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

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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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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Multiscale Spatio-Temporal Changes of Precipitation Extremes in Beijing-Tianjin-Hebei Region, China during 1958–2017

Atmosphere ◽

10.3390/atmos10080462 ◽

2019 ◽

Vol 10 (8) ◽

pp. 462 ◽

Cited By ~ 1

Author(s):

Xiaomeng Song ◽

Xianju Zou ◽

Chunhua Zhang ◽

Jianyun Zhang ◽

Fanzhe Kong

Keyword(s):

Large Scale ◽

Southern Oscillation ◽

Periodic Oscillation ◽

Precipitation Extremes ◽

Climate Indices ◽

Climate Anomalies ◽

Wet Precipitation ◽

Spatio Temporal ◽

One Year ◽

Periodic Components

In this study, based on daily precipitation records during 1958–2017 from 28 meteorological stations in the Beijing-Tianjin-Hebei (BTH) region, the spatio-temporal variations in precipitation extremes defined by twelve indices are analyzed by the methods of linear regression, Mann-Kendall test and continuous wavelet transform. The results showed that the spatial patterns of all the indices except for consecutive dry days (CDD) and consecutive wet days (CWD) were similar to that of annual total precipitation with the high values in the east and the low value in the west. Regionally averaged precipitation extremes were characterized by decreasing trends, of which five indices (i.e., very heavy precipitation days (R50), very wet precipitation (R95p), extreme wet precipitation (R99p), max one-day precipitation (R × 1day), and max five-day precipitation (R × 5day)) exhibited significantly decreasing trends at 5% level. From monthly and seasonal scale, almost all of the highest values in R × 1day and R × 5day occurred in summer, especially in July and August due to the impacts of East Asian monsoon climate on inter-annual uneven distribution of precipitation. The significant decreasing trends in annual R×1day and R×5day were mainly caused by the significant descend in summer. Besides, the possible associations between precipitation extremes and large-scale climate anomalies (e.g., ENSO (El Niño Southern Oscillation), NAO (North Atlantic Oscillation), IOD (Indian Ocean Dipole), and PDO (Pacific Decadal Oscillation)) were also investigated using the correlation analysis. The results showed that the precipitation extremes were significantly influenced by ENSO with one-year ahead, and the converse correlations between the precipitation extremes and climate indices with one-year ahead and 0-year ahead were observed. Moreover, all the indices show significant two- to four-year periodic oscillation during the entire period of 1958–2017, and most of indices show significant four- to eight-year periodic oscillation during certain periods. The influences of climate anomalies on precipitation extremes were composed by different periodic components, with most of higher correlations occurring in low-frequency components.

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Effects of Climate Variability on Water Storage in the Colorado River Basin

Journal of Hydrometeorology ◽

10.1175/2009jhm1133.1 ◽

2009 ◽

Vol 10 (5) ◽

pp. 1257-1270 ◽

Cited By ~ 11

Author(s):

Ruud Hurkmans ◽

Peter A. Troch ◽

Remko Uijlenhoet ◽

Paul Torfs ◽

Matej Durcik

Keyword(s):

Soil Moisture ◽

River Basin ◽

Colorado River ◽

Decadal Variability ◽

Southern Oscillation ◽

Water Storage ◽

Low Frequency ◽

Colorado River Basin ◽

Climate Indices ◽

Deep Soil

Abstract Understanding the long-term (interannual–decadal) variability of water availability in river basins is paramount for water resources management. Here, the authors analyze time series of simulated terrestrial water storage components, observed precipitation, and discharge spanning 74 yr in the Colorado River basin and relate them to climate indices that describe variability of sea surface temperature and sea level pressure in the tropical and extratropical Pacific. El Niño–Southern Oscillation (ENSO) indices in winter [January–March (JFM)] are related to winter precipitation as well as to soil moisture and discharge in the lower Colorado River basin. The low-frequency mode of the Pacific decadal oscillation (PDO) appears to be strongly correlated with deep soil moisture. During the negative PDO phase, saturated storage anomalies tend to be negative and the “amplitudes” (mean absolute anomalies) of shallow soil moisture, snow, and discharge are slightly lower compared to periods of positive PDO phases. Predicting interannual variability, therefore, strongly depends on the capability of predicting PDO regime shifts. If indeed a shift to a cool PDO phase occurred in the mid-1990s, as data suggest, the current dry conditions in the Colorado River basin may persist.

