Articles | Volume 22, issue 1
Research article
12 Jan 2018
Research article |  | 12 Jan 2018

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Jérémy Chardon, Benoit Hingray, and Anne-Catherine Favre


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by Editor and Referees) (06 Sep 2017) by Luis Samaniego
AR by Benoit Hingray on behalf of the Authors (22 Nov 2017)  Author's response    Manuscript
ED: Publish as is (24 Nov 2017) by Luis Samaniego
Short summary
We present a two-stage statistical downscaling model for the probabilistic prediction of local precipitation, where the downscaling statistical link is estimated from atmospheric circulation analogs of the current prediction day. The model allows for a day-to-day adaptive and tailored downscaling. It can reveal specific predictors for peculiar and non-frequent weather configurations. This approach noticeably improves the skill of the prediction for both precipitation occurrence and quantity.