15-year variability of desert dust optical depth on global and regional scales

Abstract

This study aims to investigate global, regional and seasonal temporal dust changes as well as the effect of dust particles on total aerosol loading using the ModIs Dust AeroSol (MIDAS) fine-resolution dataset. MIDAS delivers dust optical depth (DOD) at fine spatial resolution (0.1∘×0.1∘) spanning from 2003 to 2017. Within this study period, the dust burden increased across the central Sahara (up to 0.023 yr−1) and Arabian Peninsula (up to 0.024 yr−1). Both regions observed their highest seasonal trends in summer (up to 0.031 yr−1). On the other hand, declining DOD trends are encountered in the western (down to −0.015 yr−1) and eastern (down to −0.023 yr−1) Sahara, the Bodélé Depression (down to −0.021 yr−1), the Thar (down to −0.017 yr−1) and Gobi (down to −0.011 yr−1) deserts, and the Mediterranean Basin (down to −0.009 yr−1). In spring, the most negative seasonal trends are recorded in the Bodélé Depression (down to −0.038 yr−1) and Gobi Desert (down to −0.023 yr−1), whereas they are in the western (down to −0.028 yr−1) and the eastern Sahara (down to −0.020 yr−1) and the Thar Desert (down to −0.047 yr−1) in summer. Over the western and eastern sector of the Mediterranean Basin, the most negative seasonal trends are computed at summer (down to −0.010 yr−1) and spring (down to −0.006 yr−1), respectively. The effect of DOD on the total aerosol optical depth (AOD) change is determined by calculating the DOD-to-AOD trend ratio. Over the Sahara the median ratio values range from 0.83 to 0.95, whereas in other dust-affected areas (Arabian Peninsula, southern Mediterranean, Thar and Gobi deserts) the ratio value is approximately 0.6. In addition, a comprehensive analysis of the factors affecting the sign, the magnitude and the statistical significance of the calculated trends is conducted. Firstly, the implications of the implementation of the geometric mean instead of the arithmetic mean for trend calculations are discussed, revealing that the arithmetic-based trends tend to overestimate compared to the geometric-based trends over both land and ocean. Secondly, an analysis interpreting the differences in trend calculations under different spatial resolutions (fine and coarse) and time intervals is conducted.