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 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 The Dynamics of Australian Monsoon Bursts

2015 ◽  
Vol 73 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Gareth J. Berry ◽  
Michael J. Reeder
Keyword(s):  
Southern Oscillation ◽  
Convective Available Potential Energy ◽  
Southern Annular Mode ◽  
Climate Indices ◽  
Time Interval ◽  
Wet Season ◽  
Large Variability ◽  
Australian Monsoon ◽  
Sequence Of Events ◽  
Australian Continent

Abstract The wet season of the Australian monsoon is characterized by subseasonal periods of excessively wet or dry conditions, commonly known as monsoon bursts and breaks. This study is concerned with the synoptic evolution prior to monsoon bursts, which are defined here by abrupt transitions of the area-averaged rainfall over the tropical parts of the Australian continent. There is large variability in the number of monsoon bursts from year to year and in the time interval between consecutive monsoon bursts. Reanalysis data are used to construct a lag composite of the sequence of events prior to a monsoon burst. It is determined that a burst in the Australian monsoon is preceded by the development of a well-defined extratropical wave packet in the Indian Ocean, which propagates toward the Australian continent in the few days leading up to the onset of heavy rainfall in the tropics. As in previous studies on the monsoon onset, the extratropical disturbances propagate equatorward over the Australian continent. These extratropical systems are accompanied by lower-tropospheric airmass boundaries, which also propagate into low latitudes. Ahead of these boundaries, relatively warm moist air is advected from the surrounding oceans, locally increasing the convective available potential energy. Commonly employed climate indices show that monsoon bursts are more likely to occur when the active phase of the Madden–Julian oscillation is in the vicinity of Australia. Neither El Niño–Southern Oscillation nor the southern annular mode has a significant impact on the occurrence of monsoon bursts.

scholarly journals On the Remote Drivers of Rainfall Variability in Australia

2009 ◽  
Vol 137 (10) ◽  
pp. 3233-3253 ◽  
Author(s):  
James S. Risbey ◽  
Michael J. Pook ◽  
Peter C. McIntosh ◽  
Matthew C. Wheeler ◽  
Harry H. Hendon
Keyword(s):  
Large Scale ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Wet Season ◽  
The North ◽  
Eastern Australia ◽  
Different Seasons ◽  
The Individual

Abstract This work identifies and documents a suite of large-scale drivers of rainfall variability in the Australian region. The key driver in terms of broad influence and impact on rainfall is the El Niño–Southern Oscillation (ENSO). ENSO is related to rainfall over much of the continent at different times, particularly in the north and east, with the regions of influence shifting with the seasons. The Indian Ocean dipole (IOD) is particularly important in the June–October period, which spans much of the wet season in the southwest and southeast where IOD has an influence. ENSO interacts with the IOD in this period such that their separate regions of influence cover the entire continent. Atmospheric blocking also becomes most important during this period and has an influence on rainfall across the southern half of the continent. The Madden–Julian oscillation can influence rainfall in different parts of the continent in different seasons, but its impact is strongest on the monsoonal rains in the north. The influence of the southern annular mode is mostly confined to the southwest and southeast of the continent. The patterns of rainfall relationship to each of the drivers exhibit substantial decadal variability, though the characteristic regions described above do not change markedly. The relationships between large-scale drivers and rainfall are robust to the selection of typical indices used to represent the drivers. In most regions the individual drivers account for less than 20% of monthly rainfall variability, though the drivers relate to a predictable component of this variability. The amount of rainfall variance explained by individual drivers is highest in eastern Australia and in spring, where it approaches 50% in association with ENSO and blocking.

scholarly journals Climatology of Heavy Orographic Rainfall Induced by Tropical Cyclones over Madagascar: From Synoptic to Mesoscale Perspectives

2016 ◽  
Vol 5 (2) ◽  
pp. 132 ◽  
Author(s):  
Tatiana A. Arivelo ◽  
Yuh-Lang Lin
Keyword(s):  
Tropical Cyclones ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Eastern Coast ◽  
Quasi Biennial Oscillation ◽  
Trade Winds ◽  
Southwest Indian Ocean ◽  
The North ◽  
Orographic Rainfall

Variability of and generation mechanisms for Madagascar rainfall are studied by conducting climatological, synoptic and mesoscale analyses. It is found the rainfall variability is highly sensitive to seasons with high variability in summer (Nov-Apr). The rainfall in summer is controlled by the Intertropical Convergence Zone (ITCZ) and orographic rainfall associated with tropical cyclones (TCs), while the rainfall in winter (May-Oct) is controlled by trade winds and local orographic rainfall along the eastern coast. Synoptic analysis reveals that major climate variations in summer are associated with ITCZ position, which is closely related to TC genesis locations and quasi-biennial oscillation (QBO). Linkages between El-Niño Southern Oscillation Index (ENSO) and Southern Oscillation Index (SOI) are identified as the cause of inconsistent dry or wet summers. Mesoscale analysis depicts the importance of the orographic effects on prevailing wind, which are controlled by the orography in both seasons. In winter, the prevailing trade winds over the Southwest Indian Ocean are from the east and are split to the north and south when it impinges on Malagasy Mountains. On the other hand, in summer the prevailing easterlies are weaker leading to the production of lee vortices, in addition to the flow splitting upstream of the mountain. Thus, the flow is classified into two regimes: (a) flow-over regime with no lee vortices under high Froude number (Fr=1.2-1.8) flow, and (b) flow-around regime with lee vortices under low Fr (=0.88-1.16) flow. A case study of TC Domoina (1984) indicates that the long-lasting heavy rainfall was induced by the strong orographic blocking of Madagascar. The shorter-term (e.g., 2 days) heavy orographic precipitation is characterized by large VH ∙Ñh which is composed by two common ingredients, namely a strong low-level wind normal to the mountain (VH) and a steep mountain slope (∇h).

