Great work. I have enjoyed following this project. Drones seem the ideal way to determine how emissions vary from savanna fires given the heterogeneity of landscapes and fires.  I have several thoughts and a few critical comments on the findings and methods.

Can you clarify that these fires were all "head" fires as opposed to backfires?  And, if so, can you comment on why the following dimensions are adequate?  We question wether 10m is wide enough for head fires to fully develop.  This width is fine for backfires. Also, if only head fires were examined, can you justify given that many fires are purposefully set as backfires in Africa. Headfires have long been used in research on African fires, yet research finds more backfires are set.

You do not appear to have published local or ground data on weather conditions. While T and H can be collected from regional weather stations, wind speed is critical to determining fire intensity and will influence MCE as well. Do you have wind data, it would seem critical for accurate fire intensity and MCE results.

I wonder about this comment: "

The grasslands with the highest EFs (found in high-rainfall savanna Dambos) were "uncharacteristically green for the time of the season" given that many fires are set to "green" grasses in African savannas, especially the perennials (See Le Page who documented this back in 2010 as well as many West African case studies).

I think Laris et al found very similar results to: "The strongest predictors for the MCE and the CO and CH4 EF were the tree density in the plots, the grass to litter ratio, the combustion completeness and the moisture content of the consumed fuel. It might be useful to compare and to consider the hypothesis that burning of green leaves on shrubs and trees vs. dried leaves on the ground may explain why EF CH4 is not linerally related to MCE. This reasoning may also explain the following finding, "For CO and CH4, the dominant effect is a spatial redistribution with higher CO and CH4 EFs in mesic, high-tree cover savannas and lower EFs in xeric savannas compared to previous estimates. The Higher CH4 EF in mesic may well be a function of leaf burning. This is logical given the findings from Senegal research by Barker finding burning trees emitted smoke with the highest methane EF.

This needs further explanation: "Although CO and CH4 followed the same spatial pattern, we found that MCE affected the CH4 which resulted in lower CH4 to MCE ratios in open (lower tree density?) savannas…. Do you mean higher CH4/MCE in wooded savannas as compared to grass-dominated ones?  What is “open”? Clarify. Again, see works in Mali and Senegal which agree with this finding.

Not sure I agree with this logic: "Contrary to previous research which indicated that dryer conditions in the LDS would lead to higher-MCE fires late-LDS conditions (Fig. 3). In part, this may be because our measurement campaigns missed the peak-season fires when the fires may be hotter..."  Winds are the critical factor here.  When do they peak in areas studied.  High winds (especially if fires studied are head fires) result in higher intensity regardless of fuel moisture. Laris also found lower MCE in LDS due to leaf litter in the fuel load and lighter winds with much higher winds in MDS for the region studied. Note that these factors are key reasons why binary (LDS/EDS) is problematic for determining emissions.

Again, see research in Mali and Senegal which support this finding: In accordance with previous studies (e.g. Korontzi et al., 2003b; van Leeuwen and van der Werf, 2011), we found steeper CH4 EF to MCE regression slopes in woodlands compared to grasslands.  

Comments

Figure 3. What is “typical savanna” there is no such thing.

Also, use more specific terminology, what is "open"?

This and other data rely on 500 x 500 MODIS is this relevant given efforts to burn patchy EDS fires which operate at a hectare level scale?  Can you justify using 500m data for the following? For fire severity proxies we used the differential Normalized Burn Ratio (dNBR) and 5 the differential Normalized Difference Vegetation Index (dNDVI) retrieved before and after the fire. These were based on the MODIS surface spectral reflectance, corrected for atmospheric conditions (MOD09GAV6; Vermote

Respectfully submitted