Wavelet analyses of western US streamflow with ENSO and PDO

This study investigated the correlation between western US streamflow and two of the most important oceanic–atmospheric indices having significant effects in this region, namely, El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Data from 61 streamflow stations across six different hydrologic regions of the western USA were analyzed, using a study period of 60 years from 1951 to 2010. Continuous wavelet transformation along with cross wavelet transformation and wavelet coherence were used to analyze the interaction between streamflow and climate indices. The results showed that streamflows have changed coincidentally with both ENSO and PDO over the study period at different time-scale bands and at various time intervals. Both ENSO and PDO showed correlation with streamflow change behavior from 1980 to 2005. ENSO showed a strong correlation with streamflow across the entire study period in the 10–12 year band. PDO showed a strong correlation in bands of 8–10 years and bands beyond 16 years. The phase relationship showed that both ENSO and PDO preceded streamflow change behavior; in some instances, the variables were found to be moving in opposite directions even though they changed simultaneously. The results can be helpful in understanding the relationship between the climate indices and streamflow.

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Historical drought patterns over Canada and their teleconnections with large-scale climate signals

Hydrology and Earth System Sciences ◽

10.5194/hess-22-3105-2018 ◽

2018 ◽

Vol 22 (6) ◽

pp. 3105-3124 ◽

Cited By ~ 24

Author(s):

Zilefac Elvis Asong ◽

Howard Simon Wheater ◽

Barrie Bonsal ◽

Saman Razavi ◽

Sopan Kurkute

Keyword(s):

Large Scale ◽

Southern Oscillation ◽

Low Frequency ◽

Kendall Test ◽

Wavelet Coherence ◽

Climate Indices ◽

Data Sets ◽

Canadian Prairies ◽

Agriculture Industry ◽

Spatio Temporal

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

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Teleconnections between Monthly Rainfall Variability and Large-Scale Climate Indices in Southwestern Colombia

Water ◽

10.3390/w12071863 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1863 ◽

Cited By ~ 1

Author(s):

Teresita Canchala ◽

Wilfredo Alfonso-Morales ◽

Wilmar Loaiza Cerón ◽

Yesid Carvajal-Escobar ◽

Eduardo Caicedo-Bravo

Keyword(s):

Water Resources ◽

El Niño ◽

El Nino ◽

Southern Oscillation ◽

Rainfall Variability ◽

Monthly Rainfall ◽

Wavelet Coherence ◽

Climate Indices ◽

Annual Scale ◽

Wavelet Coherence Analysis

Given that the analysis of past monthly rainfall variability is highly relevant for the adequate management of water resources, the relationship between the climate-oceanographic indices, and the variability of monthly rainfall in Southwestern Colombia at different time scales was chosen as the research topic. It should also be noted that little-to-no research has been carried out on this topic before. For the purpose of conducting this research, we identified homogeneous rainfall regions while using Non-Linear Principal Component Analysis (NLPCA) and Self-Organizing Maps (SOM). The rainfall variability modes were obtained from the NLPCA, while their teleconnection in relation to the climate indices was obtained from Pearson’s Correlations and Wavelet Transform. The regionalization process clarified that Nariño has two regions: the Andean Region (AR) and the Pacific Region (PR). The NLPCA showed two modes for the AR, and one for the PR, with an explained variance of 75% and 48%, respectively. The correlation analyses between the first nonlinear components of AR and PR regarding climate indices showed AR high significant positive correlations with Southern Oscillation Index (SOI) index and negative correlations with El Niño/Southern Oscillation (ENSO) indices. PR showed positive ones with Niño1 + 2, and Niño3, and negative correlations with Niño3.4 and Niño4, although their synchronous relationships were not statistically significant. The Wavelet Coherence analysis showed that the variability of the AR rainfall was influenced principally by the Niño3.4 index on the 3–7-year inter-annual scale, while PR rainfall were influenced by the Niño3 index on the 1.5–3-year inter-annual scale. The El Niño (EN) events lead to a decrease and increase in the monthly rainfall on AR and PR, respectively, while, in the La Niña (LN) events, the opposite occurred. These results that are not documented in previous studies are useful for the forecasting of monthly rainfall and the planning of water resources in the area of study.

