## 2 Materials and Methods  
### Metrologies for Measuring Rainfall Rates and Droplet Size Distributions  
Most national meteorological measurement networks use heated tipping-bucket or weighing rain gauges to measure liquid-equivalent precipitation accumulation over a time interval (i.e., the RR). These data are often reported with a resolution of one hour [86], although some countries report data for selected sites at higher temporal resolution [87]. Some meteorological services equip these rain gauges with wind shields to reduce precipitation under-catch (particularly of snow) under high wind conditions [88]. Rain gauges remain the primary source of ground-truth information regarding precipitation receipt at the ground. Good agreement for daily accumulated precipitation (within \(\pm 10\%\)) is generally reported from closure experiments [86]. These measurements, plus RR and hydrometeor phase estimated from ground-based dual polarization Doppler RADAR [89; 90], are extremely important to hydrological applications [91]. They have relevance to, but are not sufficient for, estimation of kinetic energy transfer to wind turbine blades. This specific application requires high temporal resolution in order to capture high intensity but short duration precipitation events, plus information regarding the DSD. Thus, in past analyses, estimates of RR and hail occurrence from tipping bucket or weighing rain gauges and/or derived from ground-based dual polarization Doppler RADAR have been combined with approximations of DSD as a function of RR (Equations (6)-(11)) and simultaneous WS observations to derive estimations of time varying and annual accumulated kinetic energy transfer to wind turbine blades [78; 92]. However, such estimates are critically dependent on the degree to which the assumed rain and hail DSD represent real atmospheric conditions. Precipitation DSD can be measured using a range of different metrologies [93]. Two-dimensional video disdrometers (VDIS) comprises two video cameras with perpendicular lines of sight [94; 95]. Objects passing through the measurement area obstruct the light and are detected as shadows by the cameras [96; 97]. Impact disdrometers work by recording the kinetic energy transferred due to the impact of a falling hydrometeor on a detector [98; 99]. Acoustic disdrometers work by detecting the acoustic signal generated by rain droplet impacts on a diaphragm [93]. Herein we present data primarily from optical disdrometers (also known as light occlusion instruments) that measure droplet number and fall velocity in a number of diameter classes by detecting the breaking of a horizontal light sheet by the passage of the hydrometeors [95; 100; 101]. As with rain gauges, the quality of data obtained from disdrometers can be influenced by wind-induced under-sampling of hydrometeors [102; 103] and reporting of unrealistically low \(v_{t}\) for large \(D\) in high wind speeds [104]. In situ dichometers are also subject to interference from other droplets (e.g., sea spray or splash) in the sample volume [103; 105]. Thus, all disdrometers should be shielded using similar technologies to those deployed for rain gauges. The process of translating the signal from a disdrometer to number density normalized by the diameter range covered in a given class is shown in Equation (13) and described below using the example of the 2 nd generation OTT Particle size and velocity (Parsivel\({}^{2}\)) optical disdrometer [95; 106]:  
\[N(D_{i})\ =\ \frac{n_{i}}{Ftv_{t}(D_{i})\Delta D_{i}} \tag{13}\]  
where \(n_{i}\) = number count in diameter class \(i\) (\(D_{i}\) in mm), \(\Gamma\) = area field of view of the disdrometer (0.0054 m\({}^{2}\) for the OTT Parsivel\({}^{2}\) disdrometer), \(t\) = sampling interval (typically 60 s), \(v_{t}(D_{i})\) = fall velocity of a drop of that diameter (ms\({}^{-1}\)), \(\Delta D_{i}\) = width of the size class (mm). \(N(D_{i})\) thus has units of the number per cubic meter of air per mm.