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 Modelling persistence in annual Australia point rainfall

2003 ◽  
Vol 7 (2) ◽  
pp. 197-211 ◽  
Author(s):  
J. P. Whiting ◽  
M. F. Lambert ◽  
A. V. Metcalfe
Keyword(s):  
Markov Model ◽  
Strong Evidence ◽  
Markov Models ◽  
Southern Oscillation ◽  
Mixture Distribution ◽  
Simulation Models ◽  
Annual Rainfall ◽  
Climate Indices ◽  
Rainfall Time Series ◽  
Fractional Differencing

Abstract. Annual rainfall time series for Sydney from 1859 to 1999 is analysed. Clear evidence of nonstationarity is presented, but substantial evidence for persistence or hidden states is more elusive. A test of the hypothesis that a hidden state Markov model reduces to a mixture distribution is presented. There is strong evidence of a correlation between the annual rainfall and climate indices. Strong evidence of persistence of one of these indices, the Pacific Decadal Oscillation (PDO), is presented together with a demonstration that this is better modelled by fractional differencing than by a hidden state Markov model. It is shown that conditioning the logarithm of rainfall on PDO, the Southern Oscillation index (SOI), and their interaction provides realistic simulation of rainfall that matches observed statistics. Similar simulation models are presented for Brisbane, Melbourne and Perth. Keywords: Hydrological persistence,hidden state Markov models, fractional differencing, PDO, SOI, Australian rainfall

scholarly journals Do Climate Models Capture the Tropical Influences on North Pacific Sea Surface Temperature Variability?

2011 ◽  
Vol 24 (23) ◽  
pp. 6203-6209 ◽  
Author(s):  
Fabian Lienert ◽  
John C. Fyfe ◽  
William J. Merryfield
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Pacific ◽  
Climate Models ◽  
Southern Oscillation ◽  
Temperature Variability ◽  
Sea Surface ◽  
Model Errors ◽  
The North ◽  
The North Pacific

Abstract This study evaluates the ability of global climate models to reproduce observed tropical influences on North Pacific Ocean sea surface temperature variability. In an ensemble of climate models, the study finds that the simulated North Pacific response to El Niño–Southern Oscillation (ENSO) forcing is systematically delayed relative to the observed response because of winter and spring mixed layers in the North Pacific that are too deep and air–sea feedbacks that are too weak. Model biases in mixed layer depth and air–sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by about 30%. The study also shows that simulated North Pacific variability has more power at lower frequencies than is observed because of model errors originating in the tropics and extratropics. Implications of these results for predictions on seasonal, decadal, and longer time scales are discussed.

scholarly journals Likely Ranges of Climate Change in Bolivia

2013 ◽  
Vol 52 (6) ◽  
pp. 1303-1317 ◽  
Author(s):  
Christian Seiler ◽  
Ronald W. A. Hutjes ◽  
Pavel Kabat
Keyword(s):  
Climate Change ◽  
Amazon Basin ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Amazon Forest ◽  
Climate Change Scenarios ◽  
Wet Season ◽  
Global Circulation Models ◽  
The Andes ◽  
Interannual Rainfall Variability

AbstractBolivia is facing numerous climate-related threats, ranging from water scarcity due to rapidly retreating glaciers in the Andes to a partial loss of the Amazon forest in the lowlands. To assess what changes in climate may be expected in the future, 35 global circulation models (GCMs) from the third and fifth phases of the Coupled Model Intercomparison Project (CMIP3/5) were analyzed for the Bolivian case. GCMs were validated against observed surface air temperature, precipitation, and incoming shortwave (SW) radiation for the period 1961–90. Weighted ensembles were developed, and climate change projections for five emission scenarios were assessed for 2070–99. GCMs revealed an overall cold, wet, and positive-SW-radiation bias and showed no substantial improvement from the CMIP3 to the CMIP5 ensemble for the Bolivian case. Models projected an increase in temperature (2.5°–5.9°C) and SW radiation (1%–5%), with seasonal and regional differences. In the lowlands, changes in annual rainfall remained uncertain for CMIP3 whereas CMIP5 GCMs were more inclined to project decreases (−9%). This pattern also applied to most of the Amazon basin, suggesting a higher risk of partial biomass loss for the CMIP5 ensemble. Both ensembles agreed on less rainfall (−19%) during drier months (June–August and September–November), with significant changes in interannual rainfall variability, but disagreed on changes during wetter months (January–March). In the Andes, CMIP3 GCMs tended toward less rainfall (−9%) whereas CMIP5 tended toward more (+20%) rainfall during parts of the wet season. The findings presented here may provide inputs for studies of climate change impact that assess how resilient human and natural systems are under different climate change scenarios.

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