scholarly journals Stochastic generation of multi-site daily precipitation focusing on extreme events

2018 ◽  
Vol 22 (1) ◽  
pp. 655-672 ◽  
Author(s):  
Guillaume Evin ◽  
Anne-Catherine Favre ◽  
Benoit Hingray
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
Tail Dependence ◽  
Extended Version ◽  
Temporal Dependence ◽  
Heavy Tailed Distributions ◽  
Temporal And Spatial ◽  
Heavy Tailed ◽  
High Precipitation

Abstract. Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on the reproduction of low to high precipitation amounts at the stations concerned. This paper proposes significant extensions to the multi-site daily precipitation model introduced by Wilks, with the aim of reproducing the statistical features of extremely rare events (in terms of frequency and magnitude) at different temporal and spatial scales. In particular, the first extended version integrates heavy-tailed distributions, spatial tail dependence, and temporal dependence in order to obtain a robust and appropriate representation of the most extreme precipitation fields. A second version enhances the first version using a disaggregation method. The performance of these models is compared at different temporal and spatial scales on a large region covering approximately half of Switzerland. While daily extremes are adequately reproduced at the stations by all models, including the benchmark Wilks version, extreme precipitation amounts at larger temporal scales (e.g., 3-day amounts) are clearly underestimated when temporal dependence is ignored.

scholarly journals Stochastic generation of multi-site daily precipitation for the assessment of extreme floods in Switzerland

2017 ◽  
Author(s):  
Guillaume Evin ◽  
Anne-Catherine Favre ◽  
Benoit Hingray
Keyword(s):  
Statistical Methods ◽  
Stochastic Models ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
Statistical Features ◽  
Temporal And Spatial ◽  
High Precipitation Events ◽  
High Precipitation ◽  
Precipitation Events

Abstract. Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on the reproduction of low to high precipitation events. In this paper, a multi-site daily precipitation model is proposed and aims at reproducing the statistical features of extremely rare events at different temporal and spatial scales. Recent advances and various statistical methods (regionalization, disaggregation) are considered in order to obtain a robust and appropriate representation of the most extreme precipitation fields. Performances are shown at different temporal and spatial scales on a large region located in Switzerland.

Robust feature screening for multi-response trans-elliptical regression model with ultrahigh-dimensional covariates

2019 ◽  
Vol 09 (04) ◽  
pp. 2150001
Author(s):  
Yong He ◽  
Hao Sun ◽  
Jiadong Ji ◽  
Xinsheng Zhang
Keyword(s):  
Regression Model ◽  
Canonical Correlation ◽  
Main Idea ◽  
Tail Dependence ◽  
Real Data ◽  
Feature Screening ◽  
Canonical Correlations ◽  
Heavy Tailed Distributions ◽  
Sure Screening ◽  
Heavy Tailed

In this paper, we innovatively propose an extremely flexible semi-parametric regression model called Multi-response Trans-Elliptical Regression (MTER) Model, which can capture the heavy-tail characteristic and tail dependence of both responses and covariates. We investigate the feature screening procedure for the MTER model, in which Kendall’ tau-based canonical correlation estimators are proposed to characterize the correlation between each transformed predictor and the multivariate transformed responses. The main idea is to substitute the classical canonical correlation ranking index in [X. B. Kong, Z. Liu, Y. Yao and W. Zhou, Sure screening by ranking the canonical correlations, TEST 26 (2017) 1–25] by a carefully constructed non-parametric version. The sure screening property and ranking consistency property are established for the proposed procedure. Simulation results show that the proposed method is much more powerful to distinguish the informative features from the unimportant ones than some state-of-the-art competitors, especially for heavy-tailed distributions and high-dimensional response. At last, a real data example is given to illustrate the effectiveness of the proposed procedure.

scholarly journals Assessment of temporal change in the tails of probability distribution of daily precipitation over India due to climatic shift in 1970s

2021 ◽  
Author(s):  
Neha Gupta ◽  
Sagar Rohidas Chavan
Keyword(s):  
Extreme Precipitation ◽  
Temporal Change ◽  
Daily Precipitation ◽  
Tail Behavior ◽  
Water Control ◽  
Error Norm ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Time Periods ◽  
Heavy Tailed

