Estimating ice phenology on large northern lakes from AMSR-E: algorithm development and application to Great Bear Lake and Great Slave Lake, Canada

Abstract. Time series of brightness temperatures (TB) from the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) are examined to determine ice phenology variables on the two largest lakes of northern Canada: Great Bear Lake (GBL) and Great Slave Lake (GSL). TB measurements from the 18.7, 23.8, 36.5, and 89.0 GHz channels (H- and V- polarization) are compared to assess their potential for detecting freeze-onset/melt-onset and ice-on/ice-off dates on both lakes. The 18.7 GHz (H-pol) channel is found to be the most suitable for estimating these ice dates as well as the duration of the ice cover and ice-free seasons. A new algorithm is proposed using this channel and applied to map all ice phenology variables on GBL and GSL over seven ice seasons (2002–2009). Analysis of the spatio-temporal patterns of each variable at the pixel level reveals that: (1) both freeze-onset and ice-on dates occur on average about one week earlier on GBL than on GSL (Day of Year (DY) 318 and 333 for GBL; DY 328 and 343 for GSL); (2) the freeze-up process or freeze duration (freeze-onset to ice-on) takes a slightly longer amount of time on GBL than on GSL (about 1 week on average); (3) melt-onset and ice-off dates occur on average one week and approximately four weeks later, respectively, on GBL (DY 143 and 183 for GBL; DY 135 and 157 for GSL); (4) the break-up process or melt duration (melt-onset to ice-off) lasts on average about three weeks longer on GBL; and (5) ice cover duration estimated from each individual pixel is on average about three weeks longer on GBL compared to its more southern counterpart, GSL. A comparison of dates for several ice phenology variables derived from other satellite remote sensing products (e.g. NOAA Interactive Multisensor Snow and Ice Mapping System (IMS), QuikSCAT, and Canadian Ice Service Database) show that, despite its relatively coarse spatial resolution, AMSR-E 18.7 GHz provides a viable means for monitoring of ice phenology on large northern lakes.

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Estimating ice phenology on large northern lakes from AMSR-E: algorithm development and application to Great Bear Lake and Great Slave Lake, Canada

The Cryosphere Discussions ◽

10.5194/tcd-5-3129-2011 ◽

2011 ◽

Vol 5 (6) ◽

pp. 3129-3173

Author(s):

K.-K. Kang ◽

C. R. Duguay ◽

S. E. L. Howell

Keyword(s):

Ice Cover ◽

Brightness Temperatures ◽

Earth Observing System ◽

Bear Lake ◽

Great Slave Lake ◽

Mapping System ◽

Coarse Spatial Resolution ◽

Spatio Temporal ◽

Melt Duration ◽

Ice Phenology

Abstract. Time series of brightness temperatures (TB) from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) are examined to determine ice phenological parameters on the two largest lakes of northern Canada: Great Bear Lake (GBL) and Great Slave Lake (GSL). TB measurements from the 18.7, 23.8, 36.5, and 89.0 GHz channels (H- and V- polarization) are compared to assess their potential for detecting freeze-onset/melt-onset and ice-on/ice-off dates on both lakes. The 18.7 GHz (H-pol) channel is found to be the most suitable for estimating these ice dates as well as the duration of the ice cover and ice-free seasons. A new algorithm is proposed using this channel and applied to map all ice phenological parameters on GBL and GSL over seven ice seasons (2002–2009). Analysis of the spatio-temporal patterns of each parameter at the pixel level reveals that: (1) both freeze-onset and ice-on dates occur on average about one week earlier on GBL than on GSL (Day of Year (DY) 318 and 333 for GBL; DY 328 and 343 for GSL); (2) the freeze-up process or freeze duration (freeze-onset to ice-on) takes a slightly longer amount of time on GBL than on GSL (about 1 week on average); (3) melt-onset and ice-off dates occur on average one week and approximately four weeks later, respectively, on GBL (DY 143 and 183 for GBL; DY 135 and 157 for GSL); (4) the break-up process or melt duration (melt-onset to ice-off) lasts on average about three weeks longer on GBL; and (5) ice cover duration estimated from each individual pixel is on average about three weeks longer on GBL compared to its more southern counterpart, GSL. A cross-comparison of dates for several ice phenological parameters derived from other satellite remote sensing products (e.g. NOAA Interactive Multisensor Snow and Ice Mapping System (IMS), QuikSCAT, and Canadian Ice Service Database) show that, despite its relatively coarse spatial resolution, AMSR-E 18.7 GHz provides a viable means for monitoring of ice phenology on large northern lakes.

