Greenland's marine-terminating glaciers connect the ice sheet to the ocean and provide a critical boundary where heat, freshwater, and nutrient exchanges take place. Buoyant freshwater runoff from inland ice sheet melt is discharged at the base of marine-terminating glaciers, forming vigorous upwelling plumes. It is understood that subglacial plumes modify waters near glacier fronts and increase submarine glacier melt by entraining warm ambient waters at depth. However, ocean observations along Greenland's coastal margins remain biased toward summer months which limits accurate estimation of ocean forcing on glacier retreat and acceleration. Here, we fill a key observational gap in northwest Greenland by describing seasonal hydrographic variation at glacier fronts in Melville Bay using in situ observations from moorings deployed year-round, CTDs, and profiling floats. We evaluated local and remote forcing using remote sensing and reanalysis data products alongside a high-resolution ocean model. Analysis of the year-round hydrographic data revealed consistent above-sill seasonality in temperature and salinity. The warmest, saltiest waters occurred in spring (April–May) and primed glaciers for enhanced submarine melt in summer when meltwater plumes entrain deep waters. Waters were coldest and freshest in early winter (November–December) after summer melt from sea ice, glacier ice, and icebergs provided cold freshwater along the shelf. Ocean variability was greatest in the summer and fall, coincident with increased freshwater runoff and large wind events before winter sea ice formation. Results increase our mechanistic understanding of Greenland ice-ocean interactions and enable improvements in ocean model parameterization.

Passive acoustic monitoring has been an effective tool to study cetaceans in remote regions of the Arctic. Here, we advance methods to acoustically identify the only two Arctic toothed whales, the beluga (Delphinapterus leucas) and narwhal (Monodon monoceros), using echolocation clicks. Long-term acoustic recordings collected from moorings in Northwest Greenland were analyzed. Beluga and narwhal echolocation signals were distinguishable using spectrograms where beluga clicks had most energy >30 kHz and narwhal clicks had a sharp lower frequency limit near 20 kHz. Changes in one-third octave levels (TOL) between two pairs of one-third octave bands were compared from over one million click spectra. Narwhal clicks had a steep increase between the 16 and 25 kHz TOL bands that was absent in beluga click spectra. Conversely, beluga clicks had a steep increase between the 25 and 40 kHz TOL bands that was absent in narwhal click spectra. Random Forest classification models built using the 16 to 25 kHz and 25 to 40 kHz TOL ratios accurately predicted the species identity of 100% of acoustic events. Our findings support the use of echolocation TOL ratios in future automated click classifiers for acoustic monitoring of Arctic toothed whales and potentially for other odontocete species.

Belugas (Delphinapterus leucas) and narwhals (Monodon monoceros) are highly social Arctic toothed whales with large vocal repertoires and similar acoustic profiles. Passive Acoustic Monitoring (PAM) that uses multiple hydrophones over large spatiotemporal scales has been a primary method to study their populations, particularly in response to rapid climate change and increasing underwater noise. This study marks the first acoustic comparison between wild belugas and narwhals from the same location and reveals that they can be acoustically differentiated and classified solely by echolocation clicks. Acoustic recordings were made in the pack ice of Baffin Bay, West Greenland, during 2013. Multivariate analyses and Random Forests classification models were applied to eighty-one single-species acoustic events comprised of numerous echolocation clicks. Results demonstrate a significant difference between species’ acoustic parameters where beluga echolocation was distinguished by higher frequency content, evidenced by higher peak frequencies, center frequencies, and frequency minimums and maximums. Spectral peaks, troughs, and center frequencies for beluga clicks were generally > 60 kHz and narwhal clicks < 60 kHz with overlap between 40–60 kHz. Classification model predictive performance was strong with an overall correct classification rate of 97.5% for the best model. The most important predictors for species assignment were defined by peaks and notches in frequency spectra. Our results provide strong support for the use of echolocation in PAM efforts to differentiate belugas and narwhals acoustically.