Journal articles on the topic 'Rainfall extreme'
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Nguyen, V.-T.-V., T. D. Nguyen, and F. Ashkar. "Regional frequency analysis of extreme rainfalls." Water Science and Technology 45, no. 2 (January 1, 2002): 75–81. http://dx.doi.org/10.2166/wst.2002.0030.
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This study proposes two alternative methods for estimating the distribution of extreme rainfalls for sites where rainfall data are available (gaged sites) and for locations without data (ungaged sites). The first method deals with the estimation of short-duration rainfall extremes from available rainfall data for longer durations using the “scale-invariance” concept to account for the relationship between statistical properties of extreme rainfall processes for different time scales. The second method is concerned with the estimation of extreme rainfalls for ungaged sites. This method relies on a new definition of homogeneous sites. Results of the numerical application using data from a network of 10 recording rain gauges in Quebec (Canada) indicate that the proposed methods are able to provide extreme rainfall estimates that are comparable with those based on observed at-site rainfall data.
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Indarto, Indarto. "Trend and spatial variability of 1-day extreme rainfall from 1980 - 2015: study at the adminisitrative area of UPT PSDA Pasuruan." Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) 8, no. 1 (March 31, 2019): 29. http://dx.doi.org/10.23960/jtep-l.v8i1.29-39.
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This study aims to analyze trends, shift and spatial variability of extreme-rainfall in the area of UPT PSDA Pasuruan. The daily rainfall data from 64 stations from 1980 until 2015 were used as main input. The 1-day extreem rainfall data is determined as the maximum annual of 24-hour rainfall events. The statistical analysis using Mann-Kendall, Rank-Sum, and Median Crossing Test using significance level α = 0,05. The spatial variability of extrem rainfall data is described using average annual 24-hour rainfall during the periods of record. Each station is represented by one value. The values are then interpolated using IDW interpolation methods to maps the spatial variability of extreem rainfall event. The results show the value of statistical test for each stations that show the existing trend, shift, or randomness of data. The result also produce thematic maps show the spatial variability of extreme rainfall and the value of each trend.
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Hopkins, David. "Extreme rainfall events." Weather 61, no. 1 (January 2006): 30. http://dx.doi.org/10.1002/wea.200661108.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences 18, no. 10 (October 15, 2014): 4065–76. http://dx.doi.org/10.5194/hess-18-4065-2014.
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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.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences Discussions 11, no. 6 (June 16, 2014): 6311–42. http://dx.doi.org/10.5194/hessd-11-6311-2014.
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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.
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Arnbjerg-Nielsen, K., P. Harremoës, and P. S. Mikkelsen. "Dissemination of regional rainfall analysis in design and analysis of urban drainage at un-gauged locations." Water Science and Technology 45, no. 2 (January 1, 2002): 69–74. http://dx.doi.org/10.2166/wst.2002.0029.
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A research program in Denmark on statistical modelling of rainfall has resulted in a model for regional distribution of rainfall extremes. The results show that extreme rainfalls critical to the hydraulic function of urban drainage systems and the pollution discharge are subject to a significant regional variation of extreme rainfalls throughout the country. This has implications for design and analysis of all practical problems related to urban drainage, since the rainfall data so far recommended as input to engineering analyses underestimates the problems. Consequently, the Danish Water Pollution Control Committee has issued a statement recommending a new engineering practice. The dissemination of the research results proved to be difficult due to lack of understanding of the concepts of the new paradigm by practitioners. The traditional means of communication was supplemented by user-friendly spreadsheets and easy access to rainfall data as well as giving courses on the new paradigm. This has eased the implementation of the new concepts greatly.
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Williams, C. J. R., D. R. Kniveton, and R. Layberry. "Influence of South Atlantic Sea Surface Temperatures on Rainfall Variability and Extremes over Southern Africa." Journal of Climate 21, no. 24 (December 15, 2008): 6498–520. http://dx.doi.org/10.1175/2008jcli2234.1.
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Abstract It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.
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PASUPALAK, S., G. PANIGRAHI, T. PANIGRAHI, S. MOHANTY, and K. K. SINGH. "Extreme rainfall events over Odisha state, India." MAUSAM 68, no. 1 (November 30, 2021): 131–38. http://dx.doi.org/10.54302/mausam.v68i1.442.
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Extreme rainfall events are a significant cause of loss of life and livelihoods in Odisha. Objectives of the present study are to determine the trend of the extreme rainfall events during 1991-2014 and to compare the events between two periods before and after 1991. Block level daily rainfall data were used in identifying the extreme rainfall events, while district level aggregation was used in analysing the trend in three categories, viz., heavy, very heavy and extremely heavy rainfall as per criteria given by India Meteorological Department (IMD). The state as a whole received one extremely heavy, nine very heavy, and forty heavy rainfall events in a year. When percentage of occurrence of each category out of the total extreme events over different districts was considered, maximum % of extremely heavy rainfall occurred in Kalahandi (5.8%), very heavy rainfall in Bolangir (23.8%) and heavy rainfall in Keonjhargarh (85.4%). Trend analysis showed that number of extreme rainfall events increased in a few districts, namely, Bolangir, Nuapada, Keonjhargarh, Koraput, Malkangiri, and Nawarangapur and did not change in other districts. In Puri district, extremely heavy rainfall frequency decreased. New all-time record high one-day rainfall events were observed in twenty districts during 1992 to 2014, surpassing the earlier records, which could be attributed to climate change induced by global warming. Interior south Odisha was found as the hot spot for extreme rainfalls.
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Cross, David, Christian Onof, Hugo Winter, and Pietro Bernardara. "Censored rainfall modelling for estimation of fine-scale extremes." Hydrology and Earth System Sciences 22, no. 1 (January 26, 2018): 727–56. http://dx.doi.org/10.5194/hess-22-727-2018.
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Abstract. Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett–Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett–Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.
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Agilan, V., and N. V. Umamahesh. "Rainfall Generator for Nonstationary Extreme Rainfall Condition." Journal of Hydrologic Engineering 24, no. 9 (September 2019): 04019027. http://dx.doi.org/10.1061/(asce)he.1943-5584.0001821.
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Barnes, Andrew Paul, Marcus Suassuna Santos, Carlos Garijo, Luis Mediero, Ilaria Prosdocimi, Nick McCullen, and Thomas Rodding Kjeldsen. "Identifying the origins of extreme rainfall using storm track classification." Journal of Hydroinformatics 22, no. 2 (October 23, 2019): 296–309. http://dx.doi.org/10.2166/hydro.2019.164.
