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Numerous existing satellites observe physical or environmental properties ofthe Earth system. Many of these satellites provide global-scale observations,but these observations are often sparse and noisy. By contrast, contiguous,global maps are often most useful to the scientific community (i.e., Level 3products). We develop a spatio-temporal moving window blockkriging method to create contiguous maps from sparse and/or noisy satelliteobservations. This approach exhibits several advantages over existingmethods: (1) it allows for flexibility in setting the spatial resolution ofthe Level 3 map, (2) it is applicable to observations with variable density,(3) it produces a rigorous uncertainty estimate, (4) it exploits both spatialand temporal correlations in the data, and (5) it facilitates estimation inreal time. Moreover, this approach only requires the assumption that theobservable quantity exhibits spatial and temporal correlations that areinferable from the data. We test this method by creating Level 3 productsfrom satellite observations of CO2 (XCO2) from the Greenhouse GasesObserving Satellite (GOSAT), CH4 (XCH4) from the InfraredAtmospheric Sounding Interferometer (IASI) and solar-induced chlorophyllfluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). Weevaluate and analyze the difference in performance of spatio-temporal vs.recently developed spatial kriging methods

Spatio-temporal approach to moving window block kriging of satellite data v1.0