Analysis and modelling of wind speed in New York

In this paper we propose an ARMA time-series model for the wind speed at a single spatial location, and estimate it on in-sample data recorded in three different wind farm regions in New York state. The data have a three-hour granularity, but based on applications to financial wind derivatives contracts, we also consider daily average wind speeds. We demonstrate that there are large discrepancies in the behaviour of daily average and three-hourly wind speed records. The validation procedure based on out-of-sample observations reflects that the proposed model is reliable and can be used for various practical applications, like, for instance, weather prediction, pricing of financial wind contracts, wind generated power, etc. Furthermore, we discuss some striking resemblances with temperature dynamics.     

AACR2 and the New York State Library's CONSER Project

Abstract

Daisy P. Waters reviews Using Microsoft Access XP, Hazel Cameron reviews Business Statistics on the Web, Elizabeth Parang reviews JSTOR: A History, and Sheila Corman reviews MARC21 for Everyone.     

Trend and Return Level of Extreme Snow Events in New York City

Abstract

A major winter storm brought up to 42 inches of snow in parts of the Mid-Atlantic and Northeast states for January 22–24, 2016. The blizzard of January 2016 impacted about 102.8 million people, claiming at least 55 lives and $500 million to $3 billion in economic losses. This article studies two important aspects of extreme snowfall events: 1. trends in annual maxima and threshold exceedances and 2. return levels for extreme snowfall. Applying extreme value methods to the extreme snow data in the New York City area, we quantify linear trends in extreme snowfall and assess how severe the 2016 blizzard is in terms of return levels. To find a more realistic standard error for the extreme value methods, we extend Smith’s method to adapt to both spatial and temporal correlations in the snow data. Our results show increasing, but insignificant trends in the annual maximum snowfall series. However, we find that the 87.5th percentile snowfall has significantly increased by 0.564 inches per decade, suggesting that, while the maximum snowfall is not significantly increasing, there have been increases in the snowfall among the larger storms. We also find that the 2016 blizzard is indeed an extreme snow event equivalent to about a 40-year return level in the New York City area. The extreme value methods used in this study are thoroughly illustrated for general readers. Data and modularized programming codes are to be available online to aid practitioners in using extreme value methods in applications.     

Effects of neighbourhood demographic shifts on findings of environmental injustice: a New York City case-study

Summary We study the question of how changes in neighbourhood demographics affect findings of environmental equity. Many cross-sectional studies of association between neighbourhood racial and ethnic composition and the location of environmentally undesirable sites have been conducted. However, no evaluations have been conducted that examine how neighbourhood demographics change over time, and how those changes are related to the observed cross-sectional results. If the question is whether an observed association is the result of discrimination, it is crucial that the historical changes in neighbourhood structure are well understood. We develop some methods based on standard statistical techniques and illustrate their application by using the metropolitan New York City region as a case-study.