PhD Defense : Mohammad EL AABARIBAOUNE : “Assimilation of IASI radiances in a chemistry transport model for ozone and desert dust monitoring”
Youtube Link : https://youtu.be/Bsx2TSSeP4s
Ozone and desert dust play a crucial role in our atmosphere requiring continuous monitoring. This monitoring is done through observations and modeling. These two tools are combined by an approach called ‘data assimilation’ aiming to find an optimal trade-off between measurements and forecasts, which best describes the state of the monitored species. Data assimilation systems use products derived from satellite measurements in the infrared spectral band to improve model-based ozone forecasts. Direct assimilation of satellite radiances has been adopted recently for ozone to overcome some of the issues encountered when using retrievals. The objective of this work is to improve the assimilation of IASI (Infrared Atmospheric Sounding Interferometer) radiances for ozone and then use them to jointly correct ozone and desert dust, in order to take advantage of the sensitivity of the spectrum measured by IASI to both species. We used the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemistry-transport model, a 3D-VAR assimilation scheme and 280 channels of the IASI instrument located between 980 and 1100 cm-1, already used for ozone and desert dust retrieval in previous studies. We first investigated the observation errors and their impact on the ozone analyses. We found that updating the observation errors significantly improved the ozone assimilation results over a period of one month when compared to measurements obtained by independent instruments. Then, we computed O3 analyses over a period of one year in order to evaluate the capacity of IASI radiances assimilation to reproduce the seasonal variability of tropospheric ozone. A validation with reanalyses and simulations using more detailed chemical schemes than ours has shown that infrared measurements bring an added value for ozone analyses also over long periods. The second part of this work was devoted to the inclusion of desert dust in the radiative transfer model and in the control variable, thus allowing the correction of the modeled ozone dust. The optical thickness analyses of the total aerosol AOD (Aerosols Optical Depth) and the total desert dust columns were evaluated. The optical thickness was compared with independent instruments (MODIS and AERONET) showing a significant and positive impact of the infrared assimilation on the aerosol fields. In summary, through this work, we have improved existing ozone analyses and produced for the first time desert dust analyses by assimilating satellite observations in the infrared.