Visualizing probabilistic flood forecast information: expert preferences and perceptions of best practice in uncertainty communication. Issue 1 (23rd April 2012)

• Record Type: Journal Article
• Authors: Pappenberger, Florian; Stephens, Elisabeth; Thielen, Jutta; Salamon, Peter; Demeritt, David; van, Schalk Jan; Wetterhall, Fredrik; Alfieri, Lorenzo; Cloke, Hannah L.; Pappenberger, Florian; van, Schalk Jan; Schaake, John; Thielen, Jutta; Ramos, Maria‐Helena
• Is Part Of: Hydrological processes. Volume 27:Issue 1(2013:Jan. 01)
• Page Start: 132
• Page End: 146
• Publication Date: 2012-04-23
• Subjects: Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.9253
• Languages: English
• ISSNs: 0885-6087

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>The aim of this article is to improve the communication of the probabilistic flood forecasts generated by hydrological ensemble prediction systems (HEPS) by understanding perceptions of different methods of visualizing probabilistic forecast information. This study focuses on interexpert communication and accounts for differences in visualization requirements based on the information content necessary for individual users. The perceptions of the expert group addressed in this study are important because they are the designers and primary users of existing HEPS. Nevertheless, they have sometimes resisted the release of uncertainty information to the general public because of doubts about whether it can be successfully communicated in ways that would be readily understood to nonexperts. In this article, we explore the strengths and weaknesses of existing HEPS visualization methods and thereby formulate some wider recommendations about the best practice for HEPS visualization and communication. We suggest that specific training on probabilistic forecasting would foster use of probabilistic forecasts with a wider range of applications. The result of a case study exercise showed that there is no overarching agreement between experts on how to display probabilistic forecasts and what they consider the essential information that should accompany plots and diagrams. In this article, we propose a list of minimum properties that, if consistently displayed with probabilistic forecasts, would make the products more easily understandable. Copyright © 2012 John Wiley & Sons, Ltd.</p> </abstract>