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Logit-normal Mixed Model for Indian Monsoon Rainfall Extremes : Volume 1, Issue 1 (13/03/2014)

By Dietz, L. R.

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Book Id: WPLBN0004020089
Format Type: PDF Article :
File Size: Pages 41
Reproduction Date: 2015

Title: Logit-normal Mixed Model for Indian Monsoon Rainfall Extremes : Volume 1, Issue 1 (13/03/2014)  
Author: Dietz, L. R.
Volume: Vol. 1, Issue 1
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Dietz, L. R., & Chatterjee, S. (2014). Logit-normal Mixed Model for Indian Monsoon Rainfall Extremes : Volume 1, Issue 1 (13/03/2014). Retrieved from

Description: University of Minnesota, School of Statistics, Minneapolis, Minnesota, USA. 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.

Logit-normal mixed model for Indian Monsoon rainfall extremes

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