Comparison of digitized Canadian ice charts and passive microwave sea-ice concentrations

Agnew, T.; Howell, S.

doi:10.1109/igarss.2002.1024996

Cited by 4 publications

(6 citation statements)

References 5 publications

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“…In addition, at the ice margins and areas of ice breakup, the many different concentrations that can exist within one pixel will be smoothed to an average figure. Several studies have shown that because of the surface melt, in particular, the passive microwave-derived data tend to systematically underestimate ice concentration (e.g., Agnew and Howell, 2003;Shokr and Markus, 2006). When compared to sea-ice charts, the passive microwave sea-ice concentrations derived from the nASA Team algorithm were found to underestimate concentration during summer melt by 20.4% to 33.5%.…”

Section: Background: Measuring Sea-ice Breakupmentioning

confidence: 98%

“…There is some evidence that CIS charts are more accurate than passive microwave data for estimates of ice concentration, particularly in the presence of surface melt (documentation from Fetterer et al, 2008;Agnew and Howell, 2002). The CIS state that they rarely use passive microwave data for their charts.…”

Section: Canadian Ice Service Chartsmentioning

confidence: 99%

“…It is preferable to be overcautious in case the error is largely due to changes in atmospheric conditions or sea-ice conditions, which could be similar over a large area. There is also likely to be a systematic underestimation of concentration that is greater than this error (e.g., Agnew and Howell, 2003;Shokr and Markus, 2006) but this will not affect the overall trend unless there is a change in this systematic error between sensors.…”

Section: Passive Microwave Datamentioning

confidence: 99%

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A Step-Change in the Date of Sea-Ice Breakup in Western Hudson Bay

Scott¹,

Marshall²

2010

ARCTIC

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over the last four decades there has been a trend to earlier summer breakup of the sea ice in western Hudson Bay, Canada. As this sea ice is critical for the polar bears that use it for hunting, the earlier breakup is believed to be a factor in the declining health of the regional polar bear population. Analysis of the change to earlier breakup using passive microwave satellite data is problematic because of currently unquantifiable systematic errors between different satellites. Analysis using Canadian sea-ice charts from 1971 to 2008 shows that the change to earlier breakup is best represented by a 12-day step. This step occurs from 1988 to 1989 with no significant trend before or after the step. Although not as great as the three-week gradual change suggested by previous studies, this change is still significant. An increase in regional southwesterly winds during the first three weeks of June and a corresponding increase in surface temperature are shown to be likely contributing factors to this earlier breakup. It remains to be seen whether these changes in atmospheric circulation might be ascribed to human actions or simply to natural climate variability. Key words: sea ice, breakup, Hudson Bay, climate change, polar bear rÉSuMÉ. Ces quatre dernières décennies, la débâcle de la glace de mer d'été a eu tendance à se faire plus tôt que d'habitude dans l'ouest de la baie d'Hudson, au Canada. Puisque cette glace de mer revêt une importance primordiale chez les ours polaires qui s'en servent pour la chasse, cette débâcle plus hâtive pourrait jouer un rôle dans le déclin de la population régionale d'ours polaires. l'analyse du changement en matière de débâcle hâtive effectuée au moyen de données satellitaires passives en hyperfréquences est problématique en raison des erreurs systématiques non quantifiables qui existent entre différents satellites. l'analyse réalisée à l'aide des données sur la glace de mer prélevées au Canada de 1971 à 2008 indiquent que la débâcle plus hâtive est mieux représentée à l'aide d'une phase de 12 jours. Cette phase s'est produite de 1988 à 1989 sans qu'une tendance remarquable n'ait été enregistrée avant ou après la phase. Bien que ce changement ne soit pas aussi grand que le changement graduel sur trois semaines qui avait été suggéré par des études antérieures, ce changement est tout de même important. L'intensification des vents régionaux du sud-ouest pendant les trois premières semaines de juin de même que l'augmentation correspondante de la température de surface seraient des facteurs ayant vraisemblablement contribué à cette débâcle plus hâtive. Reste à voir si ces changements en matière de circulation atmosphérique pourraient être attribuables aux actes de l'être humain ou simplement à une variabilité climatique naturelle. Mots clés : glace de mer, débâcle, baie d'Hudson, changement climatique, ours polaire Traduit pour la revue Arctic par nicole Giguère.

