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Extreme Value Statistics [PDF]
, 2019 AbstractWhen studying peaks in electricity demand, we may be interested in understanding the risk of a certain large level for demand being exceeded. For example, there is potential interest in finding the probability that the electricity demand of a business or household exceeds the contractual limit.
Maria Jacob +2 more
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Weather and Climate Extremes, 2015 Gaining a better understanding of rare weather events is a major research challenge and of crucial relevance for societal preparedness in the face of a changing climate.
Sebastian Sippel +6 more
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Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hindcast ensemble for the Baltic Sea [PDF]
Ocean Science, 2023 Extreme sea level events, such as storm surges, pose a threat to coastlines around the globe. Many tide gauges have been measuring the sea level and recording these extreme events for decades, some for over a century.
M. Lorenz, U. Gräwe
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Extreme Value Laws for Superstatistics
Entropy, 2014 We study the extreme value distribution of stochastic processes modeled by superstatistics. Classical extreme value theory asserts that (under mild asymptotic independence assumptions) only three possible limit distributions are possible, namely: Gumbel,
Pau Rabassa, Christian Beck
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Effects of stochastic parametrization on extreme value statistics [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019 Extreme geophysical events are of crucial relevance to our daily life: they threaten human lives and cause property damage. To assess the risk and reduce losses, we need to model and probabilistically predict these events. Parametrizations are computational tools used in the Earth system models, which are aimed at reproducing the impact of unresolved ...
Guannan Hu +2 more
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Generalisation of Levine's prediction for the distribution of freezing temperatures of droplets: a general singular model for ice nucleation [PDF]
Atmospheric Chemistry and Physics, 2013 Models without an explicit time dependence, called singular models, are widely used for fitting the distribution of temperatures at which water droplets freeze. In 1950 Levine developed the original singular model.
R. P. Sear
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Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory [PDF]
Nonlinear Processes in Geophysics, 2020 Many applications require wind gust estimates at very different atmospheric height levels. For example, the renewable energy sector is interested in wind and gust predictions at the hub height of a wind power plant.
J. Steinheuer +2 more
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A probabilistic analysis of wind gusts using extreme value statistics
Meteorologische Zeitschrift, 2009 The spatial variability of wind gusts is probably as large as that of precipitation, but the observational weather station network is much less dense. The lack of an area-wide observational analysis hampers the forecast verification of wind gust warnings.
Petra Friederichs +4 more
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Extreme Values of Permutation Statistics
The Electronic Journal of CombinatoricsWe investigate extreme values of Mahonian and Eulerian distributions arising from counting inversions and descents of random elements of finite Coxeter groups. To this end, we construct a triangular array of either distribution from a sequence of Coxeter groups with increasing ranks. To avoid degeneracy of extreme values, the number of i.i.d.
Philip Dörr, Thomas Kahle
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The maximum air temperature distribution in Lithuania
Lietuvos Matematikos Rinkinys, 2013 In this article authors found out function estimate of maximum air temperature distribution in Lithuania.
Arvydas Jokimaitis, Darius Petronaitis
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