Assessment of the Met Office dust forecast model using observations from the GERBILS campaign. (Special Issue: Geostationary earth radiation budget intercomparison of longwave and shortwave radiation (GERBILS).)

摘要

This paper uses aircraft, ground-based and satellite observations to assess the performance of Met Office dust forecasts during the Geostationary Earth Radiation Budget Intercomparison of Long-wave and Short-wave radiation (GERBILS) campaign. The dust forecasts were produced from a 20 km resolution limited-area numerical weather prediction configuration of the Met Office Unified Model, based over North Africa. Dust uplift was modelled using two modified versions of the Woodward (2001) dust parametrization scheme. The model produced widespread dust over the Sahara desert in response to synoptically driven strong wind events. The modelled aerosol size distribution and short-wave optical properties compared well with aircraft in situ measurements and retrievals from the Aerosol Robotic Network (AERONET). Better size distributions and extinction coefficients were achieved by fixing the emitted dust size distribution rather than attempting to predict this dynamically. The two versions performed similarly compared to observations of other variables. The interaction of dust with short-wave and long-wave radiation compared well with aircraft observations when scaled to allow for local differences in Aerosol Optical Depth (AOD). AODs were on average 50-100% too high over south-western parts of the Sahara but 20-50% too low over the Sahel when compared to AERONET sites, aircraft profile estimates and satellite retrieval products. This implicated excessive dust emission over central parts of the Sahara and insufficient dust emissions from the Bodele depression and semi-arid regions on the southern border of the Sahara. These biases were linked to potential errors in wind speed, soil texture, soil moisture and vegetation, and possible limitations in the dust parametrization, such as the lack of an observationally constrained or geomorphologically based preferential source term.