM 10 and PM 2.5), sulphur dioxide, nitrogen dioxide, carbon monoxide, and elemental and organic carbon were associated with a 4–7% increase in mortality among those who did not complete primary school ( p<0.05) vs. 0.5–1.5% among university graduates ( p>0.05). Among those at least 85 years of age respective estimates were 2–7%. However, among the elderly who did not complete primary school, respective estimates were 11–19% ( p<0.05). The degree of effect modification was less for income and employment status than education, and sex did not modify the results. Conclusion The socially disadvantaged, especially if elderly appear to be especially susceptible to dying on days of higher air pollution. Concentrations deemed acceptable for the general population would not appear to protect this susceptible subgroup.

Multifractal temporally weighted detrended fluctuation analysis and its application in theanalysis of scaling behavior in temperature series

Detrended fluctuation analysis (DFA) is a method widely used for the study of long-rangecorrelation and fractal scaling properties of time series. Based on DFA, multifractaldetrended fluctuation analysis (MF-DFA) was proposed to give a full description ofmore complicated time series. However, the removal of local trends in DFA isbased on discontinuous polynomial fitting. It has been shown that oscillationsin the fluctuation function and significant errors in crossover locations can beintroduced in actual implementations. In terms of time series, it is generally naturalthat points near in time are more related than points some distance apart. Suchprinciples can help us circumvent the above problems in the detrending step ofMF-DFA. Based on this rationale, the ideas of moving windows and weighted movingwindows are proposed for smoothing the log–log plot of the fluctuation functionF(s) versusthe scale s so that local effects can be taken into consideration and crossover timescales, particularlylarge timescales, can be effectively detected. The multifractal moving-window detrendedfluctuation analysis (MF-MWDFA) and the more general multifractal temporally weighteddetrended fluctuation analysis (MF-TWDFA) are proposed in this paper. Numericalsimulations and the analysis of a real-life daily temperature time series are performed inorder to substantiate the arguments and evaluate the performance. With the help ofMF-TWDFA, two more crossover points, which cannot be found by the conventionalMF-DFA, have been found in the annual-detrended temperature series by theproposed model. The crossover timescales appear to correspond rather closely withthe actual variation of temperature over time under different climate regimes.

Risks Due to Variability of K-Day Extreme Precipitation Totals and Other K-Day Extreme Events

Risks Due to Variability of K-Day Extreme Precipitation Totals and Other K-Day Extreme EventsSeveral alternative definitions of extreme events are proposed. As the first step a statistical analysis of daily precipitation measurement time series from the Hurbanovo SHMI Observatory and elaboration of potentially dangerous precipitation events is carried out. Then, combined characteristics based on daily temperature, daily air humidity and daily precipitation totals are computed. The drought index based on normalized deviations from long-term averages is defined. Alternatively, to define extreme events "Data envelopment analysis" (DEA) is employed withK-day periods of values of temperature, humidity and precipitation corresponding to decision making units. In this paper we have used the period ofK= 10 days for both methodologies for identification of extreme events. The results of all definitions of extreme events are compared.

Components of Particulate Air Pollution and Emergency Department Visits in Chile

ABSTRACT The objective of the present study was to determine the association between several elements of particulates and Emergency Department (ED) visits in a general population sample. Daily time-series analyses tested the association between daily ED visit and air pollutants and components of particulates measured in Santiago Centro, a municipality, which includes downtown Santiago during the period from 2001 to 2006. The strongest individual effect was seen for elemental carbon. A 4.76 μg/m3 increase was associated with a relative risk (RR) of 1.12 (95% confidence interval [CI] = 1.10–1.14) increase in total ED visits, and a RR of 1.18 (95% CI = 1.16–1.21) for respiratory ED visit. Using factor analysis, the authors determined that traffic combustion-related particulates were significantly associated with ED visits. Among all the sources identified, traffic combustion-related particulates had the strongest association with ED visits. A factor indicating soil-sourced particles had a weaker but statistically significant observed morbidity effect. Of the many components of particulate air pollution, those from motor vehicle exhaust had the greatest observed effect on morbidity.

