scholarly journals Modeling seasonal variations of extreme rainfall on different timescales in Germany

2021 ◽  
Vol 25 (12) ◽  
pp. 6133-6149
Author(s):  
Jana Ulrich ◽  
Felix S. Fauer ◽  
Henning W. Rust
Keyword(s):  
Extreme Events ◽  
Seasonal Variations ◽  
Scale Invariance ◽  
Extreme Event ◽  
Extreme Rainfall ◽  
Rapid Decrease ◽  
Monthly Precipitation ◽  
Wide Range ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract. We model monthly precipitation maxima at 132 stations in Germany for a wide range of durations from 1 min to about 6 d using a duration-dependent generalized extreme value (d-GEV) distribution with monthly varying parameters. This allows for the estimation of both monthly and annual intensity–duration–frequency (IDF) curves: (1) the monthly IDF curves of the summer months exhibit a more rapid decrease of intensity with duration, as well as higher intensities for short durations than the IDF curves for the remaining months of the year. Thus, when short convective extreme events occur, they are very likely to occur in summer everywhere in Germany. In contrast, extreme events with a duration of several hours up to about 1 d are conditionally more likely to occur within a longer period or even spread throughout the whole year, depending on the station. There are major differences within Germany with respect to the months in which long-lasting stratiform extreme events are more likely to occur. At some stations the IDF curves (for a given quantile) for different months intersect. The meteorological interpretation of this intersection is that the season in which a certain extreme event is most likely to occur shifts from summer towards autumn or winter for longer durations. (2) We compare the annual IDF curves resulting from the monthly model with those estimated conventionally, that is, based on modeling annual maxima. We find that adding information in the form of smooth variations during the year leads to a considerable reduction of uncertainties. We additionally observe that at some stations, the annual IDF curves obtained by modeling monthly maxima deviate from the assumption of scale invariance, resulting in a flattening in the slope of the IDF curves for long durations.

scholarly journals Modeling seasonal variations of extreme rainfall on different time scales in Germany

2021 ◽  
Author(s):  
Jana Ulrich ◽  
Felix S. Fauer ◽  
Henning W. Rust
Keyword(s):  
Extreme Events ◽  
Seasonal Variations ◽  
Scale Invariance ◽  
Extreme Event ◽  
Extreme Rainfall ◽  
Monthly Precipitation ◽  
Wide Range ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Different Time Scales

Abstract. We model monthly precipitation maxima at 132 stations in Germany for a wide range of durations from one minute to about six days using a duration-dependent generalized extreme value (d-GEV) distribution with monthly varying parameters. This allows for the estimation of both monthly and annual intensity–duration–frequency (IDF) curves: (1) The monthly IDF curves are steeper in summer and exhibit higher intensities for short durations than in the rest of the year. Thus, everywhere in Germany short convective extreme events occur very likely in summer. In contrast, extreme events with a duration of several hours up to about one day are more likely to occur within a longer period or even spread throughout the whole year, depending on the station. There are major differences within Germany with respect to the months in which long-lasting stratiform extreme events are more likely to occur. At some stations the IDF curves (for a given quantile) for different months intersect. The meteorological interpretation of this intersection is that the season at which a certain extreme event is most likely to occur shifts from summer towards autumn or winter for longer durations. (2) We compare the annual IDF curves resulting from the monthly model with those estimated conventionally, that is, based on modeling annual maxima. We find that adding information in the form of smooth variations during the year leads to a considerable reduction of uncertainties. We additionally observe that at some stations, the annual IDF curves obtained by modeling monthly maxima deviate from the assumption of scale invariance, resulting in a flattening in the slope of the IDF curves for long durations.

scholarly journals A Comparative Analysis of Climate-Risk and Extreme Event-Related Impacts on Well-Being and Health: Policy Implications

2018 ◽  
Vol 15 (2) ◽  
pp. 331 ◽  
Author(s):  
Walter Leal Filho ◽  
Abul Al-Amin ◽  
Gustavo Nagy ◽  
Ulisses Azeiteiro ◽  
Laura Wiesböck ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Extreme Event ◽  
Well Being ◽  
Lessons Learned ◽  
Policy Implications ◽  
Health Impacts ◽  
Climate Risks ◽  
Wide Range ◽  
Mental Problems

