The Case for a Single Channel Composite Arctic Sea Surface Temperature Algorithm

Vincent, Ron

doi:10.3390/rs11202393

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…All AVHRR data were retrieved online from NOAA's Comprehensive Large Array-Data Stewardship System [23]. Surface temperatures were determined for METOP-A AVHRR images using the single channel Composite Arctic Sea Surface Temperature Algorithm (CASSTA) [24]. In clear sky conditions CASSTA uses Channel 4 to determine the temperature of three regimes: sea surface, ice surface, and marginal ice zones containing a combination of seawater and ice.…”

Section: Satellite Datamentioning

confidence: 99%

An Examination of the Non-Formation of the North Water Polynya Ice Arch

Vincent

2020

Remote Sensing

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The North Water (NOW), situated between Ellesmere Island and Greenland in northern Baffin Bay, is the largest recurring polynya in the Canadian Arctic. Historically, the northern border of the NOW is defined by an ice arch that forms annually in Kane Basin, which is part of the Nares Strait system. In 2007 the NOW ice arch failed to consolidate for the first time since observations began in the 1950s. The non-formation of the NOW ice arch occurred again in 2009, 2010, 2017 and 2019. Satellite Advanced Very High Resolution Radiometry data shows that large floes broke off from the normally stable landfast ice in Kane Basin for each of these years, impeding ice arch formation. A closer analysis of a 2019 event, in which 2500 km2 of ice sheared away from Kane Basin, indicates that significant tidal forces played a role. The evidence suggests that thinning ice from a warming climate combined with large amplitude tides is a key factor in the changing ice dynamics of the NOW region. The non-formation of the NOW ice arch results in an increased loss of multiyear ice through Nares Strait.

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Section: Satellite Datamentioning

confidence: 99%

An Examination of the Non-Formation of the North Water Polynya Ice Arch

Vincent

2020

Remote Sensing

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“…Automated measurements from satellite observation underpinned by remotely operated vehicles, autonomous vehicles, and buoys (such as data collected from the International Arctic Buoy Programme) offers the only currently available solution to providing the necessary synoptic measurements of multiple oceanographic parameters to characterize surface environmental heterogeneity (Shutler et al, 2019). Satellite observation can be used to study environmental conditions important in polar waters (Shutler et al, 2019) including: freshwater fluxes (e.g., Nichols and Subrahmanyam, 2019); surface water temperature (e.g., Vincent, 2019); Chlorophyll-a concentration, primary production and net community production (e.g., Babin et al, 2015), and sea ice type and depth (e.g., Kwok, 2018). Recent developments have shown that satellite observation measurements of temperature and salinity can provide observational-based estimates of surface carbonate system conditions (Land et al, 2019).…”

Section: Establish Baselinesmentioning

confidence: 99%

Satellite Observations Are Needed to Understand Ocean Acidification and Multi-Stressor Impacts on Fish Stocks in a Changing Arctic Ocean

et al. 2021

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It is widely projected that under future climate scenarios the economic importance of Arctic Ocean fish stocks will increase. The Arctic Ocean is especially vulnerable to ocean acidification and already experiences low pH levels not projected to occur on a global scale until 2100. This paper outlines how ocean acidification must be considered with other potential stressors to accurately predict movement of fish stocks toward, and within, the Arctic and to inform future fish stock management strategies. First, we review the literature on ocean acidification impacts on fish, next we identify the main obstacles that currently preclude ocean acidification from Arctic fish stock projections. Finally, we provide a roadmap to describe how satellite observations can be used to address these gaps: improve knowledge, inform experimental studies, provide regional assessments of vulnerabilities, and implement appropriate management strategies. This roadmap sets out three inter-linked research priorities: (1) Establish organisms and ecosystem physiochemical baselines by increasing the coverage of Arctic physicochemical observations in both space and time; (2) Understand the variability of all stressors in space and time; (3) Map life histories and fish stocks against satellite-derived observations of stressors.

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“…Compared with traditional in situ measurements, remote sensing technology has the advantages of low cost, wide coverage, and rapid updating. The emergence of remote sensing techniques has facilitated the detection of changes occurring on the Earth on a steady basis, such as monitoring the variation of Arctic sea ice and providing an opportunity to gain a deeper insight into surface temperature changes in the Arctic [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Many scholars have studied surface temperature retrieval within the Arctic sea ice region utilizing thermal infrared imagery acquired by satellite-borne thermal infrared sensors, such as Terra and Aqua/moderate resolution imaging spectroradiometer (MODIS), advanced very high-resolution radiometer (AVHRR), and advanced spaceborne thermal emission and reflection radiometer (ASTER), etc., to improve the understanding of climate change in the Arctic [9,[11][12][13][14]. Surface temperature quantification in the Arctic ice-water mixture zone (IWMZ) faces several challenges due to large inter-annual and intra-annual fluctuations in sea ice coverage and the complexity of the sea ice and water mixture [15,16].…”

Section: Introductionmentioning

confidence: 99%

Improvement of Ice Surface Temperature Retrieval by Integrating Landsat 8/TIRS and Operation IceBridge Observations

Song,

Wu,

Gong

et al. 2023

Remote Sensing

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Accurate retrieval of ice surface temperature (IST) over the Arctic ice-water mixture zone (IWMZ) is significantly essential for monitoring the change of the polar sea ice environment. Previous researchers have focused on evaluating the accuracy of IST retrieval in pack ice regions, possibly on account of the availability of in situ measurement data. Few of them have assessed the accuracy of IST retrieval on IWMZ. This study utilized Landsat 8/TIRS and Operation IceBridge observations (OIB) to evaluate the accuracy of the current IST retrieval method in IWMZ and proposed an adjustment method for improving the overall accuracy. An initial comparison shows that Landsat 8 IST and OIB IST have minor differences in the pack ice region with RMSE of 0.475 K, MAE of 0.370 K and cold bias of −0.256 K. In the thin ice region, however, the differences are more significant, with RMSE of 0.952 K, MAE of 0.776 K and warm bias of 0.703 K. We suggest that this phenomenon is because the current ice-water classification method misclassified thin ice as water. To address this issue, an adjusted method is proposed to refine the classification of features within the IWMZ and thus improve the accuracy of IST retrieval using Landsat 8 imagery. The results demonstrate that the accuracy of the retrieved IST in the two cases was improved in the thin ice region, with RMSE decreasing by about 0.146 K, Bias decreasing by about 0.311 K, and MAE decreasing by about 0.129 K. After the adjustment, high accuracy was achieved for both pack ice and thin ice in IWMZ.

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The Case for a Single Channel Composite Arctic Sea Surface Temperature Algorithm

Cited by 7 publications

References 28 publications

An Examination of the Non-Formation of the North Water Polynya Ice Arch

An Examination of the Non-Formation of the North Water Polynya Ice Arch

Satellite Observations Are Needed to Understand Ocean Acidification and Multi-Stressor Impacts on Fish Stocks in a Changing Arctic Ocean

Improvement of Ice Surface Temperature Retrieval by Integrating Landsat 8/TIRS and Operation IceBridge Observations

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