Trends and seasonality in birth frequency: a comparison of Muslim and Jewish populations in southern Israel: daily time series analysis of 200 009 births, 1988-2005

The aim of this study was to assess effects of natural and artificial seasonality on reproduction in a large cohort of Muslim and Jewish women, living in the same geographic area. Population included all births between January 1988 and December 2005 (6613 daily records of 200 009 births) at the Soroka University Medical Center (southern Israel). A 'classical' time series technique based on generalized linear regression models was used. A systematic increase in the number of births during Ramadan was observed in the Muslim (P < 0.001), but not in the Jewish, population. This 'Ramadan effect', adjusted for trend and seasonal factors, was statistically significant only in Muslim multiparae (P < 0.001), where the model explained more than 48% of the variance, compared with 7% in Jewish multiparae. Seasonal birth variations in Muslim primiparae were not associated with Ramadan and were similar to those in Jewish primiparae. There were no differences in length of gestation associated with Ramadan. The findings suggest an increased conception rate following the Hajj pilgrimage, which support the hypothesis that seasonality of reproductive behavior is influenced by socio-cultural factors more than by geographic and climatic factors, and can help plan preconception interventions in Muslim populations in southern Israel.

A New Multipollutant, No-Threshold Air Quality Health Index Based on Short-Term Associations Observed in Daily Time-Series Analyses

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0–10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multi-pollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 µm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.

Tree Pollen and Hospitalization for Asthma in Urban Canada

Background: Allergy to tree pollen is common and aeroallergens have been associated with severe asthma exacerbations in the community setting. To determine the impact of different trees on asthma, we tested the association between daily hospitalizations for asthma and daily concentrations of different tree pollens in 10 large Canadian cities. Methods: Daily time-series analyses were employed to remove unwanted temporal trends. For each family or genus, results were adjusted for day of the week, temperature, barometric pressure and relative humidity. Results were expressed as the percentage increase in asthma hospitalizations related to an increase in tree pollen concentration equivalent in magnitude to its interquartile range. Results: For an interquartile increase in daily tree pollen concentration, percent increases in daily hospitalization for asthma were: 2.63% (95% CI 1.19–4.07) for Ulmus (elm), 2.45% (1.12–3.78) for the group containing Pinaceae (pine, fir, spruce), Tsuga (hemlock) and Larix (larch, tamarack); 2.32% (0.93–3.71) for the group containing Quercus (oak) and Castanea (chestnut), and 2.16% (0.70–3.62) for Acer (boxelder and maple). Statistically significant (p < 0.05) but small (<2%) effects were observed for Fraxinus (ash), Populus (aspen, poplar), Alnus (alder), Betula (birch) and Corylus (hazelnut). Conclusions: Several common tree pollens are an important cause of acute exacerbations of asthma severe enough to require hospitalization.

Using a source–receptor approach to characterise VOC behaviour in a French urban area influenced by industrial emissions Part I: Study area description, data set acquisition and qualitative data analysis of the data set

The global objective of this two part study was (1) to conduct VOC measurements in order to further understand VOC behaviour in an urban area influenced by industrial emissions and (2) to evaluate the role of these specific sources relative to urban sources. In this first paper a thorough descriptive and qualitative analysis is performed. A second article will be devoted to the quantitative analysis using Chemical Mass Balance (CMB) modelling. In the Dunkerque (France) area most industrial sources are situated in the north and the west of the receptor site whereas urban and traffic sources are located in the south and the east. A data set constituted of nearly 330,000 VOC data has been developed from the hourly measurements of 53 VOCs for 1 year from September 2002 to August 2003. It also contains meteorological parameters such as temperature, wind direction and wind speed. Using different graphical methods, the influence of the different sources on the ambient VOC concentrations has been highlighted at different time scales. In this work, the analysis of daily time series for the 53 VOCs shows the influence of traffic exhaust emissions because of the increases at traffic rush hours. Besides, the seasonal evolution of the VOC/acetylene ratio points out the influence of evaporative sources on ambient VOC concentration. Concerning other point sources, the variations of measured VOC concentrations for different wind directions and scatter plots of VOC hourly concentrations highlight the influence of some industrial sources.

