Assessing the Value of Simultaneous Collocated Measurements for Optimal Satellite Configurations

This work applies a quantitative metric in order to capture the relative representativeness of nonsimultaneous or noncollocated observations and quantify how these observations decorrelate in both space and time. This methodology allows for the effective determination of thresholding decisions for representative matchup conditions and is especially useful for informing future network designs and architectures. Future weather and climate satellite missions must consider a range of architectural trades to meet observing requirements. Frequently, fundamental decisions such as the number of observatories, the instruments manifested, and orbit parameters are determined based upon assumptions about the characteristic temporal and spatial scales of variability of the target observation. With the introduced methodology, representativity errors due to separations in space and time can be quantified without prior knowledge of instrument performance, and errors driven by constellation design can be estimated without model ingest or analysis. SIGNIFICANCE STATEMENT: Dramatic changes in the space industry are enabling new architectures and business models for Earth observations. Historically, operational weather and climate satellites have been built on school bus-sized platforms, with multiple instruments comanifested on the same asset. With newer small -satellite technologies and miniaturized payloads, government agencies and private ventures alike are considering the utility of proliferated constellations. One of the many trades to consider is precisely how observations degrade in representativity when separated by space and time. We suggest an objective metric that can be applied to define optimal observing requirements and constellation design. This work also enables future architecture proposals to account for representativity error in their overall error budget and performance specifications.