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Abstract Identifying patterns in data relating to extreme rainfall is important for classifying and estimating rainfall and flood frequency distributions routinely used in civil engineering design and flood management. This study demonstrates the novel use of several self-organising map (SOM) models to extract the key moisture pathways for extreme rainfall events applied to example data in northern Spain. These models are trained using various subsets of a backwards trajectory data set generated for extreme rainfall events between 1967 and 2016. The results of our analysis show 69.2% of summer rainfall extremes rely on recirculatory moisture pathways concentrated on the Iberian Peninsula, whereas 57% of winter extremes rely on deep-Atlantic pathways to bring moisture from the ocean. These moisture pathways have also shown differences in rainfall magnitude, such as in the summer where peninsular pathways are 8% more likely to deliver the higher magnitude extremes than their Atlantic counterparts.
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Pham, Quoc, Tao-Chang Yang, Chen-Min Kuo, Hung-Wei Tseng, and Pao-Shan Yu. "Combing Random Forest and Least Square Support Vector Regression for Improving Extreme Rainfall Downscaling." Water 11, no. 3 (March 3, 2019): 451. http://dx.doi.org/10.3390/w11030451.
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A statistical downscaling approach for improving extreme rainfall simulation was proposed to predict the daily rainfalls at Shih-Men Reservoir catchment in northern Taiwan. The structure of the proposed downscaling approach is composed of two parts: the rainfall-state classification and the regression for rainfall-amount prediction. Predictors of classification and regression methods were selected from the large-scale climate variables of the NCEP reanalysis data based on statistical tests. The data during 1964–1999 and 2000–2013 were used for calibration and validation, respectively. Three classification methods, including linear discriminant analysis (LDA), random forest (RF), and support vector classification (SVC), were adopted for rainfall-state classification and their performances were compared. After rainfall-state classification, the least square support vector regression (LS-SVR) was used for rainfall-amount prediction for different rainfall states. Two rainfall states (i.e., dry day and wet day) and three rainfall states (dry day, non-extreme-rainfall day, and extreme-rainfall day) were defined and compared for judging their downscaling performances. The results show that RF outperforms LDA and SVC for rainfall-state classification. Using RF for three-rainfall-states classification and LS-SVR for rainfall-amount prediction can improve the extreme rainfall downscaling.
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Ayat, Hooman, Jason P. Evans, Steven C. Sherwood, and Joshua Soderholm. "Intensification of subhourly heavy rainfall." Science 378, no. 6620 (November 11, 2022): 655–59. http://dx.doi.org/10.1126/science.abn8657.
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Short-duration rainfall extremes can cause flash flooding with associated impacts. Previous studies of climate impacts on extreme precipitation have focused mainly on daily rain totals. Subdaily extremes are often generated in small areas that can be missed by gauge networks or satellites and are not resolved by climate models. Here, we show a robust positive trend of at least 20% per decade in subhourly extreme rainfall near Sydney, Australia, over 20 years, despite no evidence of trends at hourly or daily scales. This trend is seen consistently in storms tracked using multiple independent ground radars, is consistent with rain-gauge data, and does not appear to be associated with known natural variations. This finding suggests that subhourly rainfall extremes may be increasing substantially faster than those on more widely reported time scales.
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Aryal, Santosh K., Bryson C. Bates, Edward P. Campbell, Yun Li, Mark J. Palmer, and Neil R. Viney. "Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes." Journal of Hydrometeorology 10, no. 1 (February 1, 2009): 241–53. http://dx.doi.org/10.1175/2008jhm1007.1.
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Abstract A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.
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Hamada, Atsushi, and Yukari N. Takayabu. "A Removal Filter for Suspicious Extreme Rainfall Profiles in TRMM PR 2A25 Version-7 Data." Journal of Applied Meteorology and Climatology 53, no. 5 (May 2014): 1252–71. http://dx.doi.org/10.1175/jamc-d-13-099.1.
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AbstractThis study reports on the presence of suspicious “extreme rainfall” data in the 2A25 version-7 (V7) product of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) dataset and introduces a simple method for detecting and filtering out the suspicious data. These suspicious data in V7 are found by comparing the extreme rainfall characteristics in the V7 and version-6 products. Most of the suspicious extremes are located over land, especially in mountainous regions. Radar reflectivities in the suspicious extremes show significant monotonic increases toward the echo bottom. These facts indicate that the suspicious extremes are mainly caused by contamination from ground or sea clutter. A simple thresholding filter for eliminating the suspicious extreme data is developed using common characteristics in the horizontal and vertical rainfall structures and reflectivities in the suspicious extremes. The proposed filter mitigates deformations in the frequency distribution of the surface rainfall rate in the 2A25 V7 product.
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Johnson, K. A., J. C. Smithers, and R. E. Schulze. "A review of methods to account for impacts of non-stationary climate data on extreme rainfalls for design rainfall estimation in South Africa." Journal of the South African Institution of Civil Engineering 63, no. 3 (November 11, 2021): 1–7. http://dx.doi.org/10.17159/2309-8775/2021/v63n3a5.
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Frequency analysis of extreme rainfall and flood events are used to determine design rainfalls and design floods which are needed to design hydraulic structures such as dams, spillways and culverts. Standard methods for frequency analysis of extreme events are based on the assumption of a stationary climate. However, this assumption in rainfall and flood frequency analysis is being challenged with growing evidence of climate change. As a consequence of a changing climate, the frequency and magnitude of extreme rainfall events are reported to have increased in parts of South Africa, and these and other changes in extreme rainfall occurrences are expected to continue into the future. The possible non-stationarity in climate resulting in changes in rainfall may impact on the accuracy of the estimation of extreme rainfall quantities and design rainfall estimations. This may have significant consequences for the design of new hydraulic infrastructure, as well as for the rehabilitation of existing infrastructure. Hence, methods that account for non-stationary data, such as caused by climate change, need to be developed. This may be achieved by using data from downscaled global circulation models in order to identify non-stationary climate variables which affect rainfall, and which can then be incorporated into extreme value analysis of a non-stationary data series.
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Wubaye, Gizachew Belay, Temesgen Gashaw, Abeyou W. Worqlul, Yihun T. Dile, Meron Teferi Taye, Amare Haileslassie, Benjamin Zaitchik, et al. "Trends in Rainfall and Temperature Extremes in Ethiopia: Station and Agro-Ecological Zone Levels of Analysis." Atmosphere 14, no. 3 (February 28, 2023): 483. http://dx.doi.org/10.3390/atmos14030483.
