An analysis of mid-summer rainfall occurrence in eastern China and its relationship with large-scale warming using generalized linear models.
INT J CLIMATOL
1826 - 1834.
Daily rainfall occurrence in mid-summer (July and August) in eastern China was analyzed using binomial generalized linear models based on observations at 303 stations during 1961-2007. The models include an intraseasonal variation, previous days' rainfall to represent the Markov chain structure of daily rainfall occurrence, and the south north thermal gradient in eastern China, expressed by a zonal mean temperature difference in the region. to represent a large-scale climate background. The zonal temperature difference between south and north China exhibits a strong effect on the regional pattern of rainfall occurrence at an inter-annual timescale. A weakened thermal gradient in association with large-scale warming can thus be linked with more frequent precipitation in southern China but less in northern China during the last few decades. The zonal temperature difference was also found to modulate the local autocorrelation of rainfall occurrence. In particular. a weakened thermal gradient (1 degrees reduction) leads to an increase of about 10% in the probability of rain following a dry day in southern China. but a decrease of more than 10% in northern China. Consequently, current large-scale warming and hence a decreased zonal temperature difference in eastern China has prolonged (shortened) the duration of dry spells in northern (southern) China by about 20% (15%). Copyright (C) 2009 Royal Meteorological Society
|Title:||An analysis of mid-summer rainfall occurrence in eastern China and its relationship with large-scale warming using generalized linear models|
|Keywords:||generalised linear model, daily rainfall occurrence, temperature, dry and wet spell, large-scale warming, eastern China, PRECIPITATION, CLIMATE, TRENDS|
|UCL classification:||UCL > School of BEAMS > Faculty of Maths and Physical Sciences
UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science
Archive Staff Only