arXiv · 1605.08701
On the Calibration of Multilevel Monte Carlo Ensemble Forecasts
Abstract
Multilevel Monte Carlo can efficiently compute statistical estimates of discretized random variables, for a given error tolerance. Traditionally, only a certain statistic is computed from a particular implementation of multilevel Monte Carlo. This paper considers the multilevel case when one wants to verify and evaluate a single ensemble that forms an empirical approximation to many different statistics, namely an ensemble forecast. We propose a simple algorithm that, in the univariate case, allows one to derive a statistically consistent single ensemble forecast from the hierarchy of ensembles that are formed during an implementation of multilevel Monte Carlo. This ensemble forecast then allows the entire multilevel hierarchy of ensembles to be evaluated using standard ensemble forecast verification techniques. We demonstrate the case of evaluating the calibration of the forecast in this paper.
Explore related subjects
Keep this discovery
Alastair Gregory, Colin Cotter. 2017-03-29. On the Calibration of Multilevel Monte Carlo Ensemble Forecasts. https://doi.org/10.1002/qj.3052
Cite the original work for its findings. Save a collection to share your selection of sources.