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  • American Meteorological Society  (4)
  • Blackwell Science Ltd  (1)
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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Science Ltd
    Global change biology 6 (2000), S. 0 
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: Understanding the response of terrestrial ecosystems to climatic warming is a challenge because of the complex interactions of climate, disturbance, and recruitment across the landscape. We use a spatially explicit model (ALFRESCO) to simulate the transient response of subarctic vegetation to climatic warming on the Seward Peninsula (80 000 km2) in north-west Alaska. Model calibration efforts showed that fire ignition was less sensitive than fire spread to regional climate (temperature and precipitation). In the model simulations a warming climate led to slightly more fires and much larger fires and expansion of forest into previously treeless tundra. Vegetation and fire regime continued to change for centuries after cessation of the simulated climate warming. Flammability increased rapidly in direct response to climate warming and more gradually in response to climate-induced vegetation change. In the simulations warming caused as much as a 228% increase in the total area burned per decade, leading to an increasingly early successional and more homogenous deciduous forest-dominated landscape. A single transient 40-y drought led to the development of a novel grassland–steppe ecosystem that persisted indefinitely and caused permanent increases in fires in both the grassland and adjacent vegetation. These simulated changes in vegetation and disturbance dynamics under a warming climate have important implications for regional carbon budgets and biotic feedbacks to regional climate.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2016-03-01
    Description: The European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) has been downscaled using a regional model covering Alaska at 20-km spatial and hourly temporal resolution for 1979–2013. Stakeholders can utilize these enhanced-resolution data to investigate climate- and weather-related phenomena in Alaska. Temperature and precipitation are analyzed and compared among ERA-Interim, WRF Model downscaling, and in situ observations. Relative to ERA-Interim, the downscaling is shown to improve the spatial representation of temperature and precipitation around Alaska’s complex terrain. Improvements include increased winter and decreased summer higher-elevation downscaled seasonal average temperatures. Precipitation is also enhanced over higher elevations in all seasons relative to the reanalysis. These spatial distributions of temperature and precipitation are consistent with the few available gridded observational datasets that account for topography. The downscaled precipitation generally exceeds observationally derived estimates in all seasons over mainland Alaska, and it is less than observations in the southeast. Temperature biases tended to be more mixed, and the downscaling reduces absolute bias at higher elevations, especially in winter. Careful selection of data for local site analysis from the downscaling can help to reduce these biases, especially those due to inconsistencies in elevation. Improved meteorological station coverage at higher elevations will be necessary to better evaluate gridded downscaled products in Alaska because biases vary and may even change sign with elevation.
    Print ISSN: 1558-8424
    Electronic ISSN: 1558-8432
    Topics: Geography , Physics
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  • 3
    Publication Date: 2016-04-01
    Description: Alaska is experiencing effects of global climate change that are due, in large part, to the positive feedback mechanisms associated with polar amplification. The major risk factors include loss of sea ice and glaciers, thawing permafrost, increased wildfires, and ocean acidification. Reanalyses, integral to understanding mechanisms of Alaska’s past climate and to helping to calibrate modeling efforts, are based on the output of weather forecast models that assimilate observations. This study evaluates temperature and precipitation from five reanalyses at monthly and daily time scales for the period 1979–2009. Monthly data are evaluated spatially at grid points and for six climate zones in Alaska. In addition, daily maximum temperature, minimum temperature, and precipitation from reanalyses are compared with meteorological-station data at six locations. The reanalyses evaluated in this study include the NCEP–NCAR reanalysis (R1), North American Regional Reanalysis (NARR), Climate Forecast System Reanalysis (CFSR), ERA-Interim, and the Modern-Era Retrospective Analysis for Research and Applications (MERRA). Maps of seasonal bias and standard deviation, constructed from monthly data, show how the reanalyses agree with observations spatially. Cross correlations between the monthly gridded and daily station time series are computed to provide a measure of confidence that data users can assume when selecting reanalysis data in a region without many surface observations. A review of natural hazards in Alaska indicates that MERRA is the top reanalysis for wildfire and interior-flooding applications. CFSR is the recommended reanalysis for North Slope coastal erosion issues and, along with ERA-Interim, for heavy precipitation in southeastern Alaska.
    Print ISSN: 1558-8424
    Electronic ISSN: 1558-8432
    Topics: Geography , Physics
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  • 4
  • 5
    Publication Date: 2007-01-01
    Description: Projected climatic warming has direct implications for future disturbance regimes, particularly fire-dominated ecosystems at high latitudes, where climate warming is expected to be most dramatic. It is important to ascertain the potential range of climate change impacts on terrestrial ecosystems, which is relevant to making projections of the response of the Earth system and to decisions by policymakers and land managers. Computer simulation models that explicitly model climate–fire relationships represent an important research tool for understanding and projecting future relationships. Retrospective model analyses of ecological models are important for evaluating how to effectively couple ecological models of fire dynamics with climate system models. This paper uses a transient landscape-level model of vegetation dynamics, Alaskan Frame-based Ecosystem Code (ALFRESCO), to evaluate the influence of different driving datasets of climate on simulation results. Our analysis included the use of climate data based on first-order weather station observations from the Climate Research Unit (CRU), a statistical reanalysis from the NCEP–NCAR reanalysis project (NCEP), and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Model simulations of annual area burned for Alaska and western Canada were compared to historical fire activity (1950–2000). ALFRESCO was only able to generate reasonable simulation results when driven by the CRU climate data. Simulations driven by the NCEP and MM5 climate data produced almost no annual area burned because of substantially colder and wetter growing seasons (May–September) in comparison with the CRU climate data. The results of this study identify the importance of conducting retrospective analyses prior to coupling ecological models of fire dynamics with climate system models. The authors’ suggestion is to develop coupling methodologies that involve the use of anomalies from future climate model simulations to alter the climate data of more trusted historical climate datasets.
    Electronic ISSN: 1087-3562
    Topics: Geography , Geosciences , Physics
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