Observations of Lake Baikal ice from satellite altimetry and radiometry

Kouraev, Alexei V.; Semovski, S.V.; Shimaraev, M. N.; Mognard, N. M.; Legrésy, B.; Rémy, Frédérique

doi:10.1016/j.rse.2006.11.010

Cited by 70 publications

(62 citation statements)

References 26 publications

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“…Dual-frequency altimeters haves already demonstrated their potential for the lake-ice characteristics [120] and the estimation of snow pack thickness [121]. Preliminary work using dual-frequency observations over Antarctica indicate an ability to separate surface and volume signals, and consequently to derive parameters such as snow grain size and surface roughness.…”

Section: Discussionmentioning

confidence: 99%

Antarctic Ice Sheet and Radar Altimetry: A Review

Rémy

Parouty

2009

Remote Sensing

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Abstract:Altimetry is probably one of the most powerful tools for ice sheet observation. Our vision of the Antarctic ice sheet has been deeply transformed since the launch of the ERS1 satellite in 1991. With the launch of ERS2 and Envisat, the series of altimetric observations now provides 19 years of continuous and homogeneous observations that allow monitoring of the shape and volume of ice sheets. The topography deduced from altimetry is one of the relevant parameters revealing the processes acting on ice sheet. Moreover, altimeter also provides other parameters such as backscatter and waveform shape that give information on the surface roughness or snow pack characteristics.

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Section: Discussionmentioning

confidence: 99%

Antarctic Ice Sheet and Radar Altimetry: A Review

Rémy

Parouty

2009

Remote Sensing

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“…Waveform retracking is replaced the classic Brown model [20], which is more suited to process the waveforms returned from open ocean with statistical parameters. Empirical waveform retrackers were also invented to analyze radar echoes from ice sheet [21,22], ice floes [23] and, more recently, coastal areas [24], inland waters [25][26][27][28], and even for bare land [29]. The accuracy of satellite radar altimetry is generally ranging from the 5 cm level for open ocean [30], to the 10-40 cm level for coastal and large inland waters [24,31], and the 30-90 cm level for narrow rivers [32,33].…”

Section: Radar and Laser Altimetrymentioning

confidence: 99%

Quantifying Freshwater Mass Balance in the Central Tibetan Plateau by Integrating Satellite Remote Sensing, Altimetry, and Gravimetry

et al. 2016

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Abstract:The Tibetan Plateau (TP) has been observed by satellite optical remote sensing, altimetry, and gravimetry for a variety of geophysical parameters, including water storage change. However, each of these sensors has its respective limitation in the parameters observed, accuracy and spatial-temporal resolution. Here, we utilized an integrated approach to combine remote sensing imagery, digital elevation model, and satellite radar and laser altimetry data, to quantify freshwater storage change in a twin lake system named Chibuzhang Co and Dorsoidong Co in the central TP, and compared that with independent observations including mass changes from the Gravity Recovery and Climate Experiment (GRACE) data. Our results show that this twin lake, located within the Tanggula glacier system, remained almost steady during 1973-2000. However, Dorsoidong Co has experienced a significant lake level rise since 2000, especially during [2000][2001][2002][2003][2004][2005], that resulted in the plausible connection between the two lakes. The contemporary increasing lake level signal at a rate of 0.89˘0.05 cm¨yr´1, in a 2˝by 2˝grid equivalent water height since 2002, is higher than the GRACE observed trend at 0.41˘0.17 cm¨yr´1 during the same time span. Finally, a down-turning trend or inter-annual variability shown in the GRACE signal is observed after 2012, while the lake level is still rising at a consistent rate.

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“…The discrimination of ice cover characteristics from passive microwave brightness temperature (T B ) measurements requires a good knowledge of the radiometric properties of ice in nature (Kouraev et al, 2007). In contrast to the highloss characteristics of sea ice (due to salinity), one of the major microwave characteristics of pure freshwater ice is its low-loss transmission behavior (Ulaby et al, 1986).…”

Section: Passive Microwave Radiometry Of Lake Icementioning

confidence: 99%

“…Lake ice phenology, which encompasses freeze-onset/melt-onset, ice-on/ice-off dates, and ice cover duration, is largely influenced by air temperature changes and is therefore a robust indicator of climate conditions (e.g. Bonsal et al, 2006;Duguay et al, 2006;Kouraev et al, 2007;Latifovic and Pouliot, 2007;Schertzer et al, 2008;Howell et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Previous investigations have shown the utility of observing lake ice phenology variables through the visual interpretation of brightness temperature (T B ) changes from the Scanning Multichannel Microwave Radiometer (SMMR) at 37 GHz (Barry and Maslanik, 1993) and the Special Sensor Microwave/Imager (SSM/I) at 85 GHz (Walker et al, 1993(Walker et al, , 2000 on GSL, but identifying spatial variability in these variables is difficult due to their coarse resolution (∼25 km). In a recent study, SSM/I has been used in combination with radar altimetry to determine automatically ice phenology events on Lake Baikal (Kouraev et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

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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

2012

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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.

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Observations of Lake Baikal ice from satellite altimetry and radiometry

Cited by 70 publications

References 26 publications

Antarctic Ice Sheet and Radar Altimetry: A Review

Antarctic Ice Sheet and Radar Altimetry: A Review

Quantifying Freshwater Mass Balance in the Central Tibetan Plateau by Integrating Satellite Remote Sensing, Altimetry, and Gravimetry

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

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