Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments

Author:

Ma Pulong12ORCID,Mondal Anirban3ORCID,Konomi Bledar A.4,Hobbs Jonathan5,Song Joon Jin6,Kang Emily L.4ORCID

Affiliation:

1. Statistical and Applied Mathematical Sciences Institute, Durham, NC

2. Department of Statistical Sciences, Duke University, Durham, NC

3. Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, Cleveland, OH

4. Division of Statistics and Data Science, Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH

5. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA

6. Department of Statistical Science, Baylor University, Waco, TX

Publisher

Informa UK Limited

Subject

Applied Mathematics,Modeling and Simulation,Statistics and Probability

Reference32 articles.

1. Computer model validation with functional output

2. Objective Bayesian Analysis of Spatially Correlated Data

3. Bösch, H., Brown, L., Castano, R., Christi, M., Connor, B., Crisp, D., Eldering, A., Fisher, B., Frankenberg, C., Gunson, M., Granat, R., et al. (2017), “Orbiting Carbon Observatory. (OCO-2) Level 2 Full Physics Algorithm Theoretical Basis Document,” https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_ATBD.V8.pdf.

4. Post hoc Uncertainty Quantification for Remote Sensing Observing Systems

5. Quantification of uncertainties in OCO-2 measurements of XCO<sub>2</sub>: simulations and linear error analysis

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