Papers by Ioannis Sideris
A multi‐year assessment of sub‐hourly gridded precipitation for Switzerland based on a blended radar—Rain‐gauge dataset
International Journal of Climatology
Flash floods (FFs) evolve rapidly during and after heavy precipitation events and represent a ris... more Flash floods (FFs) evolve rapidly during and after heavy precipitation events and represent a risk for society. To predict the timing and magnitude of a peak runoff, it is common to couple meteorological and hydrological models in a forecasting chain. However, hydrological models rely on strong simplifying assumptions and hence need to be calibrated. This makes their application difficult in catchments where no direct observation of runoff is available.
Meteorological Applications
A fully automated quasi-real-time method is presented to disaggregate hourly to sub-hourly precip... more A fully automated quasi-real-time method is presented to disaggregate hourly to sub-hourly precipitation information operationally in a blended radar-rain gauge product. The method proposes a fully automated solution to disaggregate precipitation in regions characterized by measurement errors or partial absence of auxiliary information on the temporal precipitation evolution. The solution relies on a combination of low-pass filtered radar information and stochastically generated noise fields. A comprehensive validation of the new method is provided demonstrating higher skill compared to a uniform disaggregation in time. The method is now an integral part of CombiPrecip, the official operational code of MeteoSwiss for radar-rain gauge merging.
Using a 10-year radar archive for nowcasting precipitation growth and decay - a probabilistic machine learning approach
Weather and Forecasting
Machine learning algorithms are trained on a 10-yr archive of composite weather radar images in t... more Machine learning algorithms are trained on a 10-yr archive of composite weather radar images in the Swiss Alps to nowcast precipitation growth and decay in the next few hours in moving coordinates (Lagrangian frame). The hypothesis of this study is that growth and decay is more predictable in mountainous regions, which represent a potential source of practical predictability by machine learning methods. In this paper, artificial neural networks (ANN) are employed to learn the complex nonlinear dependence relating the growth and decay to the input predictors, which are geographical location, mesoscale motion vectors, freezing level height, and time of the day. The average long-term growth and decay patterns are effectively reproduced by the ANN, which allows exploring their climatology for any combination of predictors. Due to the low intrinsic predictability of growth and decay, its prediction in real time is more challenging, but is substantially improved when adding persistence in...
Natural Hazards and Earth System Sciences
more, special emphasis was placed on the predictive power of the new forecasting chains in nested... more more, special emphasis was placed on the predictive power of the new forecasting chains in nested subcatchments when compared with a prediction chain including an original version of the runoff generation module of PREVAH calibrated for one event.
A 10-year radar-based analysis of orographic precipitation growth and decay patterns over the Swiss Alpine region
Quarterly Journal of the Royal Meteorological Society
Hydrology and Earth System Sciences Discussions, 2017
In this paper we present a non-stationary stochastic generator for radar rainfall fields based on... more In this paper we present a non-stationary stochastic generator for radar rainfall fields based on the Short-Space Fourier Transform (SSFT). The statistical properties of rainfall fields often exhibit significant spatial heterogeneity due to differences in the involved physical processes and influence of orographic forcing. The traditional approach to simulate stochastic rainfall fields based on the Fourier filtering of white noise, also known as fractional Brownian noise integration, is only able to reproduce the global power spectrum and spatial autocorrelation of the precipitation fields. Conceptually similar to wavelet analysis, the SSFT is a simple and effective extension of the Fourier transform developed for space-frequency localisation, which allows using windows to better capture the local statistical structure of rainfall. The SSFT is used to generate stochastic noise and precipitation fields that replicate the local spatial correlation structure, i.e. anisotropy and correl...
