Numerical simulations of radar rainfall error propagation

Abstract

[1] The primary advantage of radar observations of precipitation compared with traditional rain gauge measurements is their high spatial and temporal resolution and large areal coverage. Unfortunately, radar data require vigorous quality control before being converted into precipitation products that can be used as input to hydrologic models. In this study we coupled a physically based atmospheric model of convective rainfall with an active microwave radiative transfer model to simulate radar observation of thunderstorms. We used the atmospheric model to simulate a well-documented tornadic supercell storm that occurred near Del City, Oklahoma, on 20 May 1977. We then generated radar observations of that storm and used them to evaluate the propagation of radar rainfall errors through distributed hydrologic simulations. This physically based methodology allows us to directly examine the impact of radar rainfall estimation errors on land-surface hydrologic predictions and to avoid the limitations imposed by the use of rain gauge data. Results indicate that the geometry of the radar beam and coordinate transformations, due to radar-watershed-storm orientation, have an effect on radar rainfall estimation and runoff prediction errors. In addition to uncertainty in the radar reflectivity versus rainfall intensity relationship, there are significant range-dependent and orientation-related radar rainfall estimation errors that should be quantified in terms of their impact on runoff predictions. Our methodology provides a tool for performing experiments that address some operational issues related to the process of radar rainfall estimation and its uses in hydrologic prediction.

Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

“…Ground-based weather radar networks provide continuous coverage with high spatial and temporal resolution at the regional scale. However, despite the advantages of radar for rainfall retrievals, the use of such techniques does have limitations, e.g., over mountain regions, which includes beam blockage, ground clutter, cold weather and their interaction with vertical structure [1,[9][10][11][12][13][14][15][16]. In addition, the high costs of radar usage also limit its application especially for the developing countries.…”

Statistical analysis of error propagation from radar rainfall to hydrological models

“…Krajewski et al (1993) and Anagnostou and Krajewski (1997) proposed and extended a physically based simulator of radar observations according to a two-dimensional time-space stochastic modelling of radar errors, combined with a vertical structure of hydrometeors and a statistically generated drop-size distribution. Sharif et al (2002Sharif et al ( , 2004) coupled a physicsbased mesoscale atmospheric model, a three-dimensional radar simulator, and a two-dimensional infiltration-excess hydrological model to analyse the radar beam geometric and sampling-related effects. It showed that radar-watershedstorm orientation-related errors in Horton runoff predictions increase significantly due to range effects, particularly beyond about 80 km.…”

Analysis of radar-rainfall error characteristics and implications for streamflow simulation uncertainty

“…The interaction of VPR errors with model parametric uncertainty was investigated recently by Hossain et al (2004). Radar beam geometric and sampling-related effects were analysed by Sharif et al (2002), which showed that range effects and storm-watershed orientationrelated errors get amplified through runoff predictions.…”