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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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Structure of ocean circulation between the Galápagos Islands and Ecuador

Advances in Geosciences ◽

10.5194/adgeo-33-3-2013 ◽

2013 ◽

Vol 33 ◽

pp. 3-12 ◽

Cited By ~ 6

Author(s):

C. Collins ◽

A. Mascarenhas ◽

R. Martinez

Keyword(s):

Sea Level ◽

Ocean Circulation ◽

Large Scale ◽

Southern Oscillation ◽

Galapagos Islands ◽

Surface Flow ◽

Climate Indices ◽

Late Winter ◽

Coastal Current ◽

Galápagos Islands

Abstract. From 27 March to 5 April 2009, upper ocean velocities between the Galápagos Islands and Ecuador were measured using a vessel mounted ADCP. A region of possible strong cross-hemisphere exchange was observed immediately to the east of the Galápagos, where a shallow (200 m) 300 km wide northeastward surface flow transported 7–11 Sv. Underlying this strong northeastward surface current, a southward flowing undercurrent was observed which was at least 600 m thick, 100 km wide, and had an observed transport of 7–8 Sv. Next to the Ecuador coast, the shallow (< 200 m) Ecuador Coastal Current was observed to extend offshore 100 km with strongest flow, 0.33 m s−1, near the surface. Immediately to the west of the Ecuador Coastal Current, flow was directed eastward and southward into the beginnings of the Peru-Chile Countercurrent. The integral of the surface currents between the Galápagos and Ecuador agreed well with observed sea level differences. Although the correlation of the sea level differences with large scale climate indices (Niño3 and the Southern Oscillation Index) was significant, more than half of the sea level variability was not explained. Seasonal variability of the sea level difference indicated that sea level was 2 cm higher at the Galápagos during late winter and early spring, which could be associated with the pattern of northward surface flows observed by R/V Knorr.

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CLUSTER–STAFF search coil magnetometer calibration – comparisons with FGM

Geoscientific Instrumentation Methods and Data Systems ◽

10.5194/gi-3-153-2014 ◽

2014 ◽

Vol 3 (2) ◽

pp. 153-177 ◽

Cited By ~ 6

Author(s):

P. Robert ◽

N. Cornilleau-Wehrlin ◽

R. Piberne ◽

Y. de Conchy ◽

C. Lacombe ◽

...

Keyword(s):

Transfer Functions ◽

Low Frequency ◽

Temporal Analysis ◽

Fluxgate Magnetometer ◽

Data Sets ◽

Spectral Matrix ◽

Spatio Temporal ◽

Cross Calibration ◽

The Waves ◽

The Way

Abstract. The main part of the Cluster Spatio-Temporal Analysis of Field Fluctuations (STAFF) experiment consists of triaxial search coils allowing the measurements of the three magnetic components of the waves from 0.1 Hz up to 4 kHz. Two sets of data are produced, one by a module to filter and transmit the corresponding waveform up to either 10 or 180 Hz (STAFF-SC), and the second by the onboard Spectrum Analyser (STAFF-SA) to compute the elements of the spectral matrix for five components of the waves, 3 × B and 2 × E (from the EFW experiment), in the frequency range 8 Hz to 4 kHz. In order to understand the way the output signals of the search coils are calibrated, the transfer functions of the different parts of the instrument are described as well as the way to transform telemetry data into physical units across various coordinate systems from the spinning sensors to a fixed and known frame. The instrument sensitivity is discussed. Cross-calibration inside STAFF (SC and SA) is presented. Results of cross-calibration between the STAFF search coils and the Cluster Fluxgate Magnetometer (FGM) data are discussed. It is shown that these cross-calibrations lead to an agreement between both data sets at low frequency within a 2% error. By means of statistics done over 10 yr, it is shown that the functionalities and characteristics of both instruments have not changed during this period.

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Variability of Arctic Sea Ice Based on Quantile Regression and the Teleconnection with Large-Scale Climate Patterns

Journal of Climate ◽

10.1175/jcli-d-19-0375.1 ◽

2020 ◽

Vol 33 (10) ◽

pp. 4009-4025

Author(s):

Shuyu Zhang ◽

Thian Yew Gan ◽

Andrew B. G. Bush

Keyword(s):

Sea Ice ◽

Quantile Regression ◽

Large Scale ◽

Southern Oscillation ◽

Arctic Sea Ice ◽

The Arctic ◽

Climate Indices ◽

The Pacific ◽

Arctic Sea ◽

Climate Patterns

AbstractUnder global warming, Arctic sea ice has declined significantly in recent decades, with years of extremely low sea ice occurring more frequently. Recent studies suggest that teleconnections with large-scale climate patterns could induce the observed extreme sea ice loss. In this study, a probabilistic analysis of Arctic sea ice was conducted using quantile regression analysis with covariates, including time and climate indices. From temporal trends at quantile levels from 0.01 to 0.99, Arctic sea ice shows statistically significant decreases over all quantile levels, although of different magnitudes at different quantiles. At the representative extreme quantile levels of the 5th and 95th percentiles, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), and the Pacific–North American pattern (PNA) have more significant influence on Arctic sea ice than El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Atlantic multidecadal oscillation (AMO). Positive AO as well as positive NAO contribute to low winter sea ice, and a positive PNA contributes to low summer Arctic sea ice. If, in addition to these conditions, there is concurrently positive AMO and PDO, the sea ice decrease is amplified. Teleconnections between Arctic sea ice and the climate patterns were demonstrated through a composite analysis of the climate variables. The anomalously strong anticyclonic circulation during the years of positive AO, NAO, and PNA promotes more sea ice export through Fram Strait, resulting in excessive sea ice loss. The probabilistic analyses of the teleconnections between the Arctic sea ice and climate patterns confirm the crucial role that the climate patterns and their combinations play in overall sea ice reduction, but particularly for the low and high quantiles of sea ice concentration.

