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

Lindström, Johan LU and Lindgren, Finn LU (2008) In Preprints in Mathematical Sciences1999-01-01+01:00 2008:8.
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
unpublished
subject
in
Preprints in Mathematical Sciences1999-01-01+01:00
volume
2008:8
pages
22 pages
publisher
Lund University
external identifiers
  • other:LUTFMS-5074-2008
ISSN
1403-9338
language
English
LU publication?
yes
id
ed5e68fb-818c-4f15-b447-413dbdff9fe4 (old id 4730170)
date added to LUP
2014-10-28 10:38:32
date last changed
2016-04-15 21:54:06
@article{ed5e68fb-818c-4f15-b447-413dbdff9fe4,
  abstract     = {A spatio-temporal model is constructed to interpolate yearly precipitation<br/><br>
data from 1982 to 1996 over the African Sahel. The precipitation<br/><br>
data used in the analysis comes from the Global Historical<br/><br>
Climatology Network.<br/><br>
The spatio-temporal model is based on a Gaussian Markov random<br/><br>
field approach with AR(1)-dependence in time and a spatial component<br/><br>
modeled using an approximation of a field withMat´ern covariance. The<br/><br>
model is defined on an irregular grid on a segment of the sphere, both<br/><br>
avoiding the issue of matching observations to a regularly spaced grid,<br/><br>
and handling the curvature of the Earth.<br/><br>
The model is estimated using a Markov chain Monte Carlo approach.<br/><br>
The formulation as a Markov field allows for relatively efficient<br/><br>
computations, even though the field has more than 3*10^4 nodes.},
  author       = {Lindström, Johan and Lindgren, Finn},
  issn         = {1403-9338},
  language     = {eng},
  pages        = {22},
  publisher    = {Lund University},
  series       = {Preprints in Mathematical Sciences1999-01-01+01:00},
  title        = {A Gaussian Markov random field model for total yearly precipitation over the African Sahel},
  volume       = {2008:8},
  year         = {2008},
}