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- W2317208087 abstract "Abstract. 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." @default.
- W2317208087 created "2016-06-24" @default.
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- W2317208087 date "2014-03-13" @default.
- W2317208087 modified "2023-10-01" @default.
- W2317208087 title "Logit-normal mixed model for Indian Monsoon rainfall extremes" @default.
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- W2317208087 doi "https://doi.org/10.5194/npgd-1-193-2014" @default.
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