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Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India

Journal of Water and Climate Change ◽

10.2166/wcc.2021.189 ◽

2021 ◽

Author(s):

Pavan Kumar Yeditha ◽

Tarun Pant ◽

Maheswaran Rathinasamy ◽

Ankit Agarwal

Keyword(s):

Wavelet Transform ◽

Temporal Variability ◽

Global Climate ◽

Phase Relationship ◽

Wavelet Coherence ◽

Climate Indices ◽

Coherence Analysis ◽

Cross Wavelet Transform ◽

Wavelet Coherence Analysis ◽

Cross Wavelet

Abstract With the increasing stress on water resources for a developing country like India, it is pertinent to understand the dominant streamflow patterns for effective planning and management activities. This study investigates the spatiotemporal characterization of streamflow of six unregulated catchments in India. Firstly, Mann Kendall (MK) and Changepoint analysis were carried out to detect the presence of trends and any abrupt changes in hydroclimatic variables in the chosen streamflows. To unravel the relationships between the temporal variability of streamflow and its association with precipitation and global climate indices, namely, Niño 3.4, IOD, PDO, and NAO, continuous wavelet transform is used. Cross-wavelet transform and wavelet coherence analysis was also used to capture the coherent and phase relationships between streamflow and climate indices. The continuous wavelet transforms of streamflow data revealed that intra-annual (0.5 years), annual (1 year), and inter-annual (2–4 year) oscillations are statistically significant. Furthermore, a better understanding of the in-phase relationship between the streamflow and precipitation at intra-annual and annual time scales were well-captured using wavelet coherence analysis compared to cross wavelet transform. Furthermore, our analysis also revealed that streamflow observed an in-phase relationship with IOD and NAO, whereas a lag correlation with Niño 3.4 and PDO indices at intra-annual, annual and interannual time scales.

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Historical drought patterns over Canada and their relation to teleconnections

10.5194/hess-2018-122 ◽

2018 ◽

Author(s):

Zilefac Elvis Asong ◽

Howard Simon Wheater ◽

Barrie Bonsal ◽

Saman Razavi ◽

Sopan Kurkute

Keyword(s):

Large Scale ◽

Southern Oscillation ◽

Low Frequency ◽

Kendall Test ◽

Wavelet Coherence ◽

Climate Indices ◽

Data Sets ◽

Canadian Prairies ◽

Agriculture Industry ◽

Climate Event

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems and health. However, nation-wide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation-Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann Kendall test, Rotated Empirical Orthogonal Function, Continuous Wavelet Transform, and Wavelet Coherence analyses are used, respectively, to investigate the trend, spatiotemporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified―the Canadian Prairies and Northern-central Canada. The analyses also revealed the presence of a dominant periodicity of between 8–32 months in the Prairie region, and 8–40 months in the Northern central region. These cycles of low-frequency variability are found to be associated principally to the Pacific-North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, the duration, and how often they do so.

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Effect of Autocorrelation On Temporal Trends In Air-Temperature In A Northern Algeria And Links With Teleconnections Patterns

10.21203/rs.3.rs-491178/v1 ◽

2021 ◽

Author(s):

Sabrina Taïbi ◽

Ayoub Zeroual ◽

Mohamed Meddi

Keyword(s):

Southern Oscillation ◽

Statistical Tests ◽

Temporal Trends ◽

Step Change ◽

The Arctic ◽

Climate Indices ◽

East Atlantic ◽

Entire Study ◽

The North ◽

Mediterranean Oscillation

Abstract This study investigates the effect of autocorrelation on temporal trends and step change on monthly, seasonal and annual temperatures of six meteorological stations of the North of Algeria from 1950 to 2016. Afterwards, links between the general atmospheric circulation, via six climate indices, and temperature are examined. Trends of temperature are analysed using six different versions of the Mann Kendall approach while the step change of the time series is computed using the original Pettitt test and the modified-Pettitt. Statistical tests have shown an increase in annual temperatures from 0.8 to 0.9°C since the 1980’s on the coastal regions and 90’s on the highlands. This warming most often exceeds 1°C on a seasonal scale, particularly in summer, while no significant trend is observed in winter. On a monthly scale, the increase in temperatures is marked between April and October. The analysis of relationships between six climate indices and average temperatures has shown that inter-annual temperature variability is most often associated with the East Atlantic oscillation for the entire study area. Winter temperatures are influenced by the Mediterranean oscillation as well as the North Atlantic oscillation. The East Atlantic oscillation is the dominant mode of circulation in spring and summer, while in autumn temperatures are strongly linked to West Mediterranean Oscillation. However, no significant correlations have been observed between temperatures and the Arctic Oscillation and El Nino southern oscillation.

