ALBERT

Description: Accurate near real time fire emissions estimates are required for air quality forecasts. To date, most approaches are based on satellite-derived estimates of fire radiative power (FRP), which can be converted to fire radiative energy (FRE) which is directly related to fire emissions. Uncertainties in these FRE estimations are often substantial. This is for a large part because the most often used low-Earth orbit satellite-based instruments like the MODerate-resolution Imaging Spectroradiometer (MODIS) have a relatively poor sampling of the usually pronounced fire diurnal cycle. In this paper we explore the spatial variation of this fire diurnal cycle and its drivers. Specifically, we assess how representing the fire diurnal cycle affects FRP and FRE estimations when using data collected at MODIS overpasses. Using data assimilation we explored three different methods to estimate hourly FRE, based on an incremental sophistication of parameterizing the fire diurnal cycle. We sampled data from the geostationary Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) at MODIS detection opportunities to drive the three approaches. The full SEVIRI time-series, providing full coverage of the diurnal cycle, were used to evaluate the results. Our study period comprised three years (2010–2012), and we focussed on Africa and the Mediterranean basin to avoid the use of potentially lower quality SEVIRI data obtained at very far off-nadir view angles. We found that the fire diurnal cycle varies substantially over the study region, and depends on both fuel and weather conditions. For example, more "intense" fires characterized by a fire diurnal cycle with high peak fire activity, long duration over the day, and with nighttime fire activity are most common in areas of large fire size (i.e., large burned area per fire event). These areas are most prevalent in relatively arid regions. Ignoring the fire diurnal cycle as done currently in some approaches caused structural errors, while generally overestimating FRE. Including information on the climatology of the fire diurnal cycle provided the most promising avenue to improve FRE estimations. This approach also improved the performance on relatively high spatiotemporal resolutions, although only when aggregating model results to coarser spatial and/or temporal scale good correlation was found with the full SEVIRI hourly reference dataset. In general model performance was best in areas of frequent fire and low errors of omission. We recommend the use of regionally varying fire diurnal cycle information within the Global Fire Assimilation System (GFAS) used in the Copernicus Atmosphere Monitoring Services, which will improve FRE estimates and may allow for further reconciliation of biomass burning emission estimates from different inventories.