**4. The application of FRE**

Kaufman et al. (1996, 1998) first showed the potential application of FRP and FRE for estimating fuel combustion rates and aerosol loading while examining prescribed fires during the Smoke, Clouds, and Radiation (SCAR) experiments. Wooster (2002) investigated the relationship between FRP/FRE and fuel consumption using small-scale experimental fires in which spectroradiometers recorded the radiative emission for the entire burning

alternative method to quantify the biomass consumed, and assuming an emission factor is

Unfortunately, sensors are unable to separate the spatially distinct components of the fire, potentially as small as millimeters, and the equation cannot distinguish between fractional areas of the entire fire which often are much smaller than the pixel itself. Thus, different methods have been tested and employed to overcome these limitations. The bi-spectral method, using two distinct channels (usually 4 and 11μm), can provide details about the fractional size and temperature of sub-pixel fire components (Dozier, 1981; Giglio & Kendall, 2001, Wooster et al., 2005), but is plagued by potential errors associated with channel misregistration and point spread function (PSF) differences between channels (Giglio & Kendall, 2001). Wooster et al. (2005) suggested that the bi-spectral method is effective, but primarily for high resolution sensors (<1km). The current method used aboard MODIS employs a single channel approach with fire and background components retrieved solely from the mid-infrared (4μm) channel (Justice et al, 2002). Kaufman et al. (1996, 1998) tested this single channel approach using the MODIS Airborne Simulator (MAS), model simulations of fire mixed-temperature pixels (to realistically mimic the nonhomogeneous behavior of biomass burning temperatures), and *in situ* measurements. Based on the simulated fires, Kaufman et al. (1998) revealed that an empirical relationship exists between instantaneous FRE (i.e. FRP) and pixel brightness temperature measured in the Moderate Resolution Imaging Spectroradiometer (MODIS) middle infrared channel (4 µm). The result was a semi-empirical relationship which forms the basis for the current FRP algorithm (equation 5) used aboard MODIS. The authors also demonstrated the correlation between rates of smoke emission and the observed rate of energy released from airborne

FRP [MW km-2] = 4.34 x 10-19 (*T*8MIR – *T*8bg, MIR) (5)

where FRP is the rate of radiative energy emitted per pixel (the MODIS 4µm channel has IFOV of 1km), 4.34x10-19 [MW km-2 Kelvin-8] is the constant derived from the Kaufman et al. (1998) simulations, *T*MIR [Kelvin] is the radiative brightness temperature of the fire component, *T*bg, MIR [Kelvin] is the neighboring nonfire background component, and MIR

Wooster et al. (2003) showed that FRP could also be derived using satellite-based middle infrared radiances and a simple power law to approximate Plank's law. The 'MIR radiance' method is applicable for temperatures covering the range of typical vegetation fires (600 – 1500 K). As with the 'MODIS' method, the MIR method relies on the difference between the fire pixel and background, but uses spectral radiance differences rather than brightness temperature. According to Wooster et al. (2005) the radiance methods allows perturbations, such as atmospheric effects and pixel area variation across the scan angles, to be accounted

Kaufman et al. (1996, 1998) first showed the potential application of FRP and FRE for estimating fuel combustion rates and aerosol loading while examining prescribed fires during the Smoke, Clouds, and Radiation (SCAR) experiments. Wooster (2002) investigated the relationship between FRP/FRE and fuel consumption using small-scale experimental fires in which spectroradiometers recorded the radiative emission for the entire burning

known, it also offers the atmospheric emission load.

observations with the MAS (Kaufman et al., 1996, 1998).

refers to middle infrared wavelength, typically 4μm.

for after FRP has been derived.

