Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large‐scale climate anomalies
TL;DR: In this article, the authors used wavelet analysis to detect significant interannual and interdecadal oscillations and their teleconnections to large-scale climate anomalies such as El Nino-Southern Oscillation (ENSO), Pacific Decadal Oscillations (PDO), and North Atlantic OscillATION (NAO), monthly and seasonal maximum daily precipitation (MMDP and SMDP) from 131 stations across Canada were analyzed by using variants of wavelet analyses.
Abstract: To detect significant interannual and interdecadal oscillations and their teleconnections to large-scale climate anomalies such as El Nino–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO), monthly and seasonal maximum daily precipitation (MMDP and SMDP) from 131 stations across Canada were analyzed by using variants of wavelet analysis. Interannual (1–8 years) oscillations were found to be more significant than interdecadal (8–30 years) oscillations for all selected stations, and the oscillations are both spatial and time-dependent. Similarly, the significant wavelet coherence and the phase difference between leading principal components of monthly precipitation extremes and climate indices were highly variable in time and in periodicity, and a single climate index explains less than 40% of the total variability. Partial wavelet coherence analysis shows that both ENSO and PDO modulated the interannual variability and PDO modulated the interdecadal variability, of MMDP over Canada. NAO is correlated with the western MMDP at interdecadal scale and the eastern MMDP at interannual scale. The composite analysis shows that precipitation extremes at about three fourths of the stations have been significantly influenced by ENSO and PDO patterns, while about one half of the stations by the NAO patterns. The magnitude of SMDP in extreme El Nino years, and extreme PDO event of positive phase, was mostly lower (higher) over the Canadian Prairies in summer and winter (spring and autumn) than in extreme La Nina years. Overall, the degree of influence of large-scale climate patterns on Canadian precipitation extremes varies by season and by region.
Citations
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TL;DR: In this article, the authors investigated the spatiotemporal characteristics of droughts on different growth stages of maize over Northeast China during 1960-2016 and found that the changes in dryness/wetness condition presented significant periodic oscillation on different time scales.
57 citations
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TL;DR: In this article, the Mann-Kendall (MK) test was applied to detect changes in annual maximum daily precipitation (AMP) and seasonal SMP (SMP) across Canada for 223 stations in six regions during four periods (1900-2010, 1930 -2010, 1950 -2010 and 1970 -2010) and the Pettitt test was used to evaluate change points.
54 citations
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TL;DR: In this paper, a non-linear, multiscale approach based on wavelets and event synchronization is proposed for unravelling teleconnection influences on rainfall in the Indian subcontinent.
Abstract: . A better understanding of precipitation dynamics in the Indian subcontinent
is required since India's society depends heavily on reliable monsoon
forecasts. We introduce a non-linear, multiscale approach, based on wavelets
and event synchronization, for unravelling teleconnection influences on
precipitation. We consider those climate patterns with the highest relevance for
Indian precipitation. Our results suggest significant influences which are
not well captured by only the wavelet coherence analysis, the
state-of-the-art method in understanding linkages at multiple timescales.
We find substantial variation across India and across timescales. In
particular, El Nino–Southern Oscillation (ENSO) and the Indian Ocean
Dipole (IOD) mainly influence precipitation in the south-east at interannual
and decadal scales, respectively, whereas the North Atlantic Oscillation
(NAO) has a strong connection to precipitation, particularly in the northern
regions. The effect of the Pacific Decadal Oscillation (PDO) stretches across the whole country, whereas the Atlantic
Multidecadal Oscillation (AMO)
influences precipitation particularly in the central arid and semi-arid
regions. The proposed method provides a powerful approach for capturing the
dynamics of precipitation and, hence, helps improve precipitation
forecasting.
44 citations
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TL;DR: The most damaging environmental disasters that may have destructive damages on societal properties and lives are those that occur when water resources are severely depleting as mentioned in this paper, and generally, socioeconomic drought occurs when water resource depletion occurs.
Abstract: Droughts are among the most damaging environmental disasters that may have destructive damages on societal properties and lives. Generally, socio-economic drought occurs when water resource...
42 citations
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TL;DR: In this paper, the authors used wavelet coherence analysis to detect significant interannual and interdecadal oscillations in monthly precipitation extremes across India and their teleconnections to three prominent climate indices, namely, Nino 3.4, Pacific Decadal Oscillation, and Indian Ocean Dipole (IOD).
Abstract: Precipitation patterns and extremes are significantly influenced by various climatic factors and large-scale atmospheric circulation patterns. This study uses wavelet coherence analysis to detect significant interannual and interdecadal oscillations in monthly precipitation extremes across India and their teleconnections to three prominent climate indices, namely, Nino 3.4, Pacific Decadal Oscillation, and Indian Ocean Dipole (IOD). Further, partial wavelet coherence analysis is used to estimate the standalone relationship between the climate indices and precipitation after removing the effect of interdependency. The wavelet analysis of monthly precipitation extremes at 30 different locations across India reveals that (a) interannual (2–8 years) and interdecadal (8–32 years) oscillations are statistically significant, and (b) the oscillations vary in both time and space. The results from the partial wavelet coherence analysis reveal that Nino 3.4 and IOD are the significant drivers of Indian precipitation at interannual and interdecadal scales. Intriguingly, the study also confirms that the strength of influence of large-scale atmospheric circulation patterns on Indian precipitation extremes varies with spatial physiography of the region.
37 citations
References
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TL;DR: In this article, a step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nino-Southern Oscillation (ENSO).
