## 5 Discussion  
The MODIS sensor has a relatively low fire detection capability and misses a large portion of FRP observations relative to the VIIRS I-band sensor. The minimal FRP (per fire pixel) across swath suggests that the MODIS sensor misses fires with intensity less than ~4.3 MW at nadir and ~31.7 MW at the scan edge (Figure 4a), whereas VIIRS I band (375m) can detect approximate 3-11 times smaller fires (Figure 4b). Across the African continent, fires missed by MODIS result in the underestimation of MODIS FRP by 42.8% (26% + bias interpreted as 16.8% of daily mean MODIS FRP in Figure 5b) because fires with FRP\(<\)31.7 MW account for a significant portion of all fires as indicated by VIIRS FRP frequency density distributions (Figure 7b). Our previous comparison between MODIS and VIIRS M-band FRP suggests that the daily MODIS sum FRP is only underestimated by approximately 10.5% across Africa [32]. Thus, much more underestimation of MODIS FRP is revealed by comparing with VIIRS I-band FRP. Similar findings on underestimation of MODIS FRP have also been demonstrated in cropland fires [43; 44]. For example, compared with the Aqua MODIS monthly summed FRP in agriculture burnings, VIIRS I-band measures 120% more FRP in Punjab, India [44], and synthesized VIIRS I-band and M-band radiances measure FRP about six times larger in eastern China [43]. Additionally, it is worth noting that, for relatively small fires detected by the MODIS  
Figure 10: Seasonal variations of VIIRS FRP observed inside MODIS swath gaps (blue) and the ratio (red) of the VIIRS FRP inside to outside MODIS swath gaps across Africa in 2017.  
sensor, high albedo across the fire-prone Africa savannas also causes uncertainty in MODIS FRP retrievals [54; 55]. Furthermore, missing MODIS FRP due to relatively lower fire detection capability is also evident at the grid level. For a given grid size from the finest 0.05\({}^{\circ}\) to the coarsest 0.5\({}^{\circ}\), MODIS senses no fires in a large number of grids where only VIIRS has fire detections (Figure 6). It indicates that VIIRS senses many more fires with FRP beyond MODIS fire detection capability. These MODIS missing fires occur in many areas across Africa, as suggested by the large percentages of grids where only VIIRS senses fires (Figure 6a). For example, the percentage is still 34% even at a grid size of 0.5\({}^{\circ}\) (Figure 6a), although fires in these grids contribute to a very small portion of daily VIIRS sum FRP (Figure 6b,c). In addition, the increase in the ratio of VIIRS to MODIS grid FRP with view angles suggests that MODIS misses more FRP at large view angles than in nadir as its detection capability reduces at off nadir. For example, as grid size grows larger than 1.0\({}^{\circ}\) (Figure 6), the underestimation of MODIS FRP could increase by up to \(\sim\)60% at the scan edge relative to in nadir (Figure 8e,f). MODIS FRP underestimation due to relatively low detection capability can be partly mitigated. At a continent scale, daily MODIS FRP underestimation can be directly adjusted based on the derived relationship between MODIS and VIIRS FRP illustrated in Figure 5b. This adjustment undoubtedly improves the estimation of total biomass-burning emissions from MODIS FRP across Africa. On a grid level, the fitted models at seven different grid resolutions can be applied to adjust MODIS FRP in grids where MODIS senses fires. Indeed, these fitted models can help to adjust grid-based MODIS FRP that is used in most of biomass-burning emissions inventories at a grid resolution from 0.1\({}^{\circ}\)-1.0\({}^{\circ}\), including GBBEPx--Global Biomass Burning Emissions Products [28]--GFAS--the Global Fire Assimilation System [24]--and FEER--Fire Energetics and Emissions Research [26]. For example, at the grid size of 0.5\({}^{\circ}\) the model can improve MODIS FRP by 40-50%. It is worthwhile to note that there is a trade-off between grid size and degree to which the MODIS FRP underestimation can be adjusted.