Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts
Möller AC, Thorarinsdottir TL, Lenkoski A, Gneiting T (2015)
arXiv:1507.05066.
Preprint | Englisch
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Autor*in
Möller, Annette ChristineUniBi ;
Thorarinsdottir, Thordis L.;
Lenkoski, Alex;
Gneiting, Tilmann
Abstract / Bemerkung
Uncertainty in the prediction of future weather is commonly assessed through
the use of forecast ensembles that employ a numerical weather prediction model
in distinct variants. Statistical postprocessing can correct for biases in the
numerical model and improves calibration. We propose a Bayesian version of the
standard ensemble model output statistics (EMOS) postprocessing method, in
which spatially varying bias coefficients are interpreted as realizations of
Gaussian Markov random fields. Our Markovian EMOS (MEMOS) technique utilizes
the recently developed stochastic partial differential equation (SPDE) and
integrated nested Laplace approximation (INLA) methods for computationally
efficient inference. The MEMOS approach shows good predictive performance in a
comparative study of 24-hour ahead temperature forecasts over Germany based on
the 50-member ensemble of the European Centre for Medium-Range Weather
Forecasting (ECMWF).
Erscheinungsjahr
2015
Zeitschriftentitel
arXiv:1507.05066
Page URI
https://pub.uni-bielefeld.de/record/2960073
Zitieren
Möller AC, Thorarinsdottir TL, Lenkoski A, Gneiting T. Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts. arXiv:1507.05066. 2015.
Möller, A. C., Thorarinsdottir, T. L., Lenkoski, A., & Gneiting, T. (2015). Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts. arXiv:1507.05066
Möller, Annette Christine, Thorarinsdottir, Thordis L., Lenkoski, Alex, and Gneiting, Tilmann. 2015. “Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts”. arXiv:1507.05066.
Möller, A. C., Thorarinsdottir, T. L., Lenkoski, A., and Gneiting, T. (2015). Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts. arXiv:1507.05066.
Möller, A.C., et al., 2015. Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts. arXiv:1507.05066.
A.C. Möller, et al., “Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts”, arXiv:1507.05066, 2015.
Möller, A.C., Thorarinsdottir, T.L., Lenkoski, A., Gneiting, T.: Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts. arXiv:1507.05066. (2015).
Möller, Annette Christine, Thorarinsdottir, Thordis L., Lenkoski, Alex, and Gneiting, Tilmann. “Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts”. arXiv:1507.05066 (2015).