scholarly journals Links between Central West Western Australian Rainfall Variability and Large-Scale Climate Drivers

2013 ◽  
Vol 26 (7) ◽  
pp. 2222-2246 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Western Australia ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Winter Season ◽  
Principal Component ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Past Century ◽  
Drying Trend

Abstract Over the past century, and especially after the 1970s, rainfall observations show an increase (decrease) of the wet summer (winter) season rainfall over northwest (southwest) Western Australia. The rainfall in central west Western Australia (CWWA), however, has exhibited comparatively much weaker coastal trends, but a more prominent inland increase during the wet summer season. Analysis of seasonally averaged rainfall data from a group of stations, representative of both the coastal and inland regions of CWWA, revealed that rainfall trends during the 1958–2010 period in the wet months of November–April were primarily associated with El Niño–Southern Oscillation (ENSO), and with the southern annular mode (SAM) farther inland. During the wet months of May–October, the Indian Ocean dipole (IOD) showed the most robust relationships. Those results hold when the effects of ENSO or IOD are excluded, and were confirmed using a principal component analysis of sea surface temperature (SST) anomalies, rainfall wavelet analyses, and point-by-point correlations of rainfall with global SST anomaly fields. Although speculative, given their long-term averages, reanalysis data suggest that from 1958 to 2010 the increase in CWWA inland rainfall largely is attributable to an increasing cyclonic anomaly trend over CWWA, bringing onshore moist tropical flow to the Pilbara coast. During May–October, the flow anomaly exhibits a transition from an onshore to offshore flow regime in the 2001–10 decade, which is consistent with the observed weaker drying trend during this period.

Interannual Tasmanian Rainfall Variability Associated with Large-Scale Climate Modes

2009 ◽  
Vol 22 (16) ◽  
pp. 4383-4397 ◽  
Author(s):  
Khalia J. Hill ◽  
Agus Santoso ◽  
Matthew H. England
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Climate Modes ◽  
Interannual Rainfall Variability ◽  
East West

Abstract Interannual rainfall variability over Tasmania is examined using observations and reanalysis data. Tasmanian rainfall is dominated by an east–west gradient of mean rainfall and variability. The Pacific–South American mode (PSA), El Niño–Southern Oscillation (ENSO), and the southern annular mode (SAM) each show clear influences on the interannual variability of Tasmanian rainfall. Composites of rainfall during each phase of ENSO and the PSA suggest a notable islandwide influence of these climate modes on Tasmanian rainfall. In contrast, the positive phase of the SAM is associated with drier conditions over the west of the island. The PSA and the SAM project most prominently over the southwest of the island, whereas the ENSO signature is strongest in the north. Empirical orthogonal functions (EOFs) of rainfall over Tasmania show a leading mode (explaining 72% of total variance) of coherent islandwide in-phase anomalies with dominant periods of 2 and 5 yr. The second EOF accounts for ∼14% of total variation, characterized by out-of-phase east–west anomalies, which is likely a combination of all three modes. The EOF1 mode can be attributed to ENSO, the PSA, and to a lesser extent the SAM.

scholarly journals Relationships between Southeast Australian Temperature Anomalies and Large-Scale Climate Drivers

2014 ◽  
Vol 27 (4) ◽  
pp. 1395-1412 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Power Spectra ◽  
Warm Season ◽  
Principal Component ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Past Century ◽  
Tasman Sea ◽  
Australian Continent

Abstract Over the past century, particularly after the 1960s, observations of mean maximum temperatures reveal an increasing trend over the southeastern quadrant of the Australian continent. Correlation analysis of seasonally averaged mean maximum temperature anomaly data for the period 1958–2012 is carried out for a representative group of 10 stations in southeast Australia (SEAUS). For the warm season (November–April) there is a positive relationship with the El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) and an inverse relationship with the Antarctic Oscillation (AAO) for most stations. For the cool season (May–October), most stations exhibit similar relationships with the AAO, positive correlations with the dipole mode index (DMI), and marginal inverse relationships with the Southern Oscillation index (SOI) and the PDO. However, for both seasons, the blocking index (BI, as defined by M. Pook and T. Gibson) in the Tasman Sea (160°E) clearly is the dominant climate mode affecting maximum temperature variability in SEAUS with negative correlations in the range from r = −0.30 to −0.65. These strong negative correlations arise from the usual definition of BI, which is positive when blocking high pressure systems occur over the Tasman Sea (near 45°S, 160°E), favoring the advection of modified cooler, higher-latitude maritime air over SEAUS. A point-by-point correlation with global sea surface temperatures (SSTs), principal component analysis, and wavelet power spectra support the relationships with ENSO and DMI. Notably, the analysis reveals that the maximum temperature variability of one group of stations is explained primarily by local factors (warmer near-coastal SSTs), rather than teleconnections with large-scale drivers.