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Variability in ice phenology on Great Bear Lake and Great Slave Lake, Northwest Territories, Canada, from SeaWinds/QuikSCAT: 2000–2006

Remote Sensing of Environment ◽

10.1016/j.rse.2008.12.007 ◽

2009 ◽

Vol 113 (4) ◽

pp. 816-834 ◽

Cited By ~ 49

Author(s):

Stephen E.L. Howell ◽

Laura C. Brown ◽

Kyung-Kuk Kang ◽

Claude R. Duguay

Keyword(s):

Northwest Territories ◽

Bear Lake ◽

Great Slave Lake ◽

Ice Phenology

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Spatial-Temporal Distribution of the Freeze–Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020

Remote Sensing ◽

10.3390/rs13091695 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1695

Author(s):

Weixiao Han ◽

Chunlin Huang ◽

Juan Gu ◽

Jinliang Hou ◽

Ying Zhang

Keyword(s):

Machine Learning ◽

Land Surface ◽

Temporal Dynamics ◽

Temporal Distribution ◽

Ice Cover ◽

Qinghai Lake ◽

Gap Filling ◽

Thaw Cycle ◽

Break Up ◽

Ice Phenology

The lake ice phenology variations are vital for the land–surface–water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water–ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years; the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.

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Carbon Fixation Trends in Eleven of the World’s Largest Lakes: 2003–2018

Water ◽

10.3390/w12123500 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3500

Author(s):

Michael Sayers ◽

Karl Bosse ◽

Gary Fahnenstiel ◽

Robert Shuchman

Keyword(s):

Climate Change ◽

Primary Production ◽

Great Lakes ◽

Satellite Remote Sensing ◽

Carbon Fixation ◽

African Great Lakes ◽

Wind Speeds ◽

Bear Lake ◽

Great Slave Lake ◽

Significant Production

Large freshwater lakes provide immense value to the surrounding populations, yet there is limited understanding of how these lakes will respond to climate change and other factors. This study uses satellite remote sensing to estimate annual, lake-wide primary production in 11 of the world’s largest lakes from 2003–2018. These lakes include the five Laurentian Great Lakes, the three African Great Lakes, Lake Baikal, and Great Bear and Great Slave Lakes. Mean annual production in these lakes ranged from under 200 mgC/m2/day to over 1100 mgC/m2/day, and the lakes were placed into one of three distinct groups (oligotrophic, mesotrophic, or eutrophic) based on their level of production. The analysis revealed only three lakes with significant production trends over the study period, with increases in Great Bear Lake (24% increase over the study period) and Great Slave Lake (27%) and a decline in Lake Tanganyika (−16%). These changes appear to be related to climate change, including increasing temperatures and solar radiation and decreasing wind speeds. This study is the first to use consistent methodology to study primary production in the world’s largest lakes, allowing for these novel between-lake comparisons and assessment of inter-annual trends.

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A daytime climatological distribution of high opaque ice cloud classes over the Indian summer monsoon region observed from 25-year AVHRR data

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-4185-2009 ◽

2009 ◽

Vol 9 (12) ◽

pp. 4185-4196 ◽

Cited By ~ 15

Author(s):

A. Devasthale ◽

H. Grassl

Keyword(s):

Summer Monsoon ◽

Indian Subcontinent ◽

Deep Convection ◽

Temporal Distribution ◽

Radiative Balance ◽

Ice Cloud ◽

Brightness Temperatures ◽

Spatio Temporal ◽

Very High ◽

Summer Monsoon Region

Abstract. A daytime climatological spatio-temporal distribution of high opaque ice cloud (HOIC) classes over the Indian subcontinent (0–40° N, 60° E–100° E) is presented using 25-year data from the Advanced Very High Resolution Radiometers (AVHRRs) for the summer monsoon months. The HOICs are important for regional radiative balance, precipitation and troposphere-stratosphere exchange. In this study, HOICs are sub-divided into three classes based on their cloud top brightness temperatures (BT). Class I represents very deep convection (BT<220 K). Class II represents deep convection (220 K

