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| Titel |
Logit-normal mixed model for Indian monsoon precipitation |
| VerfasserIn |
L. R. Dietz, S. Chatterjee |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 21, no. 5 ; Nr. 21, no. 5 (2014-09-12), S.939-953 |
| Datensatznummer |
250120940
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| Publikation (Nr.) |
 copernicus.org/npg-21-939-2014.pdf |
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| Zusammenfassung |
| Describing the nature and variability of Indian monsoon precipitation is a
topic of much debate in the current literature. We suggest the use of a
generalized linear mixed model (GLMM), specifically, the
logit-normal mixed model, to describe the underlying structure of this
complex climatic event. Four GLMM algorithms are described and simulations
are performed to vet these algorithms before applying them to the Indian
precipitation data. The logit-normal model was applied to light, moderate,
and extreme rainfall. Findings indicated that physical constructs were
preserved by the models, and random effects were significant in many cases.
We also found GLMM estimation methods were sensitive to tuning parameters and
assumptions and therefore, recommend use of multiple methods in applications.
This work provides a novel use of GLMM and promotes its addition to the
gamut of tools for analysis in studying climate phenomena. |
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