Cross Wavelet Coherence Research Articles

Rainfall Variability in the Huangfuchuang Watershed and Its Relationship with ENSO

The impact of the El Niño-Southern Oscillation (ENSO) phenomenon within the Huangfuchuan watershed, one of the major first-order sub-basins in the middle region of the Yellow River, has not clearly been established. Consequently, the co-varying relationships between rainfall and El Niño/La Niña spanning the period 1954 to 2010 are investigated. Trends and step changes in annual rainfall are investigated with the Mann-Kendall and the distribution free cumulative sum (CUSUM) tests. Wavelet transforms are employed to perform spectral analysis of temporal variations in rainfall rates within the watershed. Cross wavelet and wavelet coherence transforms are used to study localized co-varying relationships between rainfall and ENSO index. Results from statistical tests indicate that rainfall in the Huangfuchuan watershed is declining, although not significantly. In addition, wavelet coherency and cross wavelet analysis, and comparison of the extracted dominant annual rainfall and 2–7 year ENSO signals demonstrate that ENSO events impact Huangfuchuan rainfall with El Niño corresponding to rainfall decline and La Niña to rainfall increment with a semiannual to annual lag.

Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

Business cycle (de)synchronization in the aftermath of the global financial crisis: implications for the Euro area

AbstractThe introduction of Euro currency was a game-changing event intended to induce convergence of Eurozone business cycles on the basis of greater monetary and fiscal integration. The benefit of participating into a common currency area exceeds the cost of losing autonomy in national monetary policy only in case of cycle co-movement. However, synchronization was put back mainly due to country-specific differences and asymmetries in terms of trade and fiscal policies that became profound at the outset of the global financial crisis. As opposed to previous studies that are mostly based on linear correlation or causality modeling, we utilize the cross-wavelet coherence measure to detect and identify the scale-dependent time-varying (de)synchronization effects amongst Eurozone and the broad Euro area business cycles before and after the financial crisis. Our results suggest that the enforcement of an active monetary policy by the ECB during crisis periods could provide an effective stabilization instrument for the entire Euro area. However, as dynamic patterns in the lead-lag relationships of the European economies are revealed, (de)synchronization varies across different frequency bands and time horizons.

Non-stationary dynamics of climate variability in synchronous influenza epidemics in Japan.

Seasonal variation in the incidence of influenza is widely assumed. However, few studies have examined non-stationary relationships between global climate factors and influenza epidemics. We examined the monthly incidence of influenza in Fukuoka, Japan, from 2000 to 2012 using cross-wavelet coherency analysis to assess the patterns of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). The monthly incidence of influenza showed cycles of 1 year with the IOD and 2 years with ENSO indices (Multivariate, Niño 4, and Niño 3.4). These associations were non-stationary and appeared to have major influences on the synchrony of influenza epidemics. Our study provides quantitative evidence that non-stationary associations have major influences on synchrony between the monthly incidence of influenza and the dynamics of the IOD and ENSO. Our results call for the consideration of non-stationary patterns of association between influenza cases and climatic factors in early warning systems.

Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets

This study analyzed the time–frequency relationship between oil price and exchange rate for Pakistan by using measures of continuous wavelet such as wavelet power, cross-wavelet power, and cross-wavelet coherency (WTC). The results of cross-wavelet analysis indicated that covariance between oil price and exchange rate is unable to give clear-cut results, but both variables have been in phase and out phase (i.e. they are anti-cyclical and cyclical in nature) in some or other durations. However, results of squared wavelet coherence disclose that both variables are out of phase and real exchange rate was leading during the entire period studied, corresponding to the 10–15 months’ scale. These results are the unique contribution of the present study, which would have not been drawn if one would have utilized any other time series or frequency domain-based approach. This finding provides evidence of anti-cyclical relationship between oil price and real effective exchange rate; however, in most of the period studied, real exchange rate was leading and passing anti-cycle effects on oil price shocks which is the major contribution of the study.

Cutaneous leishmaniasis and sand fly fluctuations are associated with el niño in panamá.

