Characterising the space–time structure of rainfall in the  Sahel with a view to estimating IDAF curves

Abstract. Intensity–duration–area–frequency (IDAF) curves are increasingly demanded for characterising the severity of storms and for designing hydraulic structures. Their computation requires inferring areal rainfall distributions over the range of space scales and timescales that are the most relevant for hydrological studies at catchment scale. In this study, IDAF curves are computed for the first time in West Africa, based on the data provided by the AMMA-CATCH Niger network, composed of 30 recording rain gauges having operated since 1990 over a 16 000 km2 area in south-western Niger. The IDAF curves are obtained by separately considering the time (intensity–duration–frequency, IDF) and space (areal reduction factor, ARF) components of the extreme rainfall distribution. Annual maximum intensities are extracted for resolutions between 1 and 24 h in time and from point (rain gauge) to 2500 km2 in space. The IDF model used is based on the concept of scale invariance (simple scaling) which allows the normalisation of the different temporal resolutions of maxima series to which a global generalised extreme value (GEV) is fitted. This parsimonious framework allows one to use the concept of dynamic scaling to describe the ARF. The results show that coupling a simple scaling in space and time with a dynamical scaling that relates to space and time allows one to satisfactorily model the effect of space–time aggregation on the distribution of extreme rainfall.

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Characterizing the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8409-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8409-8441 ◽

Cited By ~ 3

Author(s):

G. Panthou ◽

T. Vischel ◽

T. Lebel ◽

G. Quantin ◽

G. Molinié

Keyword(s):

Extreme Rainfall ◽

Rain Gauge ◽

Space Time ◽

Reduction Factor ◽

Dynamic Scaling ◽

Catchment Scale ◽

Dynamical Scaling ◽

Space And Time ◽

Time Aggregation ◽

Simple Scaling

Abstract. Intensity–duration–area–frequency (IDAF) curves are increasingly demanded for characterizing the severity of storms and for designing hydraulic structures. Their computation requires inferring areal rainfall distributions over the range of space–time scales that are the most relevant for hydrological studies at catchment scale. In this study, IDAF curves are computed for the first time in West Africa, based on the data provided by the AMMA-CATCH Niger network, composed of 30 recording rain gauges having operated since 1990 over a 16 000 km2 area in South West Niger. The IDAF curves are obtained by separately considering the time (IDF) and space (Areal Reduction Factor – ARF) components of the extreme rainfall distribution. Annual maximum intensities are extracted for resolutions between 1 and 24 h in time and from point (rain-gauge) to 2500 km2 in space. The IDF model used is based on the concept of scale invariance (simple scaling) which allows the normalization of the different temporal resolutions of maxima series to which a global GEV is fitted. This parsimonious framework allows using the concept of dynamic scaling to describe the ARF. The results show that coupling a simple scaling in space and time with a dynamical scaling relating space and time allows modeling satisfactorily the effect of space–time aggregation on the distribution of extreme rainfall.

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Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean

Hydrology and Earth System Sciences ◽

10.5194/hess-21-2389-2017 ◽

2017 ◽

Vol 21 (5) ◽

pp. 2389-2404 ◽

Cited By ~ 28

Author(s):

Francesco Marra ◽

Efrat Morin ◽

Nadav Peleg ◽

Yiwen Mei ◽

Emmanouil N. Anagnostou

Keyword(s):

