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Scale-dependent Regional Climate Predictability over North America Inferred from CMIP3 and CMIP5 Ensemble Simulations

机译:从CMIP3和CMIP5集合模拟中推断出北美地区尺度相关的区域气候可预测性

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摘要

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty(noise) in surface temperature predictions(represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean(signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.

著录项

  • 来源
    《大气科学进展(英文版)》 |2016年第8期|905-918|共14页
  • 作者单位

    Department of Meteorology and Center for Advanced Data Assimilation and Predictability Techniques,The Pennsylvania State University, University Park, PA 16802, USA;

    Department of Meteorology and Center for Advanced Data Assimilation and Predictability Techniques,The Pennsylvania State University, University Park, PA 16802, USA;

    IMSG at NOAA/NWS/NCEP/Environmental Modeling Center, College Park, MD 20740, USA;

    Department of Meteorology and Center for Advanced Data Assimilation and Predictability Techniques,The Pennsylvania State University, University Park, PA 16802, USA;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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