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Climate extreme events have been observed more frequently since the 1970s throughout Ethiopia, which adversely affects the socio-economic development of the country, as its economy depends on agriculture, which, in turn, relies heavily on annual and seasonal rainfall. Climate extremes studies conducted in Ethiopia are mainly limited to a specific location or watershed, making it difficult to have insights at the national level. The present study thus aims to examine the observed climate extreme events in Ethiopia at both station and agro-ecological zone (AEZ) levels. Daily rainfall and temperature data for 47 and 37 stations, respectively (1986 up to 2020), were obtained from the National Meteorology Agency (NMA). The Modified Mann–Kendall (MMK) trend test and the Theil–Sen slope estimator were employed to estimate the trends in rainfall and temperature extremes. This study examines trends of 13 temperature and 10 rainfall extreme indices using RClimDex in R software. The results revealed that most of the extreme rainfall indices showed a positive trend in the majority of the climate stations. For example, an increase in consecutive dry days (CDD), very heavy rainfall days (R20), number of heavy rainfall days (R10) and consecutive wet days (CWD) were exhibited in most climate stations. In relation to AEZs, the greater number of extreme rainfall indices illustrated an upward trend in cool and sub-humid, cool and humid, and cool and moist AEZs, a declining trend in hot arid AEZ, and equal proportions of increasing and decreasing trends in warm semi-arid AEZs. Concerning extreme temperature indices, the result indicated an increasing trend of warm temperature extreme indices and a downward trend of cold temperature extreme indices in most of the climate stations, indicating the overall warming and dryness trends in the country. With reference to AEZs, an overall warming was exhibited in all AEZs, except in the hot arid AEZ. The observed trends in the rainfall and temperature extremes will have tremendous direct and indirect impacts on agriculture, water resources, health, and other sectors in the country. Therefore, the findings suggest the need for identifying and developing climate change adaptation strategies to minimize the ill effects of these extreme climate events on the social, economic, and developmental sectors.
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Sougué, Madou, Bruno Merz, Jean Mianikpo Sogbedji, and François Zougmoré. "Extreme Rainfall in Southern Burkina Faso, West Africa: Trends and Links to Atlantic Sea Surface Temperature." Atmosphere 14, no. 2 (January 31, 2023): 284. http://dx.doi.org/10.3390/atmos14020284.
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Understanding the space-time variations of extreme rainfall plays an important role in the management of water-related disasters in Sahel countries. This study investigates temporal changes in rainfall characteristics and explores the link between Atlantic Sea surface temperature and extreme rainfall in the southern part of Burkina Faso. We find substantial spatial heterogeneity in rainfall trends across the study area. In contrast to national and supra-national studies that found predominantly increasing trends in extreme rainfall, we detect more downward than upward trends, particularly for indices representing extreme rainfall. This difference is presumably a consequence of the high spatial variability in rainfall trends that can only be detected with sufficiently dense climate networks. We use the Poisson-General Pareto (Poisson-GP) distribution to quantify the frequency and intensity of extreme rainfall. Our comparison of the traditional, stationary Poisson-GP model with the nonstationary version where rainfall depends on Atlantic SST shows that the nonstationary model outperforms the traditional approach. This finding suggests that the assumption of stationary nature must be considered with care when modeling the frequency and intensity of extreme rainfall in the study area. Overall, our results suggest that the recent increase in flood disasters in Burkina Faso is rather caused by land use and land cover changes and population and urban growth and not by increasing rainfall extremes.
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DeGaetano, Arthur T., and Harrison Tran. "Recent Changes in Average Recurrence Interval Precipitation Extremes in the Mid-Atlantic United States." Journal of Applied Meteorology and Climatology 61, no. 2 (February 2022): 143–57. http://dx.doi.org/10.1175/jamc-d-21-0129.1.
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Abstract Increases in the frequency of extreme rainfall occurrence have emerged as one of the more consistent climate trends in recent decades, particularly in the eastern United States. Such changes challenge the veracity of the conventional assumption of stationarity that has been applied in the published extreme rainfall analyses that are the foundation for engineering design assessments and resiliency planning. Using partial-duration series with varying record lengths, temporal changes in daily and hourly rainfall extremes corresponding to average annual recurrence probabilities ranging from 50% (i.e., the 2-yr storm) to 1% (i.e., the 100-yr storm) are evaluated. From 2000 through 2019, extreme rainfall amounts across a range of durations and recurrence probabilities have increased at 75% of the long-term precipitation observation stations in the mid-Atlantic region. At approximately one-quarter of the stations, increases in extreme rainfall have exceeded 5% from 2000 through 2019, with some stations experiencing increases in excess of 10% for both daily and hourly durations. At over 40% of the stations, the rainfall extremes based on the 1950–99 partial-duration series show a significant (p > 0.90) change in the 100-yr ARI relative to the 1950–2019 period. Collectively, the results indicate that, given recent trends in extreme rainfall, routine updates of extreme rainfall analyses are warranted on 20-yr intervals. Significance Statement Engineering design standards for drainage systems, dams, and other infrastructure rely on analyses of precipitation extremes. Often such structures are designed on the basis of the probability of exceeding a specified rainfall rate in a given year. The frequency of extreme rainfall events has increased in the mid-Atlantic region of the United States in recent decades, leading us to evaluate how these changes have affected these exceedance probabilities. From 2000 through 2019, there has been a consistent increase of generally 2.5%–5.0% in design rainfall amounts. The increase is similar across a range of rainfall durations from 1 h to 20 days and also annual exceedance probabilities ranging from 50% to 1% (i.e., from the “2-yr storm” to the “100-yr storm”). The work highlights the need to routinely update the climatological extreme-value analyses used in engineering design, with the results suggesting that a 20-yr cycle might be an appropriate update frequency.
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Nguyen, V. T. V., T. D. Nguyen, and H. Wang. "Regional estimation of short duration rainfall extremes." Water Science and Technology 37, no. 11 (June 1, 1998): 15–19. http://dx.doi.org/10.2166/wst.1998.0425.
