## 2 Materials and Methods
### Metrologies for Measuring Rainfall Rates and Droplet Size Distributions
The Thies LPM thermometer uses a wavelength (\(\lambda_{\rm w}\)) of 785 nm, while the OTT Parsivel\({}^{2}\) operates at a \(\lambda_{\rm w}\) = 650 nm. The Thies LPM used at sites in the UK Disdrometer Verification Network (DiVeN) experiment [111] employs 20 diameter classes from \(\geq\)0.125 mm to \(>\)8 mm and 20 velocity classes from 0 ms\({}^{-1}\) to 10 ms\({}^{-1}\). For the OTT Parsivel\({}^{2}\) disdrometer the 32 measured size classes range from mid-point diameters of 0.0619 to 24 mm and the 32 velocity classes range from 0.2 to 20 ms\({}^{-1}\). The OTT Parsivel\({}^{2}\) manual denotes an expected accuracy of \(\pm\)10% in RR but does not provide information regarding the expected accuracy of the DSD. Previous work has reported highest relative uncertainty for low RR, larger diameter hydrometeors and short integration times [112]. For example, a study reported a sampling uncertainty in number concentrations of 5-11% for \(D\) of 1-2 mm, and for a \(D\) of 1.5 mm, an uncertainty of 8% for 1 min samples to 4.5% for a 10-min sampling period [103]. The presence of solid hydrometeors (snow, graupel, hail) is represented in data output from the OTT Parsivel\({}^{2}\) using the World Meteorological Organization (WMO) synoptic present weather codes (WC). WC of 71-73, inclusive indicate snow. WC of 87 (RR \(<\) 1 mmhr\({}^{-1}\), soft hail), 88 (RR \(\geq\) 1 mmhr\({}^{-1}\), soft hail), 89 (RR \(<\) 2.5 mmhr\({}^{-1}\), hail) and 90 (RR \(\geq\) 2.5 mmhr\({}^{-1}\), hail). The hydrometeor type classification is based on a combination of the \(v_{t}\), and \(D\) following a look-up chart approach [100; 113]. All optical disrometers exhibit some uncertainty due to incorrect \(v_{t}\) assigned to hydrometeors that fall through the edge of the sampling area [112] and/or strong winds causing misclassification of hydrometeor type. Present Weather Sensors (PWS) such as the Campbell Scientific PWS100 [39] use two or three optical sensors and measure the scintillation as individual hydrometeors pass through the illuminated volume. Hydrometeor type is determined by the relative contributions of light reflection, refraction and diffraction [39]. The PWS100 has been withdrawn from service, but measured droplet sizes range from 0.1 to 30 mm in 34 diameter classes and 34 velocity classes [114]. Ground-based remote sensing devices are also available that can also be used to infer RR and the size distribution of hydrometeors. Micro-rain RADAR (MRR) are active vertically pointing remote sensing systems. The Doppler shift of the backscattered radiation scales with the fall velocity of hydrometeors, which in turn is a function of their size. For MRR an assumption is made that the fall velocity of a droplet is equal to the terminal fall velocity which thus assumes the droplets are embedded in still air which is a source of uncertainty in deeply convective environments. The strength of the signal (backscatter intensity) scales with the number and size of hydrometers. Hence, the DSD can be computed and used to obtain an inferred RR. MRR provide the vertical profile (to heights of several kilometers) of hydrometeor properties including DSD at high temporal sampling rates (every 10 s) [115; 116; 117]. New techniques are being actively pursued to derive robust assessment of precipitation type based on the hydrometeor fall velocity, equivalent RADAR reflectivity, and diameter plus the presence (or not) of a bright band [118]. A key challenge in use of such technology is linking properties above the surface (even in cloud) to those at the ground, and modification of the hydrometeors as they fall through the atmosphere. An additional area of active instrument development pertains to detection and sizing of hail. Hail pads are simple and cheap and hence have been used in community-based networks (e.g., Community Collaborative Rain, Hail and Snow network (CoCoRaHS) [119]). However, they provide time-integrated measurements and are labor intensive.