A non-stationary spatial model for temperature interpolation applied to the state of Rio de Janeiro

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 stru...

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Bibliographic Details
Published in:Journal of the Royal Statistical Society Series C: Applied Statistics 2017-11, Vol.66 (5), p.919-939
Main Authors: Cunha, Marcelo, Gamerman, Dani, Fuentes, Montserrat, Paez, Marina
Format: Article
Language:English
Subjects:
Bayesian inference
Convolution
Economic models
Flexibility
Interpolation
Noise
Non‐stationarity in space
Predictions
Regression analysis
Spatial analysis
Spatial interpolation
Specification
Specifications
Surface temperature
Temperature
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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.
ISSN:0035-9254
1467-9876
DOI:10.1111/rssc.12207