**4. The application of FRE** 

process at 5 to 10 second intervals. Wooster et al. (2003, 2005) expanded on their previous work, providing additional evidence of the effectiveness of using instantaneous and total FRE measurements to estimate biomass consumed from fire. Wooster & Zhang (2004) demonstrated the application of MODIS FRP observations by verifying the often proposed hypothesis that North American boreal fires are generally more intense than Russian boreal fires, while Ichoku & Kaufman (2005) used the MODIS FRP and aerosol products to derive near real time rates of aerosol emissions at regional scales. Research by Roberts et al. (2005) has shown the effectiveness of using geostationary satellite estimates of FRP from The Spinning Enhanced Visible and Infrared Imager (SEVIRI) to quantify rates of fuel consumption and characterize the fire intensity daily cycle. A laboratory investigation of FRE and biomass fuel consumption by Freeborn et al. (2008) supported the accuracy of Wooster et al.'s (2005) findings and lends credence to the application of satellite based measurements of FRE. Ichoku et al. (2008a), in a coordinated effort with research conducted by Freeborn et al. (2008), used laboratory investigations to examine rates and total fire radiative energy emitted and associated aerosol emissions. In both the case of Freeborn et al. (2008) and Ichoku et al. (2008a), the relationship between energy emitted, fuels consumed, and trace gas and aerosol emission demonstrated the efficacy of using FRE. Ichoku et al. (2008b) offered another example of using FRP, but at continental scales while investigating the global distribution of MODIS-based FRP estimates and revealed the regional distributions of fire intensity. Their research also showed significant differences in diurnal cycles and categorized intensities of FRP between regions which could not be explained by ecosystem type alone, suggesting perhaps that land use is a factor. Roberts & Wooster (2008) built upon their previous research (Roberts et al., 2005), showcasing the application of high temporal satellite based FRP measurements from the SEVIRI geostationary sensor to calculate FRE and estimate biomass combusted. Boschetti & Roy (2009) demonstrated a novel fusion approach to derive FRE based on temporal interpolation of MODIS FRP across independently derived burned area estimates. Their work was limited to Australia and the MODIS sensor, but as the authors suggest, the methodology could be expanded to other sensors and "is a fruitful avenue for future research and validation" (Boschetti & Roy, 2009). Freeborn et al. (2009) used frequency density distributions developed from MODIS and SEVIRI fire radiative power to synthesize the two sensors as a means for cross-calibration of their respective estimates. However, until Ellicott et al. (2009) and Vermote et al. (2009) no study had derived FRE at a global scale, in part due to limitations in temporal or spatial resolution of satellite sensors.

A current limitation of fire energy retrieval from satellites is that observations are of instantaneous energy (power) over some discrete length of time and space. To address this Ellicott et al. (2009) developed a unique approach to parameterize the temporal trajectory of FRP and calculate the integral (i.e. FRE) using MODIS. The parameterization was based on the long term ratio between Terra and Aqua MODIS FRP and diurnal measurements of FRP and fire detections made by satellites with greater temporal resolution. This included the geostationary sensor SEVIRI and the VIRS aboard TRMM. VIRS's low-inclination orbit (35°) provides observation times which precesses through 24 hours of local time every 23-46 days, depending on latitude, thus capturing the general diurnal trend of fire activity. In addition, high latitude (and thus high overpass frequency) daily observations by MODIS were included. The result was a global FRE product from MODIS at 0.5° spatial and monthly temporal resolution which currently spans from 2001 – 2010 (Figure 1).

The Science and Application of Satellite Based Fire Radiative Energy 185

Fig. 2. Biome regions adopted from the Global Fire Emissions Database (GFED, van der Werf et al., 2006) used for analyzing the relationship between FRE and OCBC aerosol

Fig. 3. Total OCBC (g/m2) emissions estimated from biomass burning for 2003. High source regions include east-central Brazil, central and southern Africa, Southeast Asia, Central

emissions (Vermote et al., 2009).

America, and southeast Russia.

Fig. 1. Estimated annual mean FRE (MJ/m2) from Aqua (2003-2010) and Terra (2001-2002) MODIS. Integrated energy was calculated from FRP (MW) values derived from a Gaussian function using modeled parameters.

Based on their FRE estimates, Ellicott et al. (2009) estimated biomass consumption totals for Africa using FRE-based combustion factors derived by Wooster et al. (2005). Since Wooster et al.'s combustion factor is based on fuels typical for Africa, the estimates were limited to this continent. The results were compared with Roberts & Wooster (2008) who derived estimates of fuels consumed from the SEVIRI sensor. The results showed good agreement for a 12 month comparison of FRE-based estimates of dry matter consumed from SEVIRI (858 Tg DM) and MODIS (700 Tg DM). The GFEDv2 (van der Werf et al., 2006) though, showed nearly a factor of 3 greater fuel consumption for the same time period and area, suggesting that more work needs to be done to characterize the sources and magnitude of errors in these estimates.

Vermote et al. (2009) applied the FRE-approach described above to estimate organic and black carbon (OCBC) aerosols emitted from biomass burning in 2003. The relationship between the estimated FRE and a new MODIS-derived inversion product of daily integrated, biomass burning aerosol emissions was the foundation of their research. The inversion product (Dubovik et al., 2008) was generated from the MODIS fine mode aerosol optical thickness and inverse modeling transport processes adopted from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. The process generated fine mode aerosol sources (locations and intensities) resulting from biomass burning which were then used to derive OCBC estimates. The relationship between FRE and OCBC was analyzed globally within 3 distinct vegetation zones (Figure 2).

The estimated FRE-based OCBC emission in 2003 was 20 Tg and the spatial pattern clearly shows areas of high fire activity and thus OCBC loading (Figure 3). Though lower than the 29.6 Tg and 26.1 Tg estimates made by Generoso (2007) and van der Werf et al. (2006), respectively, the estimate is still within the error bars of both datasets. Nevertheless, the underestimation raises questions about the sources of uncertainty and error in the components used to derive OCBC quantities.

