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Estimating radar precipitation in cold climates: the role of air temperature within a non-parametric framework

Abstract. The 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.
