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  • 标题:Filling the Data Gaps in Mountain Climate Observatories Through Advanced Technology, Refined Instrument Siting, and a Focus on Gradients
  • 本地全文:下载
  • 作者:Scotty Strachan ; Eric P. Kelsey ; Renée F. Brown
  • 期刊名称:Mountain Research and Development
  • 印刷版ISSN:0276-4741
  • 电子版ISSN:1994-7151
  • 出版年度:2016
  • 卷号:36
  • 期号:4
  • 页码:518-527
  • DOI:10.1659/MRD-JOURNAL-D-16-00028.1
  • 摘要:The mountain research community is still contending with the need to monitor ecosystems, both to improve local management practices and to address regional and global science questions related to the Future Earth themes of Dynamic Planet, Global Sustainable Development, and Transformations Towards Sustainability. How such efforts may be designed and coordinated remains an open question. Historical climate and ecological observatories and networks typically have not represented the scope or spatial and topographic distribution of near-surface processes in mountains, creating knowledge gaps. Grassroots, in situ investigations have revealed the existence of topoclimates that are not linearly related to general atmospheric conditions, and are also not adequately represented in gridded model products. In this paper, we describe how some of the disconnects between data, models, and applications in mountains can be addressed using a combination of gradient monitoring, uniform observational siting and standards, and modern technology (cyberinfrastructure). Existing observational studies need to expand their topographic niches, and future observatories should be planned to span entire gradients. Use of cyberinfrastructure tools such as digital telemetry and Internet Protocol networks can reduce costs and data gaps while improving data quality control processes and widening audience outreach. Embracing this approach and working toward common sets of comparable measurements should be goals of emerging mountain observatories worldwide.
  • 关键词:Mountain observatories; ecohydrology; topographic gradients; instrumentation; siting standards; cyberinfrastructure; data networks; model testing
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