Dynamical analyses of the time series for the temperature and the humidity

We use a detrended cross-correlation analysis (DCCA) method to investigate the dynamical behaviors of the time series for the temperature and the humidity. With our model, we calculate the cross-correlation coefficient between changes in the times series for the temperature and the humidity. Our simulation is performed for and restricted to eight cities around the Korean peninsula. Particularly, for week intervals, the DCCA cross-correlation coefficient shows the largest positive value for Sokcho while it shows the largest negative value for Gangrung. Particularly, the results are compared to those between different international cities.