scholarly journals Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne

2014 ◽  
Vol 18 (10) ◽  
pp. 4065-4076 ◽  
Author(s):  
A. G. Yilmaz ◽  
I. Hossain ◽  
B. J. C. Perera
Keyword(s):  
Climate Change ◽  
Frequency Analysis ◽  
Flash Flood ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
Decadal Climate Variability ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Climate Change And Variability ◽  
Hourly Rainfall

Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity–frequency–duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.

scholarly journals Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne

2014 ◽  
Vol 11 (6) ◽  
pp. 6311-6342 ◽  
Author(s):  
A. G. Yilmaz ◽  
I. Hossain ◽  
B. J. C. Perera
Keyword(s):  
Climate Change ◽  
Frequency Analysis ◽  
Flash Flood ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
Decadal Climate Variability ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Climate Change And Variability ◽  
Hourly Rainfall

Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of, threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary Generalized Pareto Distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on Intensity–Frequency–Duration (IFD) relationships. The developed methodology was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, and 3 and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.

scholarly journals Depth area duration analysis of short duration rainfalls

MAUSAM ◽  
2022 ◽  
Vol 46 (1) ◽  
pp. 41-46
Author(s):  
U. C. KOTHYARI ◽  
S. K. GARG
Keyword(s):  
Water Resources ◽  
Short Duration ◽  
Extreme Rainfall ◽  
Duration Analysis ◽  
Rainfall Data ◽  
Review Of Literature ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Hourly Rainfall ◽  
Enormous Amount

Depth Area Duration (DAD) analysis for the extreme rainfall events forms an important step in the hydrological design for the water resources structures. Review of literature reveals that enormous amount of work has been done concerning the DAD analysis for large duration (i.e. one day or more) storms. However, no work is reported so far on this aspect for storms having shorter duration. i.e. less than one day: Hourly rainfall data for 36 rainfall stations have been analysed  to develop simple DAD-relationship. This analysis pertains to the catchments of the rivers, namely Ramganga, Gomati, Yamuna  and Ghaghara.    

Changes in grassland ecosystem function due to extreme rainfall events: implications for responses to climate change

2008 ◽  
Vol 14 (7) ◽  
pp. 1600-1608 ◽  
Author(s):  
PHILIP A. FAY ◽  
DAWN M. KAUFMAN ◽  
JESSE B. NIPPERT ◽  
JONATHAN D. CARLISLE ◽  
CHRISTOPHER W. HARPER
Keyword(s):  
Climate Change ◽  
Ecosystem Function ◽  
Extreme Rainfall ◽  
Grassland Ecosystem ◽  
Extreme Rainfall Events ◽  
Rainfall Events

scholarly journals Evaluation of climate change impacts on extreme rainfall events characteristics using a synoptic weather typing-based daily precipitation downscaling model

2017 ◽  
Vol 8 (3) ◽  
pp. 388-411 ◽  
Author(s):  
Hamed Tavakolifar ◽  
Ebrahim Shahghasemi ◽  
Sara Nazif
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Daily Precipitation ◽  
Extreme Event ◽  
Climate Change Impacts ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Study Region ◽  
Rainfall Events ◽  
Synoptic Weather Typing

Climate change has impacted all phenomena in the hydrologic cycle, especially extreme events. General circulation models (GCMs) are used to investigate climate change impacts but because of their low resolution, downscaling methods are developed to provide data with high enough resolution for regional studies from GCM outputs. The performance of rainfall downscaling methods is commonly acceptable in preserving average characteristics, but they do not preserve the extreme event characteristics especially rainfall amount and distribution. In this study, a novel downscaling method called synoptic statistical downscaling model is proposed for daily precipitation downscaling with an emphasis on extreme event characteristics preservation. The proposed model is applied to a region located in central Iran. The results show that the developed model can downscale all percentiles of precipitation events with an acceptable performance and there is no assumption about the similarity of future rainfall data with the historical observations. The outputs of CCSM4 GCM for two representative concentration pathways (RCPs) of RCP4.5 and RCP8.5 are used to investigate the climate change impacts in the study region. The results show 40% and 30% increase in the number of extreme rainfall events under RCP4.5 and RCP8.5, respectively.

scholarly journals Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 degrees’ warmer worlds – How anthropogenic aerosols change the story

2018 ◽  
Author(s):  
Ruksana H. Rimi ◽  
Karsten Haustein ◽  
Emily J. Barbour ◽  
Sarah N. Sparrow ◽  
Sihan Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Model ◽  
Substantial Reduction ◽  
Extreme Rainfall ◽  
Extreme Weather Events ◽  
Future Climate Change ◽  
Anthropogenic Aerosols ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract. Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5 °C and 2 °C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5 °C, and 2.0 °C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5 °C compared with 2 °C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events.

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