A Monsoon-Like Southwest Australian Circulation and Its Relation with Rainfall in Southwest Western Australia

2010 ◽  
Vol 23 (6) ◽  
pp. 1334-1353 ◽  
Author(s):  
Juan Feng ◽  
Jianping Li ◽  
Yun Li
Keyword(s):  
Indian Ocean ◽  
Western Australia ◽  
Large Scale ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Late Winter ◽  
Early Winter ◽  
Winter Rainfall ◽  
Enso Modoki ◽  
Distinct Features

Abstract Using the NCEP–NCAR reanalysis, the 40-yr ECMWF Re-Analysis (ERA-40), and precipitation data from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Australian Bureau of Meteorology, the variability and circulation features influencing southwest Western Australia (SWWA) winter rainfall are investigated. It is found that the climate of southwest Australia bears a strong seasonality in the annual cycle and exhibits a monsoon-like atmospheric circulation, which is called the southwest Australian circulation (SWAC) because of its several distinct features characterizing a monsoonal circulation: the seasonal reversal of winds, alternate wet and dry seasons, and an evident land–sea thermal contrast. The seasonal march of the SWAC in extended winter (May–October) is demonstrated by pentad data. An index based on the dynamics’ normalized seasonality was introduced to describe the behavior and variation of the winter SWAC. It is found that the winter rainfall over SWWA has a significant positive correlation with the SWAC index in both early (May–July) and late (August–October) winter. In weaker winter SWAC years, there is an anticyclonic anomaly over the southern Indian Ocean resulting in weaker westerlies and northerlies, which are not favorable for more rainfall over SWWA, and the opposite combination is true in the stronger winter SWAC years. The SWAC explains not only a large portion of the interannual variability of SWWA rainfall in both early and late winter but also the long-term drying trend over SWWA in early winter. The well-coupled SWAC–SWWA rainfall relationship seems to be largely independent of the well-known effects of large-scale atmospheric circulations such as the southern annular mode (SAM), El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), and ENSO Modoki (EM). The result offers qualified support for the argument that the monsoon-like circulation may contribute to the rainfall decline in early winter over SWWA. The external forcing of the SWAC is also explored in this study.

scholarly journals Skill in Simulating Australian Precipitation at the Tropical Edge*

2016 ◽  
Vol 29 (4) ◽  
pp. 1477-1496 ◽  
Author(s):  
Penelope Maher ◽  
Steven C. Sherwood
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Linear Independence ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Hadley Cell ◽  
Model Errors ◽  
Skill Scores

Abstract Expansion of the tropics will likely affect subtropical precipitation, but observed and modeled precipitation trends disagree with each other. Moreover, the dynamic processes at the tropical edge and their interactions with precipitation are not well understood. This study assesses the skill of climate models to reproduce observed Australian precipitation variability at the tropical edge. A multivariate linear independence approach distinguishes between direct (causal) and indirect (circumstantial) precipitation drivers that facilitate clearer attribution of model errors and skill. This approach is applied to observed precipitation and ERA-Interim reanalysis data and a representative subset of four models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and their CMIP3 counterparts. The drivers considered are El Niño–Southern Oscillation, southern annular mode, Indian Ocean dipole, blocking, and four tropical edge metrics (position and intensity of the subtropical ridge and subtropical jet). These models are skillful in representing the covariability of drivers and their influence on precipitation. However, skill scores have not improved in the CMIP5 subset relative to CMIP3 in either respect. The Australian precipitation response to a poleward-located Hadley cell edge remains uncertain, as opposing drying and moistening mechanisms complicate the net response. Higher skill in simulating driver covariability is not consistently mirrored by higher precipitation skill. This provides further evidence that modeled precipitation does not respond correctly to large-scale flow patterns; further improvements in parameterized moist physics are needed before the subtropical precipitation responses can be fully trusted. The multivariate linear independence approach could be applied more widely for practical model evaluation.

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.

Seasonal Relationships between Large-Scale Climate Variability and Antarctic Sea Ice Concentration

2012 ◽  
Vol 25 (16) ◽  
pp. 5451-5469 ◽  
Author(s):  
Graham R. Simpkins ◽  
Laura M. Ciasto ◽  
David. W. J. Thompson ◽  
Matthew H. England
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Large Scale ◽  
Southern Oscillation ◽  
Principal Component ◽  
Southern Annular Mode ◽  
Enso Cycle ◽  
Sea Ice Concentration ◽  
Antarctic Sea Ice ◽  
Ice Concentration