Statistical quality control for local‐scale extreme temperatures. Case study: Lisbon, Portugal

AbstractOne of the biggest constraints to the study of meteorological fields is the fact that ground‐based meteorological networks do not operate over a common period of adequate length. In general, the biggest drawback is that recorded data must be gap‐filled and quality controlled (coherent, consistent and homogeneous) to provide a reliable, continuous, reference daily/monthly/yearly series. This paper addresses procedures for statistical quality control of extremes of air temperature (daily maximum and minimum) time series. The diagnostic was accomplished based on the analysis of daily time series (1941–1996), monthly time series (1941–2001) and yearly time series (1941–2001) from 18 meteorological stations located in the Lisbon (Portugal) metropolitan region. To obtain insight into the quality of the series of the temperature data, objective statistical tests for departure from homogeneity were applied to the time series. To illustrate the procedures, one assesses the homogeneity of the reconstructed time series to check the quality of the ‘virtual’ observations and some tests were run over the annual, seasonal and monthly series of extreme temperatures. None of these assessments was able to detect a spatial non‐homogeneity in the temperature series around the tested years. As expected, the optimal interpolation approach for time series reconstruction, proposed by Lucio and Deus (2005), seems to be robust, considering a wide range of methods to test homogeneity of the reconstructed time series. Afterwards, one can apply the reconstituted monthly series of extreme air temperature anomalies, for each meteorological station, to analyse the respective trends, when they exist. Copyright © 2007 Royal Meteorological Society

Daily air pollution time series analysis of Isfahan City

Different time series analysis of daily air pollution of Isfahan city were performed in this study. Descriptive analysis showed different long-term variation of daily air pollution. High persistence in daily air pollution time series were identified using autocorrelation function except for SO 2 which seemed to be short memory. Standardized air pollution index (SAPI) time series were also calculated to compare fluctuation of different time series with different levels. SAPI time series indicated that NO and NO 2 , CH 4 and non-CH 4 have similar time fluctuations. The effects of weather condition and vehicle accumulation in Isfahan city in cold and warm seasons are also distinguished in SAPI plots.

The North–South Asymmetry of Soft X-RAY Flare Index During Solar Cycles 21, 22 and 23

In this paper the N-S asymmetry of the soft X-ray flare index during the solar cycles 21, 22 and 23 has been analyzed. The results show the existence of a real N-S asymmetry which is strengthened during solar minimum. The slope of the regression lines fitted to the daily values of asymmetry time series has been found to be negative in all the three cycles. The yearly asymmetry curve can be fitted by a sinusoidal function with a period of eleven years. The power spectral analysis of daily asymmetry time series reveals the significant periods of around 28.26 days, 550.73 days and 3.72 years.

The Role of Fungal Spores in Thunderstorm Asthma

To document the existence and investigate the etiology of "thunderstorm asthma," which has been reported sporadically over the past 20 years. We assessed the relationship between thunderstorms, air pollutants, aeroallergens, and asthma admissions to a children's hospital emergency department over a 6-year period. During thunderstorm days (n = 151 days) compared to days without thunderstorms (n = 919 days), daily asthma visits increased from 8.6 to 10 (p < 0.05), and air concentrations of fungal spores doubled (from 1,512 to 2,749/m(3)), with relatively smaller changes in pollens and air pollutants. Daily time-series analyses across the 6 years of observation, irrespective of the presence or absence of thunderstorms, demonstrated that an increase in total spores, equivalent to its seasonal mean, was associated with a 2.2% (0.9% SE) increase in asthma visits. Our results support a relationship between thunderstorms and asthma, and suggest that the mechanism may be through increases in spores that exacerbate asthma. Replication in other climates is suggested to determine whether these findings can be generalized to other aeroallergen mixes.