Remote Sensing ◽

Return Period ◽

Eastern Mediterranean ◽

Rain Gauge ◽

Catchment Scale ◽

Weather Radars ◽

The Earth ◽

Idf Curves ◽

Intensity Duration Frequency ◽

Frequency Curves

Abstract. Intensity–duration–frequency (IDF) curves are widely used to quantify the probability of occurrence of rainfall extremes. The usual rain gauge-based approach provides accurate curves for a specific location, but uncertainties arise when ungauged regions are examined or catchment-scale information is required. Remote sensing rainfall records, e.g. from weather radars and satellites, are recently becoming available, providing high-resolution estimates at regional or even global scales; their uncertainty and implications on water resources applications urge to be investigated. This study compares IDF curves from radar and satellite (CMORPH) estimates over the eastern Mediterranean (covering Mediterranean, semiarid, and arid climates) and quantifies the uncertainty related to their limited record on varying climates. We show that radar identifies thicker-tailed distributions than satellite, in particular for short durations, and that the tail of the distributions depends on the spatial and temporal aggregation scales. The spatial correlation between radar IDF and satellite IDF is as high as 0.7 for 2–5-year return period and decreases with longer return periods, especially for short durations. The uncertainty related to the use of short records is important when the record length is comparable to the return period ( ∼  50, ∼  100, and ∼  150 % for Mediterranean, semiarid, and arid climates, respectively). The agreement between IDF curves derived from different sensors on Mediterranean and, to a good extent, semiarid climates, demonstrates the potential of remote sensing datasets and instils confidence on their quantitative use for ungauged areas of the Earth.

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Simple scaling of extreme precipitation in North America

Hydrology and Earth System Sciences ◽

10.5194/hess-21-5823-2017 ◽

2017 ◽

Vol 21 (11) ◽

pp. 5823-5846 ◽

Cited By ~ 12

Author(s):

Silvia Innocenti ◽

Alain Mailhot ◽

Anne Frigon

Keyword(s):

North America ◽

Extreme Precipitation ◽

Probability Distributions ◽

Spatial Scales ◽

Extreme Rainfall ◽

Parameter Estimates ◽

Infrastructure Design ◽

Simple Scaling ◽

Intensity Duration Frequency ◽

Extreme Probability

Abstract. Extreme precipitation is highly variable in space and time. It is therefore important to characterize precipitation intensity distributions on several temporal and spatial scales. This is a key issue in infrastructure design and risk analysis, for which intensity–duration–frequency (IDF) curves are the standard tools used for describing the relationships among extreme rainfall intensities, their frequencies, and their durations. Simple scaling (SS) models, characterizing the relationships among extreme probability distributions at several durations, represent a powerful means for improving IDF estimates. This study tested SS models for approximately 2700 stations in North America. Annual maximum series (AMS) over various duration intervals from 15 min to 7 days were considered. The range of validity, magnitude, and spatial variability of the estimated scaling exponents were investigated. Results provide additional guidance for the influence of both local geographical characteristics, such as topography, and regional climatic features on precipitation scaling. Generalized extreme-value (GEV) distributions based on SS models were also examined. Results demonstrate an improvement of GEV parameter estimates, especially for the shape parameter, when data from different durations were pooled under the SS hypothesis.

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Comparing Intensity–Duration–Frequency curves derived from CMORPH and radar rainfall estimates over the Eastern Mediterranean

10.5194/hess-2016-597 ◽

2016 ◽

Cited By ~ 2

Author(s):

Francesco Marra ◽

Efrat Morin ◽

Nadav Peleg ◽

Yiwen Mei ◽

Emmanouil N. Anagnostou

Keyword(s):

Return Period ◽

Eastern Mediterranean ◽

Rain Gauge ◽

Catchment Scale ◽

Radar Rainfall ◽

Weather Radars ◽

Rainfall Extremes ◽

Idf Curves ◽

Intensity Duration Frequency ◽

Tail Distributions

Abstract. Intensity–Duration–Frequency (IDF) curves are widely used to quantify the probability of occurrence of rainfall extremes. The usual rain gauge based approach provides accurate curves for a specific location, but uncertainties arise when ungauged regions are examined or catchment scale information is required. Remotely sensed rainfall records, e.g. from weather radars and satellites, are recently becoming available, providing high resolution information on rainfall extremes at regional or even global scales: their uncertainty and implications on water resources applications urge to be investigated. This study compares IDF curves from radar and satellite (CMORPH) estimates over the Eastern Mediterranean (covering Mediterranean, semiarid and arid climates) and quantifies the uncertainty related to their limited record on varying climates. We show that radar identifies thicker tail distributions than satellite, in particular for short durations, and that the shape parameters depends on the spatial and temporal aggregation scales. The spatial correlation between radar-IDFs and satellite-IDFs is as high as 0.7 for 2–5 years return period and decreases with longer return periods, especially for short durations. The uncertainty related to the use of short records is important when the record length is comparable to the return period (~ 50 %, ~ 100 % and ~ 150 % for Mediterranean, semiarid and arid climates, respectively). The agreement between IDF curves derived from different sensors on Mediterranean and, to a good extent, semiarid climates, demonstrates the potential of remote sensing datasets and instils confidence on their quantitative use for ungauged areas of the Earth.

