Detection of melt onset over the northern Canadian Arctic Archipelago sea ice from RADARSAT, 1997–2014

Mahmud, Mallik; Howell, Stephen E. L.; Geldsetzer, Torsten; Yackel, John J.

doi:10.1016/j.rse.2016.03.003

Cited by 38 publications

(35 citation statements)

References 39 publications

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“…Previous studies on both lake and sea ice have shown that incidence angle impacts the HH backscatter from different surfaces and the incidence angle also differs between images due to the combination of ascending and descending orbits used in this dataset [23,36,37]. Lower incidence angles result in increased interaction at the surface of the ice and more surface scattering while higher incidence angles are affected by volume scattering and characteristics of the ice column [23,[37][38][39]. In order to normalize the backscatter values for the images acquired in this study, 1094 points were randomly generated for lakes in Central Ontario between 2008 to 2016.…”

Section: Radarsat-2mentioning

confidence: 99%

Evaluating RADARSAT-2 for the Monitoring of Lake Ice Phenology Events in Mid-Latitudes

2018

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Lake ice is an important component in understanding the local climate as changes in temperature have an impact on the timing of key ice phenology events. In recent years, there has been a decline in the in-situ monitoring of lake ice events in Canada and microwave remote sensing imagery from synthetic aperture radar (SAR) is more widely used due to the high spatial resolution and response of backscatter to the freezing and melting of the ice surface. RADARSAT-2 imagery was used to develop a threshold-based method for determining lake ice events for mid-latitude lakes in Central Ontario from 2008 to 2017. Estimated lake ice phenology events are validated with ground-based observations and are compared against the Moderate Resolution Imaging Spectroradiometer (MODIS band 2). The threshold-based method was found to accurately identify 12 out of 17 freeze events and 13 out of 17 melt events from 2015–2017 when compared to ground-based observations. Mean absolute errors for freeze events ranged from 2.5 to 10.0 days when compared to MODIS imagery while the mean absolute error for water clear of ice (WCI) ranged from 1.5 to 7.1 days. The method is important for the study of mid-latitude lake ice due to its unique success in detecting multiple freeze and melting events throughout the ice season.

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Section: Radarsat-2mentioning

confidence: 99%

Evaluating RADARSAT-2 for the Monitoring of Lake Ice Phenology Events in Mid-Latitudes

2018

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“…We note that the altered AHRA-A data described in Section 2.5 are identical to the AHRA data for the 1997-2012 subset shown in Figure 9 and are omitted from the figure. The MO dates from the M16 method are expected to be later than the early MO dates from the AHRA and PMWC methods since the M16 data are produced from images during the early morning local time (i.e., when SAT is colder), thus are more comparable to the continuous MO date determined by the PMW, described further by Mahmud et al [19]. The 2-4-day delay between images used by M16 could contribute to the later M16 MO dates.…”

Section: Discussionmentioning

confidence: 97%

“…Based on a preliminary comparison, the AHRA, PMWC, and PMWC-A methods compare similarly to a new active microwave based MO detection method from RADARSAT-1 and RADARSAT-2 data in the northern Canadian Arctic Archipelago region developed by Mahmud et al [19] (hereafter M16). The advantage of the M16 active method for MO detection is the higher spatial resolution (<100 m); however, image acquisition from the active microwave sensors in this region is limited to every 2-4 days [19] in contrast to daily observations (since late 1987) from the passive microwave sensors.…”

Section: Discussionmentioning

confidence: 99%

“…The advantage of the M16 active method for MO detection is the higher spatial resolution (<100 m); however, image acquisition from the active microwave sensors in this region is limited to every 2-4 days [19] in contrast to daily observations (since late 1987) from the passive microwave sensors. Higher spatial resolution data are better able to resolve smaller scale variations in MO signatures in the land fast ice areas within the northern Canadian Arctic Archipelago where the relatively coarse resolution of the passive microwave data and effects of land contamination along coastlines make the passive microwave methods less reliable.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

2017

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Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979 through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

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“…Scatterometer data has been used for mapping of sea ice extent and ice edge location, and for sea ice typing [12]. All of the sensors have been used for estimation of beginnings and endings of different sea ice thermodynamic regimes, e.g., [12][13][14], and sea ice drift based on tracking of temporal changes in the imagery, e.g., [12,[15][16][17].…”

Section: Introductionmentioning

confidence: 99%

MODIS Sea Ice Thickness and Open Water–Sea Ice Charts over the Barents and Kara Seas for Development and Validation of Sea Ice Products from Microwave Sensor Data

Mäkynen

Karvonen

2017

Remote Sensing

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Abstract:We have developed algorithms and procedures for calculating daily sea ice thickness (SIT) and open water-sea ice (OWSI) charts, based on the Moderate Resolution Imaging Spectroradiometer (MODIS), ice surface temperature (IST) (night-time only), and reflectance (R) swath data, respectively. The resolution of the SIT chart is 1 km and that of the OWSI chart is 250 m. The charts are targeted to be used in development and validation of sea ice products from microwave sensor data. We improve the original MODIS cloud masks for the IST and R data, with a focus on identifying larger cloud-free areas in the data. The SIT estimation from the MODIS IST swath data follows previous studies. The daily SIT chart is composed from available swath charts by assigning daily median SIT to a pixel. The OWSI classification is simply conducted by a fixed threshold for the MODIS band 1 R. This was based on manually selected R data for various ice types in late winter, early melt, and advanced melt conditions. The composition procedures for the daily SIT and OWSI charts somewhat compensates for errors due to the undetected clouds. The SIT and OWSI charts were compared against manual ice charts by Arctic and Antarctic Research Institute in Russia and by Norwegian Meteorological Institute, respectively, and on average, a good relationship between the charts was found. Pixel-wise comparison of the SIT and OWSI charts showed very good agreement in open water vs. sea ice classification, which gives further confidence on the reliability of our algorithms. We also demonstrate usage of the MODIS OWSI and SIT charts for validation of sea ice concentration charts based on the SENTINEL-1 SAR and AMSR2 radiometer data and two different algorithms.

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Detection of melt onset over the northern Canadian Arctic Archipelago sea ice from RADARSAT, 1997–2014

Cited by 38 publications

References 39 publications

Evaluating RADARSAT-2 for the Monitoring of Lake Ice Phenology Events in Mid-Latitudes

Evaluating RADARSAT-2 for the Monitoring of Lake Ice Phenology Events in Mid-Latitudes

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

MODIS Sea Ice Thickness and Open Water–Sea Ice Charts over the Barents and Kara Seas for Development and Validation of Sea Ice Products from Microwave Sensor Data

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