Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 9, 4365-4380, 2016
https://doi.org/10.5194/gmd-9-4365-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
06 Dec 2016
A diagram for evaluating multiple aspects of model performance in simulating vector fields
Zhongfeng Xu1, Zhaolu Hou2,3,4, Ying Han1, and Weidong Guo2,5 1RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
2Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing, China
3LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
4University of Chinese Academy of Sciences, Beijing, China
5Joint International Research Laboratory of Atmospheric and Earth System Sciences, Nanjing, China
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.

Citation: Xu, Z., Hou, Z., Han, Y., and Guo, W.: A diagram for evaluating multiple aspects of model performance in simulating vector fields, Geosci. Model Dev., 9, 4365-4380, https://doi.org/10.5194/gmd-9-4365-2016, 2016.
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Short summary
This paper devises a new diagram called the vector field evaluation (VFE) diagram. The VFE diagram is a generalized Taylor diagram and is able to provide a concise evaluation of model performance in simulating vector fields (e.g., vector winds) in terms of three statistical variables. The VFE diagram can be applied to the evaluation of full vector fields or anomaly fields as needed. Some potential applications of the VFE diagram in model evaluation are also presented in the paper.
This paper devises a new diagram called the vector field evaluation (VFE) diagram. The VFE...
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