Trends in extreme rainfall in the state of New South Wales, Australia

Hajani, Evan; Rahman, Ataur; Ishak, Elias H

doi:10.1080/02626667.2017.1368520

Cited by 35 publications

(17 citation statements)

References 59 publications

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“…Trends are examined using Mann-Kendall Tests in the monthly time series precipitation data of each of 13 stations. The slope of the trend is calculated using Theil Sen's Slope which is recommended for metrological analysis (Gujarati, 2009). The influence of climate indices on precipitation trends is assessed by the Partial Mann-Kendall test.…”

Section: Discussionmentioning

confidence: 99%

“…TS is used to compute the magnitude of the trend. It is more robust than the linear regression since it limits the influence of outliers and performs better even for the case of normally distributed data (Gujarati, 2009;Chervenkov and Slavov, 2019). According to TS method, the overall slope S Ã is the median of N values of slope S and is given by…”

Section: Theil Sen's Slope (Ts)mentioning

confidence: 99%

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The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Aamir

Hassan

2020

Tellus A: Dynamic Meteorology and Oceanography

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Section: Discussionmentioning

confidence: 99%

Section: Theil Sen's Slope (Ts)mentioning

confidence: 99%

The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Aamir

Hassan

2020

Tellus A: Dynamic Meteorology and Oceanography

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“…Further, many of the previous studies only analysed the occurrence and concurrence of droughts and heatwaves after the 1940s (e.g. Mueller and Seneviratne, 2012;Hajani et al, 2017;Sharma and Mujumdar, 2017;Sarhadi et al, 2018;Rashid and Beecham, 2019;Trancoso et al, 2020), which, for example, overlooks the widespread droughts in Australia between the 1890s and 1940s (Askarimarnani et al, 2020). The analysis covered 1889-2019 and provided a new perspective into the temporal trends of CHD events across the country.…”

Section: Introductionmentioning

confidence: 99%

Frequency of compound hot–dry weather extremes has significantly increased in Australia since 1889

Collins

2021

J Agronomy Crop Science

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There is high confidence that climate change has increased the probability of concurrent temperatureprecipitation extremes, changed their spatial-temporal variations, and affected the relationships between drivers of such natural hazards. However, the extent of such changes has been less investigated in Australia. Daily weather data (131 years, 1889-2019) at 700 grid cells (1• × 1•) across Australia was obtained to calculate annual and seasonal mean daily maximum temperature (MMT) and total precipitation (TPR). A nonparametric multivariate copula framework was adopted to estimate the return period of compound hotdry (CHD) events based on an 'And' hazard scenario (hotter than a threshold 'And' drier than a threshold). CHD extremes were defined as years with joint return periods of larger than 25 years. Mann-Kendall nonparametric tests was used to analyse trends in MMT and TPR as well as in the frequency of univariate and CHD extremes. A general cooling-wetting trend was observed over 1889-1989. Significant increasing trends were detected over 1990-2019 in the frequency and severity of hot extremes across the country while trends in dry extremes were mostly insignificant (and decreasing). Results showed a significant increase in the association between temperature and precipitation at various temporal scales. The frequency of CHD extremes was mostly stable over 1889-1989, but significantly increased between 1990 and 2019 at 44% of studied grid cells, mostly located in the north, south-east and south-west. Spatial homogeneity (i.e. connectedness) and propagation of extreme events from one grid cell to its neighbouring cells was investigated across Australia. It can be concluded that this connectedness has not significantly changed since 1889.

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“…(2009) reported an intensification in Denmark, consistent with results from the Netherlands (Lenderink et al ., 2011), Italy (Arnone et al ., 2013; Vallebona et al ., 2015), and the Czech Republic (Hanel et al ., 2016). Researchers have reported similar increasing intensities in North America (Burn et al ., 2011; Kunkel et al ., 2013; Muschinski and Katz, 2013; Barbero et al ., 2017), and in Australia (Hajani et al ., 2017; Guerreiro et al ., 2018). This intensification may be associated with the enhanced moisture holding capacity of a warmer atmosphere as described by the Clausius‐Clapeyron (CC) relationship.…”

Section: Introductionmentioning

confidence: 99%

New hourly extreme precipitation regions and regional annual probability estimates for the UK

Darwish

Tye

Prein

et al. 2020

Intl Journal of Climatology

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Recent flooding related to extreme precipitation in the UK has highlighted the importance of better understanding these events. Many studies have quantified annual exceedance probabilities (or return periods) for UK extreme daily precipitation using fixed regions (e.g., HadUKP) and region of interest (ROI) (e.g., Flood Estimation Handbook) approaches, although fewer have evaluated short-duration events, which are important for flash flooding. Existing UK extreme precipitation regions are based on daily datasets which have different characteristics compared to sub-daily extremes, and their application to quantify short-duration extremes may therefore be inappropriate. We use a recently available, quality-controlled hourly precipitation dataset for the UK from 1992 to 2014 to derive various extreme precipitation indices (e.g., annual maxima, 0.99 quantile) which are combined with additional climatological variables (e.g., temperature), geographical characteristics (e.g., latitude), and weather patterns (WPs) to characterize the UK hourly extreme precipitation climatology and to define five new hourly extreme regions. These regions fulfil regional homogeneity and discordancy statistical measures, and reflect the dynamical processes associated with the weather pattern categorisation defined over the UK and surrounding European area. Thereafter, we use regional frequency analysis (RFA) to fit generalized extreme value (GEV) and generalized Pareto (GP) distributions to 1 hr annual maxima (AMAX) and 0.99 quantile (Q99) precipitation, respectively, to calculate regional annual probability estimates (AEP) for 20%, 10%, and 2% (i.e., 5-, 10-, and 50-year return periods). The new regions capture the spatial variation of hourly precipitation across the UK. Furthermore, the AEP estimates using both distributions are similar for each region. Finally, the WPs associated with the frequency and intensity of the most extreme hourly precipitation accumulations are not identical to results reported by others for daily precipitation.

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Trends in extreme rainfall in the state of New South Wales, Australia

Cited by 35 publications

References 59 publications

The impact of climate indices on precipitation variability in Baluchistan, Pakistan

The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Frequency of compound hot–dry weather extremes has significantly increased in Australia since 1889

New hourly extreme precipitation regions and regional annual probability estimates for the UK

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