Meteorological Applications, 2016
In hydrometeorological prediction systems, meteorological real-time data and forecast data from n... more In hydrometeorological prediction systems, meteorological real-time data and forecast data from numerical weather prediction models are needed as input for hydrological and hydraulic models. This paper evaluates the application of a validated hydrological-hydraulic model chain by using real-time operationally available precipitation-forcing datasets as a benchmark. The analyses should detect the problems occurring once the prediction system will leave the calibration environment and need to be reconfigured for real-time deployment. The precipitation-forcing benchmarks used for 2013 were rain gauge measurements, quantitative radar estimates, quantitative precipitation estimates (QPE) and a radar-rain gauge merged precipitation product generated by spatio-temporal co-kriging (with external drift). The discharge was simulated in a transnational river basin in southern Switzerland and northern Italy. The best discharge simulation results were obtained when rain gauge data from automatic measurement stations were used as meteorological input for the models, because these were used for the model calibration. The modelled radar QPE greatly underestimated the rainfall volume, and thus the simulated discharge, because the raw radar time series were too short for calibration. Therefore, quantile mapping was applied to post-process the radar QPE. Quantile mapping, as applied in this work with relatively short available radar-only precipitation records, appears to be unsuitable for operational use, but adequate as a post-processing method for past data series. Combining the rain gauge and radar QPE improved simulations significantly compared with the original radar QPE. A lower performance was found in the Italian region because the meteorological stations were not considered there for processing this product.
Acceleration of phase space transport in complex Hamiltonian systems
The validity of the continuum limit in the smooth potential description of N-body systems
This talk provides a progress report on an extended collaboration which has aimed to address two ... more This talk provides a progress report on an extended collaboration which has aimed to address two basic questions, namely: Should one expect to see cuspy, triaxial galaxies in nature? And can one construct realistic cuspy, triaxial equilibrium models that are robust? Three technical results are described: (1) Unperturbed chaotic orbits in cuspy triaxial potentials can be extraordinarily sticky, much more so than orbits in many other three-dimensional potentials. (2) Even very weak perturbations can be important by drastically reducing, albeit not completely eliminating, this stickiness. (3) A simple toy model facilitates a simple understanding of why black holes and cusps can serve as an effective source of chaos. These results suggest that, when constructing models of galaxies using Schwarzschild's method or any analogue thereof, astronomers would be well advised to use orbital building blocks that have been perturbed by `noise' or other weak irregularities, since such building blocks are likely to be more nearly time-independent than orbits evolved in the absence of all perturbations.
Phase mixing of chaotic orbits exponentially distributes the orbits through their accessible phas... more Phase mixing of chaotic orbits exponentially distributes the orbits through their accessible phase space. This phenomenon, commonly called "chaotic mixing", stands in marked contrast to phase mixing of regular orbits which proceeds as a power law in time. It is inherently irreversible; hence, its associated e-folding time scale sets a condition on any process envisioned for emittance compensation. We numerically investigate phase mixing in the presence of space charge, distinguish between the evolution of regular and chaotic orbits, and discuss how phase mixing potentially influences macroscopic properties of high-brightness beams.
Orbits that are chaotic will tend to phase-mix exponentially through their accessible phase space... more Orbits that are chaotic will tend to phase-mix exponentially through their accessible phase space. This phenomenon, commonly called "chaotic mixing", stands in marked contrast to phase mixing of regular orbits. It is inherently irreversible, and thus its associated e-folding time scale sets a condition on any process envisioned for emittance compensation. Accordingly, two questions arise. First, under what conditions does chaotic mixing manifest itself in beams? Second, when it is active, over what time scale does it operate? The work described here is part of an ongoing effort to answer these questions.
Heavy precipitation, hail, and wind gusts are the fundamental meteorological hazards associated w... more Heavy precipitation, hail, and wind gusts are the fundamental meteorological hazards associated with strong convection and thunderstorms. The thread is particularly severe in mountainous areas, e.g. it is estimated that on average between 50% and 80% of all weather-related damage in Switzerland is caused by strong thunderstorms (Hilker et al., 2010). Intense atmospheric convection is governed by processes that range from the synoptic to the microphysical scale and are considered to be one of the most challenging and difficult weather phenomena to predict. Even though numerical weather prediction models have some skills to predict convection, in general the exact location of the convective initialization and its propagation cannot be forecasted by these models with sufficient precision. Hence, there is a strong interest to improve the short-term forecast by using statistical, object oriented and/or heuristic nowcasting methods. MeteoSwiss has developed several operational nowcasting ...