There are various climate risks that are caused or influenced by climate change. They are known to have a wide range of physical, economic, environmental and social impacts. Apart from damages to the physical environment, many climate risks (climate variability, extreme events and climate-related hazards) are associated with a variety of impacts on human well-being, health, and life-supporting systems. These vary from boosting the proliferation of vectors of diseases (e.g., mosquitos), to mental problems triggered by damage to properties and infrastructure. There is a great variety of literature about the strong links between climate change and health, while there is relatively less literature that specifically examines the health impacts of climate risks and extreme events. This paper is an attempt to address this knowledge gap, by compiling eight examples from a set of industrialised and developing countries, where such interactions are described. The policy implications of these phenomena and the lessons learned from the examples provided are summarised. Some suggestions as to how to avert the potential and real health impacts of climate risks are made, hence assisting efforts to adapt to a problem whose impacts affect millions of people around the world. All the examples studied show some degree of vulnerability to climate risks regardless of their socioeconomic status and need to increase resilience against extreme events.

scholarly journals Rainfall Intensity Analysis for Synoptic Stations in Northern Nigeria

2020 ◽  
Vol 17 (3) ◽  
pp. 223-228
Author(s):  
S.O. Oyegoke ◽  
A.S. Adebanjo ◽  
H.J. Ododo
Keyword(s):  
Rainfall Intensity ◽  
Linear Regression Analysis ◽  
Extreme Rainfall ◽  
Data Series ◽  
Northern Nigeria ◽  
Return Periods ◽  
Accurate Forecast ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Frequency Relationship

With the large inter-annual variability of rainfall in Northern Nigeria, a zone subject to frequent dry spells which often result in severe and widespread droughts, the need for intense study of rainfall and accurate forecast of rainfall intensity duration frequency (IDF) curves cannot be over emphasized. The Intensity Duration Frequency relationship is a mathematical relationship between the rainfall intensity and rainfall duration for given return periods. Using a subset of the network of fifteen continuous auto recording rain gauges available in Northern Nigeria, a total of seven different time durations ranging from 12 minutes to 24 hours were developed for return periods of 2, 5, 10, 25, 50 and 100 years. The maximum data series so obtained was fitted to Gumbel’s Extreme Value Type 1 distribution. Linear Regression Analysis was then used to obtain the intensity-duration relationships for the various locations from which Intensity-Duration Frequency (IDF) curves were generated using Microsoft Excel for various return periods. Keywords:  Extreme rainfall, intensity, duration, frequency, Northern Nigeria

scholarly journals Intensity–duration–frequency (IDF) rainfall curves in Senegal

2018 ◽  
Vol 18 (7) ◽  
pp. 1849-1866 ◽  
Author(s):  
Youssouph Sane ◽  
Geremy Panthou ◽  
Ansoumana Bodian ◽  
Theo Vischel ◽  
Thierry Lebel ◽  
...  
Keyword(s):  
Spatial Vision ◽  
Extreme Rainfall ◽  
Sub Saharan Africa ◽  
Parameter Estimates ◽  
Infrastructure Development ◽  
Demographic Pressure ◽  
Tropical Regions ◽  
Scaling Parameter ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract. Urbanization resulting from sharply increasing demographic pressure and infrastructure development has made the populations of many tropical areas more vulnerable to extreme rainfall hazards. Characterizing extreme rainfall distribution in a coherent way in space and time is thus becoming an overarching need that requires using appropriate models of intensity–duration–frequency (IDF) curves. Using a 14 series of 5 min rainfall records collected in Senegal, a comparison of two generalized extreme value (GEV) and scaling models is carried out, resulting in the selection of the more parsimonious one (four parameters), as the recommended model for use. A bootstrap approach is proposed to compute the uncertainty associated with the estimation of these four parameters and of the related rainfall return levels for durations ranging from 1 to 24 h. This study confirms previous works showing that simple scaling holds for characterizing the temporal scaling of extreme rainfall in tropical regions such as sub-Saharan Africa. It further provides confidence intervals for the parameter estimates and shows that the uncertainty linked to the estimation of the GEV parameters is 3 to 4 times larger than the uncertainty linked to the inference of the scaling parameter. From this model, maps of IDF parameters over Senegal are produced, providing a spatial vision of their organization over the country, with a north to south gradient for the location and scale parameters of the GEV. An influence of the distance from the ocean was found for the scaling parameter. It is acknowledged in conclusion that climate change renders the inference of IDF curves sensitive to increasing non-stationarity effects, which requires warning end-users that such tools should be used with care and discernment.