BackgroundCutaneous Leishmaniasis (CL) is a neglected tropical vector-borne disease. Sand fly vectors (SF) and Leishmania spp parasites are sensitive to changes in weather conditions, rendering disease transmission susceptible to changes in local and global scale climatic patterns. Nevertheless, it is unclear how SF abundance is impacted by El Niño Southern Oscillation (ENSO) and how these changes might relate to changes in CL transmission.Methodology and FindingsWe studied association patterns between monthly time series, from January 2000 to December 2010, of: CL cases, rainfall and temperature from Panamá, and an ENSO index. We employed autoregressive models and cross wavelet coherence, to quantify the seasonal and interannual impact of local climate and ENSO on CL dynamics. We employed Poisson Rate Generalized Linear Mixed Models to study SF abundance patterns across ENSO phases, seasons and eco-epidemiological settings, employing records from 640 night-trap sampling collections spanning 2000–2011. We found that ENSO, rainfall and temperature were associated with CL cycles at interannual scales, while seasonal patterns were mainly associated with rainfall and temperature. Sand fly (SF) vector abundance, on average, decreased during the hot and cold ENSO phases, when compared with the normal ENSO phase, yet variability in vector abundance was largest during the cold ENSO phase. Our results showed a three month lagged association between SF vector abundance and CL cases.ConclusionAssociation patterns of CL with ENSO and local climatic factors in Panamá indicate that interannual CL cycles might be driven by ENSO, while the CL seasonality was mainly associated with temperature and rainfall variability. CL cases and SF abundance were associated in a fashion suggesting that sudden extraordinary changes in vector abundance might increase the potential for CL epidemic outbreaks, given that CL epidemics occur during the cold ENSO phase, a time when SF abundance shows its highest fluctuations.

地球动力学扁率与南极涛动年际变化的小波相干分析

Variations in the Earths dynamic oblateness ( J 2) reflect large-scale interactions and dynamic changes in global layers. Previous research on the correlation between 4-6 year variations in J 2 and changes in global atmosphere, marine activity, and surface water, indicates that dominant interannual signals in J 2 arise from latitudes higher than 75°, and that variations in J 2 may be related to the ENSO (EI Nino-Southern Oscillation) phenomenon. This study, for the first time, uses a cross wavelet and wavelet coherence method to analyze the correlation between interannual variability in J 2 and the Antarctic Oscillation Index (AAOI)/Southern Oscillation Index (SOI), representing the ENSO phenomenon. The results demonstrate a strong correlation between J 2 signals and the Antarctic Oscillation (AAO) at 4-6 year time scales during 1986-2010 (correlation coefficient larger than 0.8), and show that J 2 signals lag the AAO by about 0-5 months. However, there is no significant or better correlation between variability in J 2 and other SOI signals over the same time period and scales, which may be related to differences in large scale air movement and its spatial distribution characteristics, that are reflected by the AAO and the SOI, respectively.

Effect of non-stationary climate on infectious gastroenteritis transmission in Japan.

Local weather factors are widely considered to influence the transmission of infectious gastroenteritis. Few studies, however, have examined the non-stationary relationships between global climatic factors and transmission of infectious gastroenteritis. We analyzed monthly data for cases of infectious gastroenteritis in Fukuoka, Japan from 2000 to 2012 using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Infectious gastroenteritis cases were non-stationary and significantly associated with the IOD and ENSO (Multivariate ENSO Index [MEI], Niño 1 + 2, Niño 3, Niño 4, and Niño 3.4) for a period of approximately 1 to 2 years. This association was non-stationary and appeared to have a major influence on the synchrony of infectious gastroenteritis transmission. Our results suggest that non-stationary patterns of association between global climate factors and incidence of infectious gastroenteritis should be considered when developing early warning systems for epidemics of infectious gastroenteritis.

Analyzing time–frequency relationship between interest rate, stock price and exchange rate through continuous wavelet

In this study we investigate and identify the patterns of co-movement of interest rate, stock price and exchange rate in India in the period between July 1997 and December 2010 using the cross-wavelet power, the cross-wavelet coherency, and the phase difference methodologies. Our empirical findings suggest that stock prices, exchange rates and interest rates are linked. The cross wavelet results show that stock price movements are lagging both to the exchange rate and interest rate fluctuations. The interest rate lead over the stock price movements is even clearer, especially after 2006, and it suggests that the stock market follows the interest rate signals. Comparing results of WTC and XWT, we find very clear results of phase difference of lead–lag relationship between stock prices, exchange rates and interest rates.

Climate Variability and Nonstationary Dynamics of Mycoplasma pneumoniae Pneumonia in Japan

BackgroundA stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae) pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales.MethodsWe performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO).ResultsMonthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1–2-year periodic mode in 2005–2007 and 2010–2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics.ConclusionsOur results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.

Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets

The paper examines the relationship between exchange rates and share prices using the wavelets approach, and more specifically the continuous wavelet power spectrum, cross-wavelet transform, and cross-wavelet coherency. Our results, based on Indian data, lend support to the traditional (Am Econ Rev 70:960–971, 1980) as well as the new portfolio hypothesis (Am Econ Rev 83:1356–1369, 1993), albeit over different time periods and across different time scales. The wavelet approach used in the paper has helped to uncover some interesting economic relationships within the time–frequency domain which have remained hidden thus far.

