scholarly journals Multi-century cool and warm season rainfall reconstructions for Australia's major climatic regions

Author(s):  
Mandy Freund ◽  
Benjamin J. Henley ◽  
David J. Karoly ◽  
Kathryn J. Allen ◽  
Patrick J. Baker

Abstract. Australian seasonal rainfall is strongly influenced by large-scale ocean-atmosphere climate influences. In this study, we exploit the links between these large-scale precipitation influences, regional rainfall variations, and palaeoclimate proxies in the region to reconstruct Australian regional rainfall between four and eight centuries into the past. We use an extensive network of palaeoclimate records from the Southern Hemisphere to reconstruct cool (Apr–Sep) and warm (Oct–Mar) season rainfall in eight natural resource management (NRM) regions spanning the Australian continent. Our sub-annual rainfall reconstruction aligns well with independent early documentary sources and existing reconstructions. Critically, this reconstruction allows us, for the first time, to place recent observations at a sub-annual temporal resolution into a pre-instrumental context, across the entire continent of Australia. We find that recent 30-year and 50-year trends towards wetter conditions in tropical northern Australia are highly unusual in the multi-century context of our reconstruction. Recent cool season drying trends in parts of southern Australia are also very unusual, although not unprecedented, across the multi-century context. We also use our reconstruction to investigate the spatial and temporal extent of historical drought events. Our reconstruction reveals that the spatial extent and duration of the Millennium drought (1997–2009) appears either very much below average or unprecedented in southern Australia over at least the last 400 years. Our reconstruction identifies a number of severe droughts over the past several centuries that vary widely in their spatial footprint, highlighting the high degree of diversity in historical droughts across the Australian continent. We document distinct characteristics of major droughts in terms of their spatial extent, duration, intensity, and seasonality. Compared to the three largest droughts in the instrumental period (Federation drought [1895–1903], World War II drought [1939–1945], and the Millennium drought [1997–2005]), we find that the historically documented Settlement drought [1790–1793], Sturt drought [1809–1830] and the Goyder Line drought [1861–1866] actually had more regionalised patterns and reduced spatial extents. This seasonal rainfall reconstruction provides a new opportunity to understand Australian rainfall variability, by contextualising severe droughts and recent trends in Australia.

2017 ◽  
Vol 13 (12) ◽  
pp. 1751-1770 ◽  
Author(s):  
Mandy Freund ◽  
Benjamin J. Henley ◽  
David J. Karoly ◽  
Kathryn J. Allen ◽  
Patrick J. Baker

Abstract. Australian seasonal rainfall is strongly affected by large-scale ocean–atmosphere climate influences. In this study, we exploit the links between these precipitation influences, regional rainfall variations, and palaeoclimate proxies in the region to reconstruct Australian regional rainfall between four and eight centuries into the past. We use an extensive network of palaeoclimate records from the Southern Hemisphere to reconstruct cool (April–September) and warm (October–March) season rainfall in eight natural resource management (NRM) regions spanning the Australian continent. Our bi-seasonal rainfall reconstruction aligns well with independent early documentary sources and existing reconstructions. Critically, this reconstruction allows us, for the first time, to place recent observations at a bi-seasonal temporal resolution into a pre-instrumental context, across the entire continent of Australia. We find that recent 30- and 50-year trends towards wetter conditions in tropical northern Australia are highly unusual in the multi-century context of our reconstruction. Recent cool-season drying trends in parts of southern Australia are very unusual, although not unprecedented, across the multi-century context. We also use our reconstruction to investigate the spatial and temporal extent of historical drought events. Our reconstruction reveals that the spatial extent and duration of the Millennium Drought (1997–2009) appears either very much below average or unprecedented in southern Australia over at least the last 400 years. Our reconstruction identifies a number of severe droughts over the past several centuries that vary widely in their spatial footprint, highlighting the high degree of diversity in historical droughts across the Australian continent. We document distinct characteristics of major droughts in terms of their spatial extent, duration, intensity, and seasonality. Compared to the three largest droughts in the instrumental period (Federation Drought, 1895–1903; World War II Drought, 1939–1945; and the Millennium Drought, 1997–2005), we find that the historically documented Settlement Drought (1790–1793), Sturt's Drought (1809–1830) and the Goyder Line Drought (1861–1866) actually had more regionalised patterns and reduced spatial extents. This seasonal rainfall reconstruction provides a new opportunity to understand Australian rainfall variability by contextualising severe droughts and recent trends in Australia.


2014 ◽  
Vol 27 (4) ◽  
pp. 1395-1412 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie

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.


