NDLI: Improvement of Local Categorical Precipitation Forecasts from an NWP Model by Various Statistical Postprocessing Methods

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Improvement of Local Categorical Precipitation Forecasts from an NWP Model by Various Statistical Postprocessing Methods

Content Provider	Springer Nature Link
Author	Sokol, Zbyněk Řezáčová, Daniela
Copyright Year	2000
Abstract	Several statistical postprocessing methods are applied to results from a numerical weather prediction (NWP) model to test the potential for increasing the accuracy of its local precipitation forecasts. Categorical (Yes/No) forecasts for 12hr precipitation sums equalling or exceeding 0.1, 2.0 and 5.0 mm are selected for improvement. The two 12hr periods 0600-1800 UTC and 1800-0600 UTC are treated separately based on NWP model initial times 0000 UTC and 1200 UTC, respectively. Input data are taken from three successive summer seasons, April-September, 1994-96. The forecasts are prepared and verified for five synoptic stations, four located in the western Czech Republic, and one in Germany near the Czech-German border. Two approaches to statistical postprocessing are tested. The first uses Model Output Statistics (MOS) and the second modifies the MOS approach by applying a successive learning technique (SLT). For each approach several statistical models for the relationship between NWP model predictors and predictand were studied. An independent data set is used for forecast verification with the skill measured by a True Skill Score. The results of the statistical postprocessing are compared with the direct model precipitation forecasts from gridpoints nearest the stations, and they show that both postprocessing approaches provide substantially better forecasts than the direct NWP model output. The relative improvement increases with increasing precipitation amount and there is no significant difference in performance between the two 12hr periods. The skill of the SLT does not depend significantly on the size of the initial learning sample, but its results are nevertheless comparable with the results obtained from the MOS approach, which requires larger developmental samples.
Starting Page	38
Ending Page	56
Page Count	19
File Format	PDF
ISSN	00393169
Journal	Studia Geophysica et Geodaetica
Volume Number	44
Issue Number	1
e-ISSN	15731626
Language	English
Publisher	Kluwer Academic Publishers-Plenum Publishers
Publisher Date	2000-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Structural Geology Geophysics/Geodesy Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Geochemistry and Petrology Geophysics

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