Extreme precipitation in Europe: statistical threshold selection based on climatological criteria

Αnagnostopoulou, Christina; Τολίκα, Κωνσταντία

doi:10.1007/s00704-011-0487-8

Cited by 66 publications

(39 citation statements)

References 26 publications

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“…According to the second technique, POT, the rainfall episodes with amounts higher than 99% were chosen as extremes. The percentage of 99% is in agreement with Anagnostopoulou and Tolika [14] who proved that this is the most appropriate threshold for extreme rainfalls in Europe. The two new produced data sets were fitted on both the Generalized Extreme Value Distribution (GEV) and the Generalized Pareto Distribution (GPD) respectively.…”

Section: Methodssupporting

confidence: 90%

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An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean

Lazoglou

Αnagnostopoulou

2017

Proceedings of the 2nd International Electronic Conference on Atmospheric Sciences

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Extreme rainfall is one of the most devastating natural events. The frequency and intensity of these events has increased. This trend will likely continue as the effects of climate change become more pronounced. As a consequence, it is necessary to evaluate the different statistical methods that assess the occurrence of the extreme rainfalls. This research evaluates some of the most important statistical methods that are used for the analysis of the extreme precipitation events. Extreme Value Theory is applied on ten station data located in the Mediterranean region. Furthermore, its two main fundamental approaches (Block-Maxima and POT) and three commonly used methods for the calculation of the extreme distributions parameters (Maximum Likelihood, L-Moments, and Bayesian) are analyzed and compared. The results showed that the Generalized Pareto Distribution provides better theoretical justification to predict extreme precipitation compared to Generalized Extreme Value distribution while in the majority of stations the most accurate parameters for the highest precipitation levels are estimated with the Bayesian method. Extreme precipitation for return period of 50, 150 and 300 years were finally obtained which indicated that Generalized Extreme Value Distribution with Bayesian estimator presents the highest return levels for western stations, while for the eastern Mediterranean stations the Generalized Pareto Distribution with Bayesian estimator presents the highest ones.

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Section: Methodssupporting

confidence: 90%

“…The choice of the distribution that can characterize the extreme rainfall's behavior became using goodness of fit tests. In accordance with many researches [14][15][16][17] GEV and GPD distribution seem to be the most appropriate. The importance of choosing an appropriate distribution is great, as it can affect the final results [18].…”

Section: Discussionsupporting

confidence: 79%

An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean

Lazoglou

Αnagnostopoulou

2017

Proceedings of the 2nd International Electronic Conference on Atmospheric Sciences

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“…The key aspect in this approach is the appropriate threshold selection. In this study, both POT methods and percentile indices are applied, based on the study by Anagnostopoulou and Tolika [19], for estimating extreme precipitation values over Europe. In order to deal with the sensitive concept of the POT's threshold selection, three POT methods are applied: the Mean Residual Life (MRL), the Threshold Choice (TC), and the Dispersion Index (DI), and the mean of their resulting threshold is chosen as the final threshold.…”

Section: Introductionmentioning

confidence: 99%

Climatic Study of the Marine Surface Wind Field over the Greek Seas with the Use of a High Resolution RCM Focusing on Extreme Winds

Vagenas

Αnagnostopoulou

Τολίκα

2017

Climate

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Abstract:The marine surface wind field (10 m) over the Greek seas is analyzed in this study using The RegCM. The model's spatial resolution is dynamically downscaled to 10 km × 10 km, in order to simulate more efficiently the complex coastlines and the numerous islands of Greece. Wind data for the 1980-2000 and 2080-2100 periods are produced and evaluated against real observational data from 15 island and coastal meteorological stations in order to assess the model's ability to reproduce the main characteristics of the surface wind fields. RegCM model shows a higher simulating skill to project seasonal wind speeds and direction during summer and the lowest simulating skill in the cold period of the year. Extreme wind speed thresholds were estimated using percentiles indices and three Peak Over Threshold (POT) techniques. The mean threshold values of the three POT methods are used to examine the inter-annual distribution of extreme winds in the study region. The highest thresholds were observed in three poles; the northeast, the southeast, and the southwest of Aegean Sea. Future changes in extreme speeds show a general increase in the Aegean Sea, while lower thresholds are expected in the Ionian Sea. Return levels for periods of 20, 50, 100, and 200 years are estimated.

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“…Irrigation period and therefore the calculation of IWD started with the beginning of onion cultivation (=sowing).Date of sowing has been set to 15 March equal in all simulations. Dates and duration of growth stages determined by accumulated temperature as well as corresponding crop coefficients for onion were used.…”

Section: Determination Of Onion Phenological Growth Stagesmentioning

confidence: 99%

“…Studies on the climate change impact on precipitation reveal that there is any general, world-wide validity for precipitation amount, distribution or rather occurrence of precipitation-free periods. Simulated precipitation pattern vary geographically [12][13][14][15][16][17][18][19] and annually [20]. In addition, predicted changes in precipitation differ between different climate models [21].…”

Section: Introductionmentioning

confidence: 99%

Model and Growth Stage Based Variability of the Irrigation Demand of Onion Crops with Predicted Climate Change

Schmidt

Zinkernagel

2017

Water

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Predicted climate change will affect agricultural water resources. Particularly vegetable crops will be concerned due to high water demand and high vulnerability to water scarcity. Present vegetable production already requires irrigation water. To assess future irrigation demand, the impact of climate change needs to be revealed region-and crop-specifically. For robust predictions, a wide range of scenarios has to be simulated using different climate models. The aim of this study is to identify the climate change impact on water availability, precipitation-free periods and irrigation demand of onion crops cultivated in a German model region. Focus is on crop-specific climatic water balance, considering soil characteristics and temperature-driven plant growth. Simulated climate parameters vary between four climate models. However, in all scenarios climate parameters indicate an increasing water demand until 2100. While amount of irrigation water will not increase tremendously, occurrence and duration of dry periods will require efficient irrigation infrastructure and management.

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Extreme precipitation in Europe: statistical threshold selection based on climatological criteria

Cited by 66 publications

References 26 publications

An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean

An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean

Climatic Study of the Marine Surface Wind Field over the Greek Seas with the Use of a High Resolution RCM Focusing on Extreme Winds

Model and Growth Stage Based Variability of the Irrigation Demand of Onion Crops with Predicted Climate Change

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