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Section: Background: Measuring Sea-ice Breakupmentioning

confidence: 98%

Section: Canadian Ice Service Chartsmentioning

confidence: 99%

Section: Passive Microwave Datamentioning

confidence: 99%

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A Step-Change in the Date of Sea-Ice Breakup in Western Hudson Bay

Scott¹,

Marshall²

2010

ARCTIC

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“…Various studies (e.g., Partington et al, 2003;Agnew and Howell, 2002) have shown that passive microwavederived sea ice data tend to underestimate ice concentration when compared with operational analyses. The Climate Data Record of Passive Microwave Sea Ice Concentration is a blend of output from two algorithms that results in higher ice concentrations overall for a better match with the operational analyses that predate the satellite record.…”

Section: Metrics Of Sea Ice Coveragementioning

confidence: 99%

Benchmark seasonal prediction skill estimates based on regional indices

2019

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Abstract. Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. In this study we use observational data to evaluate the contribution of the trend to the skill of persistence-based statistical forecasts of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea for which the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the winter and summer trends during the 1990s. Persistence-based statistical forecasts of the Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. In only a few regions does September ice extent correlate significantly with antecedent ice anomalies in the same region more than 2 months earlier. The springtime “predictability barrier” in regional forecasts based on persistence of ice extent anomalies is not reduced by the inclusion of several decades of pre-satellite data. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea's ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead time of a month or two.

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“…Many algorithms have been developed to retrieve sea ice concentration (SIC) from passive microwave remote sensing data [7]. A large number of studies compared microwave satellite data with other types of satellite information of higher resolution (visible, infrared, and radar) [9][10][11], as well as sea ice charts on their basis [12][13][14]. SIC data obtained using different algorithms were repeatedly compared with each other to reveal their functionality under different ice and weather conditions [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Arctic Sea Ice Concentrations from the NASA Team, ASI, and VASIA2 Algorithms with Summer and Winter Ship Data

et al. 2019

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The paper presents a comparison of sea ice concentration (SIC) derived from satellite microwave radiometry data and dedicated ship observations. For the purpose, the NASA Team (NT), Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI), and Variation Arctic/Antarctic Sea Ice Algorithm 2 (VASIA2) algorithms were used as well as the database of visual ice observations accumulated in the course of 15 Arctic expeditions. The comparison was performed in line with the SIC gradation (in tenths) into very open (1–3), open (4–6), close (7–8), very close and compact (9–10,10) ice, separately for summer and winter seasons. On average, in summer NT underestimates SIC by 0.4 tenth as compared to ship observations, while ASI and VASIA2 by 0.3 tenth. All three algorithms overestimate total SIC in regions of very open ice and underestimate it in regions of close, very close, and compact ice. The maximum average errors are typical of open ice regions that are most common in marginal ice zones. In winter, NT and ASI also underestimate SIC on average by 0.4 and 0.8 tenths, respectively, while VASIA2, on the contrary, overestimates by 0.2 tenth against the ship data, however, for open and close ice the average errors are significantly higher than in summer. In the paper, we also estimate the impact of ice melt stage and presence of new ice and nilas on SIC derived from NT, ASI, and VASIA2.

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Comparison of digitized Canadian ice charts and passive microwave sea-ice concentrations

Cited by 4 publications

References 5 publications

A Step-Change in the Date of Sea-Ice Breakup in Western Hudson Bay

A Step-Change in the Date of Sea-Ice Breakup in Western Hudson Bay

Benchmark seasonal prediction skill estimates based on regional indices

Comparison of Arctic Sea Ice Concentrations from the NASA Team, ASI, and VASIA2 Algorithms with Summer and Winter Ship Data

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