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The present study proposes a method for estimating the distribution of short-duration (e.g., 1 hour) extreme rainfalls at sites where data for the time interval of interest do not exist, but rainfall data for longer-duration (e.g., 1 day) are available (partially-gaged sites). The proposed method is based on the recently developed “scale-invariance” (or “scaling”) theory. In this study, the scaling concept implies that statistical properties of the extreme rainfall processes for different temporal scales are related to each other by a scale-changing operator involving only the scale ratio. Further, it is assumed that these hydrologic series possess a simple scaling behaviour. The suggested methodology has been applied to extreme rainfall data from a network of 14 recording raingages in Quebec (Canada). The Generalised Extreme Value (GEV) distribution was used to estimate the rainfall quantiles. Results of the numerical application have indicated that for partially-gaged sites the proposed scaling method is able to provide extreme rainfall estimates which are comparable with those based on available at-site rainfall data.
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Almazroui, Mansour. "Rainfall Trends and Extremes in Saudi Arabia in Recent Decades." Atmosphere 11, no. 9 (September 10, 2020): 964. http://dx.doi.org/10.3390/atmos11090964.
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The observed records of recent decades show increased economic damage associated with flash flooding in different regions of Saudi Arabia. An increase in extreme rainfall events may cause severe repercussions for the socio-economic sectors of the country. The present study investigated the observed rainfall trends and associated extremes over Saudi Arabia for the 42-year period of 1978–2019. It measured the contribution of extreme events to the total rainfall and calculated the changes to mean and extreme rainfall events over five different climate regions of Saudi Arabia. Rainfall indices were constructed by estimating the extreme characteristics associated with daily rainfall frequency and intensity. The analysis reveals that the annual rainfall is decreasing (5.89 mm decade−1, significant at the 90% level) over Saudi Arabia for the entire analysis period, while it increased in the most recent decade. On a monthly scale, the most significant increase (5.44 mm decade−1) is observed in November and the largest decrease (1.20 mm decade−1) in January. The frequency of intense rainfall events is increasing for the majority of stations over Saudi Arabia, while the frequency of weak events is decreasing. More extreme rainfall events are occurring in the northwest, east, and southwest regions of Saudi Arabia. A daily rainfall of ≥ 26 mm is identified as the threshold for an extreme event. It is found that the contribution of extreme events to the total rainfall amount varies from region to region and season to season. The most considerable contribution (up to 56%) is found in the southern region in June. Regionally, significant contribution comes from the coastal region, where extreme events contribute, on average, 47% of the total rainfall each month from October to February, with the largest (53%) in November. For the entire country, extreme rainfall contributes most (52%) in November and least (20%) in July, while contributions from different stations are in the 8–50% range of the total rainfall.
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Noor, Muhammad, Tarmizi Ismail, Shamsuddin Shahid, Mohamed Salem Nashwan, and Shahid Ullah. "Development of multi-model ensemble for projection of extreme rainfall events in Peninsular Malaysia." Hydrology Research 50, no. 6 (November 5, 2019): 1772–88. http://dx.doi.org/10.2166/nh.2019.097.
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Abstract Possible changes in rainfall extremes in Peninsular Malaysia were assessed in this study using an ensemble of four GCMs of CMIP5. The performance of four bias correction methods was compared, and the most suitable method was used for downscaling of GCM simulated daily rainfall to the spatial resolution (0.25°) of APHRODITE rainfall. The multi-model ensemble (MME) mean of the downscaled rainfall was developed using a random forest regression algorithm. The MME projected rainfall for four RCPs were compared with APHRODITE rainfall for the base year (1961–2005) to assess the annual and seasonal changes in eight extreme rainfall indices. The results showed power transformation as the most suitable bias correction method. The maximum changes in most of the annual and seasonal extreme rainfall indices were observed for RCP8.5 in the last part of this century. The maximum increase was observed for 1-day and 5 consecutive days' rainfall amount for RCP4.5. Spatial distribution of the changes revealed higher increase of the extremes in the northeast region where rainfall extremes are already very high. The increase in rainfall extremes would increase the possibility of frequent hydrological disasters in Peninsular Malaysia.
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McLean, Natalie Melissa, Tannecia Sydia Stephenson, Michael Alexander Taylor, and Jayaka Danaco Campbell. "Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones." Advances in Meteorology 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/425987.
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End-of-century changes in Caribbean climate extremes are derived from the Providing Regional Climate for Impact Studies (PRECIS) regional climate model (RCM) under the A2 and B2 emission scenarios across five rainfall zones. Trends in rainfall, maximum temperature, and minimum temperature extremes from the RCM are validated against meteorological stations over 1979–1989. The model displays greater skill at representing trends in consecutive wet days (CWD) and extreme rainfall (R95P) than consecutive dry days (CDD), wet days (R10), and maximum 5-day precipitation (RX5). Trends in warm nights, cool days, and warm days were generally well reproduced. Projections for 2071–2099 relative to 1961–1989 are obtained from the ECHAM5 driven RCM. Northern and eastern zones are projected to experience more intense rainfall under A2 and B2. There is less consensus across scenarios with respect to changes in the dry and wet spell lengths. However, there is indication that a drying trend may be manifest over zone 5 (Trinidad and northern Guyana). Changes in the extreme temperature indices generally suggest a warmer Caribbean towards the end of century across both scenarios with the strongest changes over zone 4 (eastern Caribbean).
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KARMAKAR, SAMARENDRA, and AYESHA KHATUN. "Variability and probabilistic estimates of rainfall extremes In Bangladesh during the southwest monsoon season." MAUSAM 46, no. 1 (January 1, 2022): 47–56. http://dx.doi.org/10.54302/mausam.v46i1.3176.
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The present study describes the temporal and spatial distributions of mean monthly rainfall and its variability together with the spatial distributions of the probabilistic estimates of rainfall extremes over Bangladesh during the- southwest monsoon season. The- probabilistic rainfall extremes have been computed for IWO lime scales: (a) in I year out of 4 years, and (b) in 1 year out of 10 years -representing relatively less extreme events and extreme events respectively. The mean monthly rainfall increases from June to July at most places over Bangladesh and then decreases up to September. The variability of rainfall decreases with increasing rainfall up to July at many places and then increases up to September. The study also reveals that the mean rainfall and the- probabilistic rainfall extremes are maximum over the southern and north-eastern parts of the country where the variability of rainfall is low and the rainfall is reliable. There exists a belt of low rainfall over the- central part of Bangladesh roughly between 23oN and 24°N. The rainfall gradients are maximum over north-eastern Bangladesh and the gradients of the probabilistic high rainfall are more than those of the probabilistic low rainfall in this area.
