Continuous wavelet analysis of rainfall fluctuations at interannual and decennial scales on the south-eastern part in the Democratic Republic of the Congo between 1940 and 1997
Albert Mbata MuliwavyoJean Marie Tshitenge MbuebueEdmond Phuku PhuatiKyandoghere KyamakyaFrançois Tondozi KetoRichard Bopili MbotiaN. Zana
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Wavelet analysis was applied to the standardized rainfall time series in the south-eastern in the Democratic Republic of the Congo in order to determine periods of rainfall fluctuations in this region at interannual and decennial timescales and to assess the influence of regional or remote climate phenomena on the rainfall of that sector between 1940 and 1997. The local, the global and the scale-averaged wavelet power spectrum of the rainfall time series of that sector indicate an important fluctuation between practically 1960 and 1970. Wavelet coherence spectral analysis shows that the southern oscillation El Nino phenomenon, the Western Hemisphere Warm Pool, the Atlantic Ocean climate variability and the Indian Ocean dipole have a very weak influence on rainfall on this territory. Scale-averaged wavelet coherence in 2-16 years band is lower than 0.5 whatever the climate index considered. Other factors must also be considered in the study of rainfall variability in this study area.Cite
The objective of this study is to understand the inter-annual variability of rainfall in the region Azib Soltane in the Sebou basin and determined the relationship with climatic fluctuations (represented by Western Mediterranean Oscillation Index [WMOI] and South Oscillation Index [SOI]). To attain this objective, the time series of precipitation at Azib Soltane is being studied by continuous wavelet analysis and wavelet coherence analysis, which are particularly adapted to the study of unstable process.The wavelet analysis of rainfall shows the existence of many groups of energy, from the annual to the inter-annual scales. These bands correspond to modes 1 year, 2-4 years, 4-8 years. The wavelet analysis of coherence shows a strong coherence between WMOI / rain, SOI/rain. The discontinuities can be observed in the late 1980s, 1995. The average contribution of climate fluctuations is about of 60%. Keys words : Climate fluctuation, Morocco, WMOI, SOI, wavelets, and coherence.
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Oscillation (cell signaling)
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This study assesses the performance of Fourier series in representing seasonal variations of the tropical rainfall process in Malaysia. Fourier series are incorporated into a spatial-temporal stochastic model in an attempt to make the model parsimonious and, at the same time, capture the annual variation of rainfall distribution. In view of Malaysia's main rainfall regime, the model is individually fitted for two regions with distinctive rainfall profiles: one being an urban area receiving rainfall from convective activities whilst the other receives rainfall from monsoonal activities. Since both regions are susceptible to floods, the study focuses on the rainfall process at fine resolution. Fourier series equations are developed to represent the model's parameters to describe their annual periodicity. The number of significant harmonics for each parameter is determined by inspecting the cumulative fraction of total variance explained by the significant harmonics. Results reveal that the number of significant harmonics assigned for the parameters is slightly higher in the region with monsoonal rains. The overall simulation results show that the proposed model is capable of generating tropical rainfall series from convective and monsoonal activities.Editor D. Koutsoyiannis Associate editor K. Hamed
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Abstract A recently developed non‐deterministic cell dynamic system model for atmospheric flows is summarized in this paper. The model predicts quantum‐like mechanics for atmospheric flows with inherent long‐range spatiotemporal correlations, now identified as signatures of self‐organized criticality or deterministic chaos. The model enables quantification of the power spectrum of temporal fluctuations of atmospheric flows in terms of the universal and unique characteristics of the statistical normal distribution. The model predictions are in agreement with continuous periodogram analysis of three sets each of 30 years (1871–1900, 1901–1930, 1956–1985) and one set of 25 years (1931–1955) summer monsoon rainfall time series for 29 meteorological subdivisions in the Indian region. The important results of the present study are as follows. (i) The power spectrum of the temporal fluctuations of rainfall follows the universal inverse power law form of the statistical normal distribution, with the square of the eddy amplitude representing the eddy probability density corresponding to the normalized standard deviation t equal to (logλlogλ 50 )‐1; where λ is the period length in years and λ 50 the period up to which the cumulative percentage contribution to total variance is equal to 50 and t =0. (ii) Periodicities in rainfall up to 3–4 years contribute to as much as 50 per cent of the total variance. A universal spectrum for interannual variability in summer monsoon rainfall indicates predictability of the overall pattern of rainfall fluctuations. A relatively recent and short period rainfall time series, such as the 30‐year period 1956–1985 in this study, enables identification of the universal structure of atmospheric variability. Further, short period fluctuations that are major contributors to interannual variability can be identified accurately in the 30‐year data sets and provide means for estimating the near future (up to 4 years) rainfall variation.
