January United States blizzard - Wikipedia
The Great New York City Blizzard of Forecast snowfall map for Winter Storm Juno as it appeared on aviabilets.info at p.m. EST on Sunday, Jan. track could result in a significant change in the outcome for the Big Apple. New York City did not meet blizzard criteria for winds and visibility. The odds of the storms bringing such extreme wet winter weather were Extreme weatherMet Office: Climate change made UK's wet winter in /4 . the result fits in with what scientists expect from a warming climate. Published online December doi: Methods: Postings submitted to Twitter for three winter storm periods were collected from selected organizations, Results: Results indicate emergency management entities were active in .. and embedded URLs – to meet the multiple needs and expectations of public users.
Blue indicates snow, green indicates rain, and purple indicates mixed precipitation. Darker shades denote heavier precipitation.
A snow emergency was declared for Washington, D. Trucks deployed brine across major roads in and around Philadelphiathough residents were advised to avoid travel unless necessary.
Do not bring your vehicle out tomorrow". Shelters were also opened for the homeless. The storm was expected to be less severe, with rain rather than snow; however, the possibility of strong winds and localized flooding was noted. Snow blankets the region, highlighting local topographic and hydrologic features. Half of the affected people were in the Northeast which includes the Northeast megalopolis ; the storm's RSI reached The primary factor driving its high classification was the affected population.
The storm's RSI of Numerous trees and power lines were downed, multiple structures were damaged, and a few were destroyed by the tornadoes. The most significant damage occurred overnight across the Florida Panhandle and neighboring Alabama. Numerous roads were shut down accordingly. An accident along Interstate 77 near Troutman resulted in the death of a 4-year-old boy.
Many roads closed because of debris, including portions of Interstate 40 in Johnston County. The National Guard was called in to assist clearing the stranded vehicles.
January 2016 United States blizzard
For example, Smith 1 demonstrated how, in the wake of the Haiti earthquake, Twitter users facilitated response activities through online information dissemination and relationship-building. Agencies and organizations, however, encounter risk of rejection by interested users, particularly potential donors, by affiliating or connecting in a deliberate way with other entities.
A not-for-profit organization relying on a reputation for neutrality, for instance, may not wish to be viewed as propagating information from government sources. On the other hand, an organization might gain respect or a wider audience based on building online relationships through following and retweeting other users.
Retweeting involves the rebroadcast of a message composed by another while simultaneously mentioning a particular user by their user-name or handle. In their analysis of Twitter usage during the Deepwater Horizon oil spill, Sutton et al. Not-for-profit organizations seemed to employ language to reflect positive emotions to encourage donation and additional relief efforts whereas the media appeared to reflect negative emotions to increase notice.
When connected to wireless or available data networks, Twitter users receive real-time streaming updates, but are limited to posts no longer than characters.
Snow Tweets: Emergency Information Dissemination in a US County During Winter Storms
Several features of Twitter authorship, however, are suggested to enhance posts. Hashtags allow users to easily search and follow a particular topic.
Consistent use of hashtags would allow users to quickly access information about the storm, response, and recovery without having to search through content of multiple accounts. Hashtag usage has, in previous research, been significantly associated with variation in retweeting behavior by other users 1314 Embedding links to external websites URLs also has been demonstrated to impact information flow and tweet survival, particularly when combined with a hashtag Here, we investigate certain Twitter usage patterns during the immediate hours preceding, during, and following warning periods for three large snowstorms in a purposeful sampling of disaster response organizations, law enforcement units, and private citizens that service one target county.
In doing so, we were interested in two specific research questions: Methods Sampled Emergency Context To address our research questions, Twitter usage periods covering three winter weather notices including winter weather advisories, watches, and warnings in March, were tracked in one county in southern New Jersey see Table 1.
Total snowfall for each storm period is noted in Table 1. We constrained our study by chronological distance all three data collection periods are within a relatively short time spangeographic variation in response agencies and social media users one countyand emergency context extreme winter weather.