Identifying Biases in Dust Source Functions
Abstract
The Sahara is the largest desert in the world and accounts for more than 50% of global dust emission. However, it is difficult to identify dust source regions as the Sahara is vastly uninhabited. In order to model North African dust, previous works have used satellite data to construct so-called dust source functions. Here we examine such dust source function using output from multi-year runs with the Weather Research and Forecasting with Chemistry (WRF-Chem) model. We find that dust source functions based on satellite data overestimate DOD in the Sahel and the western Sahara region. To eliminate the biases of the dust source function due to advection, we develop a new source function using DOD in the lowest 1 km from the model. This work suggests that dust source functions constructed with satellite retrievlas of optical depth may overestimate dust emission in the downwind regions and DOD may not be a good proxy for the source function.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A33F2419E
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0365 Troposphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSES;
- 1631 Land/atmosphere interactions;
- GLOBAL CHANGE