Northern Annular Mode Effects on the Land Surface Phenologies of Northern Eurasia

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annular mode, vegetation, arctic oscillation, climate variability, precipitation


Land surface phenology (LSP) is the spatiotemporal development of the vegetated land surface as revealed by synoptic sensors. Modeling LSP across northern Eurasia reveals the magnitude, significance, and spatial pattern of the influence of the northern annular mode. Here the authors fit simple LSP models to two normalized difference vegetation index (NDVI) datasets and calculate the Spearman rank correlations to link the start of the observed growing season (SOS) and the timing of the peak NDVI with the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) indices. The relationships between the northern annular mode and weather station data, accumulated precipitation derived from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, accumulated growing degree-days (AGDDs) derived from the NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) reanalysis, and the number of snow days from the National Snow and Ice Data Center are investigated.

The analyses confirm strong relationships between the temporal behavior of temperature and precipitation and large-scale climatic variability across Eurasia. The authors find widespread influence of the northern annular mode (NAM) on the land surface phenologies across northern Eurasia affecting 200–300 Mha. The tundra ecoregions were especially impacted with significant results for about a quarter of the biome. The influence of the AO was also extensive (>130 Mha) for the boreal forests. The AO appears to affect the Asian part of northern Eurasia more strongly than the NAO, especially for the NDVI peak position as a function of AGDD. Significant responses of vegetation timing to NAO and AO in northeastern Russia have not been as well documented as the seasonal advancement in Europe. The two Advanced Very High Resolution Radiometer NDVI datasets yield fields of LSP model parameter estimates that are more similar in dates of peak position than in dates for SOS and more similar for AO than for NAO. As a result, the authors conclude that peak position appears to be a more robust characteristic of land surface phenology than SOS to link vegetation dynamics to variability and change in regional and global climates.

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Journal of Climate





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American Meteorological Society


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