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

Abstract

Abstract. Time series of brightness temperatures (T B ) 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). T B 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 (Hpol) channel is found to be the most suitable for estimating these ice dates as well as the duration of the ice cover and icefree 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)(2003)(2004)(2005)(2006)(2007)(2008)(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 (freezeonset 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.

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

“…It can reach 100-140 cm on Baikal, 40-60 cm on Ladoga. 100-120 cm on GBL and GSL (Galaziya, 1984;Tulokhonov, 2008;Kang et al, 2010Kang et al, , 2012Rumyantsev et al, 2012;Rumyantsev, 2015; https://www.ccin.ca/home/ccw/lakeice/links). Brightness temperature oscillations (by MIRAS data) in TR2 are explained by the interference of electromagnetic waves 25 occurring due to reflection at the upper and bottom boundaries of the ice cover.…”

“…As to Baikal and Ladoga, these are Russian language works of Galaziya (1984), Tulokhonov (2008, Rumyantsev et al (2012), Rumyantsev (2015), 15 as well as websites of the Institute of Lake Science of the Russian Academy of Sciences (http://www.limno.org.ru) and the Climatic Reference Book of the Settlements of Russia (http://atlasyakutia.ru/). For GBL and GSL, we used data of Woo et al (2007), Rouse et al (2008), Kang et al (2010Kang et al ( , 2012Kang et al ( , 2014, and Kang (2012), as well as websites of the Canadian Cryospheric Information Network and Polar Data Catalogue (https://www.ccin.ca/home/ccw/lakeice/links), Environment and 20 Natural resources (https://www.canada.ca/en/services/environment.html), Environment and Climate Change Canada (http://www.ec.gc.ca/default.asp?lang=en&n=FD9B0E51-1). In case of Huron, data provided by Rumyantsev et al (2012) and NOAA websites (https://www.glerl.noaa.gov//metdata/, https://coastwatch.glerl.noaa.gov/statistic/statistic.html,) were used.…”

“…The channel data allow determining the dates of ice cover freeze-onset/melt-onset and ice-on/ice-off (Kang et al, 2010;Kang, 2012;Kang et al, 2012). It was found in (Kang et al, 2010;Kang, 2012;Kang et al, 2014) that at 18.7 GHz V-pol, brightness temperature greatly depends on ice thickness.…”

“…It was found in (Kang et al, 2010;Kang, 2012;Kang et al, 2014) that at 18.7 GHz V-pol, brightness temperature greatly depends on ice thickness. The results obtained in these works enabled the authors to develop an algorithm for the determination of 10 phenology phases of lake ice cover from 18.7 GHz H-pol (Kang, 2012;Kang et al, 2012) data, as well as calculate simple regression dependencies of ice thickness on 18.7 GHz V-pol brightness temperature (Kang, 2012;Kang et al, 2014) for GBL and GSL.…”

“…They are also used to assess the depth and phenology of ice cover of large freshwater lakes. Kang et al (2010Kang et al ( , 2012Kang et al ( , 2014 analyzed seasonal variations of brightness temperature at GBL and GSL derived from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) data. They 5 demonstrated that the 18.7 GHz H-pol channel was the most sensitive to the phenology of ice cover.…”