2016 ◽  
Vol 48 (3) ◽  
pp. 867-882 ◽  
Author(s):  
M. S. Babel ◽  
T. A. J. G. Sirisena ◽  
N. Singhrattna

Understanding long-term seasonal or annual or inter-annual rainfall variability and its relationship with large-scale atmospheric variables (LSAVs) is important for water resource planning and management. In this study, rainfall forecasting models using the artificial neural network technique were developed to forecast seasonal rainfall in May–June–July (MJJ), August–September–October (ASO), November–December–January (NDJ), and February–March–April (FMA) and to determine the effects of climate change on seasonal rainfall. LSAVs, temperature, pressure, wind, precipitable water, and relative humidity at different lead times were identified as the significant predictors. To determine the impacts of climate change the predictors obtained from two general circulation models, CSIRO Mk3.6 and MPI-ESM-MR, were used with quantile mapping bias correction. Our results show that the models with the best performance for FMA and MJJ seasons are able to forecast rainfall one month in advance for these seasons and the best models for ASO and NDJ seasons are able do so two months in advance. Under the RCP4.5 scenario, a decreasing trend of MJJ rainfall and an increasing trend of ASO rainfall can be observed from 2011 to 2040. For the dry season, while NDJ rainfall decreases, FMA rainfall increases for the same period of time.


Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2055 ◽  
Author(s):  
Sekela Twisa ◽  
Manfred F. Buchroithner

In some parts of Africa, rainfall variability has resulted in widespread droughts and floods, thus posing a substantial challenge to water availability in rural areas, especially drinking water. Therefore, due to increasing water demands, increases in the population, and economic development, water supply systems are under constant stress. One of the critical uncertainties surrounding the effects of rainfall variability in Africa is the significant impact that it imposes on rural water supply services. The present study analyzes the trends in annual and seasonal rainfall time series in the Wami River Basin to see if there have been any significant changes in the patterns during the period 1983–2017 and how they affect the access to water supply services in rural areas. The study analyzes the trends of rainfall series of three stations using simple regression, Mann–Kendal Test and Sen’s Slope Estimator. The water point mapping datasets were analyzed considering seasonal variation. The analysis showed a statistically significant positive trend in annual rainfall at Kongwa and March–April–May (MAM) seasonal rainfall at Dakawa. The maximum increase in annual rainfall occurred at Kongwa (5.3 mm year−1) and for MAM seasonal data at Dakawa (4.1 mm year−1). Water points were found to be significantly affected by seasonal changes, both in terms of availability and quality of water. There also exists a strong relationship between rural water services and seasons.


2020 ◽  
Author(s):  
Xuelin Hu

<p>Accurate simulation and prediction of intense precipitation events require better understanding of their physical mechanisms. This study uses Yaan—a place with regional maximum rainfall in central China—to investigate the cause and process of intense precipitation. Hourly rain gauge records and the new ERA5 reanalysis are used to characterize the evolution process of warm season intense regional rainfall events (RREs) in Yaan and its associated three-dimensional circulation. Results show that before the start of the Yaan intense RREs, moderate rainfall amount (frequency) appears northeast of the key region. The rainfall then moves southward in the following several hours along the eastern periphery of the Tibetan Plateau where it reaches peak. It then moves to and end up in the south and southeast Sichuan Basin. The progression of the RREs is found to be associated with a counter-clockwise rotation of anomalous surface winds associated with a developing mesoscale surface low-pressure center, which is further associated with the southeastward progression of a large-scale synoptic scale wave. The easterly phase of the winds in the counter-clockwise rotation causes upslope motion perpendicularly toward the terrain that leads to maximum rainfall. The findings illustrate how large-scale circulations, mesoscale systems, and specific topographic features interact to create the RREs evolution in Yaan.</p>


Author(s):  
M. Broich ◽  
M. G. Tulbure

Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M km<sup>2</sup>, as a case study. The MDB is the country’s primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999–2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. <br><br> We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. <br><br> Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a ‘boom’ and ‘bust’ cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. <br><br> Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the Mekong River Basin in Southeast Asia.


Author(s):  
M. Broich ◽  
M. G. Tulbure

Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M&thinsp;km<sup>2</sup>, as a case study. The MDB is the country’s primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999&ndash;2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. <br><br> We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. <br><br> Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a ‘boom’ and ‘bust’ cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. <br><br> Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the Mekong River Basin in Southeast Asia.


Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 326 ◽  
Author(s):  
Mohammed Gedefaw ◽  
Denghua Yan ◽  
Hao Wang ◽  
Tianling Qin ◽  
Abel Girma ◽  
...  

This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen’s slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = −0.37) and Adet (Z = −0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980–2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies.


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