## 6 Conclusions  
We used the fast atmospheric trace gas retrieval FOCAL v06 to retrieve XCO\({}_{2}\) from one year (2015) of OCO-2 measurements and presented the applied pre- and post-processing methods including pre-filtering, noise model, zero level offset correction, post-filtering, and bias correction. The strict pre-filtering bases on sounding quality, NASA's spike EOF analyses, OMI UV aerosol index, and MODIS Aqua cloud coverage. Due to the wider swath, MODIS cloud masking has the potential advantage to better account for 3D-effects caused by neighboring cloud contamination. However, as Aqua is lagging OCO-2 by 15 min, we chose a cloud filtering radius of 10 km, to prevent potential cloud movement from introducing cloud contamination. As a result this filter has a throughput of only about 11% and dominates the total pre-filtering throughput of about 4%. This makes this filter the main reason for FOCAL v06 having about three times less data points than NASA's operational product and an OCO-2 based cloud filtering as also done by NASA (2015) is a potential solution for future FOCAL versions. In order to consider not only instrumental noise but also (pseudo) noise of the forward model, we set up a noise model that depends on the instrument noise and one free fit parameter which we determined from the residuals of a set of relatively unconstrained retrievals. The noise model suggests that forward model errors (plus potential pseudo noise of the instrument) have a magnitude of 0.5-3.2% of the continuum radiance. This means that in dark scenes the mismatch of simulated and measured radiance is still dominated by the noise of the instrument but in bright scenes (e.g., above deserts) the forward model error dominates. Apparent or effective zero level offsets can have various reasons such as residual calibration errors or unconsidered spectroscopic effects. For the SIF, and both CO\({}_{2}\) fit windows, we found linear relationships between the retrieved zero level offsets and the continuum radiances with slopes between 0.8% and 1.8%. As FOCAL v06 usually does not retrieve the ZLO per sounding, we correct the measured radiance with the derived linear relationships before the retrieval. Post-filtering checks for convergence, for fit window residuals being smaller than the thresholds derived from the noise model analyses, and for potential outliers. Non converging soundings are often found near the SAA, the Saharan desert, and the Arabian peninsula. Soundings with too large residuals are often found above the tropical oceans. The filter for potential outliers is most active in  
Figure 16: Validation statistics bias and scatter per TCCON site with more than 250 co-locations for FOCAL v06 and NASA’s operational OCO-2 L2 product (both with and without bias correction). The summarizing values (“overall”) represent the standard deviation of the site biases and the average scatter relative to TCCON, respectively.The sites are ordered from north (top) to south (bottom). high latitudes and its dominant input parameter (above land) is the retrieved Angstrom exponent. The total post-filtering throughput is about 42%. The average RSR is 2.2%, 3.0%, 2.8%, and 3.4% for the SIF, the O\({}_{2}\), the wCO\({}_{2}\) and the sCO\({}_{2}\) fit window, respectively. A bias correction has been applied to the post-filtered results which primarily bases on the assumption that XCO\({}_{2}\) has (on average) little variations on small scales so that correlations to more variable parameters can be used to quantify biases. As a consequence, the bias correction does not require any ground truth data except for a globally constant offset of \(-1.67\,\mathrm{ppm}\). We found a distinct OCO-2 footprint dependent bias in the range between \(-0.97\,\mathrm{ppm}\) and \(1.22\,\mathrm{ppm}\) but the most prominent global bias pattern results from the land/sea bias of \(1.80\,\mathrm{ppm}\). One could speculate that the land/sea bias has its origin in FOCAL's assumption of Lambertian surfaces.