Short‐Duration Rainfalls in Sicily

Ferreri, Giovanni Battista; Ferro, Vito

doi:10.1061/(asce)0733-9429(1990)116:3(430)

Cited by 22 publications

(14 citation statements)

References 3 publications

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“…This is an often-observed features of short-duration rainfall, noted and reported, among others, by Hershfield (1962) and Bell (1969) for the United States, by Ferreri and Ferro (1990) for Italy, by Kothyari and Garde (1992) for India and by Alila (2000) for Canada. Moreover, the difference in the values reported for the scaling exponent in these studies is rather small, with a value of 0.393 for Canada (Alila, 2000), 0.386 and 0.345 in Sicily and Sardinia, respectively (Ferreri and Ferro, 1990) and 0.290 for India (Kothyari and Garde, 1992).…”

Section: Spatial Estimation Of Ddf Curves In the Study Areasupporting

confidence: 68%

“…This high degree of consistency in short-duration rainfall frequency implies that local convective cells have similar physical properties irrespective of geographical location. While this hypothesis has never been verified before in the study area, it has been advocated in other studies (Hershfield, 1962;Bell, 1969;Ferreri and Ferro, 1990;Alila, 2000), as detailed below. Incidentally, no break in scaling could be observed for the data from the Trento station (Figure 2), because the overall scaling exponent (0.399, computed for Trento station on the range from 15 min to 24 h) was pretty close to the constant value computed for the whole area for short durations rainfalls (0.366).…”

Section: Spatial Estimation Of Ddf Curves In the Study Areamentioning

confidence: 54%

“…The scaling exponent for duration shorter than 60 min can be considered fairly constant over the study area. This finding, considered within the scaling approach, provides an explanation for the often-observed empirical result that the ratio of the t-min rainfall to 60-min rainfall for the same return period may be considered constant over a given geographical region (Hershfield, 1962;Bell, 1969;Ferreri and Ferro, 1990;Kothyari and Garde, 1992;Alila, 2000).…”

Section: Introductionmentioning

confidence: 76%

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Regional Rainfall Depth–Duration–Frequency Equations for an Alpine Region

2005

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In this paper the scaling hypotheses are applied to annual maximum series of rainfall depth for different rainfall duration to derive the depth-duration-frequency (DDF) curve. It is shown that, based on the empirically observed scaling properties of rainfall and some general assumptions about the cumulative distribution function for the annual maximum of the rainfall depth, it is possible to derive a simple DDF relationship. This general framework provides a basis for the generation of maps that can be used to infer DDF curves at any point of a particular area. Data from a dense raingauge network in a mountainous region in north-eastern Italy (the Trentino Province) are used to clarify the methodology for the construction and regionalization of the DDF relationship. The geographical variation of short-duration (i.e., less than 60 min) rainfall extremes is also evaluated by using the same framework. It is found that depth-duration ratios, defined as the ratios of the t-min to the 60-min rainfall depths of the same return period, may be considered independent of return period and geographical location for any storm duration less than 60 min.

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Section: Spatial Estimation Of Ddf Curves In the Study Areasupporting

confidence: 68%

Section: Spatial Estimation Of Ddf Curves In the Study Areamentioning

confidence: 54%

Section: Introductionmentioning

confidence: 76%

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Regional Rainfall Depth–Duration–Frequency Equations for an Alpine Region

2005

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“…In particular, Castellarin et al [2009] show that if (1) the relationship between L‐coefficients of variation and skewness (i.e., L‐CV and L‐CS, for a definition of L‐moments see, e.g., Hosking [1990]) of rainfall extremes and MAP can be formalized through an exponentially decaying curve, and (2) a nondecreasing relationship holds between the mean annual maximum rainfall depth

m_{τ}

(for duration

τ

) and MAP [see, e.g., Herschfield , 1961; Bell , 1969; Ferreri and Ferro , 1990; Alila , 1999; Di Baldassarre et al , 2006], an approximate regional representation of the dependence on MAP of the ratio between the T ‐year rainfall quantile

h_{τ, T}

(for duration

τ

) and MAP can be expressed as

ln \frac{h_{τ, T}}{MAP} = A_{τ, T} + B_{τ} ln (MAP),

where

A_{τ, T}

and

B_{τ}

are regional coefficients.…”

