We present recent progress related to the night-time retrievals of aerosol and cloud optical depth using starphotometry over the PEARL (Polar Environmental Atmospheric Research Laboratory) station at Eureka (Nunavut, Canada) in the High Arctic (80° N, 86° W). In the spring of 2011 and 2012, the SPSTAR starphotometer was employed to acquire aerosol optical depth (AOD) measurements while vertical aerosol and cloud backscatter coefficient profiles were acquired using the CANDAC Raman Lidar (CRL). Several events were detected and characterized using starphotometry-lidar synergy: aerosols (short term aerosol events on 9 and 10 March 2011); a potential multi-night aerosol event across three polar nights (13–15 March 2012), a thin cloud event (21 February 2011) and a very low altitude ice crystals (10 March 2011). Using a simple backscatter coefficient threshold criterion we calculated fine and coarse (sub and super-micron) mode AODs from the vertically integrated CRL profiles. These were compared with their starphotometry analogues produced from a spectral deconvolution algorithm. The process-level analysis showed, in general, good agreement in terms of the physical coherence between high frequency starphotometry and lidar data. We argue that R2 (coefficient of determination) is the most robust means of comparing lidar and starphotometer data since it is sensitive to significant optico-physical variations associated with these two independent data sources while being minimally dependent on retrieval and calibration artifacts. Differences between the fine and course mode components of the starphotometry and lidar data is clearly also useful but is more dependent on such artifacts. Studying climatological seasonal aerosol trends necessitates effective cloud-screening procedures: temporal and spectral cloud screening of starphotometry data was found to agree moderately well with temporal cloud screening results except in the presence of thin homogeneous cloud. We conclude that better screening conditions can be implemented to arrive at a robust method for combined temporal/spectral cloud-screening of starphotometer (and possibly sunphotometer) data. In general, as our understanding of process-level details increases with growing datasets, we will inevitably have more confidence in bulk climatological analyses of ground-based and satellite retrievals of aerosol parameters where conditions are less than ideal because of the weakness of the polar winter aerosol signal.