A method to adapt radar‐derived precipitation fields for climatological applications. (21st April 2015)

• Record Type: Journal Article
• Authors: Kronenberg, R.; Bernhofer, C.
• Is Part Of: Meteorological applications. Volume 22:Number 3(2015:Sep.)
• Page Start: 636
• Page End: 649
• Publication Date: 2015-04-21
• Subjects: Meteorology -- Periodicals; Meteorological services -- Periodicals; 551.5
• DOI: 10.1002/met.1498
• Languages: English
• ISSNs: 1350-4827

Abstract

<abstract abstract-type="main" id="met1498-abs-0001"> <title>ABSTRACT</title> <p id="met1498-para-0001">In the present study, a rapid and simple approach is presented to rearrange long‐term precipitation fields (i.e. periods ≥ 1 year) from a multi‐site radar product, which were originally derived on an hourly basis as quantitative precipitation estimates (QPEs) for flood risk forecasting and management. The method consists of interquartile outlier detection and linear transformations to achieve a better representation of elevation above sea level (asl). The presented approach was deployed in the Free State of Saxony, Germany, for the period from April 2004 through December 2009. The results are compared with two independently derived and highly resolved gridded precipitation data sets (i.e. 1 km resolution). An algorithm based on the golden section search and parabolic interpolation was deployed to determine an optimal set of parameters. The results show a significant increase in quality in the long‐term precipitation information in comparison to the original QPEs. Hence, a more reasonable order of the correlation and of the empirical histogram could be obtained after processing. The scorings within the means of the Taylor diagram show that the patterns of the compared data sets are very similar. It can be inferred that the results support the application of the introduced procedure for the adjustment of QPEs for periods of 1 year and greater because a more realistic appearance of the climatological precipitation field can be achieved; in addition, it is an approach that is simple and reliable. The results can be used for climatological analysis and should help in the application of radar products for improving station‐based precipitation climatology.</p> </abstract>