This study investigates the dynamic relationship between particulate matter with less than 10μm aerodynamic diameter (PM10) and meteorological parameters (i.e., solar radiation (SR), air temperature (T), wind speed and direction (U and D), rainfall (R), relative humidity (Rh), and visibility (V)), while using time-dependent intrinsic correlation (TDIC) analysis based on complete ensemble empirical mode decomposition with adaptive noise. The TDIC analysis captured both negative and positive correlations between PM10 and the meteorological parameters at all examined time scales; nevertheless, as high PM10 concentrations were mainly related to synoptic scale sources, the correlations were more significant for a mean time period ranging from 1 to 7 d. In the high dust season (i.e., from May to September), results showed that dust outbreaks have a major impact on climate. Trends differ among meteorological parameters: At daily scale, positive (negative) correlations were found between PM10 and SR, T, U, and V (R and Rh), while correlation strength may change with increasing time scale. In addition, transition periods between the low (i.e., from October to April) and high dust season, but also before and after the passages of rainy events, were identified by the TDIC analysis. The impact of the largest African dust storm in the last 50 years on climate has also been identified locally at a time scale between 1 and 4 d, which corresponds to the duration of its passage.