Combining the Bayesian processor of output with Bayesian model averaging for reliable ensemble forecasting

R. Marty, V. Fortin, Heri Kuswanto (), A.-C. Favre and E. Parent

Journal of the Royal Statistical Society Series C, 2015, vol. 64, issue 1, 75-92

Abstract: type="main" xml:id="rssc12062-abs-0001">

Weather predictions are uncertain by nature. This uncertainty is dynamically assessed by a finite set of trajectories, called ensemble members. Unfortunately, ensemble prediction systems underestimate the uncertainty and thus are unreliable. Statistical approaches are proposed to post-process ensemble forecasts, including Bayesian model averaging and the Bayesian processor of output. We develop a methodology, called the Bayesian processor of ensemble members, from a hierarchical model and combining the two aforementioned frameworks to calibrate ensemble forecasts. The Bayesian processor of ensemble members is compared with Bayesian model averaging and the Bayesian processor of output by calibrating surface temperature forecasting over eight stations in the province of Quebec (Canada). Results show that ensemble forecast skill is improved by the method developed.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1111/rssc.2014.64.issue-1 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:64:y:2015:i:1:p:75-92

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().