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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-116
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-116
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 02 May 2019

Submitted as: development and technical paper | 02 May 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Geoscientific Model Development (GMD).

Modelling African biomass burning emissions and the effect of spatial resolution

Dave van Wees and Guido R. van der Werf Dave van Wees and Guido R. van der Werf
  • Department of Earth Sciences, Vrije Universiteit, Amsterdam, 1081 HV, the Netherlands

Abstract. Large-scale fire emission estimates may be influenced by the spatial resolution of the model and input datasets used. Especially in areas with relatively heterogeneous land cover, a coarse model resolution might lead to substantial errors in estimates. In this paper, we developed a model using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations of burned area and vegetation characteristics to study the impact of spatial resolution on modelled fire emission estimates. We estimated fire emissions for sub-Saharan Africa at 500-meter spatial resolution (native MODIS burned area) for the 2002–2017 period, using a simplified version of the Global Fire Emissions Database (GFED) modelling framework, and compared this to model runs at a range of coarser resolutions (0.050°, 0.125°, 0.250°). We estimated fire emissions of 0.68 PgC yr−1 at 500-meter resolution and 0.82 PgC yr−1 at 0.25° resolution; a difference of 24 %. At 0.25° resolution, our model results were relatively similar to GFED4, which also runs at 0.25° resolution, whereas our 500-meter estimates were substantially lower. We found that lower emissions at finer resolutions are mainly the result of reduced representation errors when comparing modelled estimates of fuel load and consumption to field measurements, as part of the model calibration. Additional errors stem from the model simulation at coarse resolution and lead to an additional 0.02 PgC yr−1 difference in estimates. These errors exist due to the aggregation of quantitative and qualitative model input data; the average- or majority- aggregated values are propagated in the coarse resolution simulation and affect the model parameterization and the final result. We identified at least three error mechanisms responsible for the differences in estimates between 500-meter and 0.25° resolution simulations, besides those stemming from representation errors in the calibration process, namely: 1. biome misclassification leading to errors in parameterization, 2. errors due to the averaging of input data and the associated reduction in variability, and 3. a temporal mechanism related to the aggregation of burned area in particular. Even though these mechanisms largely neutralized each other and only modestly affect estimates at a continental scale, they lead to substantial error at regional scales with deviations up to a factor 4, and may affect large-scale estimates differently for other continents. These findings could prove valuable in improving coarse resolution models and suggest the need for increased spatial resolution in global fire emission models.

Dave van Wees and Guido R. van der Werf
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Dave van Wees and Guido R. van der Werf
Dave van Wees and Guido R. van der Werf
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Short summary
For this paper, a novel high spatial resolution fire emission model based on the Global Fire Emissions Database (GFED) modelling framework was developed, and compared to a coarser resolution version of the same model. Our findings highlight the importance of fine spatial resolution when modelling global-scale fire emissions, especially considering the comparison of model pixels to individual field measurements and the model representation of heterogeneity in the landscape.
For this paper, a novel high spatial resolution fire emission model based on the Global Fire...
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