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Espinosa, Luis Angel, Maria Manuela Portela, João Dehon Pontes Filho, and Martina Zelenakova. "Bivariate Modelling of a Teleconnection Index and Extreme Rainfall in a Small North Atlantic Island." Climate 9, no. 5 (May 19, 2021): 86. http://dx.doi.org/10.3390/cli9050086.
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This paper explores practical applications of bivariate modelling via copulas of two likely dependent random variables, i.e., of the North Atlantic Oscillation (NAO) coupled with extreme rainfall on the small island of Madeira, Portugal. Madeira, due to its small size (∼740 km2), very pronounced mountain landscape, and location in the North Atlantic, experiences a wide range of rainfall regimes, or microclimates, which hamper the analyses of extreme rainfall. Previous studies showed that the influence of the North Atlantic Oscillation (NAO) on extreme rainfall is at its largest in the North Atlantic sector, with the likelihood of increased rainfall events from December through February, particularly during negative NAO phases. Thus, a copula-based approach was adopted for teleconnection, aiming at assigning return periods of daily values of an NAO index (NAOI) coupled with extreme daily rainfalls—for the period from December 1967 to February 2017—at six representative rain gauges of the island. The results show that (i) bivariate copulas describing the dependence characteristics of the underlying joint distributions may provide useful analytical expressions of the return periods of the coupled previous NAOI and extreme rainfall and (ii) that recent years show signs of increasing climate variability with more anomalous daily negative NAOI along with higher extreme rainfall events. These findings highlight the importance of multivariate modelling for teleconnections of prominent patterns of climate variability, such as the NAO, to extreme rainfall in North Atlantic regions, especially in small islands that are highly vulnerable to the effects of abrupt climate variability.
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Faulkner, D. S., and C. Prudhomme. "Mapping an index of extreme rainfall across the UK." Hydrology and Earth System Sciences 2, no. 2/3 (September 30, 1998): 183–94. http://dx.doi.org/10.5194/hess-2-183-1998.
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Abstract. Distance from the sea, proximity of mountains, continentality and elevation are all useful covariates to assist the mapping of extreme rainfalls. Regression models linking these and other variables calculated from a digital terrain model have been built for estimating the median annual maximum rainfall, RMED. This statistic, for rainfall durations between 1 hour and 8 days, is the index variable in the rainfall frequency analysis for the new UK Flood Estimation Handbook. The interpolation of RMED between raingauge sites is most challenging in mountainous regions, which combine the greatest variation in rainfall with the sparsest network of gauges. Sophisticated variables have been developed to account for the influence of topography on extreme rainfall, the geographical orientation of the variables reflecting the prevailing direction of rain-bearing weather systems. The different processes of short and long-duration extreme rainfall are accounted for by separate regression models. The technique of georegression combines estimates from regression models with a map of correction factors interpolated between raingauge locations using the geostatistical method of kriging, to produce final maps of RMED across the UK.
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Curtis, Scott, Ahmed Salahuddin, Robert F. Adler, George J. Huffman, Guojun Gu, and Yang Hong. "Precipitation Extremes Estimated by GPCP and TRMM: ENSO Relationships." Journal of Hydrometeorology 8, no. 4 (August 1, 2007): 678–89. http://dx.doi.org/10.1175/jhm601.1.
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Abstract Global monthly and daily precipitation extremes are examined in relation to the El Niño–Southern Oscillation phenomenon. For each month around the annual cycle and in each 2.5° grid block, extremes in the Global Precipitation Climatology Project dataset are defined as the top five (wet) and bottom five (dry) mean rain rates from 1979 to 2004. Over the tropical oceans El Niño–Southern Oscillation events result in a spatial redistribution and overall increase in extremes. Restricting the analysis to land shows that El Niño is associated with an increase in frequency of dry extremes and a decrease in wet extremes resulting in no change in net extreme months. During La Niña an increase in frequency of dry extremes and no change in wet extremes are observed. Thus, because of the juxtaposition of tropical land areas with the ascending branches of the global Walker Circulation, El Niño (La Niña) contributes to generally dry (wet) conditions in these land areas. In addition, daily rain rates computed from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis are used to define extreme precipitation frequency locally as the number of days within a given season that exceeded the 95th percentile of daily rainfall for all seasons (1998–2005). During this period, the significant relationships between extreme daily precipitation frequency and Niño-3.4 in the Tropics are spatially similar to the significant relationships between seasonal mean rainfall and Niño-3.4. However, to address the shortness of the record extreme daily precipitation frequency is also related to seasonal rainfall for the purpose of identifying regions where positive seasonal rainfall anomalies can be used as proxies for extreme events. Finally, the longer (1979–2005) but coarser Global Precipitation Climatology Project analysis is reexamined to pinpoint regions likely to experience an increase in extreme precipitation during El Niño–Southern Oscillation events. Given the significance of El Niño–Southern Oscillation predictions, this information will enable the efficient use of resources in preparing for and mitigating the adverse effects of extreme precipitation.
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Ngaina, Joshua, and Bethwel Mutai. "Observational evidence of climate change on extreme events over East Africa." Global Meteorology 2, no. 1 (October 21, 2013): 2. http://dx.doi.org/10.4081/gm.2013.e2.
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Examination of trend patterns of rainfall and temperature extremes over East Africa (EA) was based on graphical, regression and Mann-Kendall test approaches, while perturbations of rainfall, sunspot activity (SA) and southern oscillation index (SOI) extremes were computed using moving average methods. Annual total rainfall generally decreased with heavy and extreme precipitation rates confined within short spells during wet days. Observed maximum temperature extremes increased while minimum temperature extremes decreased with a statistically significant rise in the number of hot days and warm nights and a decrease in number of cool days and cold nights. However, space-time pattern of observed changes were not well organized. Perturbations of rainfall, SA and SOI indicated that extreme values were changing with increasing frequency and magnitude. Similarities in observed rainfall over EA illustrated the existence of homogeneous zones of climate change clustered as either coastal (with SA dominant), lake Victoria (unique to both SA and SOI), dry continental (SOI) or wet continental areas (both SA and SOI dominant).
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Chaubey, Pawan Kumar, Rajesh Kumar Mall, and Prashant K. Srivastava. "Changes in Extremes Rainfall Events in Present and Future Climate Scenarios over the Teesta River Basin, India." Sustainability 15, no. 5 (March 6, 2023): 4668. http://dx.doi.org/10.3390/su15054668.