Application of Cross Wavelet Transform for ECG Pattern Analysis and Classification

In this paper, we use cross wavelet transform (XWT) for the analysis and classification of electrocardiogram (ECG) signals. The cross-correlation between two time-domain signals gives a measure of similarity between two waveforms. The application of the continuous wavelet transform to two time series and the cross examination of the two decompositions reveal localized similarities in time and frequency. Application of the XWT to a pair of data yields wavelet cross spectrum (WCS) and wavelet coherence (WCOH). The proposed algorithm analyzes ECG data utilizing XWT and explores the resulting spectral differences. A pathologically varying pattern from the normal pattern in the QT zone of the inferior leads shows the presence of inferior myocardial infarction. A normal beat ensemble is selected as the absolute normal ECG pattern template, and the coherence between various other normal and abnormal subjects is computed. The WCS and WCOH of various ECG patterns show distinguishing characteristics over two specific regions R1 and R2, where R1 is the QRS complex area and R2 is the T-wave region. The Physikalisch-Technische Bundesanstalt diagnostic ECG database is used for evaluation of the methods. A heuristically determined mathematical formula extracts the parameter(s) from the WCS and WCOH. Empirical tests establish that the parameter(s) are relevant for classification of normal and abnormal cardiac patterns. The overall accuracy, sensitivity, and specificity after combining the three leads are obtained as 97.6%, 97.3%, and 98.8%, respectively.

Load-induced changes in older individual's hand-finger tremor are ameliorated with targeting

The purpose of this study was to investigate hand–finger tremor dynamics when a load was applied to the finger in a group of healthy older adults. Moreover, we sought to determine if projecting a representation of the subject's finger tremor on a target was capable of overcoming the effects of loading so that hand–finger interactions returned to a state that was similar to normal tremor. Eight healthy older males (67±1year) performed a postural pointing task, where tremor was assessed using lightweight accelerometers attached to the hand and finger. Tremor was then assessed when a laser pointer was attached to the finger and switched off (the load), and then with the laser pointer attached and switched on pointing at targets of 40mm and 20mm in diameter. The main findings of this study were that 1) loading the finger resulted in a reduction in finger tremor amplitude and increased finger tremor regularity, but no change in hand tremor, 2) loading caused increased hand–finger 8–12Hz cross wavelet coherence and phase synchrony, and 3) pointing at different targets while the finger was loaded resulted in an increase in finger tremor amplitude, and changes in inter-segmental coupling to the extent that hand–finger dynamics reflected normal unloaded conditions. Overall, these results illustrate that the damping effects of limb loading can be offset, in part, by altering the accuracy demands of the task to make the pointing action more challenging.

Complex temporal climate signals drive the emergence of human water-borne disease

Predominantly occurring in developing parts of the world, Buruli ulcer is a severely disabling mycobacterium infection which often leads to extensive necrosis of the skin. While the exact route of transmission remains uncertain, like many tropical diseases, associations with climate have been previously observed and could help identify the causative agent's ecological niche. In this paper, links between changes in rainfall and outbreaks of Buruli ulcer in French Guiana, an ultraperipheral European territory in the northeast of South America, were identified using a combination of statistical tests based on singular spectrum analysis, empirical mode decomposition and cross-wavelet coherence analysis. From this, it was possible to postulate for the first time that outbreaks of Buruli ulcer can be triggered by combinations of rainfall patterns occurring on a long (i.e., several years) and short (i.e., seasonal) temporal scale, in addition to stochastic events driven by the El Niño-Southern Oscillation that may disrupt or interact with these patterns. Long-term forecasting of rainfall trends further suggests the possibility of an upcoming outbreak of Buruli ulcer in French Guiana.

Analyzing Time-Frequency Relationship between Interest Rate, Stock Price and Exchange Rate in India Through Continuous Wavelet

In this study we investigate and identify the patterns of co-movement of interest rate, stock price and exchange rate in India in the period between July 1997 and December 2010 using the cross-wavelet power, the cross-wavelet coherency, and the phase difference methodologies. Our empirical findings suggest that stock prices, exchange rates and interest rates are linked. Moreover, the direction and type of the relationship depends on the frequency bands and over the time period studied is not same between pairs of stock-exchange rate, stock-interest rate and exchange rate-interest rate. Also, our results provide strong evidence that there are cyclical effects and anti-cyclical effects from each other.