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Hydrological alteration of the upper Yangtze River and its possible links with large-scale climate indices

Hydrology Research ◽

10.2166/nh.2019.112 ◽

2019 ◽

Vol 50 (4) ◽

pp. 1120-1137

Author(s):

Qianjin Dong ◽

Debin Fang ◽

Jian Zuo ◽

Yongqiang Wang

Keyword(s):

Yangtze River ◽

Water Resource Management ◽

Large Scale ◽

Phase Relationship ◽

Wavelet Coherence ◽

Climate Indices ◽

Hydrological Alteration ◽

Upper Yangtze River ◽

The Relationship ◽

The Upper Yangtze River

Abstract The relationship between hydrological alteration and climate variability in the upper Yangtze River is not fully understood. In this paper, the periodicity features and the intercorrelation of annual and seasonal eco-flow metrics at the Yichang gauge station are analyzed for the period 1882 to 2013. Analysis is carried out to explore the formation of the eco-flow metrics and the possible linkages between eco-flow metrics and selected climate indices, using the cross-wavelet and wavelet coherence methods on data from 1948 to 2013. The results show that the variation of eco-flow metrics correlates well with some selected climate indices, but changes in different eco-flow metrics are complex. Most annual and seasonal eco-flow metrics correlate well with the Northern Hemisphere (N.H) and Indian Ocean Dipole (IOD) and have a significant common power in the two to four years band. In addition, most annual eco-flow metrics have an obvious phase relationship with the selected climate indices. However, the seasonal eco-flow metrics have no significant phase relationship with the selected climate indices. These findings provide a better understanding of how hydrological alterations of the streamflow and better water resource management can ensure ecosystem sustainability for the Yangtze River.

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Space- and time-varying associations between Bangladesh's seasonal rainfall and large-scale climate oscillations

10.21203/rs.3.rs-260105/v1 ◽

2021 ◽

Author(s):

Khalid Mahmud ◽

Chia-Jeng Chen

Keyword(s):

Time Scales ◽

Southern Oscillation ◽

Seasonal Rainfall ◽

Wavelet Coherence ◽

Climate Indices ◽

Climate Services ◽

Monsoon Rain ◽

Post Monsoon ◽

South Central ◽

Enso Indices

Abstract Understanding teleconnections of a region's climate can be beneficial to seasonal outlooks and hydro-climate services. This study aims at analyzing the teleconnections of seasonal rainfall over Bangladesh with selected climate indices, including El Niño/Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) indices. Rainfall data spanning from 1965–2017 in the seven hydrological regions are used to derive three seasonal rains, namely the pre-monsoon (March–May), monsoon (June–September), and post-monsoon (October and November) rains, for correlation- and wavelet coherence (WC)-based teleconnection analyses. Among the three seasonal rains, the post-monsoon rain shows the negative correlations, strongest with the IOD and ENSO indices. Correlations between the pre-monsoon/monsoon rain and climate indices are subject to notable spatial and temporal variations. For instance, correlations between the pre-monsoon (monsoon) rain in the South Central (South West) region and the IOD (ENSO) index shift from negative to positive after the 1980s, whereas the comprehensive negative correlations of the post-monsoon rain with the IOD and ENSO indices further enhanced from the early to recent epochs. WC analysis not only corroborates the findings of correlation analysis at shorter time scales (e.g., 1–4 years), but also reveals significant coherence at longer time scales (e.g., 8–16 years). We find that the pre-monsoon and monsoon rains experience the phase change in WC from shorter to longer scales. In contrast, the post-monsoon rain shows the consistent anti-phase WC, more dominant at the longer time scale. Both correlation and WC analyses indicate that the association patterns of the PDO mimic those of ENSO. Lastly, the analysis results of the AMO suggest quite distinct and significant association between Bangladesh's rainfall and the Atlantic Ocean.

