A diagram for evaluating multiple aspects of model performance in simulating vector fields
A diagram for evaluating multiple aspects of model performance in simulating vector fields
复制标题
用于评估模拟矢量场中模型性能的多个方面的图
DOI:
10.5194/gmd-9-4365-2016
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发表时间:
2016-12
影响因子:
5.1
通讯作者:
Guo Weidong
中科院分区:
文献类型:
--
作者:
Xu Zhongfeng;Hou Zhaolu;Han Ying;Guo Weidong
Abstract. Vector quantities, e.g., vector winds, play an extremely important role in climate systems. The energy and water exchanges between different regions are strongly dominated by wind, which in turn shapes the regional climate. Thus, how well climate models can simulate vector fields directly affects model performance in reproducing the nature of a regional climate. This paper devises a new diagram, termed the vector field evaluation (VFE) diagram, which is a generalized Taylor diagram and able to provide a concise evaluation of model performance in simulating vector fields. The diagram can measure how well two vector fields match each other in terms of three statistical variables, i.e., the vector similarity coefficient, root mean square length (RMSL), and root mean square vector difference (RMSVD). Similar to the Taylor diagram, the VFE diagram is especially useful for evaluating climate models. The pattern similarity of two vector fields is measured by a vector similarity coefficient (VSC) that is defined by the arithmetic mean of the inner product of normalized vector pairs. Examples are provided, showing that VSC can identify how close one vector field resembles another. Note that VSC can only describe the pattern similarity, and it does not reflect the systematic difference in the mean vector length between two vector fields. To measure the vector length, RMSL is included in the diagram. The third variable, RMSVD, is used to identify the magnitude of the overall difference between two vector fields. Examples show that the VFE diagram can clearly illustrate the extent to which the overall RMSVD is attributed to the systematic difference in RMSL and how much is due to the poor pattern similarity.
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DOI:
--
发表时间:
2012
期刊:
--
影响因子:
--
作者:
K. Sperber;H. Annamalai;I. Kang;A. Kitoh;A. Moise;A. Turner;B. Wang;T. Zhou
通讯作者:
K. Sperber;H. Annamalai;I. Kang;A. Kitoh;A. Moise;A. Turner;B. Wang;T. Zhou
影响因子:
8
作者:
Kanamitsu, M;Ebisuzaki, W;Potter, GL
通讯作者:
Potter, GL
影响因子:
5.2
作者:
Jiangfeng Wei;Q. Jin;Zong‐Liang Yang;P. Dirmeyer
通讯作者:
Jiangfeng Wei;Q. Jin;Zong‐Liang Yang;P. Dirmeyer
影响因子:
3.1
作者:
Harada, Yayoi;Kamahori, Hirotaka;Takahashi, Kiyotoshi
通讯作者:
Takahashi, Kiyotoshi
影响因子:
3.4
作者:
R. Twardosz;T. Niedźwiedź;E. Łupikasza
通讯作者:
R. Twardosz;T. Niedźwiedź;E. Łupikasza