## 4 Discussion  
Questions remain about the precise mechanisms that lead to wind turbine blade LEE and the relative importance of hydroclimatic drivers relative to other geophysical stressors and manufacturing defects such as the presence of air bubbles in the top coating [20]. Given trends towards use of larger rotors and tip speeds, as well as current high cost of repairing blades due to LEE [7; 10], it is of high importance to establish which mechanisms are responsible for blade damage. As a part of this work, there is an urgent need for high fidelity, repeatable and comparable measurements of wind speeds and hydrometeor characteristics in areas with high wind resources and/or wind turbine deployments. Such data are necessary to generate robust assessments of the hydroclimate and the joint probabilities (at high temporal resolution) of high wind speeds with high RR, large droplet diameters and hail occurrence. Currently, the greatest challenge to interpreting joint probability distributions of RR and wind speed, and in ultimately constructing joint probability distributions of DSD or \(D_{m}\) and wind speed are the short durations of the measured time series. The greatest challenge to developing a comprehensive understanding of geospatial variability in likely LEE rates is the lack of publicly accessible data from disdrometers and wind speeds in high wind energy resource areas outside North America and Europe. Investment to generate high-quality, long-term, publicly accessible data at wind energy relevant locations will help to continue historical trends towards lower operating costs [154] and overall LCoE from wind [155]. Reduction of the uncertainty regarding the conditions to which wind turbines are subjected and linking geophysical measurements to actual wind turbine blade damage reports will also yield improved cost-benefit analyses of erosion prevention measures. Industry-wide solutions to reduce AEP loss due to LEE will be greatly enabled by advanced metrologies for geophysical site characterization and access to high fidelity, controlled and repeatable wind turbine blade inspection photographs and maintenance records. The remote sensing community is evolving new satellite-based metrologies to derive global and spatially explicit estimates of hydroclimates including not only rainfall rates, but hydrometeor phase and droplet size distribution [70; 156; 157]. Additionally numerical modeling is being performed at so-called convection permitting grid resolution (grid spacing of < 4 km) and with very detailed microphysics schemes with a goal of quantifying relative LEE potential. Such high-resolution simulations with the Weather Research and Forecasting (WRF) model exhibit some promise in terms of reproducing critical aspects of the hydroclimate and wind speeds [128; 129]. This type of numerical modeling or enhanced high-resolution remote sensing products may ultimately yield data sufficient to, when combined with wind speed measurements or model output, yield a comprehensive global atlas of annual accumulated kinetic energy transfer to wind turbine blades and hence LEE potential. However, in numerical models, RR, hydrometeor phase and DSD exhibit a strong dependence on the microphysics scheme selected [158] and are only partly validated. Additionally, the computational costs of such simulations are high [159; 160]. Further, satellite-based precipitation products are subject to a range of uncertainties (e.g., gap filling [161]), and at the daily scale exhibit lower fidelity than WRF simulations [162]. Thus, it seems likely that in the near-term there will be continue reliance on in situ and/or ground based instrumentation to collect the data necessary for ground-truthing of numerical model simulations and/or assessment of LEE potential. Analyses presented herein reaffirm that the specific instrument (i.e., type of disdrometer) from which DSD are drawn has a profound influence on the resulting DSD and RR.