HR: 11:20h
AN: B42A-04    [Abstracts]
TI: The Influence of the North Atlantic Oscillation on the Land Surface Phenologies of the Northern Hemisphere
AU: * de Beurs, K M
EM: kdebeurs@calmit.unl.edu
AF: Center for Advanced Land Management Information Technologies (CALMIT) School of Natural Resources University of Nebraska Lincoln, 102E. Nebraska Hall, Lincoln, NE 68588-0517 United States
AU: Henebry, G M
EM: geoffrey.henebry@sdstate.edu
AF: Geographic Information Science Center of Excellence (GIScCE) South Dakota State University, 1021 Medary Ave, Wecota Hall 1st floor, Box 506B, Brookings, SD 57007 United States
AB: The North Atlantic Oscillation (NAO) is considered the most prominent and recurrent pattern of atmospheric variability over the middle and high latitudes of the Northern Hemisphere. Significant correlations have been shown between surface air temperature and NAO variability across wide regions of North America and Eurasia. However, the study of the ecological impacts of the NAO is still relatively new. Land surface phenology (LSP) is the study of the spatio-temporal patterns of the vegetated land surface as observed by synoptic sensors at spatial resolutions and extents relevant to meteorological processes in the atmospheric boundary layer. Many studies demonstrate the NAO effect on the land surface by correlation patterns based on temperature. Since LSP is influenced not only by seasonal patterns of temperature and precipitation but also by anthropogenic influences, we do not expect the NAO influences on LSP to resemble temperature patterns. Furthermore, increases in temperature do not result in similar phenological changes in all regions and depend on the vegetation type. Here we examined the magnitude, significance, and spatial pattern of the influences of the NAO and the related Arctic Oscillation (AO) on LSP across the Northern Hemisphere. We determined LSPs using the Pathfinder AVHRR Land (PAL) dataset, which consists of maximum Normalized Difference Vegetation Index (NDVI) 10-day composites at 8 km spatial resolution. Daily minimum and maximum temperatures were extracted from the NCEP/NCAR Reanalysis Project to generate daily growing degree-days (base 0 °C) as 10-day composites (GDD10) and as seasonal accumulations (AGDD). We have previously established that quadratic models fit well the phenology of herbaceous vegetation in temperate climates, both croplands and rangelands. Woody vegetation at higher latitudes follows a more rapid green-up and stays green for a relatively long period prior to senescence; thus, a piece of a parabola does not fit well this seasonal plateau in NDVI. We found that the shape of a nonlinear spherical model significantly improved the fit for the first part of the growing season. For each NCEP Reanalysis grid cell we first fit the quadratic and spherical models separately to all available years. Based on model fit, we determined whether the LSP in a particular grid cell was better represented with a quadratic or a spherical form. We then fitted either a quadratic or a spherical model for each of nine years separately (1985-88 and 1995-2000). Based on the selected models we calculated three characteristics of LSP: (1) the NDVI at the start of the observed growing season; (2) the maximum NDVI during the growing season; and (3) the timing of the peak NDVI in AGDD (°C) and in days. We then calculated Spearman's rank correlations to compare the LSP with the observed NAO and AO indices. From the three phenological characteristics the peak time revealed the highest significant correlations with the NAO and AO indices. We found large areas with significant positive correlation between both the NAO and AO indices and the timing of the peak NDVI. We also found a few smaller regions with significant correlations between the climate modes and the peak height. The spatial pattern of the correlation was different for NAO and AO. We concluded that NAO and AO climate modes may be partially responsible for the observed changes in greenness over the northern hemisphere.
DE: 0429 Climate dynamics (1620)
DE: 0438 Diel, seasonal, and annual cycles (4227)
DE: 0439 Ecosystems, structure and dynamics (4815)
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: Fall Meeting 2005