Exploration of discrepancy between radar and gauge rainfall estimates driven by wind fields

Abstract

Due to the fact that weather radar is prone to several sources of errors, it is acknowledged that adjustment against ground observations such as rain gauges is crucial for radar measurement. Spatial matching of precipitation patterns between radar and rain gauge is a significant premise in radar bias corrections. It is a conventional way to construct radar-gauge pairs based on their vertical locations. However, due to the wind effects, the raindrops observed by the radar do not always fall vertically to the ground, and the raindrops arriving at the ground may not all be caught by the rain gauge. This study proposes a fully formulated scheme to numerically simulate the movement of raindrops in a three-dimensional wind field in order to adjust the wind-induced errors. The Brue catchment (135 km 2 ) in Southwest England covering 28 radar pixels and 49 rain gauges is an experimental catchment, where the radar central beam height varies between 500 and 700 m. The 20 typical events (with durations of 6-36 h) are chosen to assess the correlation between hourly radar and gauge rainfall surfaces. It is found that for most events, the improved rates of correlation coefficients are greater than 10%, and nearly half of the events increase by 20%. With the proposed method, except four events, all the event-averaged correlation values are greater than 0.5. This work is the first study to tackle both wind effects on radar and rain gauges, which could be considered as one of the essential components in processing radar observational data in its hydrometeorological applications.

Radar and rain gauge rainfall discrepancies driven by changes in atmospheric conditions

“…Besides the relative humidity, other meteorological variables (such as wind, which have been investigated on wind-induced error) [Collier, 1999;Nešpor and Sevruk, 1999;Duchon and Essenberg, 2001;Mittermaier et al, 2004;Lack and Fox, 2007;Fortin et al, 2008;Lauri et al, 2012;Dai et al, 2013Dai et al, , 2015Dai and Han, 2014] may also play important roles in resulting in radar-gauge rainfall discrepancies. Dai and Han [2014] proposed a scheme in tackling wind effects on radar-gauge comparison and found that it could be helpful in radar rainfall adjustment to some extent. However, the results also showed that radar-gauge rainfall agreement in some cases deteriorated due to the complicated atmospheric conditions, and it was not easily to be reproduced as it was region dependent.…”

Sensitivity analysis of raindrop size distribution parameterizations in WRF rainfall simulation

“…The normalized gamma distribution (Equation 1) is generally used as the DSD model of the disdrometer (e.g., JWD) because it allows easy comparisons of the DSD and reduces the DSD uncertainty owing to the absence of restrictions on the shape of raindrop spectra (Bringi et al, 2003;Dai and Han, 2014;Islam et al, 2012;Montopoli et al, 2008).…”

Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

“…5 minutes was chosen since this is sufficient time for raindrops larger than 1 mm, falling with a velocity of minimum 4 m/s (Beard, 1976), to travel the distance between the maximum elevation of the radar beam anywhere over the city to the ground. An optimal averaging period cannot, however, be computed simply by looking at the drops vertical fall velocity, since rain drops fall with different velocities depending on drop sizes and metrological conditions (Beard, 1976) and seldom fall vertically as pointed out by Dai and Han (2014). Note that due to the 5 minute averaging period α is actually calculated based on the previous T ad + 4 minutes of data.…”