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Theoretical study of ice cover phenology at large freshwater lakes based on SMOS MIRAS data

The Cryosphere ◽

10.5194/tc-12-2727-2018 ◽

2018 ◽

Vol 12 (8) ◽

pp. 2727-2740 ◽

Cited By ~ 1

Author(s):

Vasiliy Tikhonov ◽

Ilya Khvostov ◽

Andrey Romanov ◽

Evgeniy Sharkov

Keyword(s):

Brightness Temperature ◽

Open Water ◽

Ice Cover ◽

Freshwater Lakes ◽

Ice Melt ◽

Bear Lake ◽

Ocean Salinity ◽

Satellite Microwave ◽

Transportation Routes ◽

Temperature Time

Abstract. The paper presents a theoretical analysis of seasonal brightness temperature variations at a number of large freshwater lakes: Baikal, Ladoga, Great Bear Lake (GBL), Great Slave Lake (GSL), and Huron, retrieved from Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) data (1.4 GHz) of the Soil Moisture and Ocean Salinity (SMOS) satellite. The analysis was performed using the model of microwave radiation of plane layered heterogeneous nonisothermal medium. The input parameters for the model were real regional climatological characteristics and glaciological parameters of ice cover of the study lakes. Three distinct seasonal brightness temperature time regions corresponding to different phenological phases of the lake surfaces: complete ice cover, ice melt and deterioration, and open water were revealed. The paper demonstrates the possibility to determine the beginning of ice cover deterioration from satellite microwave radiometry data. The obtained results can be useful for setting the operating terms of winter crossings and roads on ice, as with the beginning of ice deterioration, these transportation routes across water bodies (rivers, lakes, water reservoirs) become insecure and cannot be used any more.

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Lake ice phenology changes in the northern hemisphere

10.5194/egusphere-egu21-15155 ◽

2021 ◽

Author(s):

Yubao Qiu ◽

Xingxing Wang ◽

Matti Leppäranta ◽

Bin Cheng ◽

Yixiao Zhang

Keyword(s):

Remote Sensing ◽

North America ◽

Northern Hemisphere ◽

Ice Cover ◽

Passive Microwave ◽

Lake Area ◽

Lake Ice ◽

Northern Tibetan Plateau ◽

Break Up ◽

Ice Phenology

<p>Lake-ice phenology is an essential indicator of climate change impact for different regions (Livingstone, 1997; Duguay, 2010), which helps understand the regional characters of synchrony and asynchrony. The observation of lake ice phenology includes ground observation and remote sensing inversion. Although some lakes have been observed for hundreds of years, due to the limitations of the observation station and the experience of the observers, ground observations cannot obtain the lake ice phenology of the entire lake. Remote sensing has been used for the past 40 years, in particular, has provided data covering the high mountain and high latitude regions, where the environment is harsh and ground observations are lacking. Remote sensing also provides a unified data source and monitoring standard, and the possibility of monitoring changes in lake ice in different regions and making comparisons between them. The existing remote sensing retrieval products mainly cover North America and Europe, and data for Eurasia is lacking (Cr&#233;taux et al., 2020).</p><p>Based on the passive microwave, the lake ice phenology of 522 lakes in the northern hemisphere during 1978-2020 was obtained, including Freeze-Up Start (FUS), Freeze-Up End (FUE), Break-Up Start (BUS), Break-Up End (BUE), and Ice Cover Duration (ICD). The ICD is the duration from the FUS to the BUE, which can directly reflect the ice cover condition. At latitudes north of 60&#176;N, the average of ICD is approximately 8-9 months in North America and 5-6 months in Eurasia. Limited by the spatial resolution of the passive microwave, lake ice monitoring is mainly in Northern Europe. Therefore, the average of ICD over Eurasia is shorter, while the ICD is more than 6 months for most lakes in Russia. After 2000, the ICD has shown a shrinking trend, except northeastern North America (southeast of the Hudson Bay) and the northern Tibetan Plateau. The reasons for the extension of ice cover duration need to be analyzed with parameters, such as temperature, the lake area, and lake depth, in the two regions.</p>

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Analysis of Multiple-Angle Microwave Observations of Snow and Ice Using Cluster-Analysis Techniques

