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 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 Changes in Andes snow cover from MODIS data, 2000–2016

2018 ◽  
Vol 12 (3) ◽  
pp. 1027-1046 ◽  
Author(s):  
Freddy A. Saavedra ◽  
Stephanie K. Kampf ◽  
Steven R. Fassnacht ◽  
Jason S. Sibold
Keyword(s):  
Snow Cover ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Significant Loss ◽  
Climate Indices ◽  
Climate Data ◽  
Large Area ◽  
Temperature And Precipitation ◽  
The Andes ◽  
Snow Cover Extent

Abstract. The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36∘ S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann–Kendall and Theil–Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño–Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29∘ S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36∘ S experienced a significant loss of snow cover (2–5 fewer days of snow year−1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10–30 m year−1 south of 29–30∘ S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31∘ S, whereas the SAM better predicted SP south of 31∘ S.

Coincident recruitment patterns of Southern Hemisphere fishes

2016 ◽  
Vol 73 (2) ◽  
pp. 270-278 ◽  
Author(s):  
Claudio Castillo-Jordán ◽  
Neil L. Klaer ◽  
Geoffrey N. Tuck ◽  
Stewart D. Frusher ◽  
Luis A. Cubillos ◽  
...  
Keyword(s):  
South Africa ◽  
New Zealand ◽  
Southern Hemisphere ◽  
Southern Oscillation ◽  
Global Climate ◽  
Southern Annular Mode ◽  
Fish Stock ◽  
Climate Indices ◽  
Dynamic Factor ◽  
Recruitment Patterns

Three dominant recruitment patterns were identified across 30 stocks from Australia, New Zealand, Chile, South Africa, and the Falkland Islands using data from 1980 to 2010. Cluster and dynamic factor analysis provided similar groupings. Stocks exhibited a detectable degree of synchrony among species, in particular the hakes and lings from Australia, New Zealand, Chile, and South Africa. We tested three climate indices, the Interdecadal Pacific Oscillation (IPO), Southern Annular Mode (SAM), and Southern Oscillation Index (SOI), to explore their relationship with fish stock recruitment patterns. The time series of IPO and SOI showed the strongest correlation with New Zealand hoki (blue grenadier, Macruronus novaezelandiae) and Australian jackass morwong (Nemadactylus macropterus) (r = 0.50 and r = –0.50), and SAM was positively related to Australian Macquarie Island Patagonian toothfish (Dissostichus eleginoides) (r = 0.49). Potential linkages in recruitment patterns at sub-basin, basin, and multibasin scales and regional and global climate indices do account for some of the variation, playing an important role for several key Southern Hemisphere species.

Climate variability and breeding parameters of a transhemispheric migratory seabird over seven decades

2020 ◽  
Vol 642 ◽  
pp. 191-205 ◽  
Author(s):  
CA Price ◽  
K Hartmann ◽  
TJ Emery ◽  
EJ Woehler ◽  
CR McMahon ◽  
...  
Keyword(s):  
Climate Variability ◽  
Environmental Conditions ◽  
Large Scale ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Trophic Levels ◽  
Climate Indices ◽  
Ecological Processes ◽  
Spatial And Temporal Scales ◽  
Breeding Parameters

Climate variability affects physical oceanographic systems and environmental conditions at multiple spatial and temporal scales. These changes can influence biological and ecological processes, from primary productivity to higher trophic levels. Short-tailed shearwaters Ardenna tenuirostris are transhemispheric migratory procellariiform seabirds that forage on secondary consumers such as fish (myctophids) and zooplankton (euphausiids). In this study, we investigated the breeding parameters of the short-tailed shearwater from a colony of 100 to 200 breeding pairs at Fisher Island, Tasmania, Australia, for the period 1950 to 2012, with the aim to quantify the relationship between breeding parameters with large-scale climate indices in the Northern (i.e. Northern Pacific Index and Pacific Decadal Oscillation) and Southern Hemispheres (i.e. El Niño-Southern Oscillation and Southern Annular Mode). Through the use of generalised linear models, we found that breeding participation among short-tailed shearwaters was affected by climate variability with a 12-mo temporal lag. Furthermore, breeding success decreased in years of increased rainfall at the colony. These findings demonstrate that both large-scale climate indices and local environmental conditions could explain some of the variability among breeding parameters of the short-tailed shearwater.