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Globally, changes in hydroclimate extremes such as extreme precipitation events influence water resources, natural environments, and human health and safety. During recent decades, India has observed an enormous increase in rainfall extremes during the summer monsoon (June to September) seasons. However, future extreme rainfall events have significant uncertainty at the regional scale. Consequently, a comprehensive study is needed to evaluate the extreme rainfall events at a regional river basin level in order to understand the geomorphological characteristics and pattern of rainfall events. In the above purview, the current research focuses on changes in extreme rainfall events obtained through observed gridded datasets and future scenarios of climate models derived through the Coupled Model Intercomparison Project (CMIP). The results highlight a significant rise in the extremes of precipitation events during the first half of the 21st century. In addition, our study concludes that accumulated precipitation will increase by five days in the future, while the precipitation maxima will increase from 200 to 300 mm/day at the 2-year, 50-year, and 100-year return periods. Finally, it is found that during the middle of the 21st century the 23.37% number of events will increase over the TRB at the 90th percentile.
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Soldini, Luciano, and Giovanna Darvini. "Extreme rainfall statistics in the Marche region, Italy." Hydrology Research 48, no. 3 (April 6, 2017): 686–700. http://dx.doi.org/10.2166/nh.2017.091.
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A statistical analysis of the rainfalls is carried out for detecting a possible trend in the observed data. The rainfall dataset refers to the historical series collected in the hydrographic basins of the Marche region. On the one hand, the annual maximum daily, hourly and sub-hourly rainfalls have been analysed, on the other hand Climate Change Indices by Expert Team on Climate Change Detection and Indices (ETCCDI) (R1 mm, Rx1day, R20 mm, R95pTOT, PRCPTOT) have been computed to verify an eventual variation of the frequency of the rainfall regime in the Marche region. The time series, selected in the reference period 1951–2013, have been processed by using the non-parametric Mann–Kendall test. The results confirm that most of the series relating to the annual maximum rainfalls do not exhibit any trend. The absence of trend or the presence of negative trend prevail also in the analysis of the ETCCDI indices. The annual average anomalies of the same indices computed with respect to the climatological reference period 1961–1990 are negative since the mid-1980s, but they appear to show an increasing behaviour in the period 2009–2013.
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Zipser, Edward J., and Chuntao Liu. "Extreme Convection vs. Extreme Rainfall: a Global View." Current Climate Change Reports 7, no. 4 (December 2021): 121–30. http://dx.doi.org/10.1007/s40641-021-00176-0.
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Brandão, Claudia, and Marcel Fragoso. "Extreme storms and rainfall erosivity factor in Evora (Portugal)." Zeitschrift für Geomorphologie Supplement Volumes 115 (July 1, 1999): 113–23. http://dx.doi.org/10.1127/zfgsuppl/115/1999/113.
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Mondal, M. Shahjahan, Sara Nowreen, and Mostofa Najmus Sakib. "Scale-Dependent Reliability of Projected Rainfalls over Bangladesh with the PRECIS Model." Climate 8, no. 2 (January 27, 2020): 20. http://dx.doi.org/10.3390/cli8020020.
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The regional climate model, Providing REgional Climates for Impact Studies (PRECIS), has been widely used throughout the world to generate climate change projections for impact studies and adaptations. Its recent application in South Asia also includes the projection of rainfall extremes. In spite of its wide application, a stringent validation of the model is yet to be reported. In this study, we assessed the performance of the model in simulating annual, monthly and extreme rainfalls over Bangladesh by using a number of statistical techniques, e.g., pattern (both spatial and temporal) correlation, root mean square difference (RMSD), mean absolute difference (MAD), Student’s t-test for significance, probability density functions, etc. The results indicated that the PRECIS model could capture the overall spatial pattern of mean annual and monthly rainfalls very well. However, the inter-annual variability was poorly simulated by the model. In addition, the model could not capture the rainfall extremes. A spatial aggregation of rainfall data did not improve the reliability of the model as far as variability and extremes are concerned. Therefore, further improvements of the model and/or its driving global climate model are warranted for its practical use in the generation of rainfall scenarios.
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Papalexiou, S. M., D. Koutsoyiannis, and C. Makropoulos. "How extreme is extreme? An assessment of daily rainfall distribution tails." Hydrology and Earth System Sciences Discussions 9, no. 5 (May 2, 2012): 5757–78. http://dx.doi.org/10.5194/hessd-9-5757-2012.
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Abstract. The upper part of a probability distribution, usually known as the tail, governs both the magnitude and the frequency of extreme events. The tail behaviour of all probability distributions may be, loosely speaking, categorized in two families: heavy-tailed and light-tailed distributions, with the latter generating more "mild" and infrequent extremes compared to the former. This emphasizes how important for hydrological design is to assess correctly the tail behaviour. Traditionally, the wet-day daily rainfall has been described by light-tailed distributions like the Gamma, although heavier-tailed distributions have also been proposed and used, e.g. the Lognormal, the Pareto, the Kappa, and others. Here, we investigate the issue of tails for daily rainfall by comparing the upper part of empirical distributions of thousands of records with four common theoretical tails: those of the Pareto, Lognormal, Weibull and Gamma distributions. Specifically, we use 15 029 daily rainfall records from around the world with record lengths from 50 to 163 yr. The analysis shows that heavier-tailed distributions are in better agreement with the observed rainfall extremes than the more often used lighter tailed distributios, with clear implications on extreme event modelling and engineering design.
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Bennett, Bree, Martin Lambert, Mark Thyer, Bryson C. Bates, and Michael Leonard. "Estimating Extreme Spatial Rainfall Intensities." Journal of Hydrologic Engineering 21, no. 3 (March 2016): 04015074. http://dx.doi.org/10.1061/(asce)he.1943-5584.0001316.
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Hubert, P., Y. Tessier, S. Lovejoy, D. Schertzer, F. Schmitt, P. Ladoy, J. P. Carbonnel, S. Violette, and I. Desurosne. "Multifractals and extreme rainfall events." Geophysical Research Letters 20, no. 10 (May 21, 1993): 931–34. http://dx.doi.org/10.1029/93gl01245.
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Potter, Kenneth W., and Efi Foufoula-Georgiou. "Extreme rainfall and hydrologic design." Eos, Transactions American Geophysical Union 71, no. 8 (1990): 292. http://dx.doi.org/10.1029/90eo00068.
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Baker, Nick. "Extreme rainfall events (1958–68)." Weather 61, no. 7 (July 1, 2006): 211. http://dx.doi.org/10.1256/wea.42.06.