Bayesian Changepoint Analysis for Extreme Events (Typhoons, Heavy Rainfall, and Heat Waves): An RJMCMC Approach

2010 ◽  
Vol 23 (5) ◽  
pp. 1034-1046 ◽  
Author(s):  
Xin Zhao ◽  
Pao-Shin Chu
Keyword(s):  
Heat Wave ◽  
Extreme Events ◽  
Heavy Rainfall ◽  
Extreme Event ◽  
Heat Waves ◽  
Rare Event ◽  
Extreme Rainfall ◽  
Heavy Rainfall Event ◽  
Event Time ◽  
Chicago Area

Abstract A hierarchical Bayesian framework is developed to identify multiple abrupt regime shifts in an extreme event series. Specifically, extreme events are modeled as a Poisson process with a gamma-distributed rate. Multiple candidate hypotheses are considered, under each of which there presumably exist a certain number of abrupt shifts of the rate. A Bayesian network involving three layers—data, parameter, and hypothesis—is formulated. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm is developed to calculate posterior probability for each hypothesis as well its associated within-hypothesis parameters. Based on the proposed RJMCMC algorithm, a simulated example is designed to illustrate the effectiveness of the method. Subsequently, the algorithm is applied to three real, rare event time series: the annual typhoon counts over the western North Pacific (WNP), the annual extreme heavy rainfall event counts at the Honolulu airport, and the annual heat wave frequency in the Chicago area. Results indicate that the typhoon activity over the WNP is very likely to have undergone a decadal variation, with two change points occurring around 1972 and 1989 characterized by the active 1960–71 epoch, the inactive 1972–88 epoch, and the moderately active 1989–2006 epoch. For the extreme rainfall case, only one shift around 1970 is found and heavy rainfall frequency has remained stationary since then. There is no evidence that the rate of the annual heat wave counts in the Chicago area has had any abrupt change during the past 50 years.

scholarly journals Data-driven distinction between convective, frontal and mixed extreme rainfall events in radar data

2020 ◽  
Author(s):  
Emma Dybro Thomassen ◽  
Hjalte Jomo Danielsen Sørup ◽  
Marc Scheibel ◽  
Thomas Einfalt ◽  
Karsten Arnbjerg-Nielsen
Keyword(s):  
Extreme Events ◽  
Extreme Event ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Threshold Method ◽  
Extreme Rainfall Events ◽  
Temporal Properties ◽  
Peak Over Threshold ◽  
Spatio Temporal

Abstract. This study examines characteristics of extreme events based on a high-resolution precipitation dataset (5-minute temporal resolution, 1 &times 1 km spatial resolution) over an area of 1824 km2 covering the catchment of the river Wupper, North Rhine-Westphalia, Germany. Extreme events were sampled by a Peak Over Threshold method using several sampling strategies, all based on selecting an average of three events per year. A simple identification- and tracking algorithm for rain cells based on intensity threshold and fitting of ellipsoids, is developed for the study. Extremes were selected based on maximum intensities for 15-minute, hourly and daily durations and described by a set of 17 variables. The spatio-temporal properties of the extreme events are explored by means of a principal component analysis (PCA) and a cluster analysis for these 17 variables. We found that these analyses enabled us to distinguish and characterise types of extreme events useful for urban hydrology applications. The PCA indicated between 5 and 9 dimensions in the extreme event characteristic data. The cluster analyses identified four rainfall types: convective extremes, frontal extremes, mixed very extreme events and other extreme events, the last group consisting of events that are less extreme than the other events. The result is useful for selecting events of particular interest when assessing performance of e.g. urban drainage systems.

scholarly journals Scale-Invariance Generalized Logistic (GLO) Model for Estimating Extreme Design Rainfalls in the Context of Climate Change

10.29007/5xqt ◽  
2018 ◽  
Author(s):  
Truong-Huy Nguyen ◽  
Van-Thanh-Van Nguyen
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Scale Invariance ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Extreme Rainfall ◽  
Logistic Distribution ◽  
Generalized Logistic Distribution ◽  
Climate Simulations ◽  
Wide Range

