July 2023
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Several large-scale networks using automated ceilometers and LiDARs now exist. Some networks, such as MPLNET, have developed algorithms that can be applied uniformly across all instruments. However, cross-network tools are not so readily available such as those used for cloud base height comparison. The London (CDN) node of the CANadian Micro-pulse LiDAR Network (MPLCAN) hosts both a miniHD MPL (MPLNET) and Lufft 15k ceilometer (European E-PROFILE network). Each has its own algorithm to estimate cloud base height. The MPL algorithm was developed by the NASA Langley MPLNET team, and the ceilometer has the manufacturers provided Sky Condition Algorithm. The cloud base should be in principle the same for these co-located instruments. Using the MPLNET vs. Lufft measurements for the first year of operation, the monthly correlation coefficient, R, varies between 0.45 and 0.97. This difference between instruments is mostly accounted for by a poor comparison below 1 km due to aerosols, precipitation, and overlap uncertainties. Applying a gradient-based algorithm (GBD) onto the measurements improves the worst comparison to greater than \(R = 0.9\). However, this GBD algorithm has low accuracy with decreased signal to noise. Thus, we can utilize this tool to help verify the overall agreement of measurements between these 2 instruments, and it offers a tool for standard processes of the 2 instruments.