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Dynamic spatio-temporal generation of large-scale synthetic gridded precipitation: with improved spatial coherence of extremes

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-019-01724-9 ◽

2019 ◽

Vol 34 (9) ◽

pp. 1369-1383 ◽

Cited By ~ 1

Author(s):

Dirk Diederen ◽

Ye Liu

Keyword(s):

Large Scale ◽

Spatial Coherence ◽

Original Data ◽

Return Level ◽

Data Sets ◽

Large Set ◽

Precipitation Data ◽

Data Set ◽

Spatio Temporal ◽

Synthetic Precipitation

Abstract With the ongoing development of distributed hydrological models, flood risk analysis calls for synthetic, gridded precipitation data sets. The availability of large, coherent, gridded re-analysis data sets in combination with the increase in computational power, accommodates the development of new methodology to generate such synthetic data. We tracked moving precipitation fields and classified them using self-organising maps. For each class, we fitted a multivariate mixture model and generated a large set of synthetic, coherent descriptors, which we used to reconstruct moving synthetic precipitation fields. We introduced randomness in the original data set by replacing the observed precipitation fields in the original data set with the synthetic precipitation fields. The output is a continuous, gridded, hourly precipitation data set of a much longer duration, containing physically plausible and spatio-temporally coherent precipitation events. The proposed methodology implicitly provides an important improvement in the spatial coherence of precipitation extremes. We investigate the issue of unrealistic, sudden changes on the grid and demonstrate how a dynamic spatio-temporal generator can provide spatial smoothness in the probability distribution parameters and hence in the return level estimates.

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Probabilistic streamflow forecasts based on hydrologic persistence and large-scale climate signals in central Texas

Journal of Hydroinformatics ◽

10.2166/hydro.2010.133 ◽

2010 ◽

Vol 13 (4) ◽

pp. 760-774 ◽

Cited By ~ 6

Author(s):

Wenge Wei ◽

David W. Watkins

Keyword(s):

Large Scale ◽

Southern Oscillation ◽

River System ◽

Forecast Model ◽

Climate Indices ◽

Lead Times ◽

Forecast Performance ◽

Streamflow Forecasts ◽

Central Texas ◽

Multiple Predictor

Skillful streamflow forecasts at seasonal lead times may be useful to water managers seeking to provide reliable water supplies and maximize system benefits. In this study, streamflow autocorrelation and large-scale climate information are used to generate probabilistic streamflow forecasts for the Lower Colorado River system in central Texas. A number of potential predictors are evaluated for forecasting flows in various seasons, including large-scale climate indices related to the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and others. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. An ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distribution-oriented metrics, and implications for decision making are discussed.

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The Role of Pacific Climate on Low-Frequency Hydroclimatic Variability and Predictability in Southern Alberta, Canada

Journal of Hydrometeorology ◽

10.1175/2009jhm1119.1 ◽

2009 ◽

Vol 10 (6) ◽

pp. 1465-1478 ◽

Cited By ~ 15

Author(s):

Adam K. Gobena ◽

Thian Y. Gan

Keyword(s):

Phase Difference ◽

Southern Oscillation ◽

Spatial Coherence ◽

Low Frequency ◽

Rank Correlation ◽

Stable Phase ◽

Climate Indices ◽

Southern Alberta ◽

The 1950S ◽

Hydroclimatic Variability

Abstract Wavelet and rank correlation analysis were used to identify the links between primary Pacific climate variability modes and low-frequency hydroclimatic variability in the South Saskatchewan River basin (SSRB) of southern Alberta. The April–September average streamflow shows strong interdecadal oscillations with dominant scales of 19–22, 41–42, and 62 yr whereas statistically significant wavelet power in the interannual scale was organized on a background scale of approximately 20–25 yr. At interannual scales, strong coherency is observed between streamflow and the Niño-3 index prior to the 1940s, and in the 1950s, 1970s, and 1980s. However, a change in the phase difference from near 0° in the 1950s to near 180° in the 1980s indicates that the relationship between streamflow and the El Niño–Southern Oscillation (ENSO) is not consistent. Streamflow–Pacific–North America pattern (PNA) and streamflow–Pacific decadal oscillation (PDO) relationships at interannual scales also exhibit similar inconsistencies in phase difference. At interdecadal scales, PDO and streamflow exhibited consistently strong coherence with a stable phase difference of 180° for scales >20 yr. From the period of 1913–2001, the median partial correlation between streamflow and PDO|Niño-3 (read as PDO given Niño-3) was −0.36, whereas it was zero between streamflow and Niño-3|PDO, suggesting that PDO is the primary mode of importance in streamflow variability and predictability in the SSRB. Precipitation variability was also dominated by interdecadal oscillations; however, there is less spatial coherence for dominant scales. Correlations between the basin’s winter precipitation and climate indices are also weaker than with streamflow.

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