## 5 Conclusions  
We merged SMAP enhanced TBs and CYGNSS reflectivity values to create 3 km SMAP/CYGNSS TBs. Future work includes using 3 km SMAP/CYGNSS TBs to create a 3 km NSSM product. Globally, the correlations between SMAP emissivity and CYGNSS reflectivity values are good (more negative), except in forested areas, barren areas, or areas with high topographic roughness. In this way, SMAP/CYGNSS \(\beta\) values are similar to SMAP active-passive \(\beta\) values [2]. Lower \(\beta\) values yield greater spatial heterogeneity in SMAP/CYGNSS TBs. Areas with very low mean annual precipitation and NSSM variability have poorly correlated linear regressions with near-zero \(\beta\) values. Areas with high topographic roughness or high mean NDVI also have poorly correlated linear regressions with near-zero \(\beta\) values. Well correlated linear regressions with lower (more negative) \(\beta\) values are generally found in areas with low topographic roughness (<350 m), moderate NSSM variance (\(\sim\)0.01-0.0325), low-to-moderate mean annual precipitation (\(\sim\)0.25-1.5 m), and moderate mean NDVI (\(\sim\)0.2-0.6). \(\beta\) values are lowest in croplands and grasslands and highest in forested and barren lands. 3 km SMAP/CYGNSS TBs are more spatially heterogenous than 9 km SMAP TBs and capture expected soil moisture patterns on the landscape. The median RMSD between 3 km SMAP/CYGNSS TBs and 9 km SMAP TBs is 3.03 K. The spatial heterogeneity of 3 km SMAP/CYGNSS TBs is similar to the spatial heterogeneity of 3 km SMAP/Sentinel TBs. In upcoming years, GNSS-R constellation sizes will increase, along with the number of received signals [33; 34]. Additional GNSS-R constellations will provide more opportunities for downscaled NSSM products. Hopefully, the SMAP/CYGNSS TB algorithm can serve as a model for future downscaling efforts. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs14205262/s1](https://www.mdpi.com/article/10.3390/rs14205262/s1)]([https://www.mdpi.com/article/10.3390/rs14205262/s1](https://www.mdpi.com/article/10.3390/rs14205262/s1)): A netcdf file containing \(\beta\) values, their corresponding correlations, and median RMSD TB and \(\Delta\Gamma\) values for 2020 (as shown in Figures 6 and 7). Conceptualization, C.C.C. and E.E.S. ; methodology, L.J.W., C.C.C., E.E.S. and N.N.D. ; software, L.J.W. and C.C.C. ; validation, L.J.W. ; formal analysis, L.J.W. ; resources, C.C.C. and E.E.S. ; data curation, L.J.W. and C.C.C. ; writing--original draft preparation, L.J.W. ; writing--review and editing, E.E.S., C.C.C. and N.N.D. ; visualization, L.J.W. ; supervision, E.E.S. and C.C.C. ; project administration, C.C.C. and E.E.S. ; funding acquisition, C.C.C. and E.E.S. All authors have read and agreed to the published version of the manuscript. This research was funded by the NASA Soil Moisture Active-Passive (SMAP) Science Team, award number 80 NSSC20K1793. **Data Availability Statement:**\(\beta\) values, their corresponding correlations, and median RMSD TB and \(\Delta\Gamma\) values for 2020 (as shown in Figures 6 and 7) are available in the Supplementary Materialsnetedf file. SMAP data is publicly available in the NSIDC DAAC [20; 29; 32]. CYGNSS data is publicly available in the PO.DAAC [10]. Downscaled SMAP/CYGNSS TB data will be publicly available with the downscaled SMAP/CYGNSS NSSM product in the future and are available on request from the corresponding author. We would like to thank [PERSON] for helpful discussions regarding this project and [PERSON] for help with batch processing and parallel computing. We would also like to thank anonymous reviewers for their constructive comments. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.