Abstract
Complex terrain poses significant challenges to the radar based quantitative precipitation estimation (QPE) because of blockages to the lower tilts of radar observations. The blockages often force the use of higher tilts data to estimate precipitation at the ground and result in errors due to vertical variations of the radar variables. To obtain accurate radar QPEs in the subtropical complex terrain of Taiwan, a vertically corrected composite algorithm (VCCA) was developed for two C-band polarimetric radars. The new algorithm corrects higher tilt radar variables with the vertical profile of reflectivity (VPR) or vertical profile of specific differential phase (VPSDP) and estimates rainfall rate at the ground through an automated combination ofR-ZandR-KDPrelations. The VCCA was assessed with three precipitation cases of different regimes including typhoon, mei-yu, and summer stratiform precipitation events. The results showed that a combination ofR-ZandR-KDPrelations provided more accurate QPEs than each alone becauseR-Zprovides better rainfall estimates for light rains andR-KDPrelation is more suitable for heavy rains. The vertical profile corrections for reflectivity and specific differential phase significantly reduced radar QPE errors caused by inadequate sampling of the orographic enhancement of precipitation near the ground.
Highlights
Polarimetric radars have shown great potential in hydrometeorological researches and for operational applications in weather agencies
When radar beams at low tilts are blocked due to the complex terrains, the high tilt data is used in the rainfall estimated to achieve whole radar coverage quantitative precipitation estimation (QPE)
To avoid the biases caused by the vertical variations in precipitation system, techniques of vertical profile of reflectivity (VPR) and vertical profile of specific differential phase (VPSDP) were proposed in previous studies to correct the vertical variations in radar observations, and the resulted rainfall estimations were enhanced with the corrected radar variables
Summary
Polarimetric radars have shown great potential in hydrometeorological researches and for operational applications in weather agencies. Ryzhkov et al [9] developed a synthetic rainfall estimation algorithm on a Weather Surveillance Radar-1988 Doppler (WSR-88D) KOUN operated by National Severe Storms Laboratory (NSSL). This synthetic algorithm automatically selects the optimal estimator from the combination of R(Z, ZDR), R(KDP, ZDR), and R(KDP) according to various thresholds of rain intensities [9]. The new algorithm is unique in that it automatically combines locally derived R-Z and R-KDP relationships with VPR and VPSDP corrections It is physically based and computationally efficient, suitable for operational implementation.
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