# Evaluation of the Landsat-8 Albedo Product across the Circumpolar Domain
## 3 Results
### Accuracy of Circumpolar Full-Expression Blue-Sky Albedo  
The full expression blue-sky albedo (BLUE_full(MODIS_AOD)) was compared to tower measurements at 26 sites as shown in Figure 3. All sites were north of 40\({}^{\circ}\) in latitude and represented a diversity of land cover and conditions as specified in Table 1. The suitability of the validation data was refined to include only tower footprints in which greater than 70% of the Landsat pixels were valid, high-quality returns. The validation data were initially cloud screened using the Fmask algorithm and then visually inspected for misidentified clouds and cloud shadow. For the operational blue-sky albedo algorithm, the RMSE and bias to 0.0475 and \(-\)0.00026, respectively, within 0.05 required by climate modelers [55] with a sample size of 661. The results are shown in Figure 3b with the scatter shown along the 1:1 and +/\(-\)0.05 validation threshold indicated by the black lines. The dependence of solar zenith angle of the blue-sky albedo results was also investigated, as [PERSON] et al. [56] have shown that MODIS albedo values are most accurate with solar zenith angles (SZA) less than 70\({}^{\circ}\). As such, for the purpose of this comparison, SZA was restricted to less than 70\({}^{\circ}\), in doing so the Landsat RMSE and bias improved slightly to 0.0395 and 8.67 \(\times\) 10\({}^{-5}\), respectively. The Landsat albedo product was also well able to capture ephemeral events when they occurred at the time of instrument overpass. Temporal plots for the tower data, MCD43A3 MODIS albedo, and blue-sky albedo derived from MODIS and AERONET AOD sources are shown at three tower sites are shown in Figure 4.  
Figure 2: Monthly average white-sky albedo across the circumpolar domain for 2018 with associated QA metrics. The albedo and QA values have been aggregated to 500 m for the purpose of static visualization. The missing data, primarily occurring in November-February across the northern-most regions result from insufficient solar illumination due to polar night. Figure 4: Temporal comparison of Landsat and MODIS albedo products with Landsat albedo shown in red and green for MODIS and AERONET AODs, respectively, MODIS albedo at 500 m resolution in blue and the tower albedo in black. Insets of the tower footprints and surrounding landscape at each site are shown for summer months. Missing AERONET data points largely result from unavailable Level 2.0 AOD information. Figure 3: (**a**) Comparison of the Landsat blue-sky albedo results using MODIS-based AOD values (BLUE_full(MODS_AOD)) to tower measured albedo values across the circumpolar domain. RMSE and bias to 0.0395 and 8.67 \(\times\) 10\({}^{-5}\), respectively. Almost all the points outside of the \(+/-0.05\) are scenes where snow is present in the footprint, highlighting the need for further development of high-resolution products to capture these conditions. (**b**) Comparison of the MODIS blue-sky albedo results to tower measured albedo values at both spatially representative and non-representative sites for the spatial resolution of the MODIS sensors across the circumpolar domain. RMSE and bias to 0.074 and \(-0.0011\), respectively. Again, most points outside the \(+/-0.05\) are scenes in which snow is present, with Ny-Alesund and Sodankyla being especially poorly captured by MODIS albedo. The tower sites were also analyzed for their representativeness at 2 km subsets surrounding the tower with the assessment results per site listed in indicated in Table 1. In the growing/snow-free season, 12 of the 22 sites with available snow-free imagery were classified as representative suggesting the landscape can be accurately captured by lower spatial resolution satellites such as MODIS and VIIRS. However, on the dates when snow was present, only 2 of 21 sites with available imagery were classified as representative, highlighting the importance of higher spatial resolution when attempting to capture and quantify changes in dynamic and complex systems.