## 3 Results
### Landscape Factors Affecting FT Classification Accuracy  
The mean annual FT classification agreement was analyzed for the 2016-2017 SMAP PM FT data records from both the 36 km and 9 km global grid products. Generally, we found lower FT accuracy in areas with a higher fw, defined as the spatial proportion of open water within a 36 km and 9 km grid cell derived from the 300 m ESA water body map (Figure 5). The lower FT quality flag was assigned to cells with significant fw (grey shading in Figure 5), while cells with larger (>50%) fw levels, identified from a static water mask (MOD44W), are screened from further processing. The remaining FT cells with fw > 50% are attributed to differences between the ESA and MOD44W water masks, and primarily occur along coastal areas and large water bodies. These water-contaminated grid cells are identified from the ESA water body map used in this study, but were missed by the MOD44W static water map used for water body screening during SMAP operational processing. The inverse relationship between FT accuracy and fw cover is consistent with strong L-band microwave sensitivity to open water, which can degrade the Tb signal from adjacent land areas within the satellite footprint [54; 55; 56; 57]. The FT accuracy was also inversely proportional to the amount of forest cover and terrain complexity within a grid cell, derived from respective MOD44B 250 m vegetation and 30 m DEM data. The mountainous terrain flag was assigned to grid cells with a large (>250 m) elevation spatial standard deviation (SD), identified from the 30 m global DEM (grey shading in Figure 5). The 36 km grid product showed less sensitivity to vegetation cover, terrain heterogeneity and fw constraints than the 9 km grid product. Overall, the combined landscape factors explained approximately 53% and 29% (R\({}^{2}\), \(p<0.01\)) of the global variation in mean annual FT accuracy from the respective 36 km and 9 km PM products relative to the global SAT station network (Figure 5).  
The SMAP FT results are generally sensitive to the predominant frozen or thaw status of the land surface within a coarse (-40-km) radiometer footprint. However, the actual FT pattern may be more spatially complex due to variations in microclimate and land cover conditions that may not be adequately resolved by the satellite footprint [11; 40; 57]. These factors can contribute to a mismatch between in situ SAT observations that predominantly reflect local land surface conditions and overlapping satellite Tb retrievals representing an integrated regional signal.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**FT Product** & **AM Overpass** & **AM Overpass** & **PM Overpass** & **PM Overpass** \\ \hline  & 2016 & 2017 & 2016 & 2017 \\ \hline
36 km & 78.0 (74.9) & 77.8 (74.7) & 89.6 (87.8) & 89.7 (87.6) \\ \hline
9 km & 74.4 (71.8) & 74.3 (71.7) & 85.6 (84.2) & 85.8 (84.0) \\ \hline \end{tabular}
\end{table}
Table 1: The mean annual FT classification accuracy (%) of SMAP 36 km (L3_FT_P) and 9 km (L3_FT_P_E) daily FT products in relation to surface air temperature-based FT estimates from \(\sim\)5000 global weather stations. The values in parentheses represent the mean annual FT classification accuracy (%) in the northern (\(\geq\)45\({}^{\circ}\)N) portion of the domain. The FT accuracy is determined from SMAP ascending (PM) and descending (AM) orbital overpass Tb retrievals.