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Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

Lookup NU author(s): Professor Andras Bardossy

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

The use of radar measurements for the space time estimation of precipitation has for many decades beena central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-dailyextreme values of precipitation at gauged or ungauged locations which are important for design. The purposeof the paper is to develop a methodology to combine daily precipitation observations and radarmeasurements to estimate sub-daily extremes at point locations. Radar data corrected usingprecipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities ofcorrecting systematic errors using the daily observations are investigated. Observed gauged dailyamounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily valuesobtained by the radar. Different corrections based on the spatial variability and the subdaily entropyof scaled rainfall distributions are used to provide unbiased corrections of short duration extremes.Additionally a statistical procedure not based on a matching day by day correction is tested. In this lastprocedure as we are only interested in rare extremes, low to medium values of rainfall depth wereneglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typicallycomprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolatedusing a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbourprocedure. The daily sums are then disaggregated by using the relative values of the biggest L radarbased days. Of course, the timings of radar and gauge maxima can be different, so the method presentedhere uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract themaxima of sub-hourly through to daily rainfall.The methodologies were tested in South Africa, where an S-band radar operated relatively continuouslyat Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 kmspacing) set of 45 pluviometers recording in the same 6-year period. This valuable set of data wasobtained from each of 37 selected radar pixels [1 km square in plan] which contained a pluviometernot masked out by the radar foot-print. The pluviometer data were also aggregated to daily totals, forthe same purpose. The extremes obtained using disaggregation methods were compared to the observedextremes in a cross validation procedure. The unusual and novel goal was not to obtain the reproductionof the precipitation matching in space and time, but to obtain frequency distributions of the pointextremes, which we found to be stable.


Publication metadata

Author(s): Bardossy A, Pegram G

Publication type: Article

Publication status: Published

Journal: Journal of Hydrology

Year: 2017

Volume: 544

Pages: 397-406

Print publication date: 01/01/2017

Online publication date: 24/11/2016

Acceptance date: 19/11/2016

Date deposited: 06/09/2017

ISSN (print): 0022-1694

Publisher: Elsevier

URL: https://doi.org/10.1016/j.jhydrol.2016.11.039

DOI: 10.1016/j.jhydrol.2016.11.039


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