# Benefits and Lessons Learned from the Sentinel-3 Tandem Phase
## 10 Discussion  
The Sentinel-3 tandem phase has provided very significant results at several levels. Tandem data can be used to precisely quantify the inter-operability of all instruments. Assessment of its impact on climate data records is possible in some cases. Triple collocations studies for altimetry (land ice and sea state) highlight the excellent consistency of the measurements, in terms of accuracy and precision. However, the sea state analysis would have benefitted from a longer tandem period to increase the number of collocation opportunities with buoys.  
We have shown that harmonization of OLCI L1 data could improve the interoperability of the sensors. Although the inter-calibration coefficients are shown to be stable during the tandem period, the stability over the mission lifetime is an issue. To address this point, an inter-comparison method based on deep convective clouds (DCC) is recently developed [22]. The method, which can be used throughout the mission lifetime, is shown to reproduce tandem inter-comparison results with 0.5%.  
Tandem data has also been used to address some fundamental questions about error sources and uncertainties. The tandem analyses have, for example, quantified the impact of swell on SAR mode altimetry, assessed the validity of SLSTR per-pixel uncertainties, and quantified the impact of uncertainties on trend retrieval capabilities for OLCI ocean color products. In the case of the impact of  
Figure 14: Geometric acquisition differences during the tandem (**left**) and post-tandem drift phase (**right**). While the geometric conditions are almost identical for both satellites during the tandem phase, the sensor acquire the same target with significantly different viewing conditions during the drift phase.  
Figure 15: Inter-satellite comparisons of OLCI level2 products OGVI (**left**) and chlorophyll concentration (**right**) during the drift phase: histograms of relative differences as a function of the differences in viewing angles. OGVI shows a relatively strong dependency on the viewing angle, while the chlorophyll retrieval algorithm seems to be immune to such geometric effects. Reprinted from [23].  
the swell, we have shown that processing SAR data at 80 Hz greatly reduces aliasing errors on the measurements. Some perspectives for improvement are also identified for OLCI products beyond the harmonization discussed in Section 6.2: flat-fielding or equalization of camera gains, modification of the smile correction approach for red-edge bands. For all these cases, additional investigations or validation work will be required before an operational solution can be implemented.  
Another interesting aspect is the possibility to assess the effects of the viewing geometry on optical measurements. During the drift phase at the end of the tandem, the two satellites are acquiring nearly simultaneous observations with different viewing geometries. Preliminary analyses performed during our study show the potential of this dataset to investigate the sensibility of the level-2 retrieval algorithms to geometry or to compare the different views of the SLSTR instrument. However, the investigations are somewhat limited by the scarcity of the collected data and the lack of an optimal calibration. Deeper analyses beyond the scope of the present study would be needed to progress on geometric aspects of level 2 processing.