Improvement of 6–15 day precipitation forecasts using a time-lagged ensemble method View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-03

AUTHORS

Weihua Jie, Tongwen Wu, Jun Wang, Weijing Li, Xiangwen Liu

ABSTRACT

A time-lagged ensemble method is used to improve 6–15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model, version 2.0.1. The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs, all at the same forecast valid time. This lagged average forecast (LAF) method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean. Our analyses of the Equitable Threat Score, the Hanssen and Kuipers Score, and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6–15 day forecasts of precipitation frequency above 1 mm d−1 and 5 mm d−1 in many regions of China, and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members. In particular, significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40%–50% in the summer season; these regions include northeastern and central to southern China, and the southeastern Tibetan Plateau. More... »

PAGES

293-304

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00376-013-3037-8

DOI

http://dx.doi.org/10.1007/s00376-013-3037-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1031783407


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