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This work applies a quantitative metric well-known to the data assimilationcommunity to a new context in order to capture the relative representativenessof non-simultaneous or non-co-located observations and quantify how theseobservations decorrelate in both space and time. This methodology allows forthe effective determination of thresholding decisions for representativematchup conditions, and is especially useful for informing future networkdesigns and architectures. Future weather and climate satellite missions mustconsider a range of architectural trades to meet observing requirements.Frequently, fundamental decisions such as the number of observatories, theinstruments manifested, and orbit parameters are determined based uponassumptions about the characteristic temporal and spatial scales of variabilityof the target observation. With the introduced methodology, representativityerrors due to separations in space and time can be quantified without priorknowledge of instrument performance, and errors driven by constellation designcan be estimated without model ingest or analysis.

Sampled Together: Assessing the Value of Simultaneous Co-located Measurements