*3.8. Scale-Dependence in Sentinel-3A OLCI versus SNPP VIIRS*

Sentinel-3A OLCI is yet without enough SNO data to demonstrate the scaling phenomenon in full a time series result, but the scale-dependence can be examined within individual SNO events as done in Figure 6. Figure 17 shows the dependence of ratio (top) and error bar (bottom) on area scale for Sentinel-3A OLCI Oa02 (412.5 nm) versus SNPP VIIRS M1 (410 nm), for a 13 April 2017 event for the three cases of unconstrained sample size (red triangles), constrained size at 1000 samples (blue squares), and constrained size at 500 samples (green diamonds).

**Figure 17.** The scale-dependent result of radiometric comparison of Sentinel-3A OLCI Oa02 versus SNPP VIIRS M1 for the 13 April 2017 event for ratio (top panel) and the error bar (bottom panel) shown for the three cases of unconstrained sample size (red triangles), constrained size at 1000 samples (blue squares), and constrained size at 500 samples (green diamonds).

All features of the OLCI-based result effectively repeat identically. This result reinforces the recommendation to confine the SNO analysis to a "nadir-only" condition using small area and that scaling phenomenon is a general effect impacting any inter-RSB comparison of two polar-orbiting instruments.

#### *3.9. Discussion and Summary*

The key finding is that a homogeneity-ranked, sample size constrained sampling procedure under a small-area restriction stabilizes the ratio against some broad-scale variability to generate result that is reliable and robust. A smaller area size such as under the 50-km scale contains enough pixels for the refined sampling procedure but simultaneously avoids the pitfall of large-area or large-angle bias. As the ratio result has been stabilized, the application of various criteria, such as scale or homogeneity threshold, is further shown to have impact on the comparison time series.

Since Aqua MODIS B5 versus SNPP VIIRS M8 is one the most stable inter-RSB comparisons due to good spectral match and long-term radiometric stability, the average precision of the time series at ~1.0% very well represents the general statistical capability of inter-RSB comparison at the 1-km regime. While the clear-scene result such as in Figure 5 is remarkably stable and precise at 0.2% or so, its number is not sufficient for full evaluation. In general, radiometric comparison time series are best used as a tool of discovery of deviating features such as the multiyear drift.

Also important is the generality of the scene-based variability over both polar regions as shown in the inter-RSB comparison results of MODIS and OLCI versus SNPP VIIRS. Therefore, any inter-RSB comparisons of polar-orbiting multispectral sensors necessarily need to treat this polar scene variability with some care.