Regionalisation of the base flow index from dynamically simulated flow components — a case study in the Elbe River Basin

This study investigates possibilities for the regionalisation of flow components within large river basins. One main purpose is the derivation of an empirical relationship for the estimation of the average base flow index (i.e. the ratio of base flow to total flow, BFI), which can be included into simplified models in form of decision support systems aimed at rapid integrated water resources assessment. Based on results from the hydrological models ARC/EGMO and HBV in 25 mesoscale sub basins of the macroscale Elbe River Basin, the modelled BFI is regionalised for the whole German part of the Elbe Basin, divided into 114 subbasins. For regionalisation of the average BFI multiple regression (MREG) and two geostatistical approaches (ordinary kriging (OK) and external drift kriging (EDK)) are applied using different physical catchment attributes and observed climate data as independent variables. The average base flow index is strongly related to topographical, pedological, hydrogeological and precipitation characteristics and less influenced by land cover/land use properties of the catchments. As indicated by cross validations, both EDK and MREG are suitable for regionalising the BFI with coefficients of determination of 0.80 and 0.77, respectively. Furthermore, the plausibility of the estimated BFI values is shown by comparisons with parameters calculated from statistical and fractal analysis of daily flow time series, which represent a strong relation to the regionalised BFI values.

Intraseasonal oscillations in sea surface temperature, wind stress, and sea level off the central California coast

The wavelet transform is used to conduct spectral and cross-spectral analysis of daily time series of sea surface temperature (SST), surface wind stress, and sea level off the central California coast for an 18-year period from 1974 through 1991. The spectral band of primary interest is given by intraseasonal time scales ranging from 30 to 70 days. Using the wavelet transform, we examine the evolutionary behavior of the frequently observed 40–50 day oscillation originally discovered in the tropics by Madden and Julian, and explore the relative importance of atmospheric vs oceanic forcing for a range of periods where both could be important. Wavelet power spectra of each variable reveal the event-like, nonstationary nature of the intraseasonal band. Peaks in wavelet power typically last for 3–4 months and occur, on average, approximately once every 18 months. Thus, their occurrence and/or duration off central California is somewhat reduced in comparison to their presence in the tropics. Although peaks in wind stress often coincide with peaks in SST and/or sea level, no consistent relationships between the variables was initially apparent. The spectra suggest, however, that relationships between the variables, if and where they do exist, are event-dependent and thus have time scales of the same order. Cross-wavelet spectra between wind stress and SST indicate that periods of high coherence (>0.90) occur on at least six occasions over the 18-year period of record. Phase differences tend to be positive, consistent with wind forcing. For wind stress vs sea level, the cross-wavelet spectra indicate that periods of high coherence, which tend to correlate with lags close to zero, also occur, but are less frequent. As with SST, the periods of high coherence usually coincide with events in the wavelet power spectra. The somewhat weaker relationship between wind stress and sea level may be due to an independent contribution to sea level through remote forcing by the ocean originating in the tropics. Finally, simple dynamical arguments regarding the lag relationships between the variables appear to be consistent with the cross-wavelet results.

Chaos, potential predictability and model validation of climate variations

In this paper, we review recent computational techniques which make it possible to separate interannual climate variability of seasonal means into chaotic and potentially predictable components. Based on analysis of variance and frequency analysis of daily time series, the techniques are applicable to both observed data sets and ensembles of multidecadal simulations using atmospheric general circulation models forced by observed sea surface temperatures and different initial conditions. A new technique for validating the interannual variability in ensembles of model simulations is also outlined. The methodologies have been applied to a study of the interannual variability of the global 200hPa geopotential height field.