Physical review. E, Statistical, nonlinear, and soft matter physics, 2002
This paper uses the assumptions of ergodicity and a microcanonical distribution to compute estima... more This paper uses the assumptions of ergodicity and a microcanonical distribution to compute estimates of the largest Lyapunov exponents in lower-dimensional Hamiltonian systems. That the resulting estimates are in reasonable agreement with the actual values computed numerically corroborates the intuition that chaos in such systems can be understood as arising generically from a parametric instability and that this instability may be modeled by a stochastic-oscillator equation [cf. Casetti, Clementi, and Pettini, Phys. Rev. E 54, 5969 (1996)], linearized perturbations of a chaotic orbit satisfying a harmonic-oscillator equation with a randomly varying frequency.
Physical review. E, Statistical, nonlinear, and soft matter physics, 2001
This paper summarizes a numerical investigation of the statistical properties of orbits evolved i... more This paper summarizes a numerical investigation of the statistical properties of orbits evolved in "frozen," time-independent N-body realizations of smooth, time-independent density distributions corresponding to integrable potentials, allowing for 10(2.5) < or = N < or = 10(5.5). Two principal conclusions were reached: (1) In agreement with recent work by Valluri and Merritt, one finds that, in the limit of a nearly "unsoftened" two-body kernel, i.e., V(r) approximately equals (r(2) + epsilon(2))(-1/2) for epsilon --> 0, the value of the largest Lyapunov exponent chi does not decrease systematically with increasing N, so that, viewed in terms of the sensitivity of individual orbits to small changes in initial conditions, there is no sense in which chaos "turns off" for large N. However, it is clear that, for any finite epsilon, chi will tend to zero for sufficiently large N. (2) Even though chi does not decrease for an unsoftened kernel, there...
Chaos Analysis Using the Patterns Method
Astrophysics and Space Science Proceedings, 2008
The Astrophysical Journal, 2003
Integrations in fixed N-body realisations of smooth density distributions corresponding to a chao... more Integrations in fixed N-body realisations of smooth density distributions corresponding to a chaotic galactic potential can be used to derive reliable estimates of the largest (finite time) Lyapunov exponent χ S associated with an orbit in the smooth potential generated from the same initial condition, even though the N -body orbit is typically characterised by an N -body exponent χ N ≫ χ S . This can be accomplished either by comparing initially nearby orbits in a single N -body system or by tracking orbits with the same initial condition evolved in two different N -body realisations of the same smooth density.
The Astrophysical Journal, 2004
This paper describes how parametric resonances associated with a galactic potential subjected to ... more This paper describes how parametric resonances associated with a galactic potential subjected to relatively low amplitude, strictly periodic time-dependent perturbations can be impacted by pseudo-random variations in the pulsation frequency, modeled as coloured noise. One aim thereby is to allow for the effects of a changing oscillation frequency as the density distribution associated with a galaxy evolves during violent relaxation. Another is to mimic the possible effects of internal substructures, satellite galaxies, and or a high density environment. The principal conclusion is that allowing for a variable frequency does not vitiate the effects of parametric resonance; and that, in at least some cases, such variations can increase the overall importance of parametric resonance associated with systematic pulsations.
The Astrophysical Journal, 2003
This paper focuses on the dynamical implications of close supermassive black hole binaries both a... more This paper focuses on the dynamical implications of close supermassive black hole binaries both as an example of resonant phase mixing and as a potential explanation of inversions and other anomalous features observed in the luminosity profiles of some elliptical galaxies. The presence of a binary comprised of black holes executing nearly periodic orbits leads to the possibility of a broad resonant coupling between the black holes and various stars in the galaxy. This can result in efficient chaotic phase mixing and, in many cases, systematic increases in the energies of stars and their consequent transport toward larger radii. Allowing for a supermassive black hole binary with plausible parameter values near the center of a spherical, or nearly spherical, galaxy characterized initially by a Nuker density profile enables one to reproduce in considerable detail the central surface brightness distributions of such galaxies as NGC 3706.
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Papers by Ioannis Sideris