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Manzano-Agugliaro, F., A. Zapata-Sierra, C. Fernández-Castañeda, A. García-Cruz, and Q. Hernández-Escobedo. "Extreme rainfall relationship in Mexico." Journal of Maps 11, no. 3 (August 7, 2014): 405–14. http://dx.doi.org/10.1080/17445647.2014.945105.
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Eden, Philip, and Stephen Burt. "Extreme monthly rainfall: November 2009." Weather 65, no. 3 (March 2010): 82–83. http://dx.doi.org/10.1002/wea.568.
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Singh, Vishal, and Xiaosheng Qin. "Rainfall variability in Malay Peninsula region of Southeast Asia using gridded data." E3S Web of Conferences 81 (2019): 01002. http://dx.doi.org/10.1051/e3sconf/20198101002.
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Southeast Asia is recognized as a climate-change vulnerable region as it has been significantly affected by many extreme events in the past. This study carried out a rainfall analysis over the Malay Peninsula region of Southeast Asia utilizing historical (1981-2007) gridded rainfall datasets (0.5°×0.5°). The rainfall variability was analyzed in an intra-decadal time series duration. The uncertainty involved in all datasets was also checked based on the comparison of multiple global rainfall datasets. Rainfall gap filling analysis was conducted for producing more accurate rainfall time series after testing multiple mathematical functions. Frequency-based rainfall extreme indices such as Dry Days and Wet days are generated to assess the rainfall variability over the study area. Our results revealed a notable variation existed in the rainfalls over Malay Peninsula as per the long historical duration (1981-2007).
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Yeo, Myeong-Ho, James Pangelinan, and Romina King. "Identifying Characteristics of Guam’s Extreme Rainfalls Prior to Climate Change Assessment." Water 14, no. 10 (May 14, 2022): 1578. http://dx.doi.org/10.3390/w14101578.
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Extreme rainfall and its consequential flooding account for a devastating amount of damage to the Pacific Islands. Having an improved understanding of extreme rainfall patterns can better inform stormwater managers about current and future flooding scenarios, so they can minimize potential damages and disruptions. In this study, the scaling invariant properties of annual maximum precipitations (AMPs) are used for describing the regional patterns of extreme rainfalls over Guam. AMPs are calculated at seven stations in Guam and exhibit distinct simple scaling behavior for two different time frames: (1) from 15 min to 45 min; and (2) from 45 min to 24 h. With these two different behaviors, the conventional estimation methods for sub-hourly durations overestimate the frequencies at a site in which breakpoints are clearly observed, while the proposed Scaling Generalized Extreme Value (GEV) method, based on the Scaling Three-NCM (S3NCM) method, provides comparable estimates. A new regional extreme rainfall analysis approach based on scaling exponents is introduced in this study. Results show distinct extreme rainfall patterns over Guam. Moreover, the numerical and graphical analyses identify that a tropical cyclone may increase daily AMPs by 3%, on average.
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Panthou, Gérémy, Alain Mailhot, Edward Laurence, and Guillaume Talbot. "Relationship between Surface Temperature and Extreme Rainfalls: A Multi-Time-Scale and Event-Based Analysis*." Journal of Hydrometeorology 15, no. 5 (September 25, 2014): 1999–2011. http://dx.doi.org/10.1175/jhm-d-14-0020.1.
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Abstract Recent studies have examined the relationship between the intensity of extreme rainfall and temperature. Two main reasons justify this interest. First, the moisture-holding capacity of the atmosphere is governed by the Clausius–Clapeyron (CC) equation. Second, the temperature dependence of extreme-intensity rainfalls should follow a similar relationship assuming relative humidity remains constant and extreme rainfalls are driven by the actual water content of the atmosphere. The relationship between extreme rainfall intensity and air temperature (Pextr–Ta) was assessed by analyzing maximum daily rainfall intensities for durations ranging from 5 min to 12 h for more than 100 meteorological stations across Canada. Different factors that could influence this relationship have been analyzed. It appears that the duration and the climatic region have a strong influence on this relationship. For short durations, the Pextr–Ta relationship is close to the CC scaling for coastal regions while a super-CC scaling followed by an upper limit is observed for inland regions. As the duration increases, the slope of the relationship Pextr–Ta decreases for all regions. The shape of the Pextr–Ta curve is not sensitive to the percentile or season. Complementary analyses have been carried out to understand the departures from the expected Clausius–Clapeyron scaling. The relationship between dewpoint temperature and extreme rainfall intensity shows that the relative humidity is a limiting factor for inland regions, but not for coastal regions. Using hourly rainfall series, an event-based analysis is proposed in order to understand other deviations (super-CC, sub-CC, and monotonic decrease). The analyses suggest that the observed scaling is primarily due to the rainfall event dynamic.
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Stewart, E. J., D. W. Reed, D. S. Faulkner, and N. S. Reynard. "The FORGEX method of rainfall growth estimation I: Review of requirement." Hydrology and Earth System Sciences 3, no. 2 (June 30, 1999): 187–95. http://dx.doi.org/10.5194/hess-3-187-1999.
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Abstract. A growth factor is the ratio of the T-year extreme value to an index extreme value such as the mean of annual maxima. Whereas a record length of ten or more years may suffice to estimate the index variable, it is generally necessary to blend data from several sites if estimates of exceptional extreme values are to be obtained. Methods of rainfall growth estimation are reviewed, including traditional methods which extend frequency curves to long return period by a distributional assumption, and methods which study spatial dependence in extreme rainfalls. It is desirable that estimates at neighbouring sites, and across different durations and return periods, are internally consistent. The review concludes that rather special techniques may be required if this goal of estimation extreme rainfall depth consistently is to be met. The motivation of the Focused Rainfall Growth Extension (FORGEX) method is presented.
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Li, Y., W. Cai, and E. P. Campbell. "Statistical Modeling of Extreme Rainfall in Southwest Western Australia." Journal of Climate 18, no. 6 (March 15, 2005): 852–63. http://dx.doi.org/10.1175/jcli-3296.1.
