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Investigation of Enhancements to Two Fundamental Components of the Statistical Interpolation Method used by the Canadian Precipitation Analysis (CaPA).

机译:调查加拿大插值分析(CaPA)使用的统计插值方法的两个基本组成部分的增强。

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摘要

The Canadian Precipitation Analysis (CaPA) generates gridded precipitation data outputs based on the assimilation of both observation and climate model data. CaPA outputs are highly valuable to modelling efforts dependent on precipitation inputs, and as such the quality of CaPA outputs is crucial. Two improvements to CaPA were investigated: reducing transformation bias though correction against moving-window averaged CaPA output that avoids transformation, and enhancing semivariograms through anisotropy and convection considerations. Accounting for convection in the semivariogram proved ineffectual, while the bias correction technique and anisotropic semivariograms both reduced bias and improved related metrics. No methods improved the Equitable Threat Score. If implemented separately, the bias correction or anisotropic semivariogram approaches will yield targeted benefits for CaPA users, particularly for applications focused on extreme precipitation values. Improvements were not so comprehensive as to warrant adoption in the operational CaPA configuration, although availability in experimental versions is recommended.
机译:加拿大降水分析(CaPA)基于对观测数据和气候模型数据的同化,生成网格化降水数据输出。 CaPA输出对于依赖降水输入的建模工作非常有价值,因此,CaPA输出的质量至关重要。研究了对CaPA的两项改进:通过针对可避免转换的移动窗口平均CaPA输出进行校正来减少转换偏差,以及通过各向异性和对流考虑增强半变异函数。证明半变异函数中的对流是无效的,而偏差校正技术和各向异性半变异函数都可以减少偏差并改善相关指标。没有任何方法可以改善公平威胁评分。如果单独实施,则偏差校正或各向异性半变异函数方法将为CaPA用户带来针对性的收益,尤其是针对极端降水值的应用。尽管建议在实验版本中使用,但改进并不全面,不能保证可在操作CaPA配置中采用。

著录项

  • 作者

    Evans, Andrea Marie.;

  • 作者单位

    University of Manitoba (Canada).;

  • 授予单位 University of Manitoba (Canada).;
  • 学科 Engineering Civil.;Meteorology.
  • 学位 M.Sc.
  • 年度 2014
  • 页码 308 p.
  • 总页数 308
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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