A Differential Effect of Indian Ocean Dipole and El Niño on Cholera Dynamics in Bangladesh

BackgroundA stationary (i.e., constant through time) association between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and epidemics of cholera in Bangladesh has been widely assumed. However, whether or not elements of the local climate that are relevant for cholera transmission have stationary signatures of the IOD on their dynamics over different time scales is still not clear. Here we report results on the time-varying relationships between the various remote and local environmental drivers and cholera incidence in Bangladesh.Methodology/Principal FindingsWe performed a cross wavelet coherency analysis to examine patterns of association between monthly cholera cases in the hospitals in Dhaka and Matlab (1983–2008) and indices for both IOD and ENSO. Our results showed that the strength of both the IOD and ENSO associations with cholera hospitalizations changed across time scales during the study period. In Dhaka, 4-year long coherent cycles were observed between cholera and the index of IOD in 1988–1997. In Matlab, the effect of ENSO was more dominant while there was no evidence for an IOD effect on cholera hospitalizations.Conclusions/SignificanceOur results call for the consideration of non-stationary, possibly non-linear, patterns of association between cholera hospitalizations and climatic factors in cholera epidemic early warning systems.

Spatial and temporal variability of water discharge in the Yellow River Basin over the past 60 years

Water discharge data of the Yellow River over the past 60 years was analyzed using the continuous wavelet transform (CWT) and Mann-Kendall (MK) test methods to identify spatial and temporal variation patterns. Potential connections between water discharge in the Yellow River Basin and El Nino/Southern Oscillation (ENSO) were also examined by the cross wavelet and wavelet coherence methods. CWT results show that the periodic oscilla- tions in water discharges had occurred at the temporal scales of 1-, 2- to 4-, 6- to 8- and 10- to 22-year. It was also found that at the annual timescale (1-year) the phase relations be- tween water discharge and ENSO were indistinct probably due to the strong influence by human disturbances. However, over the longer time scales, the phase relation becomes much clearer with an anti-phase relation being found mainly at inter-annual scale (2- to 8-year) and in-phase relation at decadal scale (16- to 22-year). According to the MK test results water discharge at most stations except Tangnaihai have decreased significantly and the abrupt change occurred in the mid-1980s or the early 1990s. The changes in water discharge were found to be influenced by both climate changes and human activities. Before 1970 the change in water discharge was positively related to precipitation variations in the river basin, but after 1970 the decrease in water discharge has been largely caused by various human activities including constructions of reservoirs, water abstraction and water-soil conservation with water abstraction being the main cause.

Phase relationship between the relative sunspot number and solar 10.7 cm flux

A range of analysis approaches, namely continuous wavelet, cross wavelet, and wavelet coherence analyses, are employed to clarify the phase relationship between the smoothed monthly mean sunspot number and solar 10.7 cm flux (F10.7). Analysis shows that there is a region of high spectral power sitting across the Schwabe cycle belt, where the two time series are in phase. However, analysis of the cross-wavelet transform and wavelet coherence unveils asynchronous behavior featured with phase mixing in the high-frequency components of sunspot activity and solar F10.7, which may explain the different activity properties of the photosphere and corona on a short time scale.

The Time-Delayed Correlation Analysis of the Several Factors which Affect “0801 Blizzard” Based on the Cross Wavelet and Wavelet Coherence Transform Methods

We think the " 0801 blizzard " is not only caused by La Nina events, but also caused by the combined effect of multiple factors just as "combination of abnormity" .So firstly in this paper, the mutative character of several primary affecting factors are elementarily analyzed. Then based on the cross wavelet and wavelet coherence transform methods, these factors how to affect rain and snow disasters is found in time-delayed characteristics and the correlation between them is confirmed, to further explain the partial reason of the “0801 blizzard”.

Indian Ocean Dipole drives malaria resurgence in East African highlands

Malaria resurgence in African highlands in the 1990s has raised questions about the underlying drivers of the increase in disease incidence including the role of El-Niño-Southern Oscillation (ENSO). However, climatic anomalies other than the ENSO are clearly associated with malaria outbreaks in the highlands. Here we show that the Indian Ocean Dipole (IOD), a coupled ocean-atmosphere interaction in the Indian Ocean, affected highland malaria re-emergence. Using cross-wavelet coherence analysis, we found four-year long coherent cycles between the malaria time series and the dipole mode index (DMI) in the 1990s in three highland localities. Conversely, we found a less pronounced coherence between malaria and DMI in lowland localities. The highland/lowland contrast can be explained by the effects of mesoscale systems generated by Lake Victoria on its climate basin. Our results support the need to consider IOD as a driving force in the resurgence of malaria in the East African highlands.