Bayesian statistical modeling of spatially correlated error structure in atmospheric tracer inverse analysis
We present and discuss the use of Bayesian modeling and computational methods for atmospheric chemistry inverse analyses that incorporate evaluation of spatial structure in model-data residuals. Motivated by problems of refining bottom-up estimates of source/sink fluxes of trace gas and aerosols...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2011-06-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | http://www.atmos-chem-phys.net/11/5365/2011/acp-11-5365-2011.pdf |