In phase 1 of this study, we conducted semi-structured interviews with eight NOAA-affiliated experts that were identified by the CPC. These interviews provided insight into the current and aspirational goals of the outlook products and the target end-users of the products. Importantly, there was a consensus amongst the interviewees that many target end-users do not properly interpret the current outlook visuals, and often times the intended user audiences do not use the climate outlook products due to a mismatch between the timescale of decision-making and the temporal range of the outlook products.
Given the results from phase 1, we identified target end-user entities in four sectors of interest to the CPC: agriculture, emergency management, energy, and water resource management. The database was constructed through methods such as snowball sampling, Internet searches of websites and literature that either stated use or alluded to use of the CPC temperature and precipitation outlooks, and IP address lookup from the CPC website. This database is intended to be continually updated throughout the study given emergent information.
To assess the target end-users’ baseline understanding, we conducted focus groups with individuals in each sector as well as distributing a web-based survey to the entities included in the database. The results from both the survey and focus groups provide insight into sectoral decision-making contexts, types of decisions, uses, and challenges with outlook understandability.
Given an understandability diagnosis, we are collaborating with CPC on modifications to the seasonal climate outlooks. These modifications will be tested with our target end-users to evaluate the modifications to the visualizations that improve understandability. Selected modifications will be implemented and re-tested in the second round of focus groups and a web-based survey to assess the effectiveness of the modifications. The results provide an evidence-based approach to decision support visualization modifications to meet the needs of users and constraints of data providers.
Supplementary URL: indicators.umd.edu