Delineation of Eastern Beaufort Sea Sub-regions Using Self-Organizing Maps Applied to 17 Years of MODIS-Aqua Data

Abstract

Satellite observations are an integral component of long-term Arctic Ocean monitoring and help identifying changes resulting from climate warming. A Self-Organizing Maps (SOM) approach was applied to four-day composite satellite images of the Eastern Beaufort Sea (EBS) acquired by the MODerate resolution Imaging Spectroradiometer over the period 2003–2019. Using sea-surface temperature (SST), suspended particulate matter concentration (SPM) and chlorophyll-a concentration (Chl-a) as input the EBS was partitioned into six biogeochemical regions. The SOM approach revealed region-specific mean conditions and seasonal cycles for all properties, particularly for SPM and Chl-a. Three of the six regions, located on the continental shelf, had the highest SST, SPM and Chl-a with earlier maxima compared to the remaining three regions which comprised the shelf edge, Canada Basin and Amundsen Gulf. While mean and maximum SST did not exhibit significant trends over the 17 years of observations, the annual maximum SST in Amundsen Gulf was reached significantly earlier in recent years compared to the start of the time series. With the exception of Amundsen Gulf, sea-ice concentration (SIC) derived from microwave satellites declined throughout the study area; monthly trends showed dramatic SIC declines in regions on the shelf during May and June, and in Canada Basin during August. Correlation analysis of properties within and between regions showed that SST and SIC were driven by large scale processes while SPM and Chl-a showed regional features. SST and Chl-a in the regions nearest the Mackenzie River showed a strong relationship during seasonal warming. The SOM approach, applied to 17 years of satellite data, revealed spatially distinct marine units with unique characteristics, emphasizing the need for regional considerations when assessing the impact of climate warming in the Arctic Ocean.

Biogeochemical River Runoff Drives Intense Coastal Arctic Ocean CO2 Outgassing

“…A plume region delimited by Mulligan and Perrie (2019) observations at isohaline S = 27 was computed to evaluate the contribution of the Mackenzie plume to CO 2 fluxes and net primary production (NPP) in the SBS. The plume region was coherent with the Mackenzie inner‐shelf sub‐region determined by a neural network (not shown), which combined 17 years of satellite data acquired by the Aqua‐MODIS sensor (Hilborn & Devred, 2022).…”

Improving Satellite Chlorophyll-a Retrieval in the Turbid Waters of the Bay of Fundy, Canada

“…In the Arctic Ocean, the bluegreen ratio algorithm was recalibrated with a large in situ database to account for the low sun elevation, different phytoplankton bio-optical characteristics due to adaptations to an extreme light environment, and relatively high levels of CDOM (Lewis and Arrigo 2020). Yet in regions with high sediment loading, such as the shelf region impacted by the direct outflow of the Mackenzie River where sediment concentrations regularly exceed 10 g m −3 (Doxaran et al 2015), chl-a may still be overestimated (Hilborn and Devred 2022). Elsewhere in the Atlantic Ocean, using red/ near-infrared (NIR) algorithms with narrow band ranges, chl-a retrievals were improved in the Río de la Plata estuary (Dogliotti et al 2021) where suspended particulate matter concentrations (SPM) range from 10 to 100's g m −3 (Camiolo et al 2019).…”