Evaluation of the Interactive Multisensor Snow and Ice Mapping System (IMS) for monitoring sea ice phenology

Brown, Laura C.; Howell, Stephen E. L.; Mortin, Jonas; Derksen, Chris

doi:10.1016/j.rse.2014.02.012

Cited by 17 publications

(29 citation statements)

References 35 publications

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“…From 34 years of satellite data the calculated trends of delayed freezing and earlier melting are consistent in sign and general magnitude with those of Markus et al (2009), Mortin et al (2014), and Brown et al (2014). We can use the calculated long-term trends in the Chukchi Sea to extrapolate freeze-up and break-up dates for a future year.…”

Section: Figurementioning

confidence: 60%

“…We rely on ice concentration from passive microwave measurements because that data set is well validated and well understood. Of particular interest is that the passive microwave data from 1979 onwards provide a longer context for changes in sea-ice phenology than recent studies (e.g., Brown et al, 2014) where the choice of sensors shifts the focus to the current decade.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Arctic sea-ice freeze-up and break-up from the satellite record: A comparison of different approaches in the Chukchi and Beaufort Seas

Johnson

Eicken

2016

Elementa: Science of the Anthropocene

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Elementa: Science of the Anthropocene • 4: 000124 • doi: 10.12952/journal.elementa.000124 elementascience.org 1. Abstract The recognized importance of the annual cycle of sea ice in the Arctic to heat budgets, human behavior, and ecosystem functions, requires consistent definitions of such key events in the ice cycle as break-up and freeze-up. An internally consistent and reproducible approach to characterize the timing of these events in the annual sea-ice cycle is described. An algorithm was developed to calculate the start and end dates of freeze-up and break-up and applied to time series of satellite-derived sea-ice concentration from 1979 to 2013. Our approach builds from discussions with sea-ice experts having experience observing and working on the sea ice in the Bering, Chukchi and Beaufort Seas. Applying the algorithm to the 1979-2013 satellite data reveals that freeze-up is delayed by two weeks per decade for the Chukchi coast and one week per decade for the Beaufort coast. For both regions, break-up start is arriving earlier by 5-7 days per decade and break-up end is arriving earlier by 10-12 days per decade. In the Chukchi Sea, "early" break-up is arriving earlier by one month over the 34-year period and alternates with a "late" break-up. The calculated freeze-up and break-up dates provide information helpful to understanding the dynamics of the annual sea-ice cycle and identifying the drivers that modify this cycle. The algorithm presented here, and potential refinements, can help guide future work on changes in the seasonal cycle of sea ice. The sea-ice phenology of freeze-up and break-up that results from our approach is consistent with observations of sea-ice use. It may be applied to advancing our understanding and prediction of the timing of seasonal navigation, availability of ice as a biological habitat, and assessment of numerical models.

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Section: Figurementioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Estimating Arctic sea-ice freeze-up and break-up from the satellite record: A comparison of different approaches in the Chukchi and Beaufort Seas

Johnson

Eicken

2016

Elementa: Science of the Anthropocene

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“…Both CIS and IMS products rely partially on observations from optical sensors such as AVHRR and their accuracy is influenced by adverse weather conditions, including the presence of cloud cover. IMS-derived lake ice products have been widely used in monitoring global climate change (Duguay et al, 2013(Duguay et al, , 2015b; however, the IMS detected freeze onset was found to be too early for some lakes in northern Québec, presumably due to misclassification by inclusion of coarse-resolution satellite passive microwave observations during periods of prolonged cloud cover Brown et al, 2014); this may cause the low correlations between LIP and IMS CFO dates, as well as a delayed LIP CFO bias relative to IMS.…”

Section: Discussionmentioning

confidence: 99%

Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015

Kimball

Duguay

et al. 2017

The Cryosphere

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Abstract.A new automated method enabling consistent satellite assessment of seasonal lake ice phenology at 5 km resolution was developed for all lake pixels (water coverage ≥ 90 %) in the Northern Hemisphere using 36.5 GHz H-polarized brightness temperature (T b ) observations from the Advanced Microwave Scanning Radiometer for EOS and Advanced Microwave Scanning Radiometer 2 (AMSR-E/2) sensors. The lake phenology metrics include seasonal timing and duration of annual ice cover. A moving t test (MTT) algorithm allows for automated lake ice retrievals with daily temporal fidelity and 5 km resolution gridding. The resulting ice phenology record shows strong agreement with available ground-based observations from the Global Lake and River Ice Phenology Database (95.4 % temporal agreement) and favorable correlations (R) with alternative ice phenology records from the Interactive Multisensor Snow and Ice Mapping System (R = 0.84 for water clear of ice (WCI) dates; R = 0.41 for complete freeze over (CFO) dates) and Canadian Ice Service (R = 0.86 for WCI dates; R = 0.69 for CFO dates). Analysis of the resulting 12-year (2002-2015) AMSR-E/2 ice record indicates increasingly shorter ice cover duration for 43 out of 71 (60.6 %) Northern Hemisphere lakes examined, with significant (p < 0.05) regional trends toward earlier ice melting for only five lakes. Higherlatitude lakes reveal more widespread and larger trends toward shorter ice cover duration than lower-latitude lakes, consistent with enhanced polar warming. This study documents a new satellite-based approach for rapid assessment and regional monitoring of seasonal ice cover changes over large lakes, with resulting accuracy suitable for global change studies.

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“…The IMS data utilizing a variety of multisourced datasets, like passive microwave, visible imagery, and other ancillary data [33,35], has been shown to be an effective product for snow applications [36,37]. The dataset provides snow cover maps for Northern Hemisphere from February 1997 to the present.…”

Section: Study Area and Data Processingmentioning

confidence: 99%

Temporal and Spatial Changes in Snow Cover and the Corresponding Radiative Forcing Analysis in Siberia from the 1970s to the 2010s

Liu

Zhang

2017

Advances in Meteorology

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In the context of global climate change, the extent of snow cover in Siberia has significantly decreased since the 1970s, especially in spring. The changes of snow cover at middle and high latitudes have significant impacts on the meteorological and hydrological processes because the snow cover can affect the surface energy, water balance, and the development of the atmospheric boundary layer. In this paper, the temporal and spatial changes in snow cover were firstly estimated based on a long time series of remote sensing snow cover data, both showing a decreased trend. Based on this, we estimated the radiative forcing caused by the snow cover changes from the 1970s to the 2010s and compared it with the radiative forcing caused by the vegetation cover changes over the same time period in Siberia, indicating that the snow cover changes in Siberia can accelerate climate warming and the vegetation cover changes here have the opposite effect. Furthermore, the snow cover changes may play a more important role than the vegetation cover changes in regulating the surface radiation balance in Siberia on the regional scale.

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Evaluation of the Interactive Multisensor Snow and Ice Mapping System (IMS) for monitoring sea ice phenology

Cited by 17 publications

References 35 publications

Estimating Arctic sea-ice freeze-up and break-up from the satellite record: A comparison of different approaches in the Chukchi and Beaufort Seas

Estimating Arctic sea-ice freeze-up and break-up from the satellite record: A comparison of different approaches in the Chukchi and Beaufort Seas

Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015

Temporal and Spatial Changes in Snow Cover and the Corresponding Radiative Forcing Analysis in Siberia from the 1970s to the 2010s

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