Estimating changes in temperature extremes from millennial scale climate simulations using generalized extreme value (GEV) distributions

Changes in extreme weather may produce some of the largest societal impacts of anthropogenic climate change. However, it is intrinsically difficult to estimate changes in extreme events from the short observational record. In this work we use millennial runs from the CCSM3 in equilibrated pre-industrial and possible future conditions to examine both how extremes change in this model and how well these changes can be estimated as a function of run length. We estimate changes to distributions of future temperature extremes (annual minima and annual maxima) in the contiguous United States by fitting generalized extreme value (GEV) distributions. Using 1000-year pre-industrial and future time series, we show that the magnitude of warm extremes largely shifts in accordance with mean shifts in summertime temperatures. In contrast, cold extremes warm more than mean shifts in wintertime temperatures, but changes in GEV location parameters are largely explainable by mean shifts combined with reduced wintertime temperature variability. In addition, changes in the spread and shape of the GEV distributions of cold extremes at inland locations can lead to discernible changes in tail behavior. We then examine uncertainties that result from using shorter model runs. In principle, the GEV distribution provides theoretical justification to predict infrequent events using time series shorter than the recurrence frequency of those events. To investigate how well this approach works in practice, we estimate 20-, 50-, and 100-year extreme events using segments of varying lengths. We find that even using GEV distributions, time series that are of comparable or shorter length than the return period of interest can lead to very poor estimates. These results suggest caution when attempting to use short observational time series or model runs to infer infrequent extremes.Comment: 33 pages, 22 figures, 1 tabl

Rocket observations of the ionosphere during the eclipse of 26 February 1979

Electron density profiles and energetic particle fluxes were determined from two rockets launched, respectively, at the beginning and end of totality during the solar eclipse of 26 February 1979. These, and one other rocket at the same time of day on 24 February 1979, were launched from near Red Lake, Ontario. The electron density profile from 24 February shows the electron density to be normal above 110 km, to rocket apogee. Below 110 km, the electron density is enhanced, by an order of magnitude in the D region, compared with data from Wallops Island at the same solar zenith angle (63 deg). The enhancement is qualitatively explained by the large flux of field aligned energetic particles observed on the same rocket. During totality (on 26 February) the electron density above 110 km to rocket apogee is reduced by a factor of about three. Below 110 km, the electron density is much greater than observed during previous eclipses. The particle flux measured on the 26 February was an order of magnitude less than that on the 24 February but showed greater variability, particularly at the higher energies (100 keV). A feature of the particle flux is that, for the two rockets that were separated horizontally by 38 km while above the absorbing region, the variations are uncorrelated

Spatio-temporal metrics that distinguish play outcomes: A pilot study

In team invasion sports, tactical behaviour can be examined using spatio-temporal data, i.e. the position of the players at a given time. A review of the spatio-temporal metrics used in team invasion sports performance analysis indicated that thousands of variations of metrics being used. Information about the distribution of metrics' individual effects can inform us of the best variable-selection method. The aim of this pilot study was to estimate the distribution of strong marginal effects of spatio-temporal metrics of field hockey plays. With institutional ethical approval, the Womens’ and Mens’ gold medal games from the EuroHockey 2015 field hockey tournament were recorded. Best, acceptable and worst-case outcomes for plays were described by 1,837 spatio-temporal metrics. Each metric's marginal effects were estimated using Cramér's V, Mutual Information and the I-score. Values for Cramér's V of 0.2 and 0.4 to mark the boundaries of small, moderate and large effects. Less than 1% of metrics show large effects with > 87% of all metrics showing small effects as per the Cramér's V thresholds. These large effect metrics where all within the 98th percentile of Mutual Information values and within the 96th percentile of the I-score values, which supports the Cramér's V distribution of marginal effects. Therefore, according to the recommendations of Tibshirani (1996), univariate variable-selection methods will be the most appropriate for selecting important metrics

Job Satisfaction as Related to Safety Performance: A Case for a Manufacturing Firm

Many companies have made significant improvements in safety records, but have eventually reached a plateau. This article examines employee safety performance in regards to their job satisfaction and its implications to managers for improving employees safety performance through job redesign

Job Satisfaction as Related to Safe Performance: A Case for a Manufacturing Firm

Many companies have made significant improvements in safety records, but have eventually reached a plateau. This article examines employee safety performance in regards to their job satisfaction and its implications to managers for improving employees safety performance through job redesign

Gender Differences In Responses To Hypothetical Business Ethical Dilemmas By Business Undergraduates

Business leaders are often failing to display ethical behavior in business decisions. This paper examines the gender differences found in undergraduate business students when faced with ethical decision making dilemmas

Whole Atmosphere Climate Change: Dependence on Solar Activity

We conducted global simulations of temperature change due to anthropogenic trace gas emissions, which extended from the surface, through the thermosphere and ionosphere, to the exobase. These simulations were done under solar maximum conditions, in order to compare the effect of the solar cycle on global change to previous work using solar minimum conditions. The Whole Atmosphere Community Climate Model‐eXtended was employed in this study. As in previous work, lower atmosphere warming, due to increasing anthropogenic gases, is accompanied by upper atmosphere cooling, starting in the lower stratosphere, and becoming dramatic, almost 2 K per decade for the global mean annual mean, in the thermosphere. This thermospheric cooling, and consequent reduction in density, is less than the almost 3 K per decade for solar minimum conditions calculated in previous simulations. This dependence of global change on solar activity conditions is due to solar‐driven increases in radiationally active gases other than carbon dioxide, such as nitric oxide. An ancillary result of these and previous simulations is an estimate of the solar cycle effect on temperatures as a function of altitude. These simulations used modest, five‐member, ensembles, and measured sea surface temperatures rather than a fully coupled ocean model, so any solar cycle effects were not statistically significant in the lower troposphere. Temperature change from solar minimum to maximum increased from near zero at the tropopause to about 1 K at the stratopause, to approximately 500 K in the upper thermosphere, commensurate with the empirical evidence, and previous numerical models

Fast and accurate method for computing non-smooth solutions to constrained control problems

Introducing flexibility in the time-discretisation mesh can improve convergence and computational time when solving differential equations numerically, particularly when the solutions are discontinuous, as commonly found in control problems with constraints. State-of-the-art methods use fixed mesh schemes, which cannot achieve superlinear convergence in the presence of non-smooth solutions. In this paper, we propose using a flexible mesh in an integrated residual method. The locations of the mesh nodes are introduced as decision variables, and constraints are added to set upper and lower bounds on the size of the mesh intervals. We compare our approach to a uniform fixed mesh on a real-world satellite reorientation example. This example demonstrates that the flexible mesh enables the solver to automatically locate the discontinuities in the solution, has superlinear convergence and faster solve time