Abstract The observed relationships between anomalous Antarctic sea ice concentration (SIC) and the leading patterns of Southern Hemisphere (SH) large-scale climate variability are examined as a function of season over 1980–2008. Particular emphasis is placed on 1) the interactions between SIC, the southern annular mode (SAM), and El Niño–Southern Oscillation (ENSO); and 2) the contribution of these two leading modes to the 29-yr trends in sea ice. Regression, composite, and principal component analyses highlight a seasonality in SH sea ice–atmosphere interactions, whereby Antarctic sea ice variability exhibits the strongest linkages to the SAM and ENSO during the austral cold season months. As noted in previous work, a dipole in SIC anomalies emerges in relation to the SAM, characterized by centers of action located near the Bellingshausen/Weddell and Amundsen/eastern Ross Seas. The structure and magnitude of this SIC dipole is found to vary considerably as a function of season, consistent with the seasonality of the overlying atmospheric circulation anomalies. Relative to the SAM, the pattern of sea ice anomalies linked to ENSO exhibits a similar seasonality but tends to be weaker in amplitude and more diffuse in structure. The relationships between ENSO and sea ice also exhibit a substantial nonlinear component, highlighting the need to consider both season and phase of the ENSO cycle when diagnosing ENSO–SIC linkages. Trends in SIC over 1980–2008 are not significantly related to trends in either the SAM or ENSO during any season, including austral summer when the trend in the SAM is most pronounced.

scholarly journals A New Daily Pressure Dataset for Australia and Its Application to the Assessment of Changes in Synoptic Patterns during the Last Century

2010 ◽  
Vol 23 (5) ◽  
pp. 1111-1126 ◽  
Author(s):  
Lisa V. Alexander ◽  
Petteri Uotila ◽  
Neville Nicholls ◽  
Amanda Lynch
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Past Century ◽  
Strongly Correlated ◽  
Self Organizing Maps ◽  
Sea Level Pressure ◽  
Synoptic Patterns ◽  
The Past

Abstract A high-quality daily dataset of in situ mean sea level pressure was collated for Australia for the period from 1907 to 2006. This dataset was used to assess changes in daily synoptic pressure patterns over Australia in winter using the method of self-organizing maps (SOMs). Twenty patterns derived from the in situ pressure observations were mapped to patterns derived from ERA-40 data to create daily synoptic pressure fields for the past century. Changes in the frequencies of these patterns were analyzed. The patterns that have been decreasing in frequency were generally those most strongly linked to variations in the southern annular mode (SAM) index, while patterns that have increased in frequency were more strongly correlated with variations in the positive phase of El Niño–Southern Oscillation. In general, there has been a reduction in the rain-bearing systems affecting southern Australia since the beginning of the twentieth century. Over the past century, reductions in the frequencies of synoptic patterns with a marked trough to the south of the country were shown to be linked to significant reductions in severe storms in southeast Australia and decreases in rainfall at four major Australian cities: Sydney, Melbourne, Adelaide, and Perth. Of these, Perth showed the most sustained decline in both the mean and extremes of rainfall linked to changes in the large-scale weather systems affecting Australia over the past century. The results suggest a century-long decline in the frequency of low pressure systems reaching southern Australia, consistent with the southward movement of Southern Hemisphere storm tracks. While most of these trends were not significant, associated changes in rainfall and storminess appear to have had significant impacts in the region.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1359 ◽  
Author(s):  
Scott Curtis ◽  
Thomas Crawford ◽  
Munshi Rahman ◽  
Bimal Paul ◽  
M. Miah ◽  
...  
Keyword(s):  
Interannual Variability ◽  
River Basin ◽  
Significant Relationship ◽  
Large Scale ◽  
Monsoon Rainfall ◽  
Southern Oscillation ◽  
Wave Train ◽  
Principal Component ◽  
South Atlantic ◽  
The Ganges

Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges–Brahmaputra–Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.

Large-Scale Atmospheric Drivers of Snowfall on Thwaites Glacier

2020 ◽  
Author(s):  
Michelle Maclennan ◽  
Jan Lenaerts
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Southern Annular Mode ◽  
Spatial And Temporal Variability ◽  
Atmospheric Conditions ◽  
Amundsen Sea ◽  
Weather Patterns

<p>High snowfall events on Thwaites Glacier are a key influencer of its ice mass change. In this study, we diagnose the mechanisms for orographic precipitation on Thwaites Glacier by analyzing the atmospheric conditions that lead to high snowfall events. A high-resolution regional climate model, RACMO2, is used in conjunction with MERRA-2 and ERA5 reanalysis to map snowfall and associated atmospheric conditions over the Amundsen Sea Embayment. We examine these conditions during high snowfall events over Thwaites Glacier to characterize the drivers of the precipitation and their spatial and temporal variability. Then we examine the seasonal differences in the associated weather patterns and their correlations with El Nino Southern Oscillation and the Southern Annular Mode. Understanding the large-scale atmospheric drivers of snowfall events allows us to recognize how these atmospheric drivers and consequent snowfall climatology will change in the future, which will ultimately improve predictions of accumulation on Thwaites Glacier.</p>

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