Abstract Daily precipitation extremes are crucial in the hydrological design of major water control structures and are expected to show a changing tendency over time due to climate change. The magnitude and frequency of extreme precipitation can be assessed by studying the upper tail behavior of probability distributions of daily precipitation. Depending on the tail behavior, the distributions can be classified into two categories: heavy-tailed and light-tailed distributions. Heavier tails indicate more frequent occurrences of extreme precipitation events. In this paper, we have analyzed the temporal change in the tail behavior of daily precipitation over India from pre- to post-1970 time periods as per the global climatic shift. A modified Probability Ratio Mean Square Error norm is used to identify the best-fit distribution to the tails of daily precipitation among four theoretical distributions (e.g., Pareto-type II, Lognormal, Weibull, and Gamma distributions). The results indicate that the Lognormal distribution, which is a heavy-tailed distribution, fits the tails of daily precipitation for the majority of the grids. It is inferred from the study that there is an increase in the heaviness of tails of daily precipitation data over India from pre- to post-1970 time periods.

scholarly journals Temporal and spatial scaling impacts on extreme precipitation

2015 ◽  
Vol 15 (10) ◽  
pp. 5957-5971 ◽  
Author(s):  
B. Eggert ◽  
P. Berg ◽  
J. O. Haerter ◽  
D. Jacob ◽  
C. Moseley
Keyword(s):  
Extreme Precipitation ◽  
Climate Model ◽  
Spatial Scales ◽  
Reduction Factor ◽  
Spatial And Temporal Scales ◽  
Stratiform Precipitation ◽  
Temporal And Spatial ◽  
Clear Shift ◽  
Precipitation Events ◽  
Reduction Factors

Abstract. Convective and stratiform precipitation events have fundamentally different physical causes. Using a radar composite over Germany, this study separates these precipitation types and compares extremes at different spatial and temporal scales, ranging from 1 to 50 km and 5 min to 6 h, respectively. Four main objectives are addressed. First, we investigate extreme precipitation intensities for convective and stratiform precipitation events at different spatial and temporal resolutions to identify type-dependent space and time reduction factors and to analyze regional and seasonal differences over Germany. We find strong differences between the types, with up to 30% higher reduction factors for convective compared to stratiform extremes, exceeding all other observed seasonal and regional differences within one type. Second, we investigate how the differences in reduction factors affect the contribution of each type to extreme events as a whole, again dependent on the scale and the threshold chosen. A clear shift occurs towards more convective extremes at higher resolution or higher percentiles. For horizontal resolutions of current climate model simulations, i.e., ~10 km, the temporal resolution of the data as well as the chosen threshold have profound influence on which type of extreme will be statistically dominant. Third, we compare the ratio of area to duration reduction factor for convective and stratiform events and find that convective events have lower effective advection velocities than stratiform events and are therefore more strongly affected by spatial than by temporal aggregation. Finally, we discuss the entire precipitation distribution regarding data aggregation and identify matching pairs of temporal and spatial resolutions where similar distributions are observed. The information is useful for planning observational networks or storing model data at different temporal and spatial scales.

scholarly journals Characterizing the Spatial Scales of Extreme Daily Precipitation in the United States

2018 ◽  
Vol 31 (19) ◽  
pp. 8023-8037 ◽  
Author(s):  
Danielle Touma ◽  
Anna M. Michalak ◽  
Daniel L. Swain ◽  
Noah S. Diffenbaugh
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
The United States ◽  
Spatial Extent ◽  
Precipitation Event ◽  
Length Scales ◽  
Precipitation Records ◽  
Northwest Region

The spatial extent of an extreme precipitation event can be important for a basin’s hydrologic response and subsequent flood risk, and may yield insights into underlying atmospheric processes. Using a relaxed moving-neighborhood approach, we develop indicator semivariograms based on precipitation records from the Global Historical Climatology Network–Daily (GHCN-D) station network to directly quantify the climatological length scales of extreme daily precipitation over the United States during 1965–2014. We find that the length scales of extreme (90th percentile) daily precipitation events vary both regionally and seasonally. Over the eastern half of the United States, daily extreme precipitation length scales reach 400 km during the winter months, but are approximately half as large during the summer months. The Northwest region, on the other hand, exhibits little seasonal variation, with extreme precipitation length scales of approximately 150 km throughout the year. By leveraging in situ station measurements, our study avoids some of the uncertainties associated with satellite or interpolated precipitation data, and provides the longest climatological assessment of length scales of extreme daily precipitation over the United States to date. Although the length scales that we calculate can be sensitive to station density, neighborhood size, and neighborhood relaxation, we find that the interregional and interseasonal differences in length scales are relatively robust. Our method could be extended to quantify changes in the spatial extent of extreme daily precipitation in the recent past, and to investigate the underlying causes of any changes that are detected.

