Time of Detection as a Metric for Prioritizing Between Climate Observation Quality, Frequency, and Duration

We advance a simple framework based on "time of detection" for estimating the observational needs of studies assessing climate changes amidst natural variability and apply it to several examples related to ocean acidification. This approach aims to connect the Global Ocean Acidification Observing Network "weather" and "climate" data quality thresholds with a single dynamic threshold appropriate for a range of potential ocean signals and environments. A key implication of the framework is that measurement frequency can be as important as measurement accuracy, particularly in highly variable environments. Pragmatic cost-benefit analyses based on this framework can be performed to quantitatively determine which observing strategy will accomplish a given detection goal soonest and resolve a signal with the greatest confidence and to assess how the trade-offs between measurement frequency and accuracy vary regionally.