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The most widely used device to measure rainfall is the tipping bucket rain gauge (TBR), although there is no standard design. The precision and accuracy of TBR measurements vary, and calibration procedures are dependent upon the organisation or institution operating a network. Consequently, rainfall datasets may be heterogeneous and not easily comparable. Environmental conditions at the gauge orifice also adversely influence the accuracy of measurement. The height at which the gauge is mounted has a significant influence on the gauge catch. Reference measurements can be made using a rain gauge in a pit structure, with the gauge orifice positioned at ground level. Different types of rainfall events, occurring in differing geographical and micro-topographical contexts, vary the influence of the wind on rainfall measurement. Hence, it is difficult to develop and apply an allencompassing correction procedure for wind using empirical observational methods alone. Computational Fluid Dynamics (CFD) provides an ideal framework within which to develop an understanding of how wind affects catch accuracy. Observational data from the field can be used to validate CFD simulations and enhance correction algorithms.

Intercomparison of rainfall measurements from three different types of weather radars covering the same urban area