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Original Articles

European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset

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Pages 3303-3330 | Received 09 Sep 2002, Accepted 26 May 2003, Published online: 04 Jun 2010
 

Abstract

Vegetation distribution and state have been measured since 1981 by the AVHRR (Advanced Very High Resolution Radiometer) instrument through satellite remote sensing. In this study a correction method is applied to the Pathfinder NDVI (Normalized Difference Vegetation Index) data to create a continuous European vegetation phenology dataset of a 10-day temporal and 0.1° spatial resolution; additionally, land surface parameters for use in biosphere–atmosphere modelling are derived. The analysis of time-series from this dataset reveals, for the years 1982–2001, strong seasonal and interannual variability in European land surface vegetation state. Phenological metrics indicate a late and short growing season for the years 1985–1987, in addition to early and prolonged activity in the years 1989, 1990, 1994 and 1995. These variations are in close agreement with findings from phenological measurements at the surface; spring phenology is also shown to correlate particularly well with anomalies in winter temperature and winter North Atlantic Oscillation (NAO) index. Nevertheless, phenological metrics, which display considerable regional differences, could only be determined for vegetation with a seasonal behaviour. Trends in the phenological phases reveal a general shift to earlier (−0.54 days year−1) and prolonged (0.96 days year−1) growing periods which are statistically significant, especially for central Europe.

Acknowledgments

The funding for this study was provided by the National Centre of Competence in Research on climate variability, predictability, and climate risks (NCCR) funded by the Swiss National Science Foundation (NSF). The authors would like to first express their thanks for the support and suggestions of Professor Christoph Schär.

We would like to thank Sietse O. Los, Jim Collatz and Jim Tucker for discussions and data and would like to acknowledge ETH and Code 912/913 at Goddard Space Flight Center for being able to use their computing resources, which were essential for the successful completion of this project. Special thanks go to Scott Denning, Kevin Schaefer and Ian Baker from CSU for providing access to the mapper code used to process the derived biophysical land surface parameters.

The Land Pathfinder NDVI data used in this study were produced through funding from the Earth Observing System Pathfinder Program of NASA's Mission to Planet Earth in cooperation with the National Oceanic and Atmospheric Administration. The data were provided by the Earth Observing System Data and Information System (EOSDIS), Distributed Active Archive Center at Goddard Space Flight Center, which archives, manages and distributes this dataset.

We highly encourage the use of the presented biophysical land surface parameters as a climatology (1982–2001) or as a 20-year time-series. This dataset is designed for and capable of enhancing existing LSMs with a boundary condition allowing the representation of spatial and temporal dynamics of land surface vegetation. The parameter set is available from the authors upon request.

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