1. Composite patterns of DJF U200 anomalies for (a) strong EAJS, (b) weak EAJS, (c) El Niño and (d) La Niña.

2. DJF correlation between the EAJS and surface air temperature (a) and that between the EAJS and CMAP precipitation (b).

3. Difference in the SON SST before the strong and weak DJF EAJS.
Difference in DJF SST (°C) between strong and weak EAJS.

4. Difference in the std dev of the DJF mean surface air temperatures; (a), (b) are the influence of snow variability; (c), (d) are the influence of SST variability. Contour interval is 0.3 K. Dashed contours are for negative values.

5. Difference in the std dev of the DJF mean 200-mb heights; (a), (b) are the influence of snow variability; (c), (d) are the influence of SST variability. Contour interval is 0.3 K. Dashed contours are for negative values.

6. The influence of snow variability was confined to the lower troposphere, and little change in the interannual variability of upper-tropospheric circulation, for example, 200-hPa heights, occurred. This bottom-up vertical structure of the influence of snow on the atmospheric variability was in contrast to the top-down influence of tropical SST variability on the extra-tropical flow.

7. Schematic diagram showing the air–sea interaction in the western North Pacific that maintains the Philippine Sea anticyclonic anomalies and associated negative SST anomalies in the western North Pacific. The double arrows denote the mean trade winds. The heavy lines with black arrows represent the anomalous winds. The long (short) dashed lines indicate contours of positive (negative) SST anomalies..

10. Once the monsoon is active, the correlation with ENSO is very low.

11. Chapter 6: Interannual Variability of the Asian Monsoon

12. Dipole structure
Dipole structure

13. Webster-Yang index summer monsoon index

15. Concept of monsoon year for the study of Asian climate

17. Biennial oscillation → monsoon anomalies reverse from one summer to the next

19. Fig.6.4