Abstract: A practical step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nino–Southern Oscillation (ENSO). The guide includes a comparison to the windowed Fourier transform, the choice of an appropriate wavelet basis function, edge effects due to finite-length time series, and the relationship between wavelet scale and Fourier frequency. New statistical significance tests for wavelet power spectra are developed by deriving theoretical wavelet spectra for white and red noise processes and using these to establish significance levels and confidence intervals. It is shown that smoothing in time or scale can be used to increase the confidence of the wavelet spectrum. Empirical formulas are given for the effect of smoothing on significance levels and confidence intervals. Extensions to wavelet analysis such as filtering, the power Hovmoller, cross-wavelet spectra, and coherence are described. The statistical significance tests are used to give a quantitative measure of change...
12,803 citations
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TL;DR: It is demonstrated how phase angle statistics can be used to gain confidence in causal relation- ships and test mechanistic models of physical relationships between the time series and Monte Carlo methods are used to assess the statistical significance against red noise backgrounds.
Abstract: Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coher- ence for examining relationships in time frequency space be- tween two time series. We demonstrate how phase angle statistics can be used to gain confidence in causal relation- ships and test mechanistic models of physical relationships between the time series. As an example of typical data where such analyses have proven useful, we apply the methods to the Arctic Oscillation index and the Baltic maximum sea ice extent record. Monte Carlo methods are used to assess the statistical significance against red noise backgrounds. A software package has been developed that allows users to perform the cross wavelet transform and wavelet coherence (http://www.pol.ac.uk/home/research/waveletcoherence/). As we are interested in extracting low s/n ratio signals in time series we discuss only CWT in this paper. While CWT is a common tool for analyzing localized intermittent os- cillations in a time series, it is very often desirable to ex- amine two time series together that may be expected to be linked in some way. In particular, to examine whether re- gions in time frequency space with large common power have a consistent phase relationship and therefore are sug- gestive of causality between the time series. Many geophys- ical time series are not Normally distributed and we suggest methods of applying the CWT to such time series. From two CWTs we construct the Cross Wavelet Transform (XWT) which will expose their common power and relative phase in time-frequency space. We will further define a measure of Wavelet Coherence (WTC) between two CWT, which can find significant coherence even though the common power is low, and show how confidence levels against red noise back- grounds are calculated. We will present the basic CWT theory before we move on to XWT and WTC. New developments such as quanti- fying the phase relationship and calculating the WTC sig- nificance level will be treated more fully. When using the methods on time series it is important to have solid mecha- nistic foundations on which to base any relationships found, and we caution against using the methods in a "scatter-gun" approach (particularly if the time series probability density functions are modified). To illustrate how the various meth- ods are used we apply them to two data sets from meteo- rology and glaciology. Finally, we will provide links to a MatLab software package.
4,586 citations
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IBM1
TL;DR: In this paper, the authors present a regional L-moments algorithm for detecting homogeneous regions in a set of homogeneous data points and then select a frequency distribution for each region.
Abstract: Preface 1. Regional frequency analysis 2. L-moments 3. Screening the data 4. Identification of homogeneous regions 5. Choice of a frequency distribution 6. Estimation of the frequency distribution 7. Performance of the regional L-moment algorithm 8. Other topics 9. Examples Appendix References Index of notation.
2,329 citations
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TL;DR: In this article, the authors describe an investigation of the typical North American precipitation and temperature patterns associated with the El Nino/Southern Oscillation (ENSO) and analyze monthly surface temperature and precipitation data using a method designed to identify regions of the globe that have responses associated with ENSO.
Abstract: This paper describes an investigation of the “typical” North American precipitation and temperature patterns associated with the El Nino/Southern Oscillation (ENSO). Monthly surface temperature and precipitation data are analyzed using a method designed to identify regions of the globe that have responses associated with ENSO. Monthly composites, covering idealized two-year ENSO episodes, are computed for temperature and precipitation at all stations with data spanning seven or more ENSO events. The firm harmonic is extracted from the 24 monthly composite values and plotted in the form of a two-year harmonic dial vector. When plotted on a map of North America, these vectors reveal both the regions of coherent response and the phase of the responses with respect to the evolution of the ENSO episode. Time series of temperature and precipitation for the regions identified in the harmonic vector maps are examined to determine the magnitudes of the responses and the percentage of the time that the ide...
1,343 citations
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TL;DR: In this paper, the authors analyzed trends in Canadian temperature and precipitation during the 20th century using recently updated and adjusted station data and found that from 1900 to 1998, the annual mean temperature has increased between 0.5 and 1.5°C in the south.
Abstract: Trends in Canadian temperature and precipitation during the 20th century are analyzed using recently updated and adjusted station data. Six elements, maximum, minimum and mean temperatures along with diurnal temperature range (DTR), precipitation totals and ratio of snowfall to total precipitation are investigated. Anomalies from the 1961–1990 reference period were first obtained at individual stations, and were then used to generate gridded datasets for subsequent trend analyses. Trends were computed for 1900–1998 for southern Canada (south of 60°N), and separately for 1950–1998 for the entire country, due to insufficient data in the high arctic prior to the 1950s. From 1900–1998, the annual mean temperature has increased between 0.5 and 1.5°C in the south. The warming is greater in minimum temperature than in maximum temperature in the first half of the century, resulting in a decrease of DTR. The greatest warming occurred in the west, with statistically significant increases mostly seen during...
1,046 citations