Journal of Glaciology ◽

10.1017/s0022143000011254 ◽

1981 ◽

Vol 27 (95) ◽

pp. 89-97 ◽

Cited By ~ 6

Author(s):

Stanley R. Rotman ◽

Arthur D. Fisher ◽

David H. Staelin

Keyword(s):

Cluster Analysis ◽

Sea Ice ◽

Accumulation Rate ◽

Ice Cover ◽

Ice Age ◽

Analysis Techniques ◽

Brightness Temperatures ◽

Microwave Spectrometer ◽

Angular Data ◽

Microwave Signatures

AbstractThe Nimbus-6 satellite carries the Scanning Microwave Spectrometer experiment (SCAMS) which continuously maps the Earth’s surface at two frequencies (22.235 and 31.65 GHz) and at six angles besides nadir. Cluster analysis was applied to these observations to determine the influence of various geophysical parameters on the radiometric brightness temperatures.Characteristic microwave signatures for a variety of terrain were obtained by this method; discrete clusters were distinguished for sea ice (with sub-classes for ice age and fractional ice cover) and firn (with accumulation-rate sub-classes). The availability of the angular data greatly facilitated separate determinations of the extent of continuous sea ice and mixtures of sea ice and water.

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Range extension for Pygmy Whitefish (Prosopium coulterii) in the Northwest Territories, Canada

The Canadian Field-Naturalist ◽

10.22621/cfn.v129i1.1669 ◽

2015 ◽

Vol 129 (1) ◽

pp. 70 ◽

Cited By ~ 1

Author(s):

Paul Vecsei ◽

Damian Panayi

Keyword(s):

Northwest Territories ◽

Range Extension ◽

Bear Lake ◽

Great Slave Lake ◽

First Occurrence

We document the first occurrence of Pygmy Whitefish (Prosopium coulterii) in the Northwest Territories outside of Great Bear Lake. Six specimens were captured in Bluefish Lake in September 2012. Bluefish Lake is on the Yellowknife River, approximately 25 km upstream from Great Slave Lake.

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An improved sea ice detection algorithm using MODIS: application as a new European sea ice extent indicator

The Cryosphere ◽

10.5194/tc-15-2803-2021 ◽

2021 ◽

Vol 15 (6) ◽

pp. 2803-2818

Author(s):

Joan Antoni Parera-Portell ◽

Raquel Ubach ◽

Charles Gignac

Keyword(s):

Sea Ice ◽

Regional Scale ◽

Ice Cover ◽

Detection Algorithm ◽

Temporal Variations ◽

The Arctic ◽

Sea Ice Extent ◽

Monitoring Tools ◽

Spatio Temporal ◽

Ice Detection

Abstract. The continued loss of sea ice in the Northern Hemisphere due to global warming poses a threat to biota and human activities, evidencing the necessity of efficient sea ice monitoring tools. Aiming at the creation of an improved sea ice extent indicator covering the European regional seas, the new IceMap500 algorithm has been developed to classify sea ice and water at a resolution of 500 m at nadir. IceMap500 features a classification strategy built upon previous MODIS sea ice extent algorithms and a new method to reclassify areas affected by resolution-breaking features inherited from the MODIS cloud mask. This approach results in an enlargement of mapped area, a reduction of potential error sources and a better delineation of the sea ice edge, while still systematically achieving accuracies above 90 %, as obtained by manual validation. Swath maps have been aggregated at a monthly scale to obtain sea ice extent with a method that is sensitive to spatio-temporal variations in the sea ice cover and that can be used as an additional error filter. The resulting dataset, covering the months of maximum and minimum sea ice extent (i.e. March and September) over 2 decades (from 2000 to 2019), demonstrates the algorithm's applicability as a monitoring tool and as an indicator, illustrating the sea ice decline at a regional scale. The European sea regions located in the Arctic, NE Atlantic and Barents seas display clear negative trends in both March (−27.98 ± 6.01 × 103 km2yr−1) and September (−16.47 ± 5.66 × 103 km2yr−1). Such trends indicate that the sea ice cover is shrinking at a rate of ∼ 9 % and ∼ 13 % per decade, respectively, even though the sea ice extent loss is comparatively ∼ 70 % greater in March.

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