The Influence of North American Carbon Flux Spatial Distribution on the Temporal Variability of Atmospheric Carbon Dioxide
Deborah
N
Huntzinger, University of Michigan, dnhuntzi@umich.edu
(Presenting)
Sharon
M
Gourdjii, University of Michigan, sharongourdji@gmail.com
Anna
M
Michalak, University of Michigan, amichala@umich.edu
A small subset of biospheric model estimates of net ecosystem exchange are used to assess the ability of the 2004 North American continuous CO2 sampling network to detect regional spatial variability (i.e., 1° x 1°) in land-atmospheric carbon flux. Using three case studies, the atmospheric signal resulting from biospheric model-derived flux is quantified using the WRF-STILT atmospheric transport model. These cases involve manipulating each model’s surface flux distribution in order to isolate the influence of (1) sub-ecosystem-scale variability; (2) ecosystem-scale variability; and (3) the near-field of observation locations on observed CO2 concentrations. At each tower, the resulting weekly-averaged CO2 concentration time series are compared to determine if changes in surface fluxes translate into statistically significant differences in their corresponding atmospheric CO2 signal. Two-sample, two-tailed z-tests, using tower-specific model-data mismatch error derived from real data are employed to assess the significance of observed differences among the time series. In general, distinct atmospheric CO2 signals resulting from the different biospheric models appear to be attributable to large scale variability in flux magnitude, rather than differences in sub-ecosystem flux distributions. Towers with larger measurement footprints, and those located in more dynamic flux regions, however, do appear to be sensitive to sub-ecosystem-scale variability both in the near and far field. Highlighting those regions where variation in flux distribution do not translate into significant differences in atmospheric CO2 signals provides information about the uniqueness of flux estimations from inversions. Such information will help inform inverse modeling, and improve our understanding of land-atmosphere carbon exchange.
Presentation Type: Poster
Poster Session: Carbon Cycle Science
NASA TE Funded Awards Represented:
Michalak, Anna
Contstraining North-American Fluxes of Carbon Dioxide and Inferring their Spatiotemporal Covariances through Assimilation of Remote Sensing and Atmospheric Data in a Geostatistical Framework