Next Article in Journal
Tropical Species Classification with Structural Traits Using Handheld Laser Scanning Data
Previous Article in Journal
Large-Scale Detection of the Tableland Areas and Erosion-Vulnerable Hotspots on the Chinese Loess Plateau
Article

A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model

CNRM, Université de Toulouse, Météo-France, CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse, France
*
Author to whom correspondence should be addressed.
Academic Editor: Hanlim Lee
Remote Sens. 2022, 14(8), 1949; https://doi.org/10.3390/rs14081949
Received: 6 March 2022 / Revised: 10 April 2022 / Accepted: 12 April 2022 / Published: 18 April 2022
In this study we present a pre-operational forecasting assimilation system of different types of aerosols. This system has been developed within the chemistry-transport model of Météo-France, MOCAGE, and uses the assimilation of the Aerosol Optical Depth (AOD) from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard both Terra and Aqua. It is based on the AOD assimilation system within the MOCAGE model. It operates on a daily basis with a global configuration of 1×1 (longitude × latitude). The motivation of such a development is the capability to predict and anticipate extreme events and their impacts on the air quality and the aviation safety in the case of a huge volcanic eruption. The validation of the pre-operational system outputs has been done in terms of AOD compared against the global AERONET observations within two complete years (January 2018–December 2019). The comparison between both datasets shows that the correlation between the MODIS assimilated outputs and AERONET over the whole period of study is 0.77, whereas the biases and the RMSE (Root Mean Square Error) are 0.006 and 0.135, respectively. The ability of the pre-operational system to predict extreme events in near real time such as the desert dust transport and the propagation of the biomass burning was tested and evaluated. We particularly presented and documented the desert dust outbreak which occurred over Greece in late March 2018 as well as the wildfire event which happened on Australia between July 2019 and February 2020. We only presented these two events, but globally the assimilation chain has shown that it is capable of predicting desert dust events and biomass burning aerosols which happen all over the globe. View Full-Text
Keywords: aerosol; assimilation; air quality; aerosol optical depth; pre-operational system; MODIS aerosol; assimilation; air quality; aerosol optical depth; pre-operational system; MODIS
Show Figures

Graphical abstract

MDPI and ACS Style

El Amraoui, L.; Plu, M.; Guidard, V.; Cornut, F.; Bacles, M. A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model. Remote Sens. 2022, 14, 1949. https://doi.org/10.3390/rs14081949

AMA Style

El Amraoui L, Plu M, Guidard V, Cornut F, Bacles M. A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model. Remote Sensing. 2022; 14(8):1949. https://doi.org/10.3390/rs14081949

Chicago/Turabian Style

El Amraoui, Laaziz, Matthieu Plu, Vincent Guidard, Flavien Cornut, and Mickaël Bacles. 2022. "A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model" Remote Sensing 14, no. 8: 1949. https://doi.org/10.3390/rs14081949

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop