Show simple item record

dc.contributor.authorGascón, Estíbaliz
dc.contributor.authorHewson, Tim
dc.contributor.authorHaiden, Thomas
dc.date.accessioned2019-09-19T10:05:17Z
dc.date.available2019-09-19T10:05:17Z
dc.date.copyright11/29/2017 12:00:00 AM
dc.date.issued2017
dc.identifier.otherwaf-d-17-0114.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261377
dc.description.abstractAbstractThe medium-range ensemble (ENS) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) is used to create two new products intended to face the challenges of winter precipitation-type forecasting. The products themselves are a map product that represents which precipitation type is most likely whenever the probability of precipitation is >50% (also including information on lower probability outcomes) and a meteogram product, showing the temporal evolution of the instantaneous precipitation-type probabilities for a specific location, classified into three categories of precipitation rate. A minimum precipitation rate is also used to distinguish dry from precipitating conditions, setting this value according to type, in order to try to enforce a zero frequency bias for all precipitation types. The new products differ from other ECMWF products in three important respects: first, the input variable is discretized, rather than continuous; second, the postprocessing increases the output information content; and, third, the map-based product condenses information into a more accessible format. The verification of both products was developed using four months? worth of 3-hourly observations of present weather from manual surface synoptic observation (SYNOPs) in Europe during the 2016/17 winter period. This verification shows that the IFS is highly skillful when forecasting rain and snow, but only moderately skillful for freezing rain and rain and snow mixed, while the ability to predict the occurrence of ice pellets is negligible. Typical outputs are also illustrated via a freezing-rain case study, showing interesting changes with lead time.
dc.publisherAmerican Meteorological Society
dc.titleImproving Predictions of Precipitation Type at the Surface: Description and Verification of Two New Products from the ECMWF Ensemble
dc.typeJournal Paper
dc.journal.volume33
dc.journal.issue1
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-17-0114.1
dc.journal.fristpage89
dc.journal.lastpage108
dc.treeWeather and Forecasting:;2017:;volume 033:;issue 001
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record