Modeling greenup date of dominant grass species in the Inner Mongolian Grassland using air temperature and precipitation data.

This work was undertaken to examine the combined effect of air temperature and precipitation during late winter and early spring on modeling greenup date of grass species in the Inner Mongolian Grassland. We used the traditional thermal time model and developed two revised thermal time models coupling air temperature and precipitation to simulate greenup date of three dominant grass species at six stations from 1983 to 2009. Results show that climatic controls on greenup date of grass species were location-specific. The revised thermal time models coupling air temperature and precipitation show higher simulation parsimony and efficiency than the traditional thermal time model for five of 11 data sets at Bayartuhushuo, Xilinhot and Xianghuangqi, whereas the traditional thermal time model indicates higher simulation parsimony and efficiency than the revised thermal time models coupling air temperature and precipitation for the other six data sets at E'ergunayouqi, Ewenkeqi and Chaharyouyihouqi. The mean root mean square error of the 11 models is 4.9 days. Moreover, the influence of late winter and early spring precipitation on greenup date seems to be stronger at stations with scarce precipitation than at stations with relatively abundant precipitation. From the mechanism perspectives, accumulated late winter and early spring precipitation may play a more important role as the precondition of forcing temperature than as the supplementary condition of forcing temperature in triggering greenup. Our findings suggest that predicting responses of grass phenology to global climate change should consider both thermal and moisture scenarios in some semiarid and arid areas.