Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

• Published in: Geoscientific Model Development
• Main Authors: Klingmüller, Klaus, Metzger, Swen, Abdelkader, Mohamed, Karydis, Vlassis A., Stenchikov, Georgiy L., Pozzer, Andrea, Lelieveld, Jos
• Format: Text
• Language: English
• Published: 2019
• Subjects: Aerosol Robotic Network
• Online Access: https://doi.org/10.5194/gmd-11-989-2018; https://gmd.copernicus.org/articles/11/989/2018/

To improve the aeolian dust budget calculations with the global ECHAM/MESSy atmospheric chemistry–climate model (EMAC), which combines the Modular Earth Submodel System (MESSy) with the ECMWF/Hamburg (ECHAM) climate model developed at the Max Planck Institute for Meteorology in Hamburg based on a weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), we have implemented new input data and updates of the emission scheme. The data set comprises land cover classification, vegetation, clay fraction and topography. It is based on up-to-date observations, which are crucial to account for the rapid changes of deserts and semi-arid regions in recent decades. The new Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover and vegetation data are time dependent, and the effect of long-term trends and variability of the relevant parameters is therefore considered by the emission scheme. All input data have a spatial resolution of at least 0.1 ∘ compared to 1 ∘ in the previous version, equipping the model for high-resolution simulations. We validate the updates by comparing the aerosol optical depth (AOD) at 550 nm wavelength from a 1-year simulation at T106 (about 1.1 ∘ ) resolution with Aerosol Robotic Network (AERONET) and MODIS observations, the 10 µ m dust AOD (DAOD) with Infrared Atmospheric Sounding Interferometer (IASI) retrievals, and dust concentration and deposition results with observations from the Aerosol Comparisons between Observations and Models (AeroCom) dust benchmark data set. The update significantly improves agreement with the observations and is therefore recommended to be used in future simulations.