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

constraints to plant growth ( Kimball et al. 2006 ). The objective of the current investigation is to clarify the role of spring thaw timing in determining annual vegetation productivity, and whether a recent advance in the northern seasonal thaw cycle is sufficient to account for the sign and magnitude of the estimated positive vegetation productivity trend for the western Arctic. To accomplish this objective we conducted a temporal change classification of daily terrestrial microwave emissions from the

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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

considered for use in this study were datasets based on global-scale reanalyses, global climate datasets based on “interpolation” of surface observations, and a prognostic climate dataset based on a regional simulation of a mesoscale climate model. We organized three global reanalysis datasets at 25 km × 25 km resolution for the WALE region: 1) the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis project ( Kalnay et al. 1996 ), which we refer

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

: Passive microwave data from the AVHRR Polar Pathfinder Mission of the Television Infrared Observation Satellite (TIROS) satellite are utilized as proxies for temperature data. Temperature data are calculated from satellite observations of pseudo-clear-sky temperatures following methods described by Fowler et al. ( Folwer et al. 2002 ) and are stored with reference to EASE grid. Polar Pathfinder (PATH, APP) data are utilized here in the form identified as “PCT data,” which are derived using the latest

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

CO 2 from observations averaged from the Mauna Loa and South Pole monitoring stations ( Keeling et al. 1995 , updated). 2.6. Simulation protocol The TEM simulations were initialized by running the model to equilibrium (NEP = 0 ± 1 g C m −2 yr −1 ) using the mean monthly climate for each climate driver dataset (e.g., mean monthly NCEP1 temperature data for 1980–2000), and then running through five cycles of the climate dataset (i.e., five cycles of 1980–2000 for the simulation driven by NCEP1

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J. S. Kimball, M. Zhao, A. D. McGuire, F. A. Heinsch, J. Clein, M. Calef, W. M. Jolly, S. Kang, S. E. Euskirchen, K. C. McDonald, and S. W. Running

annual variability and regional trends in vegetation productivity for the WALE domain, and the primary mechanisms driving observed changes over the 19-yr (1982–2000) study period. To accomplish these objectives, we apply a biome-specific Production Efficiency Model (PEM) driven by daily surface meteorology and satellite remote sensing observations of photosynthetic leaf area. We also conduct prognostic regional simulations of terrestrial carbon budgets for the same period using two ecosystem process

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