## 6 Conclusions  
MODIS FRP has been applied to estimate biomass-burning emissions [24; 25; 26; 27; 28; 29] and generate global emissions products [24; 26; 28] for nearly two decades. However, MODIS misses a large amount of small and cool fires because of a coarse pixel size of 1.0-4.83 km [30; 31; 32; 33] and all fires inside MODIS swath gaps [35; 40], which could result in a significant omission of actively burning fires, and the underestimation of emissions subsequently. This is especially noticeable in Africa where fires have characteristics of low-to-moderate intensity and high frequency [58] and release more than half of global biomass-burning emissions [6].  
This study investigates FRP observations missed by Aqua MODIS due to sampling limitations and swath gaps using the S-NPP VIIRS I-band (375 m) active fire data across Africa. The variation of pixel-level minimum, mean, and maximum FRP across swath indicates that MODIS detection capability decreases sharply while that of VIIRS is generally consistent as view angle increases from nadir to the scan edge. The dependence of the MODIS and VIIRS fire detection capability on view angle is expected to be validated in the next step using the airborne-based very-high-resolution FRP observations during the NASA and NOAA lead 2019 FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaign [59]. Comparing FRP from fire detections observed contemporaneously by MODIS and VIIRS for the whole Africa continent and in seven grid sizes from 0.05\({}^{\circ}\)-5\({}^{\circ}\) quantifies the underestimation of MODIS FRP. On a continental scale, MODIS underestimates FRP by at least 42.8% relative to the contemporaneous VIIRS FRP. In grids, MODIS misses more than half of VIIRS fire detections and ~39% VIIRS FRP in 0.05\({}^{\circ}\)grids, although the missing rate decreases with grid size. The MODIS FRP underestimation could be partially mitigated using FRP adjustment models established from VIIRS-to-MODIS FRP ratio at seven different grid sizes, separately. Moreover, MODIS misses a large number of fires inside its swath gaps, where the missed FRP accounts for 12.5% of VIIRS FRP observed in the areas outside swath gaps. The missing MODIS FRP could be predicted using VIIRS fire data if available. Overall, the significantly large underestimation of MODIS FRP found in this study provides crucially quantitative information for understanding the uncertainties in the MODIS FRP and the related applications, especially biomass-burning emissions estimation. These uncertainties could be significantly improved by using the FRP adjustment models developed in this study.  
Conceptualization and methodology, F.L. and X.Z.; writing, F.L., X.Z., and S.K. All authors have read and agreed to the published version of the manuscript.  
This study is funded by NOAA contract NA14 NES4320003.  
The manuscript contents are solely the opinions of the author(s) and do not constitute a statement of policy, decision, or position on behalf of NOAA or the U.S. Government. The raw input datasets (Aqua MODIS C6 MYD14 and MYD03, and Suomi NPP VIIRS I-band VNP14 IMG) used in this study are available for the public at NASA's Level-1 and Atmosphere Archive and Distribution System (LAADS; [[https://ladsweb.modaps.eosdis.nasa.gov/](https://ladsweb.modaps.eosdis.nasa.gov/)]([https://ladsweb.modaps.eosdis.nasa.gov/](https://ladsweb.modaps.eosdis.nasa.gov/))). We thank three anonymous reviewers' comments that improved this paper.