Journal article
A non‐stationary spatial model for temperature interpolation applied to the state of Rio de Janeiro
Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol.66(5), pp.919-939
11/2017
DOI: 10.1111/rssc.12207
Abstract
Summary
We propose a model for spatial and temporal interpolation and prediction for a set of monthly minimum temperature measurements from 37 stations in the state of Rio de Janeiro, Brazil, from 1961 to 2010. The model is based on a hierarchical specification where data are modelled with a regression structure for the mean and a non‐stationary spatial representation for the spatially structured noise term. The regression term is also allowed to contain spatial dependence through coefficients and its covariates. A novel structure is assumed for the spatial non‐stationarity, based on a generalization of a currently proposed convolution of stationary models. It allows more flexibility in the model specification and automatically selects the number of model components. This model provides superior performance when compared with two special cases: one stationary, and one non‐stationary, provided by a sum of locally stationary processes. The results show a growth in the spread of temperature, with largely urbanized, warmest areas growing warmer, and largely forested, coolest areas growing cooler.
Details
- Title: Subtitle
- A non‐stationary spatial model for temperature interpolation applied to the state of Rio de Janeiro
- Creators
- Marcelo Cunha - Fundação Oswaldo CruzDani Gamerman - Universidade Federal do Rio de JaneiroMontserrat Fuentes - North Carolina State UniversityMarina Paez - Universidade Federal do Rio de Janeiro
- Resource Type
- Journal article
- Publication Details
- Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol.66(5), pp.919-939
- DOI
- 10.1111/rssc.12207
- ISSN
- 0035-9254
- eISSN
- 1467-9876
- Number of pages
- 21
- Grant note
- Brazilian agency Conselho Nacional de Desenvolvimento Cientifico e Tecnológico Fundeção de Amparo à Pesquisa do Estado do Rio de Janeiro Brazilian agencies Conselho Nacional de Desenvolvimento Cientifico e Tecnológico
- Language
- English
- Date published
- 11/2017
- Academic Unit
- President; Biostatistics; Statistics and Actuarial Science
- Record Identifier
- 9984065776802771
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