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Assessing of IDF curves for hydrological design by simple scaling of 1-day precipitation totals

Slovak Journal of Civil Engineering ◽

10.2478/v10189-010-0010-8 ◽

2010 ◽

Vol 18 (3) ◽

pp. 1-6 ◽

Cited By ~ 2

Author(s):

M. Bara ◽

S. Kohnová ◽

J. Szolgay ◽

L. Gaál ◽

K. Hlavčová

Keyword(s):

Extreme Rainfall ◽

Meteorological Station ◽

Short Term ◽

Scaling Properties ◽

Daily Data ◽

Design Values ◽

Simple Scaling ◽

Recurrence Intervals ◽

Idf Curves ◽

Intensity Duration Frequency

Assessing of IDF curves for hydrological design by simple scaling of 1-day precipitation totalsIn this paper the scaling properties of short term extreme rainfall in Slovakia were investigated. The simple scaling theory was applied to the intensity-duration-frequency (IDF) characteristics of a short duration rainfall. This method allows for the estimation of the design values of rainfall of selected recurrence intervals and durations shorter than a day by using only the daily data. The scaling behavior of rainfall intensities was examined, and the possibility of using simple scaling in Slovakia was verified. The methodology for the simple scaling of rainfall is demonstrated using an example of the meteorological station in Ilava.

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An Integrated Extreme Rainfall Modeling Tool (SDExtreme) for Climate Change Impacts and Adaptation

10.21203/rs.3.rs-338969/v1 ◽

2021 ◽

Author(s):

Myeong-Ho Yeo ◽

Van-Thanh-Van Nguyen ◽

Yong Sang Kim ◽

Theodore A. Kpodonu

Keyword(s):

Climate Change ◽

Climate Model ◽

Regional Climate ◽

Climate Change Impacts ◽

Extreme Rainfall ◽

Rain Gauge ◽

Climate Change Scenarios ◽

Climate Conditions ◽

Modeling Software ◽

Intensity Duration Frequency

Abstract The estimation of the Intensity-Duration-Frequency (IDF) relations is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change condition. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for the current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4).

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Radar–rain-gauge rainfall estimation for hydrological applications in small catchments

Advances in Geosciences ◽

10.5194/adgeo-44-61-2017 ◽

2017 ◽

Vol 44 ◽

pp. 61-66 ◽

Cited By ~ 5

Author(s):

Salvatore Gabriele ◽

Francesco Chiaravalloti ◽

Antonio Procopio

Keyword(s):

Extreme Rainfall ◽

Mediterranean Area ◽

Rain Gauge ◽

Spatial And Temporal Variability ◽

Rainfall Runoff ◽

Catchment Scale ◽

Extreme Rainfall Events ◽

Rain Gauges ◽

Small Catchments ◽

Hydrological Applications

Abstract. The accurate evaluation of the precipitation's time–spatial structure is a critical step for rainfall–runoff modelling. Particularly for small catchments, the variability of rainfall can lead to mismatched results. Large errors in flow evaluation may occur during convective storms, responsible for most of the flash floods in small catchments in the Mediterranean area. During such events, we may expect large spatial and temporal variability. Therefore, using rain-gauge measurements only can be insufficient in order to adequately depict extreme rainfall events. In this work, a double-level information approach, based on rain gauges and weather radar measurements, is used to improve areal rainfall estimations for hydrological applications. In order to highlight the effect that precipitation fields with different level of spatial details have on hydrological modelling, two kinds of spatial rainfall fields were computed for precipitation data collected during 2015, considering both rain gauges only and their merging with radar information. The differences produced by these two precipitation fields in the computation of the areal mean rainfall accumulation were evaluated considering 999 basins of the region Calabria, southern Italy. Moreover, both of the two precipitation fields were used to carry out rainfall–runoff simulations at catchment scale for main precipitation events that occurred during 2015 and the differences between the scenarios obtained in the two cases were analysed. A representative case study is presented in detail.

