Search Results

You are looking at 1 - 9 of 9 items for :

  • Western Arctic Linkage Experiment (WALE) x
  • User-accessible content x
Clear All
T. Scott Rupp, Xi Chen, Mark Olson, and A. David McGuire

-parameter regression analysis similar to that used by Kasischke et al. ( Kasischke et al. 2002) . We stratified interior Alaska by ecoregion ( Gallant et al. 1995 ), growing-season climate ( Fleming et al. 2000 ), and fire frequency ( Kasischke et al. 2002 ). We assumed the Canadian portion of our domain to be similar and therefore did not incorporate region-specific data for the analysis. Fire frequencies and climate variables were computed directly (and respectively) from the Bureau of Land Management, Alaska

Full access
M. A. Rawlins, S. Frolking, R. B. Lammers, and C. J. Vörösmarty

temporal dynamics of arctic water fluxes. Deficiencies leading to biases in model input data can significantly impact the usefulness of the data for climate change research and other efforts to solve environmental problems. In a sensitivity experiment, an arctic hydrological model was more sensitive to changes in daily precipitation than in the prescribed land surface parameterizations ( Rawlins et al. 2003 ). Uncertainties in precipitation data used to drive hydrological models are a particular

Full access
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

simulation models. Therefore, the objectives of WALE were to evaluate uncertainties among alternative driving datasets for the region, evaluate uncertainties among applications of different models using common driving data, and evaluate uncertainties in hydrologic and ecosystem models driven with different datasets. In this paper, we provide an overview of WALE and a synthesis of results from the papers in the WALE special theme of Earth Interactions . Design of WALE High-latitude terrestrial ecosystems

Full access
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

of these biomes ( Saugier et al. 2001 ). We defined this area in terms of nodes of the National Snow and Ice Data Center (NSIDC) north polar Equal-Area Scalable Earth (EASE) grid ( Armstrong and Brodzik 1995 ). The domain spans a latitudinal range from 56.19° to 71.24°N, while land areas within the region comprise 3511 grid cells with nominal 25 km × 25 km resolution and a total representative area of approximately 2.2 million km 2 . We used a National Oceanic and Atmospheric Administration (NOAA

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

× 25 km resolution and a total representative area of approximately 2.2 million km 2 . We used a NOAA AVHRR–based global land cover classification to define major biomes for PEM calculations within the study region ( Myneni et al. 1997b ; DeFries et al. 1998 ). Boreal forests and tundra are the major biomes within the region and represent approximately 52% and 30% of the region, respectively. The rest of the domain is composed of permanent ice and snow, barren land, and inland water bodies. These

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

%), dry coniferous boreal forest (10%), boreal deciduous forest (10%), and temperate maritime coniferous forest (1%). This 1-km-resolution land cover classification was developed by aggregating the 23 land cover classes in the commonly used Advanced Very High Resolution Radiometer (AVHRR)-based classification for Alaska ( Fleming 1997 ) using topography, climate, and geographic location. In Fleming ( Fleming 1997 ), land cover classes corresponding to tundra were delineated from classes corresponding

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

based on a static data assimilation scheme, the data analysis is global in extent, and many observations are used. Data quality has been discussed in numerous studies ( Kalnay et al. 1996 ; Serreze et al. 1998 ; Serreze and Hurst 2000 ; Serreze et al. 2003 ). In general, the reanalysis data capture the broad spatial patterns, but it overestimates annual total precipitation over land and has the seasonal precipitation maximum one month early over the Arctic ( Serreze and Hurst 2000 ; Serreze et

Full access
Wanli Wu, Amanda H. Lynch, Sheldon Drobot, James Maslanik, A. David McGuire, and Ute Herzfeld

because of technical and environmental limitations. It has been suggested that an alternative to estimating terrestrial water and energy cycles is to use land surface models (LSMs; Bonan 2002 ) or regional climate models (RCMs; Wu and Lynch 2000 ; Wu et al. 2005 ). The models close the water and energy budget by design. Thus, if the large-scale forcing data, which drive LSMs and RCMs, are accurate, and if model biases are small, these modeled water and energy fluxes might be used in lieu of

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

1. Introduction and objectives The goal of the Western Arctic Linkage Experiment (WALE) is to investigate the role of high-latitude terrestrial ecosystems in the response of the Arctic system to global change. To further this goal, climate datasets and climate model results are compiled, collected, and compared for the WALE study region, which includes land areas in Alaska and northwestern Canada at 55°–70°N, 165°–110°W approximately [see McGuire et al. 2006, manuscript submitted to Earth

Full access