Directions of Inquiry Given a fixed atmospheric CO2 concentration assimilation scheme, what is the optimal network expansion? Given the wide array of available data, what is the optimal assimilation strategy? Feedbacks between assimilation strategy and network will be critical

Optimal Network Expansion Accuracy of measurements vs. density of measurements in space and time Location of measurements on high signal, high variability to low signal, low variability continuum What is the necessary vertical coverage? Will satellite CO2 measurements be useful? What degree of validation will they require?

Optimal Assimilation Strategy How handle unresolvable variability (model-data mismatch)? Flux correlations – fixed patterns or ecosystem/ocean models with tunable parameters? What else can we assimilate? What level of increased computing power, model resolution can we expect? How can we use currently unused data? Better estimates of transport errors from operational centers?

Accuracy vs. Density Using high frequency data makes signals bigger, but they are different signals The annual-mean signals are still very small

Equilibrium surface CO2 concentrations (“footprints”), relative to the South Pole, calculated with the TM3 model for 1 GtCyr-1 sources evenly distributed over (a) North America, (b) tropical South America, and (c) the western mid-latitude South Atlantic. The source in (c) corresponds to a region of significantly high chlorophyll and low pCO2 (LSCOP, 2002)

Flux footprint, in ppm(GtCyr-1)-1, for a 106 km2 chaparral region in the U.S. Southwest (Gloor et al., 1999).

3 GtC/yr uptake for 3 months 1.5 GtC/yr uptake for 2 months 0.5 GtC/yr release for 2 months 1.0 GtC/yr release for 5 months  Net annual uptake of 0.5 GtC To measure to ± 0.05 Gt uncertainty: If errors are random, need to measure monthly fluxes to ± 0.17 GtC/yr or ± 12% If errors are systematic (more likely), need to measure monthly fluxes to ± 0.05 GtC/yr or ± 3.5% (scale numbers by ~ 1/10 for fluxes on regional scales of interest)