The visual communication of climate information is one of the cornerstones of climate services. It often requires the translation of multidimensional data to visual channels by combining colors, distances, angles, and glyph sizes. However, visualizations including too many layers of complexity can hinder decision-making processes by limiting the cognitive capacity of users, therefore affecting their attention, recognition, and working memory. Methodologies grounded on the fields of user-centered design, user interaction, and cognitive psychology, which are based on the needs of the users, have a lot to contribute to the climate data visualization field. Here, we apply these methodologies to the redesign of an existing climate service tool tailored to the wind energy sector. We quantify the effect of the redesign on the users’ experience performing typical daily tasks, using both quantitative and qualitative indicators that include response time, success ratios, eye-tracking measures, user perceived effort, and comments, among others. Changes in the visual encoding of uncertainty and the use of interactive elements in the redesigned tool reduced the users’ response time by half, significantly improved success ratios, and eased decision-making by filtering nonrelevant information. Our results show that the application of user-centered design, interaction, and cognitive aspects to the design of climate information visualizations reduces the cognitive load of users during tasks performance, thus improving user experience. These aspects are key to successfully communicating climate information in a clearer and more accessible way, making it more understandable for both technical and nontechnical audiences.The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreements 776787 (S2S4E), 776613 (EUCP), and (ClimatEurope). This work was also supported by the MEDSCOPE project. MEDSCOPE is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by AEMET (ES), ANR (FR), BSC (ES), CMCC (IT), CNR (IT), IMR (BE), and Météo-France (FR), with co-funding by the European Union (Grant 690462). The research team would like to thank the participants of the test who generously shared their time and opinions for the purposes of this research. This study is a part of the PhD of the corresponding author, Luz Calvo.Peer ReviewedPostprint (published version
