Effects of Rain Gauge Temporal Resolution on the Specification of a Z–R Relationship

Abstract

The weather radar is an efficient alternative for measuring spatially varying rainfall covering a large area at a high temporal resolution. This paper studies the impact of rainfall gauge temporal resolution on optimal relationships between radar reflectivity (Z) and rainfall rate (R). Four datasets of radar reflectivity and corresponding rain gauge rainfall data from Sydney and Brisbane, Australia, and one dataset from Bangkok, Thailand, were used in the analysis. Climatological Z-R relationships were calibrated using rainfall aggregated over 1-24 h to investigate the evidence of temporal scaling in the Z-R calibrated parameters. This analysis points to an increase in the multiplicative term (the A parameter) of the Z-R relationship as temporal resolutions become finer. This pattern is repeated in all the datasets analyzed. Thereafter, a simple scaling hypothesis was proposed to develop transformations that could scale the A parameter in the Z-R relation across a range of temporal resolutions. This scaling relationship was found to be suitable, with the scaling exponent attaining values close to 0.055 across all the datasets analyzed. The proposed relationship has a significant role in radar rainfall estimation studies, especially in regions where subdaily gauge rainfall measurements are not readily available to ascertain optimal Z-R parameters.

An evaluation of numerical weather prediction based rainfall forecasts

“…Each parameter set (α and β), which was estimated for each event, was used to calculate the new radar rain rates for the individual event over the entire northern part of the radar coverage using the power-law relationship in equation (2). This event-dependent calibration method accounts for the dependency of the Z-R relationship on rainfall characteristics such as rainfall drop size distribution, which varies in both space and time (Atlas et al, 1999;Mapiam et al, 2009). …”

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“…The empirical coefficients depend on climate characteristic in each area exclusively [11]. A lot of researches have been done to determinate Z-R relationships and relevant regional coefficient [12]. More than 100 relationships are available for different rainfall form such as strait form, tropical, convective, thunderstorm, shower, monsoon and hurricanes [7].…”

An improved algorithm in unipolar weather radar calibration for rainfall estimation

“…The A and b are empirical coefficients which refer to climatological characters, location of rainfall, rainfall seasons, geographic latitudes [11,12] and rainfall time duration [13,14]. The empirical coefficients depend on climate characteristic in each area exclusively [15], and were used to determine Z-R relationships and relevant regional coefficient [16]. More than 100 relationships are available for different rainfall forms such as strait form, tropical, convective, thunderstorm, shower, monsoon and hurricanes [9].…”