Can correcting feature location in simulated mean climate improve agreement on projected changes?
Can correcting feature location in simulated mean climate improve agreement on projected changes?
复制标题
修正模拟平均气候中的特征位置能否提高对预测变化的一致性？
DOI：
10.1002/2012gl053964
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发表时间：
2013
影响因子：
5.2
通讯作者：
M. Allen
中科院分区：
文献类型：
--
作者：
A. A. Levy;W. Ingram;M. Jenkinson;C. Huntingford;F. Hugo Lambert;M. Allen
在GCM对降水的模拟中的缺陷是由于位置和时间的持续误差所致，纠正特征的空间和季节分布将在物理基础上改进模式间对未来变化的一致。我们使用一个医学图像分析工具来扭曲14个大气环流模式(GCM)的降水气候，使之更接近于观测的重新分析，而不是像传统的偏差校正技术那样局部调整强度。然后，这些翘曲被应用于相同的GCM在二氧化碳翻两番实验下模拟的平均气候变化。我们发现，翘曲过程不仅使GCM的历史气候更接近于再分析，而且还减少了模型对这种外部强迫的反应之间的分歧。开发一种为气候领域的具体要求量身定做的工具可能会带来进一步的改进，特别是与当地的偏差校正技术相结合。
To the extent that deficiencies in GCM simulations of precipitation are due to persistent errors of location and timing, correcting the spatial and seasonal distribution of features would provide a physically based improvement in inter‐model agreement on future changes. We use a tool for the analysis of medical images to warp the precipitation climatologies of 14 General Circulation Models (GCMs) closer to a reanalysis of observations, rather than adjusting intensities locally as in conventional bias correction techniques. These warps are then applied to the same GCMs' simulated changes in mean climate under a CO2 quadrupling experiment. We find that the warping process not only makes GCMs' historical climatologies more closely resemble reanalysis but also reduces the disagreement between the models' response to this external forcing. Developing a tool that is tailored for the specific requirements of climate fields may provide further improvement, particularly in combination with local bias correction techniques.