...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Climate dynamics >The potential to narrow uncertainty in projections of regional precipitation change
【24h】

The potential to narrow uncertainty in projections of regional precipitation change

机译：缩小区域降水变化预测中不确定性的潜力

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We separate and quantify the sources of uncertainty in projections of regional (~ 2,500 km) precipitation changes for the twenty-first century using the CMIP3 multi-model ensemble, allowing a direct comparison with a similar analysis for regional temperature changes. For decadal means of seasonal mean precipitation, internal variability is the dominant uncertainty for predictions of the first decade everywhere, and for many regions until the third decade ahead. Model uncertainty is generally the dominant source of uncertainty for longer lead times. Scenario uncertainty is found to be small or negligible for all regions and lead times, apart from close to the poles at the end of the century. For the global mean, model uncertainty dominates at all lead times. The signal-to-noise ratio (S/N) of the precipitation projections is highest at the poles but less than 1 almost everywhere else, and is far lower than for temperature projections. In particular, the tropics have the highest S/N for temperature, but the lowest for precipitation. We also estimate a 'potential S/N' by assuming that model uncertainty could be reduced to zero, and show that, for regional precipitation, the gains in S/N are fairly modest, especially for predictions of the next few decades. This finding suggests that adaptation decisions will need to be made in the context of high uncertainty concerning regional changes in precipitation. The potential to narrow uncertainty in regional temperature projections is far greater. These conclusions on S/N are for the current generation of models; the real signal may be larger or smaller than the CMIP3 multi-model mean. Also note that the S/N for extreme precipitation, which is more relevant for many climate impacts, may be larger than for the seasonal mean precipitation considered here.
机译：我们使用CMIP3多模型合集分离并量化了21世纪区域（〜2,500 km）降水变化预测中的不确定性来源，从而可以与区域温度变化的类似分析直接进行比较。对于季节平均降水量的十年平均值而言，内部可变性是到处第一个十年的预测的主要不确定性，而对于许多地区，直到未来第三个十年的预测仍不确定。通常，模型不确定性是较长交付周期内不确定性的主要来源。发现场景不确定性对于所有地区和交付周期都是很小的或可以忽略的，除了本世纪末接近两极。对于全球平均值，模型不确定性在所有交货时间均占主导地位。降水预测的信噪比（S / N）在两极最高，但几乎在其他所有地方都小于1，并且远低于温度预测。特别是，热带地区的温度信噪比最高，而降水的信噪比最低。我们还通过假设模型不确定性可以减小到零来估计“潜在信噪比”，并表明，对于区域降水，信噪比的增长相当适度，尤其是对未来几十年的预测。这一发现表明，在有关降水区域变化的高度不确定性的背景下，需要做出适应性决策。缩小区域温度预测的不确定性的潜力更大。这些关于信噪比的结论适用于当前的模型。实际信号可能大于或小于CMIP3多模型平均值。另请注意，极端降水的S / N与许多气候影响更相关，可能比此处考虑的季节性平均降水更大。

著录项

  • 来源
    《Climate dynamics》 |2011年第2期|p.407-418|共12页
  • 作者

    Ed Hawkins; Rowan Sutton;

  • 作者单位

    NCAS-Climate, Department of Meteorology.University of Reading, Reading, UK;

    NCAS-Climate, Department of Meteorology.University of Reading, Reading, UK;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    precipitation; uncertainty;

    机译：沉淀;不确定;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号