## 6 Conclusions
However, retrievals of simulated ocean observations done in part 1[23] do not support this hypothesis. We compared FOCAL v06 XCO\({}_{2}\) results with co-located values of the CAMS v15r4 model. Both data sets show similar large scale spatial patterns and the systematic temporal and regional differences have a standard deviation of \(1.0\,\mathrm{ppm}\). The standard deviation of the single sounding mismatches amounts to \(1.1\,\mathrm{ppm}\) which agrees reasonably well with the average reported uncertainty of \(1.2\,\mathrm{ppm}\). We also compared FOCAL's v06 XCO\({}_{2}\) with the operational NASA OCO-2 product. Large scale patterns of both data sets are similar and the most prominent difference is that the NASA product has about three times more soundings. The primary reason for this is the inherently poor throughput (11%) of the MODIS based cloud screening of FOCAL's preprocessor. The NASA product has on average 0.7 ppm larger values than FOCAL v06. The standard deviation of the difference between both products is \(1.1\,\mathrm{ppm}\). Finally, we validated one year (2015) of FOCAL v06 XCO\({}_{2}\) data with and without bias correction as well as NASA's operational OCO-2 XCO\({}_{2}\) product with and without bias correction with co-located ground based TCCON observations. The algorithms show similarities in the site-to-site patterns of bias and scatter. The standard deviations of the site biases are \(0.82\,\mathrm{ppm}\) and \(0.67\,\mathrm{ppm}\) for the NASA product and FOCAL, respectively (\(0.69\,\mathrm{ppm}\) and \(0.78\,\mathrm{ppm}\) without bias correction). These algorithm-to-algorithm differences are barely significant because TCCON's per site accuracy is about \(0.4\,\mathrm{ppm}\) (\(1\sigma\))[32]. The average scatter relative to TCCON is \(1.31\,\mathrm{ppm}\) and \(1.34\,\mathrm{ppm}\) for NASA and FOCAL, respectively (\(1.62\,\mathrm{ppm}\) and \(1.60\,\mathrm{ppm}\) without bias correction). Additionally, we performed an initial validation of one year (2015) of FOCAL v06 XH\({}_{2}\)O data with co-located ground based TCCON observations and found site-to-site biases with a standard deviation of \(206\,\mathrm{ppm}\) and an average single sounding precision of \(293\,\mathrm{ppm}\). However, due to the much larger natural variability of XH\({}_{2}\)O compared to XCO\({}_{2}\), future studies are needed to quantify or minimize the influence of representation errors. Processing an entire year of OCO-2 data with FOCAL v06 took about two weeks on a small cluster with 8 Intel Xeon E5-2687W CPUs with eight cores running at \(3.1\,\mathrm{GHz}\) (released in 2012). This means that FOCAL is fast enough to process data from current and future satellites similar to CarbonSat[4; 54] providing at least an order of magnitude more data with a reasonable amount of CPU cores - especially, when taking into account the to be expected CPU developments until launch date.Additionally, FOCAL's computations are simple enough for an adaptation to GPU architecture with reasonable effort which has the potential for a further substantial acceleration. This work was in part funded by ESA/ESRIN (GHG-CCI II project), the European Union (Copernicus Climate Change Service led by ECMWF), and the State and the University of Bremen. ECMWF provided the used meteorological profiles. The OCO-2 data were produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center. Additionally, NASA provided the MODIS L2 collection 6 MYD35 cloud mask data, the OMI L3 OMAERUVd v003 UV aerosol index data, and the absorption cross section database ABSCO. We used data of the CAMS greenhouse gas flux inversion model and thank [PERSON] for his comments. The used solar spectra were made available by [PERSON] and [PERSON], and we used a chlorophyll fluorescence spectrum published by [PERSON].