NASA’s archive of Earth observation and modeling datasets has an incredibly diverse range of uses, and assessing data uncertainty is a critical step toward ensuring the data and analyses are accurate, reliable, and trustworthy. Several factors, such as instrument calibration, atmospheric corrections, and land-surface albedo, can affect the quality of satellite data. For users working with solar and meteorological datasets, quantifying uncertainty is especially critical, as these data often inform decisions and policymaking at the community level.
However, characterizing data product uncertainty can be a complex process, especially for less technical users. Existing options frequently require a level of know-how that can present a barrier to entry and may dissuade users from trusting the data. NASA’s Prediction of Worldwide Energy Resources (POWER) project, which provides datasets from NASA in support of energy, buildings, and agroclimatology decisions, developed a tool that enables users to assess data uncertainty for selected surface variables from POWER’s data catalog with corresponding surface measurements.
The cloud-based tool — the PaRameter Uncertainty ViEwer (PRUVE) — makes assessing data uncertainty more straightforward for users across disciplines and skill levels. PRUVE uses surface observed site meteorological data from the National Oceanic and Atmospheric Administration (NOAA) and surface radiation data from Baseline Surface Radiation Network (BSRN) to compare against POWER-provided surface meteorological and radiation data values. This user-friendly application gives users an opportunity to quickly confirm data validation through customizable queries.