Fig. 1. Estimated annual mean FRE (MJ/m2) from Aqua (2003-2010) and Terra (2001-2002) MODIS. Integrated energy was calculated from FRP (MW) values derived from a Gaussian

Based on their FRE estimates, Ellicott et al. (2009) estimated biomass consumption totals for Africa using FRE-based combustion factors derived by Wooster et al. (2005). Since Wooster et al.'s combustion factor is based on fuels typical for Africa, the estimates were limited to this continent. The results were compared with Roberts & Wooster (2008) who derived estimates of fuels consumed from the SEVIRI sensor. The results showed good agreement for a 12 month comparison of FRE-based estimates of dry matter consumed from SEVIRI (858 Tg DM) and MODIS (700 Tg DM). The GFEDv2 (van der Werf et al., 2006) though, showed nearly a factor of 3 greater fuel consumption for the same time period and area, suggesting that more work needs to be done to characterize the sources and magnitude of

Vermote et al. (2009) applied the FRE-approach described above to estimate organic and black carbon (OCBC) aerosols emitted from biomass burning in 2003. The relationship between the estimated FRE and a new MODIS-derived inversion product of daily integrated, biomass burning aerosol emissions was the foundation of their research. The inversion product (Dubovik et al., 2008) was generated from the MODIS fine mode aerosol optical thickness and inverse modeling transport processes adopted from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. The process generated fine mode aerosol sources (locations and intensities) resulting from biomass burning which were then used to derive OCBC estimates. The relationship between FRE and OCBC was

The estimated FRE-based OCBC emission in 2003 was 20 Tg and the spatial pattern clearly shows areas of high fire activity and thus OCBC loading (Figure 3). Though lower than the 29.6 Tg and 26.1 Tg estimates made by Generoso (2007) and van der Werf et al. (2006), respectively, the estimate is still within the error bars of both datasets. Nevertheless, the underestimation raises questions about the sources of uncertainty and error in the

analyzed globally within 3 distinct vegetation zones (Figure 2).

components used to derive OCBC quantities.

function using modeled parameters.

errors in these estimates.

Fig. 2. Biome regions adopted from the Global Fire Emissions Database (GFED, van der Werf et al., 2006) used for analyzing the relationship between FRE and OCBC aerosol emissions (Vermote et al., 2009).

Fig. 3. Total OCBC (g/m2) emissions estimated from biomass burning for 2003. High source regions include east-central Brazil, central and southern Africa, Southeast Asia, Central America, and southeast Russia.

The Science and Application of Satellite Based Fire Radiative Energy 187

Freeborn et al. (2011) highlighted an issue with the MODIS Collection 5 FRP product. In the C5 FRP the calculation of the instantaneous energy (MW) derived from the brightness temperature includes a multiplication by the pixel area. Although this is fundamentally correct, since energy is measured per unit time and space, the adjustment leads to an overestimate with increasing scan angle because the pixel area grows as the scan moves off nadir. Interestingly, the opposite effect occurs when examining fire pixel counts (i.e. greater

With regards to the application of FRE-based biomass consumption estimates published by Ellicott et al. (2009) and Roberts & Wooster (2008), there is some degree of uncertainty. Although the assumption that a single combustion factor is applicable for all fuel types and conditions (i.e. moisture content) will incur some bias, in general, heat yield does not vary much between fuels (Stott, 2000) and therefore until more research demonstrates otherwise, the two

Atmospheric attenuation is another component generally unaccounted for. In simulations conducted by Ellicott (unpublished), the MODIS FRP may be underestimated by as much as 20% (Figure 4). Similarly, Roberts & Wooster (2008) applied a constant correction factor

FRP Comparisons

0 250 500 750 1000 1250 1500 1750 TOA FRP (MW)

Fig. 4. Comparison of simulated surface and TOA FRP. Radiances were simulated from

randomly generated fire pixel temperature and fractional area components (fire, smoldering, and background). MODIS Aqua profiles were used to provide realistic atmospheric parameters used in the radiative transfer modeling. The 1:1 (dashed) line is

cited FRE-based combustion factors (Freeborn et al., 2008; Wooster, 2005) seem realistic.

number of detections near nadir and decreasing detections with scan angle).

(0.89) to SEVIRI FRP to account for atmospheric transmission loss.

y = 1.205x - 3.345

 = 0.996 *E* = 0.751 RMSE = 80.8 mean bias = -59.8 precision = 54.3

R2

0

250

plotted for reference.

500

750

1000

Surface FRP (MW)

1250

1500

1750
