Dataset Information

Weaker Links Between Zonal Convective Clustering and ITCZ Width in Climate Models Than in Observations.

ABSTRACT: Strong links are seen in observations between convective clustering and several properties of the Intertropical Convergence Zone (ITCZ). These links suggest that biases in how climate models simulate the ITCZ may be related to model biases in convective clustering or that there may be biases in how models represent the relationship between clustering and the ITCZ. We investigate these issues by analyzing convective clustering, and the link between clustering and ITCZ properties in 18 climate models. We find that the links between variability in convective clustering and variability of ITCZ properties are generally weaker and less robust in models than in observations. By contrast, model biases in the climatological convective clustering explain a substantial fraction of the climatological double-ITCZ bias, though they do not explain biases in the climatological ITCZ width.

SUBMITTER: Popp M

PROVIDER: S-EPMC7757163 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Weaker Links Between Zonal Convective Clustering and ITCZ Width in Climate Models Than in Observations.

Popp Max M Lutsko Nicholas J NJ Bony Sandrine S

Geophysical research letters 20201121 22

Strong links are seen in observations between convective clustering and several properties of the Intertropical Convergence Zone (ITCZ). These links suggest that biases in how climate models simulate the ITCZ may be related to model biases in convective clustering or that there may be biases in how models represent the relationship between clustering and the ITCZ. We investigate these issues by analyzing convective clustering, and the link between clustering and ITCZ properties in 18 climate mod ...[more]

PMID: 33380761

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Project description:Cluster analysis plays vital role in pattern recognition in several fields of science. Silhouette width is a widely used index for assessing the fit of individual objects in the classification, as well as the quality of clusters and the entire classification. Silhouette combines two clustering criteria, compactness and separation, which imply that spherical cluster shapes are preferred over others-a property that can be seen as a disadvantage in the presence of complex, nonspherical clusters, which is common in real situations. We suggest a generalization of the silhouette width using the generalized mean. By changing the p parameter of the generalized mean between -∞ and +∞, several specific summary statistics, including the minimum, maximum, the arithmetic, harmonic, and geometric means, can be reproduced. Implementing the generalized mean in the calculation of silhouette width allows for changing the sensitivity of the index to compactness versus connectedness. With higher sensitivity to connectedness, the preference of silhouette width toward spherical clusters should reduce. We test the performance of the generalized silhouette width on artificial data sets and on the Iris data set. We examine how classifications with different numbers of clusters prepared by different algorithms are evaluated, if p is set to different values. When p was negative, well-separated clusters achieved high silhouette widths despite their elongated or circular shapes. Positive values of p increased the importance of compactness; hence, the preference toward spherical clusters became even more detectable. With low p, single linkage clustering was deemed the most efficient clustering method, while with higher parameter values the performance of group average, complete linkage, and beta flexible with beta = -0.25 seemed better. The generalized silhouette allows for adjusting the contribution of compactness and connectedness criteria, thus avoiding underestimation of clustering efficiency in the presence of clusters with high internal heterogeneity.

Dataset Information

Weaker Links Between Zonal Convective Clustering and ITCZ Width in Climate Models Than in Observations.

Publications

Weaker Links Between Zonal Convective Clustering and ITCZ Width in Climate Models Than in Observations.

Similar Datasets

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