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Disentangling spatiotemporal characteristics of six different unregulated streamflow stations in India

10.5194/egusphere-egu21-7362 ◽

2021 ◽

Author(s):

Tarun Pant ◽

Pavan kumar Yeditha ◽

Ankit Agarwal ◽

Maheswaran Rathinasamy

Keyword(s):

Wavelet Transform ◽

Water Resources ◽

Phase Relationship ◽

Wavelet Coherence ◽

Detection Methods ◽

Climate Indices ◽

Almost All ◽

Precipitation Changes ◽

The Impact ◽

Cross Wavelet

<p>With the increasing stress on water resources for a developing country like India, it is very much pertinent to study how the water resources are varying with time and investigate the dominant streamflow patterns for carrying effective planning and management activities. In this study, we attempt to investigate the spatiotemporal characterization of streamflow of six unregulated catchments in India and also quantify the impact of precipitation changes and four climate indices, namely, Ni&#241;o 3.4, IOD, PDO and NAO on streamflow. Initial analysis of streamflow and precipitation was carried out using Mann Kendall and step change detection methods. Temporal variability of streamflow and its association with precipitation and climate indices was unraveled using continuous wavelet transform and Wavelet coherence respectively. Cross-wavelet transform was also used to capture the coherent relationships and phase relationships between streamflow and climate indices. The results of the study reveal an in-phase relationship between precipitation and streamflow. The analysis also considers that streamflow is mostly affected by Ni&#241;o 3.4 and PDO indices. Based on the results of this work, better understanding of interrelationship between the streamflow and precipitation was well captured using Wavelet coherence when compared to Cross wavelet. It was observed that almost all basins had showed the effect of changes in precipitation on streamflow. Based on these observations, it is clear that WTC can be used for understanding interrelationship between variable when compared to XWT and gives better insights regarding the interrelationship</p>

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Streamflow Variability in Colombian Pacific Basins and Their Teleconnections with Climate Indices

Water ◽

10.3390/w12020526 ◽

2020 ◽

Vol 12 (2) ◽

pp. 526 ◽

Cited By ~ 3

Author(s):

Teresita Canchala ◽

Wilmar Loaiza Cerón ◽

Félix Francés ◽

Yesid Carvajal-Escobar ◽

Rita Andreoli ◽

...

Keyword(s):

River Basin ◽

El Niño ◽

El Nino ◽

Southern Oscillation ◽

Wavelet Coherence ◽

Climate Indices ◽

Decadal Scale ◽

Streamflow Variability ◽

Wavelet Coherence Analysis ◽

Colombian Pacific

Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows in the ARB and PRB and the oceanic-atmospheric factors have not been examined considering different temporal scales. Hence, this article studies the relations of the climate indices and the variability of the streamflows in the ARB and PRB at interannual and decadal timescales. To this, the streamflow variability modes were obtained from the principal component analysis (PCA); furthermore, their linear dependence with indices of the El Niño/Southern Oscillation (ENSO), precipitation (PRP), the Choco low-level jet (CJ), and other indices were quantified through (a) Pearson and Kendall’s tau correlations, and (b) wavelet transform. The PCA presented a single significant mode for each basin, with an explained variance of around 80%. The correlation analyses between the PC1s of the ARB and PRB, and the climate indices showed significant positive (negative) high correlations with PRP, CJ, and Southern Oscillation Index (SOI) (ENSO indices). The wavelet coherence analysis showed significant coherencies between ENSO and ARB: at interannual (2–7 years) and decadal scale (8–14), preferably with the sea surface temperature (SST) in the east and west Tropical Pacific Ocean (TPO). For PRB with the SST in the central and western regions of the TPO in the interannual (4–8 years) and decadal (8–14 years) scales, the decreases (increases) in streamflow precede the El Niño (La Niña) events. These results indicate multiscale relations between the basins’ streamflow and climate phenomena not documented in previous works, relevant to forecast the extreme flow events in the Colombian Pacific rivers and for planning and implementing strategies for the sustainable use of water resources in the basins studied.

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Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Climate Dynamics ◽

10.1007/s00382-021-05638-7 ◽

2021 ◽

Author(s):

Mark D. Risser ◽

Michael F. Wehner ◽

John P. O’Brien ◽

Christina M. Patricola ◽

Travis A. O’Brien ◽

...

Keyword(s):

Climate Variability ◽

Extreme Precipitation ◽

Southern Oscillation ◽

Statistical Significance ◽

In Situ Measurements ◽

Climate Indices ◽

Natural Climate Variability ◽

Modes Of Variability ◽

Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

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