## 4 Simulation of the Meteosat Third Generation Imager Fire Channel Potential
* MTG-I/FCI fire application MIR and TIR channel data will allow for detection of nearly all fires in the 1 km sampling mode which are also detected by MODIS, but it will miss most of the small fires (usually detected by BIRD, FireBIRD or VIIRS) unless they are located close together--together occupying one MTG-I/FCI pixel. Nevertheless, in fire scenes with intensive burning, the MTG-I/FCI data will underestimate the total accumulated FRP by 0-4% only in the 1 km sampling mode and by 6-18% in the 2 km sampling mode, depending on the fire size distribution. (The FRP underestimation may be more significant in the scenes dominated by small fires.) * MTG-I/FCI fire application channel data will probably fulfill the \"30% FRP accuracy\" condition for two out of every three detected active fires in both MTG-I/FCI sampling modes for typical wildfire scenarios. * MTG-I/FCI fire application channel data will permit an estimation of: \(\circ\) The effective fire temperature with an accuracy of 100 K; \(\circ\) The effective fire area (i) for only 7-17% of the detected active fires in the 1 km sampling mode (with an area accuracy \"factor of 2\") and (ii) only in exceptional cases in the 2 km sampling mode. Capability of FireBIRD Class Data for Validation of the Fire Radiative Power Obtained from MTG-I/FCI--Class IR Data  
In Table 9 of the previous chapter, minimum FRP values of 48 or 96 MW for the detected fires in the simulated MTG-I/FCI images in the 2 km sampling mode for the Benin or Portugal scene, respectively, are presented. The simulated MTG-I/FCI 2 km mode corresponds to the GSD of the Himawari-8 AHI at its sub-satellite point (SSP). These values confirm the statement of [13] that \"... AHI underestimates FRP by around 50% compared to the simultaneous MODIS view, because it cannot easily detect the (rather common) fires whose FRP lies below \(\sim\)40 MW\". MTG-I/FCI will provide unsaturated MIR and TIR fire application channel data of wildfires in Africa and Southern Europe within a time interval of 10 min with two selectable GSDs at an SSP of 2 km or 1 km. The ground resolution of 1 km for the FCI at the SSP of MTG-I is comparable to the resolution of fire application channel data of MODIS and SLSTR, and it will be a little bit coarser than the VIIRS M-band fire product with a 750 m GSD. Therefore, one can assume that an improved quality of fire observation and quantitative evaluation of fires in their diurnal cycle can be achieved if:  
* MIR and TIR band data acquired by MTG-I/FCI within time intervals of 10 min with ground resolutions of \(\sim\)1 km can be used to derive the Fire Radiative Power (FRP) of medium and larger fire clusters--every 10 min and covering their whole diurnal cycle;
* MIR and TIR band data acquired several times per day with ground resolutions of \(\sim\)200 m, for instance, by BIROS, or by thinkable prospective satellites of the FireBIRD class, are used to derive the FRP of these medium and larger fire clusters with higher accuracy;* These FRP figures with a higher estimation accuracy are used to augment or validate the FRP derived from geostationary satellite 1 km resolution data--as it is illustrated in Figure 5 (copied from [13]) for data from MODIS and Himawari-8;
* The FRP values of these selected and validated fire clusters can serve as local reference points for the FRP figures obtained by MTG-I/FCI within 10 min intervals, which should then be integrated into Fire Radiative Energy (FRE) figures--for each fire cluster over its whole time of burning;
* These FRE figures are used to estimate the amount of carbon, i.e., CO\({}_{2}\), CO, particulate matter (PM) and black carbon (BC), released by each fire cluster during its live time. The possibility to calculate the FRE over the fire diurnal cycles may significantly improve, for instance, the estimation accuracy of Dry Matter Burned (DMB), an important input parameter for the Global Fire Assimilation System (GFAS) [11; 13].