Storm is an astronaut in the 21st century who makes a journey to the Great Red Spot of Jupiter. The Great Red Spot is an anticyclonic storm which has already been there for at least 300 years. Once arrived, his ship gets dragged into the storm. When Storm manages to escape, it seems he has traveled through time. The civilizations on Earth have collapsed and turned into a barbaric society. This is where the adventures of Storm begin.
Hy, The storm links in dutch don't seem to work...is it possible you could re-up them, and also the ones for english, some of the links above are for storm albums in serbian ?...thanks in advance for your help ;-)
Storm Don Lawrence Pdf Download
Download Zip: https://slocinoutteu.blogspot.com/?file=2vGugF
Together, these factors, their trends, and the lack of proper comprehensive policy attention countering them have created a perfect storm in the teacher labor market, as evident in the spiking shortage of highly qualified teachers, especially in high-poverty schools. The sixth and final report in the series calls for immediate policy steps to address this national crisis.
Downloads for ESIs that were generated using GIS (post-1993) include metadata in PDF format. Other metadata formats, as available, are included as a separate download. Additionally, for more recent atlases, links are provided to metadata in the NOAA metadata repository, InPort. Metadata for the post-2014 atlases is only available in InPort.
Humans often prefer representations that are cognitively easier to store, and these representations are easier to retrieve later to make judgments about events. Exemplification theory draws on evolutionary logic and argues that simple, iconic, concrete, and emotionally arousing depictions of events (exemplars) are favored and thus more likely to be stored and used than are abstract, inconsequential depictions or representations. This study examined exemplified aspects of storm warnings in a Twitter feed. A three-condition study was completed, and variables examined included storm severity, susceptibility, hazard, outrage, and willingness to change or engage in specific behaviors. Results suggest the possibility of a sleeper effect impacting perceptions of severity. Results are discussed in theoretical and practical applications along with the consideration of other theories to be applied to future research.
The naming of such storms may also provide the opportunity for individuals to use heuristic processing to understand the severity and threat of a storm. Consequently, it is possible that a more menacing or iconic name may motivate people differently that a more subdued or unemotional name. Rainear et al. (2017) were one of the first to put forth research investigating if naming storms has any impact on perceptions of the event, and the American Meteorological Society even formed an ad hoc committee on the process at their 2017 annual meeting (American Meteorological Society 2017). With this focus in mind, the current study is an initial examination into the perceptions of threats and the actions of public as a result of a name given to a storm, specifically when viewed on social media. In the following section, the history of storm naming is reviewed, as there has been much recent debate in the field of meteorology on the subject (see Fritz 2015; Palmer 2013). Then, exemplification theory is presented as a means of explaining the potential of named storms to influence perceptions, followed by an explanation of how social media is used for information seeking and communication during weather-related events. The results of an experiment examining this feature are presented, followed by discussion and implications for future research.
In the field of meteorology, storm naming is not a novel concept. The exercise of naming Atlantic tropical cyclones has been in practice for more than 60 years. In the 1950s, the Institute for Meteorology of Free University Berlin began using female names for low pressure systems and male names for high pressure systems, in order to track large-scale weather systems without the necessity of naming storms after awkward longitude and latitude data. The current North Atlantic and eastern Pacific naming lists are managed by the WMO, and the names are assigned by the National Hurricane Center, once a storm reaches the magnitude of a tropical storm. Storms are named in alphabetical order, starting with the letter A (five letters are excluded) until either the season ends, or the 21 names are used in succession and a secondary list is utilized (NOAA 2017).
Exemplification theory (Zillmann 1999, 2002; Zillmann and Brosius 2000) suggests that events portrayed in an emotional and vivid manner will have a stronger influence on receivers of that message than events that are constructed with more general descriptions or base-rate information. Exemplification theory is a theory of media influence that translates well to social media and risk events. The theory revolves around the use and effects of media representations, or exemplars. Exemplars exist on a continuum from how accurately or inaccurately a portrayal represents the larger occurrence; they are portrayals that have a high likelihood to drive judgments of the public. The theory draws on evolutionary principles along with three cognitive mechanisms (quantification, representativeness, and availability heuristics) to explain and predict that exemplars that are concrete, iconic, and emotionally arousing influence issue perceptions more than portrayals that are abstract, symbolic, and emotionally inconsequential exemplars (Zillmann 2002; Spence et al. 2016a). The representations that humans attentionally favor, find cognitively easier to store, and retrieve from memory are more likely to be used to make judgments of the social world than abstract, base-rate information. Base-rate information is simply another way to provide information, or it can be explained as another way to tell a story. Base-rate information often consists of statistics and detailed nonemotional descriptions of events. Often humans consider base-rate information inconsequential and not necessary, and therefore it is discarded and not acted upon. Thus, in providing information about any event (for purpose of this article, a weather event), a media outlet, government agency, emergency manager, or social media feed manager can explain the facts about the storm in a measured, systematic, and unemotional style, or the same weather even can be portrayed with exemplars, such as images of fierce winds and destruction, emotional quotes about the weather event, and graphic descriptions. Zillmann (1999) notes that in a highly fact-focused story, the presence of one exemplar can cause the public to perceive the event as congruent with the exemplified portrayal and thus forget the base-rate information. Thus, a storm with a name that is concrete and iconic may drive impressions of the severity of the threat and have more influence on motivations of the public than a storm with a name that is considered inconsequential or unemotional or no name at all, even when only base-rate information is provided.
Because social media users have the ability to both create and transmit information, it may be the case that messages with particular characteristics may be more likely to be retweeted (Lin et al. 2016c). In an initial exploration of these factors, Sutton et al. (2014) analyzed tweets sent by emergency response agencies during a wildfire in Colorado. They found that tweets that were advisory in nature (e.g., articulating the nature of the risk and its consequences) were more likely to be retweeted than those that were purely instructive. They also found that tweets that contained imperative (as opposed to declarative) statements were more likely to receive serial transmission. In short, there were aspects of the content that led the messages to be retweeted and spread organically throughout the community of those affected, resulting in greater reach. These message aspects were related to the nature of the event, threats proposed, and actions that can be taken. To some degree, the magnitude of the event played a role in this response, and it may be assumed that to a certain degree the induction of fear or negative affect may have promoted this serial transmission. It could be the case that different storm naming strategies also elicit varying levels of fear or negative affect, and that this may lead to similar degrees of serial transmission. However, consideration of the factors driving serial transmission, including negative affect, is largely ignored by organizations using Twitter to manage crises and disasters.
The research outlined in this article has supported the notion that exemplified portrayals can impact perceptions of risk and intentions to change behavior in legacy media and social media environments. However, less is known about exemplified portrayals of weather-related events through social media. Because this is a new area of application of exemplification theory, the following research question is offered: To what extent does the naming of a story have effects on perceptions of 1) storm severity, 2) likelihood of storm damage, 3) intentions to change behavior, and 4) perception of event hazard and outrage?
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