Technical Note: Adapting a fixed-lag Kalman smoother to a geostatistical atmospheric inversion framework

[摘要] Inverse modeling methods are now commonly used for estimating surface fluxesof carbon dioxide, using atmospheric mass fraction measurements combinedwith a numerical atmospheric transport model. The geostatistical approach toflux estimation takes advantage of the spatial and/or temporal correlationin fluxes and does not require prior flux estimates. In this work, a previously-developed,computationally-efficient, fixed-lag Kalman smoother is adapted for application with a geostatisticalapproach to atmospheric inversions.This method makes it feasible to perform multi-year geostatistical inversions,at fine resolutions, and with large amounts of data. The new method is applied to the recovery of globalgridscale carbon dioxide fluxes for 1997 to 2001 using pseudodatarepresentative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

[学科分类] 大气科学