Fig. 4: Variations in dust emissions and the contributions of drivers under the Coupled Model Intercomparison Project Phase 6 (CMIP6) scenarios.
From: Vegetation greening drives long-term dust mitigation in Eastern Asia
a–c The dust-emission time series in the CMIP6 scenarios obtained from two types of experiments (the first and second rows of columns; Supplementary Table 1), and the contributions of vegetation cover (FVC) to dust calculated from Experiment 2 (the third row of columns). The thick line represents the locally estimated scatterplot smoothing (LOESS) smoothing. The bold horizontal lines flanking the columns represent the means of dust emission in the preceding and succeeding two decades, serving as indicators of the magnitudes of the dust anomalies. d Relationships between drivers and predicted dust emission. Partial correlation analysis (Par Corr) was used to calculate the partial correlation coefficient between each factor and the original model output, controlling for the other two factors. Pearson-1 represents the Pearson correlation between the factors and the original model output. Pearson-2 is similar to Pearson-1, but the simulated dust emission was subjected to a twenty-year window Savitzky-Golay filter to represent its trend component. The dashed boxes represent the dominant factors driving the two types of dust variations. * P < 0.05; ** P < 0.01; *** P < 0.001.
