Other in situ quasi-continuous CO2 time series used are from the NOAA ESRL observatories at Barrow (BRW), Mauna Loa (MLO), Samoa (SMO), and South Pole (SPO); the EC Canadian sites at Alert, Nunavut (ALT), Sable Island, Nova Scotia (SBL) and Egbert, Ontario (EGB); and the NCAR sites at Niwot Ridge, Colorado (NWR) and Storm Peak Laboratory, Colorado (SPL). Note that all of these observations are calibrated against the same world CO2 standard (WMO-X2007). Also, note that aircraft observations from the NOAA ESRL program were NOT assimilated, but used for independent assessment of the CarbonTracker results.

For most of the quasi-continuous sampling sites, we construct an afternoon daytime average mole fraction for each day from the time series, recognizing that our atmospheric transport model does not always capture the continental nighttime stability regime while daytime well-mixed conditions are better matched. At mountain-top sites (MLO, NWR, and SPL), we use an average of nighttime hours as this tends to be the most stable time period and avoids periods of upslope flows that contain local vegetative and/or anthropogenic influence. Moreover, observations at sub-daily time scales are likely to be strongly correlated and therefore add relatively little independent information to our results.

Data from the Sutro tower (STR_01P0) and the Boulder tower (BAO_01P0, BAO_01C3) are strongly influenced by local urban emissions, which CarbonTracker is unable to resolve. At these two sites, pollution events have been identified using co-located measurements of carbon monoxide. In this study, measurements thought to be affected by pollution events have been excluded. This technique is still being developed.

Also based on Transcom continuous simulations, we decided to move a set of coastal sites by one degree into the ocean to force the model sample to be more representative of the actual site conditions. These sites are labeled for reference in the complete table of sites used in CarbonTracker. Table 1 summarizes how data from the different measurement programs are preprocessed for this study.

The preprocessed data used in CarbonTracker are freely available for download. Preprocessed data are not the original measurement data. Users are encouraged to review the literature and contact the measurement labs directly for details about and access to the actual observations.

We apply a further selection criterion during the assimilation to exclude non-marine boundary layer (MBL) observations that are very poorly forecasted in our framework. We use the so-called model-data mismatch in this process, which is the random error ascribed to each observation to account for measurement errors as well as modeling errors of that observation. We interpret an observed-minus-forecasted (OmF) mole fraction that exceeds 3 times the prescribed model-data mismatch as an indicator that our modeling framework fails. This can happen for instance when an air sample is representative of local exchange not captured well by our 1° x 1° fluxes, when local meteorological conditions are not captured by our offline transport fields, but also when large-scale CO2 exchange is suddenly changed (e.g. fires, pests, droughts) to an extent that can not be accommodated by our flux modules. This last situation would imply an important change in the carbon cycle and has to be recognized by the researchers when analyzing the results. In accordance with the 3-sigma rejection criterion, ~2% of the observations are discarded through this mechanism in our assimilations.

Table 2 (below) gives a summary of the observing sites used in CarbonTracker, and the performace of the assimilation scheme at each site. These diagnostics are useful for evaluating how well CarbonTracker does in simulating observed CO2.