Multivariable integrated evaluation of model performance with the vector field evaluation diagram
This paper develops a multivariable integrated evaluation (MVIE) method to measure the overall performance of climate model in simulating multiple fields. The general idea of MVIE is to group various scalar fields into a vector field and compare the constructed vector field against the observed...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-10-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/10/3805/2017/gmd-10-3805-2017.pdf |
| Summary: | This paper develops a multivariable integrated evaluation (MVIE) method to
measure the overall performance of climate model in simulating multiple
fields. The general idea of MVIE is to group various scalar fields into a
vector field and compare the constructed vector field against the observed
one using the vector field evaluation (VFE) diagram. The VFE diagram was
devised based on the cosine relationship between three statistical
quantities: root mean square length (RMSL) of a vector field, vector field
similarity coefficient, and root mean square vector deviation (RMSVD). The
three statistical quantities can reasonably represent the corresponding
statistics between two multidimensional vector fields. Therefore, one can
summarize the three statistics of multiple scalar fields using the VFE
diagram and facilitate the intercomparison of model performance. The VFE
diagram can illustrate how much the overall root mean square deviation of
various fields is attributable to the differences in the root mean square
value and how much is due to the poor pattern similarity. The MVIE method can
be flexibly applied to full fields (including both the mean and anomaly) or
anomaly fields depending on the application. We also propose a multivariable
integrated evaluation index (MIEI) which takes the amplitude and pattern
similarity of multiple scalar fields into account. The MIEI is expected to
provide a more accurate evaluation of model performance in simulating
multiple fields. The MIEI, VFE diagram, and commonly used statistical metrics
for individual variables constitute a hierarchical evaluation methodology,
which can provide a more comprehensive evaluation of model performance. |
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| ISSN: | 1991-959X 1991-9603 |