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Evaluating the performance of a max-stable process for estimating intensity-duration-frequency curves

10.5194/egusphere-egu2020-19707 ◽

2020 ◽

Author(s):

Oscar E. Jurado ◽

Jana Ulrich ◽

Henning W. Rust

Keyword(s):

Reference Model ◽

Stable Process ◽

Extreme Rainfall ◽

Rain Gauge ◽

Dependence Structure ◽

Stable Model ◽

Asymptotic Dependence ◽

Skill Scores ◽

Idf Curves ◽

Intensity Duration Frequency

<p>A recent development in the modeling of intensity-duration-frequency (IDF) curves involves the use of a spatial max-stable process to explicitly account for asymptotic dependence between durations. To accomplish this, we use a duration-space instead of a geographic-space, following Tyralis and Langousis (2018). The resulting IDF curves can then be used to estimate extreme rainfall for any arbitrary rainfall duration. We aim to determine whether the use of a model that explicitly accounts for the dependence between durations could improve the estimates of extreme rainfall. The performance of the max-stable process is compared to the duration dependent GEV (d-GEV) approach for IDF-curve estimation proposed by Koutsoyiannis et al. (1998). The max-stable approach explicitly models the dependence via a parametric model, while the d-GEV approach assumes that the durations are independent. The performance of both approaches is assessed for two scenarios, in a controlled simulation experiment, and for observations from a rain gauge. A Brown-Resnick max-stable process and a duration-dependent GEV was fitted to the data in both scenarios. The performance is measured using the Quantile Skill Score (QSS) with the d-GEV as the reference model. The resulting skill scores show that correctly specifying the dependence structure leads to the max-stable model perfomring similarly to the d-GEV. This pattern was observed also for low and high levels of dependence.</p>

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Simple Scaling of extreme precipitation in North America

10.5194/hess-2016-586 ◽

2016 ◽

Author(s):

Silvia Innocenti ◽

Alain Mailhot ◽

Anne Frigon

Keyword(s):

North America ◽

Extreme Precipitation ◽

Probability Distributions ◽

Spatial Scales ◽

Extreme Rainfall ◽

Parameter Estimates ◽

Infrastructure Design ◽

Simple Scaling ◽

Intensity Duration Frequency ◽

Extreme Probability

Abstract. Extreme precipitation is highly variable in space and time. It is therefore important to characterize precipitation intensity distributions at several temporal and spatial scales. This is a key issue in infrastructure design and risk analysis, for which Intensity-Duration-Frequency (IDF) curves are the standard tools used for describing the relationships among extreme rainfall intensities, their frequencies, and their durations. Simple Scaling (SS) models, characterizing the relationships among extreme probability distributions at several durations, represent a powerful means for improving IDF estimates. This study tested SS models for approximately 2700 stations in North America. Annual Maxima Series (AMS) over various duration intervals from 15 h to 7 days were considered. The range of validity, magnitude, and spatial variability of the estimated scaling exponents were investigated. Results provide additional guidance for the influence of both local geographical characteristics, such as topography, and regional climatic features on precipitation scaling. Generalized Extreme Value (GEV) distributions based on SS models were also examined. Results demonstrate an improvement of GEV parameter estimates, especially for the shape parameter, when data from different durations were pooled under the SS hypothesis.

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Espaço, Tempo e Modernidade

GEOgraphia ◽

10.22409/geographia2000.23.a13374 ◽

2009 ◽

Vol 2 (3) ◽

pp. 51

Author(s):

Gilvan Luiz Hansen

Keyword(s):

Modern Philosophy ◽

Space Time ◽

Space And Time ◽

Time Concepts

Resumo Este artigo é uma discussão introdutória acerca da importância das concepções de espaço e tempo na modernidade. O objetivo deste texto é enfatizar os aspectos teóricos e práticos dos conceitos de espaço e tempo, mediante a apresentação de três perspectivas de interpretação desta questão na filosofia desenvolvida na modernidade. Palavras-chave: Modernidade, Espaço, Tempo, Filosofia Moderna, J. Habermas.Abstract This article is an introductory debate about the importance of space and time conceptions in modernity. The objective from this text is emphasize the theoretical and practical aspects of space and time concepts, by presentation of three interpretation perspectives of this question in the philosophy developed in modernity. Keywords: Modernity, Space, Time, Modern Philosophy, J. Habermas.

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