Arctic primary producer phenology is undergoing shifts attributed to the increased transmission of light resulting from climate change-induced declines in sea ice thickness, age, and extent. However, the investigation of phenological events, particularly near the ocean surface, is challenging due to limited time-series observations caused by logistical constraints and accessibility issues. Data collected from a subsurface oceanographic mooring deployed in Dease Strait, Nunavut, from 2017 to 2019 were used to determine primary producer biomass using the normalized difference index (NDI) chlorophyll-a retrieval algorithm. Sentinel-1 and RADARSAT-2 synthetic aperture radar (SAR) data and related meteorological variables were used to identify snow and sea-ice melt phase timing. The results revealed a relationship between light availability and surface primary producer timing and magnitude. Specifically, an 18-day difference in the length of ice algal blooms between 2017 and 2019 was observed, with both blooms peaking near snow melt onset and exhibiting similar daily production rates. The extended duration of the 2019 ice algal bloom was due to lower air temperatures compared to 2017, and a deeper snowpack prior to snow melt. Moreover, a 6-7 day under-ice phytoplankton bloom occurred in both years, coinciding with melt pond formation. However, the 2019 under-ice bloom exhibited a lower accumulation rate, likely due to nutrient depletion beneath the ice by the prolonged ice algal bloom. Following ice break-up in 2019, a 31-day late-summer bloom occurred via sustained wind-driven mixing, highlighting the importance of ocean-atmosphere coupling in the region following ice break-up. The findings of this thesis provide a novel approach to investigating surface primary producer phenology and suggest the potential application of this technique to support future long-term monitoring.