Impact of Observation Operators on Low-Level Wind Speed Retrieved by Variational Multiple-Doppler Analysis

Abstract

This study investigated the impact of observation operators on low-level wind speed analysis. An evaluation of wind speeds retrieved by variational multiple-Doppler analyses using radial velocities (V r ) based on the formats of both a Plan Position Indicator (PPI) (hereafter, PPI-VAR) and a Constant Altitude Plan Position Indicator (CAPPI) (hereafter, CAPPI-VAR) was performed for comparison with wind speeds observed by a wind profiler during the warm season of three consecutive years. The statistical analysis showed that PPI-VAR was more accurate than CAPPI-VAR at 500 m above ground level (AGL). The error of CAPPI-VAR at 500 m AGL was caused by a representative error of CAPPI-formatted V r derived from a certain radar whose beam height was far from the analysis level, and this error became more obvious the greater the vertical difference in wind speed across the analysis level. CAPPI-VAR uses CAPPI-formatted V r from each radar equally; thus, the representative error might cause performance degradation of CAPPI-VAR at 500 m AGL. Conversely, PPI-VAR uses PPI-formatted V r from each radar with appropriate weighting based on the beam height distance from the analysis level. PPI-VAR showed better results at 500 m AGL because the observation grid points were dense around 500 m AGL.

Quantitative Precipitation Estimation and Hydrological Modeling in Japan

“…The application of weather radar for hydrometeorological research in Japan has been described in many studies, but mainly for C-band (Kato and Maki 2009;Shusse et al, 2011;Kato et al, 2016) and X-band Hirano et al, 2010;Suzuki et al, 2010;Sakurai et al, 2012;Suzuki et al, 2012;Sakurai et al, 2015;Shusse et al, 2015;Shimose et al, 2016) wavelengths. Although C-band meteorological long-range radars are able to monitor rain fields over wide areas, they do not provide a sufficiently high spatial and temporal resolution, and have high purchase and maintenance costs.…”

Sensitivity Analysis on Data Time Difference for Wind Fields Synthesis of Array Weather Radar

“…A three-dimensional variational data assimilation (3DVAR) wind field retrieval method has been proved to provide more accurate wind analysis in the observation system simulation and real observation experiments. (e.g., Gao et al 1999Gao et al , 2004Shapiro et al 2009;Potvin et al 2011;Shimose et al 2016, North et al 2017Dahl et al 2019). However, the real precipitation system also rapidly moves and changes when the weather radar is performing a volume scanning.…”