Tuesday, 24 January 2017
4E (Washington State Convention Center )
Africa south of the Sahara Desert contributes well over 50% of the global annual carbon emissions from open biomass burning (Van der Werf et al., 2010). The fires responsible for this biomass-burning phenomenon are regularly observed from a variety of satellite sensors, such as AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate-resolution imaging spectroradiometer), and VIIRS (Visible Infrared Imaging Radiometer Suite). The frequency of fire detection per unit land area in the African region is about an order of magnitude higher than that of North America and five times higher than for South America (Ichoku et al., 2008). It is important to understand the variability in hydrological fluxes due to fires to improve our understanding of hydrological processes, ecosystem functions and decisions as it affects the partitioning of energy as well evapotranspiration. The change in albedo due to bio mass burning has been estimated in a previous study, (Gatebe et al., 2014) over different land cover types in the Africa using MODIS time series for the period of 2003–11. However, questions still remain over the magnitude and duration of the changes in surface characteristics that are capable of inducing noticeable effects. The development of a comprehensive approach to implement and model the impact of albedo darkening due to burning in regional climate simulations has been scarce. Such an approach would allow a broader understanding of the impact of burned areas on hydrology, which is challenging to accomplish via observation studies alone. To capture the effects of albedo darkening on the land surface, NASA's Catchment land Surface Model coupled with NASA's Land Information System (LIS) is being used to simulate some of the fire-induced anomalies in the surface albedo. We also compare the estimated soil moisture based on new and pre-existing baseline parameterization schemes to the remotely-sensed observations obtained from satellite-based soil moisture observations and land surface temperatures (LST) from the Advanced Microwave Scanning Radiometer (AMSR-E) instrument and MODIS, respectively. The root mean square error (RMSE) and bias are seen to decrease appreciably with the introduction of the fire-induced surface albedo change parameterization. Soil moisture is seen to decrease following a fire event and the effect was shown to last for the next 2-3 years and finally sets to recover.
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