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| Titel |
Logit-normal mixed model for Indian Monsoon rainfall extremes |
| VerfasserIn |
L. R. Dietz, S. Chatterjee |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
2198-5634
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 1, no. 1 ; Nr. 1, no. 1 (2014-03-13), S.193-233 |
| Datensatznummer |
250115076
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| Publikation (Nr.) |
 copernicus.org/npgd-1-193-2014.pdf |
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| Zusammenfassung |
| Describing the nature and variability of Indian monsoon rainfall extremes 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. Several GLMM algorithms are described and simulations are performed to
vet these algorithms before applying them to the Indian precipitation data procured from the
National Climatic Data Center. The logit-normal model was applied with fixed covariates of
latitude, longitude, elevation, daily minimum and maximum temperatures with a random intercept by
weather station. In general, the estimation methods concurred in their suggestion of
a relationship between the El Niño Southern Oscillation (ENSO) and extreme rainfall
variability estimates. This work provides a valuable starting point for extending GLMM to
incorporate the intricate dependencies in extreme climate events. |
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