Abstract
As a sensitive indicator for climate change, the spring phenology of alpine grassland on the Qinghai–Tibet Plateau (QTP) has received extensive concern over past decade. It has been demonstrated that temperature and precipitation/snowfall play an important role in driving the green-up in alpine grassland. However, the spatial differences in the temperature and snowfall driven mechanism of alpine grassland green-up onset are still not clear. This manuscript establishes a set of process-based models to investigate the climate variables driving spring phenology and their spatial differences. Specifically, using 500 m three-day composite MODIS NDVI datasets from 2000 to 2015, we first estimated the land surface green-up onset (LSGO) of alpine grassland in the QTP. Further, combining with daily air temperature and precipitation datasets from 2000 to 2015, we built up process-based models for LSGO in 86 meteorological stations in the QTP. The optimum models of the stations separating climate drivers spatially suggest that LSGO in grassland is: (1) controlled by temperature in the north, west and south of the QTP, where the precipitation during late winter and spring is less than 20 mm; (2) driven by the combination of temperature and precipitation in the middle, east and southwest regions with higher precipitation and (3) more likely controlled by both temperature and precipitation in snowfall dominant regions, since the snow-melting process has negative effects on the air temperature. The result dictates that snowfall and rainfall should be concerned separately in the improvement of the spring phenology model of the alpine grassland ecosystem.
Highlights
IntroductionThe spatial differences in the temperature and snowfall driven mechanism of alpine grassland green-up onset are still not clear
Geospatial Science Center of Excellence, Department of Geography and Geospatial Sciences, Abstract: As a sensitive indicator for climate change, the spring phenology of alpine grassland on the Qinghai–Tibet Plateau (QTP) has received extensive concern over past decade
The optimum models of the stations separating climate drivers spatially suggest that land surface green-up onset (LSGO) in grassland is: (1) controlled by temperature in the north, west and south of the QTP, where the precipitation during late winter and spring is less than 20 mm; (2) driven by the combination of temperature and precipitation in the middle, east and southwest regions with higher precipitation and (3) more likely controlled by both temperature and precipitation in snowfall dominant regions, since the snow-melting process has negative effects on the air temperature
Summary
The spatial differences in the temperature and snowfall driven mechanism of alpine grassland green-up onset are still not clear This manuscript establishes a set of process-based models to investigate the climate variables driving spring phenology and their spatial differences. The majority of previous research is based on statistical methods to reveal the relationship between the spring phenology and climate variables [3,6,7,10,12,15,16,19,20], process models and process simulations of green-up onset are not well applied, and the climate control mechanism of grassland green-up onset and the spatial difference are not well investigated [11,21]. It has been published maps and institutional affiliations. The ground phenology observations are very limited and are mainly distributed in the margin of the QTP [11,29,30], so that the resultant phenological models only represent the corresponding phenological sites, but they are generally unable to explain detailed spatial patterns of climate controls on alpine grassland spring phenology on a large scale
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