Statistical models based on the scale-invariance (or scaling) concept has increasingly become an essential tool for modeling extreme rainfall processes over a wide range of time scales. In particular, in the context of climate change these scaling models can be used to describe the linkages between the distributions of sub-daily extreme rainfalls (ERs) and the distribution of daily ERs that is commonly provided by global or regional climate simulations. Furthermore, the Generalized Logistic distribution (GLO) has been recommended in UK for modeling of extreme hydrologic variables. Therefore, the main objective of the present study is to propose a scaling GLO model for modeling ER processes over different time scales. The feasibility and accuracy of this model were assessed using ER data from a network of 21 raingages located in Ontario, Canada. Results of this assessment based on different statistical criteria have indicated the comparable performance of the proposed scaling GLO model as compared to other popular models in practice. Furthermore, an illustrative application of the proposed model for evaluating the climate change impacts on the ERs in Ontario using the available NASA downscaled regional climate simulations has demonstrated the accuracy and robustness of the GLO model.

scholarly journals Sub-daily extreme events distribution and changes in Northeastern Brazil in the 20th century

2015 ◽  
Vol 369 ◽  
pp. 135-140 ◽  
Author(s):  
R. Basso ◽  
D. Allasia ◽  
R. Tassi ◽  
D. M. Bayer
Keyword(s):  
20Th Century ◽  
Extreme Events ◽  
Regional Analysis ◽  
Extreme Rainfall ◽  
Northeastern Brazil ◽  
The North ◽  
Hourly Rainfall ◽  
Northern Portion ◽  
Intensity Duration Frequency ◽  
Engineering Projects

Abstract. The regional analysis of extreme hydrological events is connected with the availability of a dense network of rainfall data that is absent or inaccessible in Brazil, especially for sub-daily information. In engineering, extreme events rainfall information is represented by intensity–duration–frequency (IDF) relationships which are the most commonly used tools in water resources engineering for planning and design. Even if the sub-daily information that is included in the relationships is not available, the extreme rainfall information rest in the fundamentals of the IDF. This paper analyzes spatial distribution and track changes in sub-daily precipitation over Northeastern (NE) Brazil. Precipitation was estimated from IDF relationships information in Brazil based in rainfall measured from 1920's to 1950's (but still used in engineering projects) and information from the last half of the 20th century obtained from several IDFs gathered from municipalities' manuals, local symposia and books in many cases not easily obtainable. Results showed an intensification of extreme events in recent years, especially in shorter duration rainfall (less than 12 h). Hourly rainfall is bigger in almost all the Brazilian region, but especially in littoral and Northern portion, however, 12 and 24 h rainfall exhibit increases in the North, but, lower values in the Southern half of the region in concordance with flood changes reported by Milly et al. (2005). Analyzing the ratio between 1 and 24 h rainfall is possible to confirm its increase in all the region, with up to 35% in some areas. These results were able to show insight of sub-daily extreme events changes during 20th century in NE Brazil were previous reports were not found. The results also alerts for the necessity of engineering projects review, as outdated information is still being used for design purposes.

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

2010 ◽  
Vol 18 (3) ◽  
pp. 1-6 ◽  
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.

Analysis of potential impacts of climate change on intensity–duration–frequency (IDF) relationships for six regions in the United States

2012 ◽  
Vol 3 (3) ◽  
pp. 185-196 ◽  
Author(s):  
Jianting Zhu ◽  
Mark C. Stone ◽  
William Forsee
Keyword(s):  
Climate Change ◽  
United States ◽  
Rainfall Intensity ◽  
Extreme Rainfall ◽  
The United States ◽  
Regional Patterns ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Projected Changes ◽  
Impacts Of Climate Change

Potential changes in climate are expected to lead to future changes in the characteristics of precipitation events, including extreme rainfall intensity in most regions. In order for government agencies and design engineers to incorporate these trends and future changes into assessment and design processes, tools for planning and design should be capable of considering nonstationary climate conditions. In this work, potential changes are investigated in intensity–duration–frequency (IDF) curves, which are often used for assessment of extreme rainfall events, using historic data and future climate projections. An approach is proposed for calculating IDF curves that incorporates projected changes in rainfall intensity at a range of locations in the United States. The results elucidate strong regional patterns in projected changes in rainfall intensity, which are influenced by the rainfall characteristics of the region. Therefore, impacts of climate change on extreme hydrologic events will be highly regional and thus such assessments should be performed for specific project locations.

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