A Gaussian Markov random field model for total yearly precipitation over the African Sahel

Författare

Johan Lindström
Finn Lindgren

Summary, in English

A spatio-temporal model is constructed to interpolate yearly precipitation

data from 1982 to 1996 over the African Sahel. The precipitation

data used in the analysis comes from the Global Historical

Climatology Network.

The spatio-temporal model is based on a Gaussian Markov random

field approach with AR(1)-dependence in time and a spatial component

modeled using an approximation of a field withMat´ern covariance. The

model is defined on an irregular grid on a segment of the sphere, both

avoiding the issue of matching observations to a regularly spaced grid,

and handling the curvature of the Earth.

The model is estimated using a Markov chain Monte Carlo approach.

The formulation as a Markov field allows for relatively efficient

computations, even though the field has more than 3*10^4 nodes.

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