Adjustment of one-minute rain gauge time series using co-located drop size distribution and wind speed measurements

. A procedure to adjust rainfall intensity (RI) measurements to account for the wind-induced measurement bias of 10 traditional catching-type gauges is proposed and demonstrated with application to a suitable case study. The objective is to demonstrate that adjustment curves derived from numerical simulation and disdrometer measurements allows for a-posteriori correction of rainfall time series based on the wind velocity measurements alone. One-minute RI measurements from a cylindrical tipping-bucket rain gauge installed at the Hong Kong Observatory are adjusted to quantify the impact of wind on long-term records. Catch ratios deriving from the instrument aerodynamic behaviour under varying wind speed and drop size 15 combinations are obtained by fitting computational fluid-dynamic simulation results already available in the literature. Co-located high-resolution wind speed measurements from a cup and vane sensor and drop size distribution measurements from an optical video disdrometer (the 2DVD) are used to infer the collection efficiency of the gauge as a function of wind speed and RI alone, and to adjust raw data from a four-year dataset (2018-2021) of one-minute RI measurements. Due to the specific local climatology, where strong wind is often associated with intense precipitation, adjustments are limited to 4% of the RI 20 values in 80% of the dataset. This however results in a significant amount of available freshwater resources that would be missing from the calculated hydrological and water management budget of the region should the adjustments be neglected. This work raises the need of quantifying the impact of the wind-induced bias in other sites where disdrometer data support characterizing the relationship between the drop size distribution and the measured RI. Depending on the local rain and wind climatology the correction may account for a significant portion