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A. D. McGuire, J. E. Walsh, J. S. Kimball, J. S. Clein, S. E. Euskirchen, S. Drobot, U. C. Herzfeld, J. Maslanik, R. B. Lammers, M. A. Rawlins, C. J. Vorosmarty, T. S. Rupp, W. Wu, and M. Calef

influencing global water and energy balance ( Curry et al. 1996 ; Chapin et al. 2000 ; McGuire and Chapin 2006 ; McGuire et al. 2003 ; McGuire et al. 2004 ; McGuire et al. 2006 ; McGuire et al. 2007 ). Responses of high-latitude terrestrial ecosystems to global change have the potential to affect the Earth system through changes in 1) water and energy exchange with the atmosphere, 2) the exchange of radiatively active gases with the atmosphere, and 3) the delivery of freshwater to the Arctic Ocean

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Ute C. Herzfeld, Sheldon Drobot, Wanli Wu, Charles Fowler, and James Maslanik

southern area boundary, while the central areas have the least interannual variability and lowest F -values. Figures 2c and 2d , in comparison with Figures 2a and 2b , show that January precipitation, according to ERA-40 reanalysis data, shows little variability in most of the study area ( F < 0.5), with the exception of coastal areas (0.15 < F < 0.2). Over the entire region, the similarity values for temperature compare to those for January precipitation. In contrast, summer (July) precipitation

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Sheldon Drobot, James Maslanik, Ute Christina Herzfeld, Charles Fowler, and Wanli Wu

other dataset (MM5, CRU, MW, and ERA-40) have an overall worse similarity, with only small areas of similarity better than 0.1 and maximal values above 0.35 or 0.4. Areas of best agreement tend to occur over the southern coastal ranges in southeast Alaska, and in an area north of the Gulf of Alaska, whereas areas of poor similarity are found in the northern-central inland regions of the study area and along its northern limit; in particular, problematic areas in temperature and in precipitation data

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J. S. Kimball, K. C. McDonald, and M. Zhao

SSM/I time series to determine the spatial pattern and annual variability of the primary springtime thaw event for Alaska and northwest Canada from 1988 to 2000. We also applied a biome-specific production efficiency model (PEM) driven by daily surface meteorological inputs from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis ( Kistler et al. 2001 ) and National Oceanic and Atmospheric Administration (NOAA) Advanced Very High

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Joy Clein, A. David McGuire, Eugenie S. Euskirchen, and Monika Calef

decreases for the southern part of the border. Spatially averaged annual NEP from 1980 to 2000 increases significantly in the CRU simulation, and the increase in the NCEP1 simulation is marginally significant ( Figure 4e ; Table 3 ). The increases in NEP in the CRU simulation is associated with a nonsignificant increase in NPP coupled with a significant decrease in simulated R h over the time period ( Table 3 ). In contrast, the increase in NEP in the NCEP1 simulation is associated with a marginally

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