Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST

• Published in: Journal of Geophysical Research
• Main Authors: Menut, Laurent, Chiapello, Isabelle, Moulin, Cyril
• Other Authors: Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2009
• Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces; environment; Aerosol Robotic Network
• Online Access: https://hal.science/hal-03197734; https://hal.science/hal-03197734/document; https://hal.science/hal-03197734/file/2008JD010523.pdf; https://doi.org/10.1029/2008JD010523

International audience The predictability of northern Africa dust events is assessed using daily numerical forecast simulations for the next 3 days. The dust concentration fields, modeled with the CHIMERE-DUST model, were first evaluated by comparison with both Aerosol Robotic Network (AERONET) surface data and Ozone Monitoring Instrument (OMI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite measurements. The accuracy and spread between measurements and simulations are discussed for the first short observation period of the African Monsoon Multidisciplinary Analysis (AMMA) experiment in western Africa, between January and March 2006. The predictability of dust events was then estimated by comparing model results for different leads in a forecast mode. The model performance was evaluated with respect to its capability to forecast the surface wind speed, which is the key process for dust emission, and the transport of mineral dust near source regions and toward remote areas. It is shown that forecast emissions can vary up to 80% (close to the sources) but that the variability on forecasted dust concentrations and optical thicknesses do not exceed 40% and 20%.