scholarly journals Influence of the Characteristics of Weather Information in a Thunderstorm-Related Power Outage Prediction System

Forecasting ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 541-560
Author(s):  
Peter L. Watson ◽  
Marika Koukoula ◽  
Emmanouil Anagnostou
Keyword(s):  
Weather Prediction ◽  
The United States ◽  
Power Outage ◽  
Convective Storms ◽  
Emergency Responders ◽  
Weather Information ◽  
Prediction Systems ◽  
Power Utilities ◽  
Impact Models

Thunderstorms are one of the most damaging weather phenomena in the United States, but they are also one of the least predictable. This unpredictable nature can make it especially challenging for emergency responders, infrastructure managers, and power utilities to be able to prepare and react to these types of events when they occur. Predictive analytical methods could be used to help power utilities adapt to these types of storms, but there are uncertainties inherent in the predictability of convective storms that pose a challenge to the accurate prediction of storm-related outages. Describing the strength and localized effects of thunderstorms remains a major technical challenge for meteorologists and weather modelers, and any predictive system for storm impacts will be limited by the quality of the data used to create it. We investigate how the quality of thunderstorm simulations affects power outage models by conducting a comparative analysis, using two different numerical weather prediction systems with different levels of data assimilation. We find that limitations in the weather simulations propagate into the outage model in specific and quantifiable ways, which has implications on how convective storms should be represented to these types of data-driven impact models in the future.

Methods for Improvement of Drift Forecast Models

2010 ◽  
Author(s):  
Christophe Maisondieu ◽  
O̸yvind Breivik ◽  
Jens-Christian Roth ◽  
Arthur A. Allen ◽  
Bertrand Forest ◽  
...  
Keyword(s):  
Field Experiments ◽  
Prediction Models ◽  
Weather Prediction ◽  
The United States ◽  
Search And Rescue ◽  
Environmental Data ◽  
Fishing Vessels ◽  
Forecast Models ◽  
Definition Of

Over the past decades, various operational drift forecast models were developed for trajectory prediction of objects lost at sea for search and rescue operations. Most of these models are now based on a stochastic, Monte Carlo definition of the object’s initial position and its time-evolving search area through computation of an ensemble of equally probable trajectories (Breivik [1]). Uncertainties in environmental forcing, mainly surface currents and wind, as well as the uncertainties inherent in the simplified computation of leeway speed and direction relative to the wind are also accounted for through this ensemble-based approach. Accuracy of the drift forecast obviously depends to a large extent on the quality of the environmental forecast data provided by numerical weather prediction models and ocean models, but it also depends on the level of uncertainty associated with the estimation of the drift properties (leeway) of the objects themselves. The present work mostly focuses on this second aspect of the problem. Drift properties of objects can be described by means of their downwind and crosswind leeway coefficients, according to the definition of leeway as stated by Allen [2, 3]. Assessment of the leeway coefficients is based on a direct method, which requires measurements acquired during field tests. Such field experiments basically entail deploying one or more objects at sea and simultaneously recording the environmental parameters (namely wind speed and motion of the object relative to the ambient water masses, i.e., its leeway) as well as the object’s position while adrift for periods ranging from several hours to several days. Using this method, a large database providing leeway coefficients for more than sixty object classes ranging from medical waste to a person-in-water to small fishing vessels was compiled over the years by the United States Coast Guard (Allen [2]). More recently additional trials were conducted, which allowed evaluation of new objects, including 20-ft shipping containers. We present in this paper the methods and analysis procedures for field determination of leeway coefficients of typical search-and-rescue objects. As an example we present the case study of a 20-ft container and discuss results obtained from a drift forecast model assessing sensitivity of such a model to the quality of environmental data as well as uncertainty levels of some reference parameters.

Precarious Work and Young Workers in the United States

2018 ◽  
Author(s):  
Arne L. Kalleberg
Keyword(s):  
Labor Market ◽  
The United States ◽  
Young Workers ◽  
Severe Problem ◽  
Precarious Work ◽  
The Great Recession ◽  
The Us ◽  
Training Opportunities ◽  
And Training

This chapter discusses how the growth of precarious work and the polarization of the US labor market have produced major problems for the employment experiences of young workers. A prominent indicator of young workers’ difficulties in the labor market has been the sharp increase in their unemployment rates since the Great Recession. Another, equally if not more severe, problem faced by young workers today is the relatively low quality of the jobs that they were able to get. Other problems include the exclusion of young workers from the labor market and from education and training opportunities; the inability to find jobs that utilize their education, training, and skills; and the inability to obtain jobs that provide them with an opportunity to get a foothold in a career that would lead to progressively better jobs and thus be able to construct career narratives.

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