Larval Feeding: Mechanisms, Rates, and Performance in Nature

2018 ◽  
Keyword(s):  
Marine Invertebrates ◽  
Spatial Scales ◽  
Size Spectrum ◽  
Larval Feeding ◽  
Natural Habitats ◽  
Feeding Mechanism ◽  
Temporal And Spatial ◽  
And Performance ◽  
Bioenergetics Models ◽  
Many Particles

Larvae of many marine invertebrates must capture and ingest particulate food in order to develop to metamorphosis. These larvae use only a few physical processes to capture particles, but implement these processes using diverse morphologies and behaviors. Detailed understanding of larval feeding mechanism permits investigators to make predictions about feeding performance, including the size spectrum of particles larvae can capture and the rates at which they can capture them. In nature, larvae are immersed in complex mixtures of edible particles of varying size, density, flavor, and nutritional quality, as well as many particles that are too large to ingest. Concentrations of all of these components vary on fine temporal and spatial scales. Mechanistic models linking larval feeding mechanism to performance can be combined with data on food availability in nature and integrated into broader bioenergetics models to yield increased understanding of the biology of larvae in complex natural habitats.

Probability and Random Processes

2018 ◽  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl
Keyword(s):  
Random Processes ◽  
Distribution Functions ◽  
Basic Logic ◽  
Heavy Tailed Distributions ◽  
Random Components ◽  
Classical Distribution ◽  
Heavy Tailed ◽  
Basic Facts ◽  
Stochastic Events ◽  
Stochastic Event

Phenomena, systems, and processes are rarely purely deterministic, but contain stochastic,probabilistic, or random components. For that reason, a probabilistic descriptionof most phenomena is necessary. Probability theory provides us with the tools for thistask. Here, we provide a crash course on the most important notions of probabilityand random processes, such as odds, probability, expectation, variance, and so on. Wedescribe the most elementary stochastic event—the trial—and develop the notion of urnmodels. We discuss basic facts about random variables and the elementary operationsthat can be performed on them. We learn how to compose simple stochastic processesfrom elementary stochastic events, and discuss random processes as temporal sequencesof trials, such as Bernoulli and Markov processes. We touch upon the basic logic ofBayesian reasoning. We discuss a number of classical distribution functions, includingpower laws and other fat- or heavy-tailed distributions.

Humans and the Environment

2013 ◽  
Keyword(s):  
Spatial Scales ◽  
Empirical Studies ◽  
Human Action ◽  
Cultural Practice ◽  
Environmental Archaeology ◽  
Archaeological Data ◽  
Temporal And Spatial ◽  
Global And Local ◽  
The Relationship ◽  
The Way

The environment has always been a central concept for archaeologists and, although it has been conceived in many ways, its role in archaeological explanation has fluctuated from a mere backdrop to human action, to a primary factor in the understanding of society and social change. Archaeology also has a unique position as its base of interest places it temporally between geological and ethnographic timescales, spatially between global and local dimensions, and epistemologically between empirical studies of environmental change and more heuristic studies of cultural practice. Drawing on data from across the globe at a variety of temporal and spatial scales, this volume resituates the way in which archaeologists use and apply the concept of the environment. Each chapter critically explores the potential for archaeological data and practice to contribute to modern environmental issues, including problems of climate change and environmental degradation. Overall the volume covers four basic themes: archaeological approaches to the way in which both scientists and locals conceive of the relationship between humans and their environment, applied environmental archaeology, the archaeology of disaster, and new interdisciplinary directions.The volume will be of interest to students and established archaeologists, as well as practitioners from a range of applied disciplines.

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