For over a century, the electric Potential Gradient (PG) of the atmosphere has been measured and studied. The local vertical electric field (Ez) is strongly influenced by the presence of lightning, electrified clouds, rainfall, aerosols, and many others. The One Year Electric Field Study-North Slope of Alaska (OYES-NSA) field campaign was established in the summer of 2017 to measure the vertical electric field at the ARM site in Barrow, Alaska alongside a wide array of supplementary instrumentation, including a Micro-Pulse Lidar and upward facing Ka-band radar. Two years of observations (072017-062019) have shown the possibility to quantify the local effects from aerosols and clouds observed by the Lidar and Radar on the measured EZ. Throughout the manuscript, the physics convention of negative downward fair-weather electric fields is used. Three cases (convective clouds, high concentration of near surface aerosols, and blowing snow) are used to demonstrate the localized effects on the measured EZ. Utilizing the relationships between EZ and backscatter/reflectivity, we have developed a methodology to distinguish samples with local influences. A fair-weather (FW) condition is determined to be associated with a low Lidar backscattering (less than 15 km−1sr−1), in the presence of no significant cloud activity (radar reflectivity less than −10dBZ). The samples satisfying these criteria are found with a 5-min averaged standard deviation of less than 15 V/m, and EZ between −250 V/m to −50 V/m. Using only properties of the EZ measurements allows for the simultaneous comparisons of FW at multiple sites, without the need for supplementary information of local weather conditions. Simultaneous EZ measurements from 8 FW cases are shown between Barrow, AK and Corpus Christi, TX on the timescale of minutes to hours. Similar variation patterns in the FW EZ are shown at both sites, providing evidence of the global nature of the atmospheric electric system. Furthermore, the seasonal-diurnal variability of FW at multiple sites shows similar distributions of the PG.