Section: Methodsmentioning

confidence: 99%

Extreme rainstorms: Comparing regional envelope curves to stochastically generated events

Viglione¹,

Castellarin

Rogger³

et al. 2012

Water Resources Research

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[1] The depth-duration envelope curves (DDECs) are regional upper bounds on observed rainfall maxima for several durations. Recently, a probabilistic interpretation has been proposed in the literature in order to associate a recurrence interval T to the DDECs and, consequently, to retrieve point rainfall quantiles for ungauged sites. Alternatively, extreme rainfall quantiles can be retrieved from long synthetic rainfall series obtained with stochastic rainfall generators calibrated to local time series of rainfall events. While DDECs are sensitive to outliers and data errors, the stochastic rainfall generator performance is affected by the limited record lengths used for calibration. The objective of this study is to assess the reliability of the two alternative methods by verifying if they give consistent results for a wide study region in Austria. Relative to previous studies, we propose some generalizations of the DDEC procedure in order to better represent the Austrian data. The comparison of rainfall quantiles estimated with the two methods for large T shows an excellent agreement for intermediate durations (from 1 to 6 h), while the agreement worsen for very short (15 min) and long (24 h) durations. The results are scrupulously analyzed and discussed in light of the exceptionality of rainfall events that set the regional envelopes and the characteristics of the stochastic generator used. Our study points out that the combined use of these regional and local methods can be very useful for estimating reliable point rainfall quantiles associated with large T within regions where many rain gauges are available, but with limited record lengths.

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“…The value of n has been believed to be independent of return period (e.g., Ferreri and Ferro, 1990). However, in fact, as showed in Fig.…”

Section: Estimation Of Probable Precipitationmentioning

confidence: 98%

Geographical Distributions of Probable Hourly Precipitation and Probable Daily Precipitation over Japan-Using

Suda

1991

Journal of the Meteorological Society of Japan

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Probable precipitation is estimated from a complete-duration data set of the AMeDAS data, which has a dense station coverage over Japan, instead of annual maximum precipitation data sets used in previous studies. Thus, we can obtain probable precipitation with a relatively small estimation error due to the large size of the data set. The probable precipitation is estimated by applying the gamma distribution to the AMeDAS data. The results are summarized as follows: 1) The geographical distribution of probable daily precipitation is closely related to topography, and that of probable hourly precipitation shows large latitudinal difference. In Kyushu, the high-ranked stations in probable hourly precipitation are distributed in the western part, and those in probable daily precipitation are found along the backbone range. Also, in eastern Shikoku, the probable hourly precipitation and probable daily precipitation are greater in coastal regions and mountainous regions, respectively. These differences indicate that the duration and intensity of heavy rain differ with geographical factors, such as topographical conditions and latitude, its cause having peculiar regional characteristics.2) The relationship between probable precipitation R(t) and time t can be expressed by the equation R(t)=ctn. A station with a large value of n has long duration of heavy rains. The value of n at each station changes slightly with the length of a return period, and the regional difference in the value becomes increasingly large with an increase in the length.

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Short‐Duration Rainfalls in Sicily

Cited by 22 publications

References 3 publications

Regional Rainfall Depth–Duration–Frequency Equations for an Alpine Region

Regional Rainfall Depth–Duration–Frequency Equations for an Alpine Region

Extreme rainstorms: Comparing regional envelope curves to stochastically generated events

Geographical Distributions of Probable Hourly Precipitation and Probable Daily Precipitation over Japan-Using

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