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Abstract This article deals with the characteristics of rainfall variability in West Africa. Time series of June—July, August—September and annual rainfall anomalies are derived for 19 regions, most of which are in the Sahel—Soudan zones of West Africa. The temporal characteristics of the series, such as trend, persistence, and low frequency variance are evaluated using regression, lag‐1 autocorrelation, and spectral analysis. High‐frequency‐filtered series are also derived. The spatial teleconnections among the regions are examined using linear correlations and principal component analysis. The study shows that there are primarily three spatial modes of rainfall variability in the region and these differ with respect to the part of the rainy season in which they are most important and to what extent they describe high and low‐frequency components of the variability. The study also defines three broad homogeneous sectors and demonstrates that the characteristics of rainfall variability in these sectors differ markedly. A strong contrast between the bulk of the Sahel—Soudan and its West Coast sector is apparent.
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Abstract A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.
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Abstract This study examines space–time characteristics of seasonal rainfall predictability in a tropical region by analyzing observed data and model simulations over Senegal. Predictability is analyzed in terms of the spatial coherence of observed interannual variability at the station scale, and within-ensemble coherence of general circulation model (GCM) simulations with observed sea surface temperatures (SSTs) prescribed. Seasonal mean rainfall anomalies are decomposed in terms of daily rainfall frequency and daily mean intensity. The observed spatial coherence is computed from a 13-station network of daily rainfall during the July–September season 1961–98 in terms of (i) interannual variability of a standardized anomaly index (i.e., the average of the normalized anomalies of each station), (ii) the external variance (i.e., the fraction of common variance among stations), and (iii) the number of spatiotemporal degrees of freedom. Spatial coherence of interannual anomalies across stations is found to be much stronger for seasonal rainfall amount and daily occurrence frequency, compared with daily mean intensity of rainfall. Combinatorial analysis of the station observations suggests that, for occurrence and seasonal amount, the empirical number of spatial degrees of freedom is largely insensitive to the number of stations considered, and is between 3 and 4 for Senegal. For daily mean intensity, by contrast, each station is found to convey almost independent information, and the number of degrees of freedom would be expected to increase for a denser network of stations. The GCM estimates of potential predictability and skill associated with the SST forcing are found to be remarkably consistent with those inferred from the observed spatial coherence: there is a moderate-to-strong skill at reproducing the interannual variations of seasonal amounts and rainfall occurrence, whereas the skill is weak for the mean intensity of rainfall. Over Senegal during July–September, it is concluded that (i) regional-scale seasonal amount and rainfall occurrence frequency are predictable from SSTs, (ii) daily mean intensity of rainfall is spatially incoherent and largely unpredictable at the regional scale, and (iii) point-score estimates of seasonal rainfall predictability and skill are subject to large sampling variability.
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Global warming and climate change are the mayor concerns of scientists, engineers and policy makers because they affect every aspect of nature and human life. Rainfall and air temperature are the most important variables used to detect climate change, through the statistical analysis of set of indices that describe temperature and rainfall extremes. Over the last decades concepts and methods from complex system science were applied in analysis of hydrological data to describe variability of hydrological processes on multiple temporal and spatial scales. In this work we analyzed daily rainfall temporal series in Recife, Brazil (during the period from 1962 to 2019) using Multifractal Detrended Fluctuation analysis (MFDFA) in order to study long term correlations in subsets of small and large rainfall fluctuations. We calculated multifractal parameters (that quantify position of maximum, width and asymmetry of multifractal spectrum) which are related to different properties of rainfall fluctuations. By comparing the values of these parameters for two subperiods of 29 years, we found that after 1990, rainfall dynamics changed towards stronger persistency, weaker multifractality and decreased dominance of small fluctuations.
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