scholarly journals Bayesian Hierarchical Models for the Frequency of Winter Heavy Precipitation Events Over the Central United States: The Role of Atmospheric Rivers

2020 ◽  
Vol 56 (11) ◽  
Author(s):  
Munir Ahmad Nayak ◽  
Mary Kathryn Cowles ◽  
Gabriele Villarini ◽  
Burhan Ul Wafa
Keyword(s):  
United States ◽  
Hierarchical Models ◽  
Heavy Precipitation ◽  
Bayesian Hierarchical Models ◽  
Atmospheric Rivers ◽  
Bayesian Hierarchical ◽  
Central United States ◽  
Precipitation Events

scholarly journals Changes in Intense Precipitation over the Central United States

2012 ◽  
Vol 13 (1) ◽  
pp. 47-66 ◽  
Author(s):  
Pavel Ya. Groisman ◽  
Richard W. Knight ◽  
Thomas R. Karl
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
The Past ◽  
Extreme Precipitation Events ◽  
Intense Precipitation ◽  
Central United States ◽  
Extreme Rain ◽  
Rain Events ◽  
Precipitation Events

Abstract In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested.

scholarly journals The role of passing network indicators in modeling football outcomes: an application using Bayesian hierarchical models

2021 ◽  
Author(s):  
Riccardo Ievoli ◽  
Aldo Gardini ◽  
Lucio Palazzo
Keyword(s):  
Hierarchical Models ◽  
Team Sports ◽  
Bayesian Hierarchical Models ◽  
Structural Features ◽  
Bayesian Hierarchical ◽  
Real Dataset ◽  
Main Determinants

AbstractPasses are undoubtedly the more frequent events in football and other team sports. Passing networks and their structural features can be useful to evaluate the style of play in terms of passing behavior, analyzing and quantifying interactions among players. The present paper aims to show how information retrieved from passing networks can have a relevant impact on predicting the match outcome. In particular, we focus on modeling both the scored goals by two competing teams and the goal difference between them. With this purpose, we fit these outcomes using Bayesian hierarchical models, including both in-match and network-based covariates to cover many aspects of the offensive actions on the pitch. Furthermore, we review and compare different approaches to include covariates in modeling football outcomes. The presented methodology is applied to a real dataset containing information on 125 matches of the 2016–2017 UEFA Champions League, involving 32 among the best European teams. From our results, shots on target, corners, and such passing network indicators are the main determinants of the considered football outcomes.

scholarly journals A Regional Modeling Study of Climate Change Impacts on Warm-Season Precipitation in the Central United States*

2011 ◽  
Vol 24 (7) ◽  
pp. 1985-2002 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
David J. Karoly
Keyword(s):  
United States ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Warm Season ◽  
Heavy Precipitation ◽  
Climate System Model ◽  
Average Precipitation ◽  
Central United States ◽  
Precipitation Events

Abstract In this study, the Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to dynamically downscale output from the National Center for Atmospheric Research’s (NCAR’s) Community Climate System Model (CCSM) version 3 and the National Centers for Environmental Prediction (NCEP)–NCAR global reanalysis (NNRP). The latter is used for verification of late-twentieth-century climate simulations from the WRF. This analysis finds that the WRF is able to produce precipitation that is more realistic than that from its driving systems (the CCSM and NNRP). It also diagnoses potential issues with and differences between all of the simulations completed. Specifically, the magnitude of heavy 6-h average precipitation events, the frequency distribution, and the diurnal cycle of precipitation over the central United States are greatly improved. Projections from the WRF for late-twenty-first-century precipitation show decreases in average May–August (MJJA) precipitation, but increases in the intensity of both heavy precipitation events and rain in general when it does fall. A decrease in the number of 6-h periods with rainfall accounts for the overall decrease in average precipitation. The WRF also shows an increase in the frequency of very heavy to extreme 6-h average events, but a decrease in the frequency of all events lighter than those over the central United States. Overall, projections from this study suggest an increase in the frequency of both floods and droughts during the warm season in the central United States.

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

2008 ◽  
Author(s):  
Ralph F. Milliff ◽  
Mark Berliner ◽  
Emanuele D. Lorenzo ◽  
Christopher K. Wikle
Keyword(s):  
Hierarchical Models ◽  
Bayesian Hierarchical Models ◽  
Forecast System ◽  
Bayesian Hierarchical ◽  
The Mediterranean

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

2010 ◽  
Author(s):  
Christopher K. Wikle ◽  
L. M. Berliner ◽  
Emanuele Di Lorenzo ◽  
Ralph F. Milliff
Keyword(s):  
Hierarchical Models ◽  
Bayesian Hierarchical Models ◽  
Forecast System ◽  
Bayesian Hierarchical ◽  
The Mediterranean

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

2010 ◽  
Author(s):  
Ralph F. Milliff ◽  
Christopher K. Wikle ◽  
L. M. Berliner ◽  
Emanuele Di Lorenzo
Keyword(s):  
Hierarchical Models ◽  
Bayesian Hierarchical Models ◽  
Forecast System ◽  
Bayesian Hierarchical ◽  
The Mediterranean
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