Finn Lindgren (Edinburgh)
EUSTACE: Latent Gaussian process models for weather and climate reconstruction
Hicks J11, 2pm
The EUSTACE project will give publicly available daily estimates of surface air temperature
since 1850 across the globe for the first time by combining surface and satellite data using
novel statistical techniques. To this end, a spatio-temporal multiscale statistical Gaussian random field model is constructed, using connections between SPDEs and Markov random fields to obtain sparse matrices for the practical computations. The extreme size of the problem necessitates the use of iterative solvers, making use of the multiscale structure of the model to design an effective preconditioner.