Visualization System Suite for Probabilistic Weather Forecasting

A. Rusu, Amalia I. Rusu, John Williams
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Abstract

Today, forecasts from most media sources are communicated in a deterministic manner that supplies explicit weather prediction information for timeframes and specific events. For the most part, these basic forecasts provide enough information to allow a consumer to confidently make plans. However, there are situations in which forecasts uncertainty matters, and a deterministic weather forecast does not provide enough information for a consumer to plan confidently. By reporting probabilistic information such as forecast confidence and by quantifying uncertainty, users would be able to trust the forecast and proceed with making their plans, or know to check back frequently for updates if the forecast is uncertain and likely to change. In this paper, we present a series of visualization concepts that are used to present weather uncertainty, along with corresponding in person and online user studies. The goals of our research are to use visualization to instill appropriate confidence in weather predictions, drive people’s decisions, and propel the world by helping people to find good times for outside activities while protecting health, safety, and business interests. We hope that the outcome will enable consumers to perform at their best aided by more informative weather information.Deterministic weather forecasts are easily consumed and are found everywhere from apps on mobile phones, to social media sites, radio, and television. Our research provides a roadmap for augmenting these with forecast uncertainty and probabilities. One example of communicating forecast uncertainty may occur with winter storm tracks several days prior to an event. An on-camera meteorologist might describe to their viewers that if the winter storm goes north of the region one type of winter precipitation will fall but if it takes a southerly track a different outcome is expected. As the event gets closer, the meteorologist can hone the forecast and also provide a level of confidence to the viewer. In this example a human meteorologist describes the possible weather outcomes and to plan appropriately.
可视化系统套件的概率天气预报
今天,大多数媒体来源的天气预报以一种确定性的方式传播,为时间框架和特定事件提供明确的天气预报信息。在大多数情况下,这些基本的预测提供了足够的信息,让消费者自信地制定计划。然而,在某些情况下,预报的不确定性很重要,而确定性的天气预报并不能为消费者提供足够的信息来自信地计划。通过报告概率信息(如预测置信度)和量化不确定性,用户将能够信任预测并继续制定计划,或者知道如果预测不确定且可能改变,则经常检查更新。在本文中,我们提出了一系列用于表示天气不确定性的可视化概念,以及相应的现场和在线用户研究。我们的研究目标是利用可视化来灌输对天气预测的适当信心,推动人们的决策,并通过帮助人们找到户外活动的好时机来推动世界,同时保护健康、安全和商业利益。我们希望这一结果将使消费者能够在更丰富的天气信息的帮助下发挥最大的作用。确定性天气预报很容易被消费,从手机应用程序到社交媒体网站、广播和电视,随处可见。我们的研究为增加这些预测的不确定性和概率提供了一个路线图。传达预报不确定性的一个例子可能发生在冬季风暴发生的几天前。镜头前的气象学家可能会向观众描述,如果冬季风暴从该地区向北移动,就会出现一种冬季降水,但如果它向南移动,就会出现不同的结果。随着事件的临近,气象学家可以磨练预报,也为观众提供一定程度的信心。在这个例子中,人类气象学家描述了可能的天气结果,并制定了适当的计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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