scholarly journals Combined analysis of temperature and rainfall variability as they relate to climate indices in Northern Algeria over the 1972–2013 period

2016 ◽  
Vol 48 (2) ◽  
pp. 584-595 ◽  
Author(s):  
Ayoub Zeroual ◽  
Ali A. Assani ◽  
Mohamed Meddi
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Coastal Region ◽  
Western Mediterranean ◽  
Seasonal Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Mean Values ◽  
Northern Algeria

Many studies have highlighted breaks in mean values of temperature and precipitation time series since the 1970s. Given that temperatures have continued to increase following that decade, the first question addressed in this study is whether other breaks in mean values have occurred since that time. The second question is to determine which climate indices influence temperature and rainfall in the coastal region of Northern Algeria. To address these two questions, we analyzed the temporal variability of temperature and annual and seasonal rainfall as they relate to four climate indices at seven coastal stations in Algeria during the 1972–2013 period using the Mann–Kendall, Lombard, and canonical correlation (CC) analysis methods.The annual and seasonal maximum, minimum and mean temperatures increased significantly over that time period. Most of these increases are gradual, implying a slow warming trend. In contrast, total annual and seasonal rainfall did not show any significant change. CC analysis revealed that annual and seasonal temperatures are negatively correlated with the Western Mediterranean Oscillation (WeMOI) climate index that characterizes atmospheric circulation over the Mediterranean basin. On the other hand, rainfall is positively correlated with a large-scale atmospheric index such as the Southern Oscillation Index.

scholarly journals Describing rainfall in northern Australia using multiple climate indices

2016 ◽  
Author(s):  
Cassandra Rogers ◽  
Jason Beringer
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Human Populations ◽  
Wet Season ◽  
Australian Monsoon ◽  
The North

Abstract. Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the implications on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas, and in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, inter-annual and decadal time scales. Precipitation trends, climate index trends, and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where inter-annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas inter-annual variability was related to a greater number of climatic phenomena (predominately the El Niño-Southern Oscillation along with Tasman Sea and Indonesian sea surface temperatures). These findings highlight the importance of rainfall variability and the need to understand the climate processes driving variability, and subsequently being able to accurately represent these in climate models in order to project future rainfall patterns in the Northern Territory.

scholarly journals Describing rainfall in northern Australia using multiple climate indices

2017 ◽  
Vol 14 (3) ◽  
pp. 597-615 ◽  
Author(s):  
Cassandra Denise Wilks Rogers ◽  
Jason Beringer
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Human Populations ◽  
Wet Season ◽  
Australian Monsoon ◽  
The North

Abstract. Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere–biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index–rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian–Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño–Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

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

2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
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.

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

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1863 ◽  
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.

scholarly journals Structure of ocean circulation between the Galápagos Islands and Ecuador

2013 ◽  
Vol 33 ◽  
pp. 3-12 ◽  
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.

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

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.

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

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 462 ◽  
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.

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

2010 ◽  
Vol 13 (4) ◽  
pp. 760-774 ◽  
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.

Including climatic variability in stochastic rainfall for flood catastrophe modelling – The effect of ENSO and SOI in China

2020 ◽  
Author(s):  
Jose Luis Salinas ◽  
Rebecca Smith ◽  
Shuangcai Li ◽  
Ludovico Nicotina ◽  
Arno Hilberts
Keyword(s):  
Tropical Cyclone ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Climatic Variability ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Natural Catastrophes ◽  
Socio Economic Impact ◽  
Catastrophe Modelling

&lt;p&gt;Damages from flooding in China account on average for 60-70% of the total Annual Losses derived from natural catastrophes. The extreme rainfall events responsible for these inundations can be broadly categorised in two well differentiated mechanisms: Tropical Cyclone (TC) induced, and non Tropical Cyclone induced (nonTC) precipitation. Between 2001 and 2015, inland nonTC rainfall flood events occurred roughly with double the frequency as TC events. While TC events can be highly destructive for coastal locations, over the entire China territory nonTC flooding accounted for more than half of the total economic flood loss for events with significant socio-economic impact, highlighting the importance of the nonTC flooding mechanism on the regional and national scale.&lt;/p&gt;&lt;p&gt;Large-scale modes of climate variability modulate in different ways TC and nonTC induced precipitation, both in the frequency and the magnitude of the events. In a stochastic rainfall generation framework, it becomes therefore useful to model these two mechanisms separately and include their differentiated long-term climatic influences in order to fully reproduce the overall observed rainfall variability. This work presents results on the effect of ENSO and Southern Oscillation Index (SOI) values on seasonal rainfall in China, and how to include this climatic variability in stochastic rainfall for flood catastrophe modelling.&lt;/p&gt;

scholarly journals Historical drought patterns over Canada and their relation to teleconnections

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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