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 TREND IN PRECIPITATION OVER SUMATERA UNDER THE WARMING EARTH

2013 ◽  
Vol 8 (1) ◽  
Author(s):  
Iskhaq Iskandar ◽  
Muhammad Irfan ◽  
Fadli Syamsuddin ◽  
Akmal Johan ◽  
Pradanto Poerwono
Keyword(s):  
Southern Oscillation ◽  
Monsoon Season ◽  
Climate Indices ◽  
Precipitation Trend ◽  
Climate Variations ◽  
Climate Trends ◽  
Wet Season ◽  
Drying Trend ◽  
The Indian Ocean

A long-term climate variations in the western Indonesian region (e.g. Sumatera) were evaluated using precipitation data as a proxy. The result showed that there was a long-term climate variation over Sumatera region indicated by a decreasing trend in precipitation (drying trend). Moreover, the long-term precipitation trend has a strong seasonality. Remarkable decreasing trend at a rate of 3.9 cm/year (the largest trend) was observed during the northwest monsoon (DJF) season, while the smallest decreasing trend of 1.5 cm/year occurred during the southeast monsoon (JJA) season. This result suggested that the Sumatera Island experienced a drying trend during the northwest monsoon season, and a dryer condition will be more frequently observed during the southeast monsoon season. The long-term precipitation over the Sumatera Island was linked to coupled air-sea interactions in the Indian and Pacific oceans. The connection between the seasonal climate trends and sea surface temperature (SST) in the Indian and Pacific oceans was demonstrated by the simultaneous correlations between the climate indices (e.g. Dipole Mode Index (DMI) and the Niño3.4 index) and the precipitation over the Sumatera Island. The results suggested that both the Indian Ocean Dipole (IOD) and the El Niño-Southern Oscillation Index (ENSO) have significant correlation with precipitation. However, remarkable correlations were observed during the fall transition of the IOD event. Keywords: Climate variations, Dry season, Precipitation, Sumatera and Kalimantan, Wet season.

scholarly journals Seasonal climate influences on the timing of the Australian monsoon onset

2021 ◽  
Vol 2 (2) ◽  
pp. 489-506
Author(s):  
Joel Lisonbee ◽  
Joachim Ribbe
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Monsoon Onset ◽  
Climate Indices ◽  
Australian Monsoon ◽  
Onset Timing ◽  
Climate Influences ◽  
The Impact

Abstract. The timing of the first monsoon burst of the season, or the monsoon onset, can be a critical piece of information for agriculture, fire management, water management, and emergency response in monsoon regions. Why do some monsoon seasons start earlier or later than others? Previous research has investigated the impact of climate influences such as the El Niño–Southern Oscillation (ENSO) on monsoon variability, but most studies have considered only the impact on rainfall and not the timing of the onset. While this question could be applied to any monsoon system, this research presented in this paper has focused on the Australian monsoon. Even with the wealth of research available on the variability of the Australian monsoon season, the timing of the monsoon onset is one aspect of seasonal variability that still lacks skilful seasonal prediction. To help us better understand the influence of large-scale climate drivers on monsoon onset timing, we recreated 11 previously published Australian monsoon onset datasets and extended these to all cover the same period from the 1950/1951 through the 2020/2021 Australian wet seasons. The extended datasets were then tested for correlations with several standard climate indices to identify which climate drivers could be used as predictors for monsoon onset timing. The results show that many of the relationships between monsoon onset dates and ENSO that were previously published are not as strong when considering the extended datasets. Only a strong La Niña pattern usually has an impact on monsoon onset timing, while ENSO-neutral and El Niño patterns lacked a similar relationship. Detrended Indian Ocean Dipole (IOD) data showed a weak relationship with monsoon onset dates, but when the trend in the IOD data is retained, the relationship with onset dates diminishes. Other patterns of climate variability showed little relationship with Australian monsoon onset dates. Since ENSO is a tropical climate process with global impacts, it is prudent to further re-examine its influences in other monsoon regions too, with the aim to evaluate and improve previously established prediction methodologies.