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Abstract Rainfall over southwest Western Australia (SWWA; 32°S southward and 118°E westward) has been decreasing over the past decades, putting further constraints on water resources in an already dry area. In this study, daily rainfall over five geographically dispersed and homogenized weather stations within SWWA are analyzed. A peak over threshold method from the extreme value theory is used to model daily rainfall above a given threshold. The Mann–Whitney–Pittitt (change point) test was applied to detect changes in annual, winter (May–October), and summer (November–April) maximum daily rainfall. Change points for winter extreme daily rainfall were found around 1965, based on different individual stations, with the extreme daily rainfall reduced since then. To demonstrate the degree of change in the winter extreme daily rainfall, at 1965 the data were stratified, and generalized Pareto distributions were fitted to the tails of the distributions for daily rainfall in the prechange period of 1930–65 (including 1965) and the postchange period of 1966–2001. The fitted tail distributions also allow the estimation of probabilities and return periods of the daily rainfall extreme. Results show that return periods for the winter extreme daily rainfall have increased after 1965, implying that winter daily rainfall extremes in SWWA are lower after 1965 than they were before. There has been vigorous debate as to what forces the drying trend, that is, whether it is part of multidecadal variability or whether it is driven by secular forcings, such as increasing atmospheric CO2 concentration. In this paper, statistical modeling is also used to identify possible associated changes in atmospheric circulation. It is found that there is a change point near 1965 in a dominant atmospheric circulation mode of the Antarctic Oscillation (AAO). The result offers qualified support for the argument that the AAO may contribute to the drying trend.
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Burić, D., J. Luković, B. Bajat, M. Kilibarda, and V. Ducić. "Recent trends in daily rainfall extremes over Montenegro (1951–2010)." Natural Hazards and Earth System Sciences Discussions 3, no. 4 (April 10, 2015): 2347–77. http://dx.doi.org/10.5194/nhessd-3-2347-2015.
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Abstract. More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analyzed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period 1951–2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivošije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals, and their trends to identify possible changes. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. Calculated trends for each index are spatially presented and examined using a plotGoogleMaps software package. This study also examined spatial pattern of relationship between extreme rainfall indices and North Atlantic Oscillation. Results suggested negative, mainly statistically significant correlations at annual, winter and autumn scale.
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Jun, Tackseung, Lalith Munasinghe, and David H. Rind. "A New Metric for Indian Monsoon Rainfall Extremes*." Journal of Climate 28, no. 7 (March 27, 2015): 2842–55. http://dx.doi.org/10.1175/jcli-d-13-00764.1.
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Abstract Extreme monsoon rainfall in India has disastrous consequences, including significant socioeconomic impacts. However, little is known about the overall trends and climate factors associated with extreme rainfall because rainfall greatly varies across India and because few appropriate methods are available to measure extreme rainfall in the context of such heterogeneity. To provide a comprehensive assessment of extreme monsoon rainfall, the authors developed a metric using record rainfall data to measure the changes in the likelihood of extreme high and extreme low rainfall over time; this metric is independent of the characteristics of the underlying rainfall distributions. Hence, the metric is ideally suited to aggregate extreme rainfall information across heterogeneous regions covering India. The authors found that from 1930 to 2013, the likelihood of extreme high and extreme low rainfall increases 2-fold and 4-fold, respectively. These overall trend increases are driven by anomalous increases, particularly in the early 2000s; the likelihood of extreme high and extreme low rainfall increases 5-fold and 18-fold in 2005 and 2002, respectively. These findings imply a broadening of the underlying monsoon rainfall distribution over the past century. The authors also show that the time patterns of the likelihood of extreme rainfall in recent decades are correlated with El Niño–Southern Oscillation, especially when it is in the same phase with the Pacific decadal oscillation and Indian Ocean dipole.
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Pinna, Maria Silvia, Maria Cecilia Loi, Giulia Calderisi, and Giuseppe Fenu. "Extremes Rainfall Events on Riparian Flora and Vegetation in the Mediterranean Basin: A Challenging but Completely Unexplored Theme." Water 14, no. 5 (March 5, 2022): 817. http://dx.doi.org/10.3390/w14050817.
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In a global climate change scenario “Extreme climatic events” are expected to widely affect flora and vegetation in Med-regions, especially “Extremes Rainfall Events” which will have impacts on riparian environments. Aiming to provide an in-depth picture on the effects of these events on the riparian flora and vegetation in the Mediterranean Basin, especially focusing on islands, a bibliographic search was performed in the main international databases, which led to 571 articles published from 2000 to 2021. Most studies have analyzed these phenomena from the climatic point of view identifying three main topics “Rainfall”, “Global/Climate change”, and “Flood”. 81 papers concerned effects of extreme events on Mediterranean woodland formations and cultivated plants. A further analysis focused on European countries and Mediterranean bioregion using “Extreme rainfall events” and “Extreme rainfall and floods” as keywords. A low number of records relating to Mediterranean island regions was found, having Sicily as the study area. Moreover, seven articles had Sardinia as a study area, four of which referred to flora and vegetation. A lack of studies on the effects of extreme rainfall events on riparian flora and vegetation were highlighted. This review constitutes a call for researchers to explore extreme phenomena that have become recurrent in the Mediterranean Basin.
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Tayşi, H., and M. Özger. "Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods." Journal of Water and Climate Change 13, no. 2 (October 29, 2021): 684–706. http://dx.doi.org/10.2166/wcc.2021.241.
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Abstract Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.
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Papalexiou, S. M., D. Koutsoyiannis, and C. Makropoulos. "How extreme is extreme? An assessment of daily rainfall distribution tails." Hydrology and Earth System Sciences 17, no. 2 (February 28, 2013): 851–62. http://dx.doi.org/10.5194/hess-17-851-2013.
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Abstract. The upper part of a probability distribution, usually known as the tail, governs both the magnitude and the frequency of extreme events. The tail behaviour of all probability distributions may be, loosely speaking, categorized into two families: heavy-tailed and light-tailed distributions, with the latter generating "milder" and less frequent extremes compared to the former. This emphasizes how important for hydrological design it is to assess the tail behaviour correctly. Traditionally, the wet-day daily rainfall has been described by light-tailed distributions like the Gamma distribution, although heavier-tailed distributions have also been proposed and used, e.g., the Lognormal, the Pareto, the Kappa, and other distributions. Here we investigate the distribution tails for daily rainfall by comparing the upper part of empirical distributions of thousands of records with four common theoretical tails: those of the Pareto, Lognormal, Weibull and Gamma distributions. Specifically, we use 15 029 daily rainfall records from around the world with record lengths from 50 to 172 yr. The analysis shows that heavier-tailed distributions are in better agreement with the observed rainfall extremes than the more often used lighter tailed distributions. This result has clear implications on extreme event modelling and engineering design.