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dc.contributor.authorSivasubramaniam, Kuganesan
dc.contributor.authorAlfredsen, Knut
dc.contributor.authorSharma, Ashish
dc.description.abstractThe use of ground-based precipitation measurements in radar precipitation estimation is well known in radar hydrology. However, the approach of using gauged precipitation and near-surface air temperature observations to improve radar precipitation estimates in cold climates is much less common. In cold climates, precipitation is in the form of snow, rain or a mixture of the two phases. Air temperature is intrinsic to the phase of the precipitation and could therefore be a possible covariate in the models used to ascertain radar precipitation estimates. In the present study, we investigate the use of air temperature within a non-parametric predictive framework to improve radar precipitation estimation for cold climates. A non-parametric predictive model is constructed with radar precipitation rate and air temperature as predictor variables and gauge precipitation as an observed response using a k nearest neighbour (k-nn) regression estimator. The relative importance of the two predictors is ascertained using an information theory-based weighting. Four years (2011– 2015) of hourly radar precipitation rates from the Norwegian national radar network over the Oslo region, hourly gauged precipitation from 68 gauges and gridded observational air temperatures were used to formulate the predictive model, hence making our investigation possible. Gauged precipitation data were corrected for wind-induced under-catch before using them as true observed response. The predictive model with air temperature as an added covariate reduces root-mean-square error (RMSE) by up to 15 % compared to the model that uses radar precipitation rate as the sole predictor. More than 80 % of gauge locations in the study area showed improvement with the new method. Further, the associated impact of air temperature became insignificant at more than 85 % of gauge locations when the near-surface air temperature was warmer than 10 ◦C, which indicates that the partial dependence of precipitation on air temperature is most useful for colder temperatures.nb_NO
dc.publisherCopernicus Publicationsnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleEstimating Radar Precipitation in Cold Climates: The role of Air Temperature within a Nonparametric Frameworknb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.source.journalHydrology and Earth System Sciences Discussionsnb_NO
dc.description.localcode(C) Author(s) 2018. CC BY 4.0 License.nb_NO
cristin.unitnameInstitutt for bygg- og miljøteknikk

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal