Journal
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
Volume 59, Issue 1, Pages 11-23Publisher
SPRINGER
DOI: 10.1007/s00484-014-0817-5
Keywords
Tibetan Plateau; Alpine grassland; MODIS time series; Climate change
Funding
- Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences [2013LDE002]
- International Cooperation and Exchanges NSFC [41120114001]
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The Tibetan Plateau, a unique cold and dry region recognized as the Earth's third pole, is primarily composed of alpine grasslands (> 60 %). While a warming climate in the plateau is being recorded, phenology of alpine grasslands and its climatic dependencies are less investigated. This study tests the feasibility of the frequently observed Moderate Resolution Imaging Spectroradiometer (MODIS) time series (500 m, 8 days) in examining alpine phenology in the plateau. A set of phenological metrics are extracted from the MODIS Normalized Difference Vegetation Index (NDVI) series in each year, 2000-2010. A nonparametric Mann-Kendall trend analysis is performed to find the trends of these phenological metrics, which are then linked to monthly climatic records in the growing season. Opposite trends of phenological change are observed between the east and west of the plateau, with delayed start of season, peak date, and end of season in the west and advanced phenophases in the east. The correlation analysis indicates that precipitation, with a decreasing trend in the west and increasing trend in the east, may serve as the primary driver of the onset and peak dates of greenness. Temperature increases all over the plateau. While the delay of the end of season in the west could be related to higher late-season temperature, its advance in the east needs further investigation in this unique cold region. This study demonstrates that frequent satellite observations are able to extract phenological features of alpine grasslands and to provide spatiotemporally detailed base information for long-term monitoring on the plateau under rapid climate change.
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