scholarly journals Seasonal climate influences on the timing of the Australian monsoon onset

2021 ◽  
Author(s):  
Joel Lisonbee ◽  
Joachim Ribbe
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Monsoon Onset ◽  
Climate Indices ◽  
Australian Monsoon ◽  
Onset Timing ◽  
Climate Influences ◽  
The Impact

Abstract. The timing of the first monsoon burst of the season, or the monsoon onset, can be a critical piece of information for agriculture, fire management, water management and emergency response in monsoon regions. Why do some monsoon seasons start earlier or later than others? Previous research has investigated the impact of climate influences such as the El Niño–Southern Oscillation (ENSO) on monsoon variability, but most studies have considered only the impact on rainfall and not the timing of the onset. While these questions could be applied to any monsoon system, this research presented in this paper has focused on the Australian monsoon. Even with the wealth of research available on the variability of the Australian monsoon season, the timing of the monsoon onset is one aspect of seasonal variability that still lacks skilful seasonal prediction. To help us better understand the influence of large-scales climate drivers on monsoon onset timing, we recreated 11 previously published Australian monsoon onset datasets and extended these to all cover the same period from the 1950–51 through the 2020–21 Australian wet seasons. The extended datasets were then tested for correlations with several standard climate indices to identify which climate drivers could be used as predictors for monsoon onset timing. The results show that many of the relationships between monsoon onset dates and ENSO that were previously published are not as strong when considering the extended datasets. Only a strong La Niña pattern usually has an impact on monsoon onset timing, while ENSO–neutral and El Niño patterns lacked a similar relationship. Detrended Indian Ocean Dipole (IOD) data showed a weak relationship with monsoon onset dates, but when the trend in the IOD data is retained, the relationship with onset dates diminishes. Other patterns of climate variability showed little relationship with Australian monsoon onset dates. Since ENSO is a tropical climate process with global impacts, it is prudent to further re-examine its influences in other monsoon regions too, with the aim to evaluate and improve previously established prediction methodologies.

scholarly journals Sensitivity Analysis of Sentinel-1 Backscatter to Oil Palm Plantations at Pluriannual Scale: A Case Study in Gabon, Africa

2021 ◽  
Vol 13 (11) ◽  
pp. 2075
Author(s):  
J. David Ballester-Berman ◽  
Maria Rastoll-Gimenez
Keyword(s):  
Time Series ◽  
Sensitivity Analysis ◽  
Oil Palm ◽  
Time Interval ◽  
Potential Candidate ◽  
Initial Growth ◽  
Natural Forests ◽  
Wet Season ◽  
Radar Signatures ◽  
The Times

The present paper focuses on a sensitivity analysis of Sentinel-1 backscattering signatures from oil palm canopies cultivated in Gabon, Africa. We employed one Sentinel-1 image per year during the 2015–2021 period creating two separated time series for both the wet and dry seasons. The first images were almost simultaneously acquired to the initial growth stage of oil palm plants. The VH and VV backscattering signatures were analysed in terms of their corresponding statistics for each date and compared to the ones corresponding to tropical forests. The times series for the wet season showed that, in a time interval of 2–3 years after oil palm plantation, the VV/VH ratio in oil palm parcels increases above the one for forests. Backscattering and VV/VH ratio time series for the dry season exhibit similar patterns as for the wet season but with a more stable behaviour. The separability of oil palm and forest classes was also quantitatively addressed by means of the Jeffries–Matusita distance, which seems to point to the C-band VV/VH ratio as a potential candidate for discrimination between oil palms and natural forests, although further analysis must still be carried out. In addition, issues related to the effect of the number of samples in this particular scenario were also analysed. Overall, the outcomes presented here can contribute to the understanding of the radar signatures from this scenario and to potentially improve the accuracy of mapping techniques for this type of ecosystems by using remote sensing. Nevertheless, further research is still to be done as no classification method was performed due to the lack of the required geocoded reference map. In particular, a statistical assessment of the radar signatures should be carried out to statistically characterise the observed trends.

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