Ice and snow cover on lakes from radar altimetry and radiometry: case of the lake Baikal
14 av Edouard Belin,
Alexei V. Kouraev (1,2), Sergei V. Semovski (3), Michail N. Shimaraev (3), Nelly M. Mognard (1), Benoit Legresy (1), Frederique Remy (1)
(1) Laboratory of geophysical studies and satellite oceanography (LEGOS), Toulouse, France,
(2) State Oceanography Institute, St. Petersburg branch, St. Petersburg, Russia,
(3) Limnological Institute, Siberian Branch of Russian Academy of Sciences, Irkutsk, Russia
The state of ice cover, and the freeze-up and break-up dynamics of lakes are good indicators of large-scale climate changes. We demonstrate the potential of multi-sensor data fusion for studies of ice and snow cover for lake Baikal in Siberia. We show the synergy of the combined use of passive and active microwave satellite data - simultaneous active and passive observations available from the recent satellite altimetry missions (TOPEX/Poseidon, Jason-1, ENVISAT and Geosat Follow-On), as well as passive data fromSSM/I sensor. All altimetry platforms have two nadir-looking instruments: a dual-frequency radar altimeter and a passive microwave radiometer that operate simultaneously. Though the primary mission of satellite altimeters was to measure sea level, we have found that the combination of active and passive microwave measurements could be successfully used for the sea, lake and river ice cover studies. This information was complemented by long time series from the SMMR side-looking radiometer.
We propose a methodology for ice discrimination and estimation of snow height and we discuss the drawbacks and benefits of each type of data. The resulting satellite-derived series of dates of ice cover formation and break-up and snow height estimations are analysed together with existing observations at coastal stations and other satellite and in situ data. These time series show pronounced regional, seasonal and interannual variability and for the first time provide continuous time series of modern ice cover variability in lake Baikal at the lake-wide scale. Comparison of historical data with satellite observations shows that fusion of multi-sensor data is able to reliably extend existing time series of ice cover parameters and provide new information for regions not previously covered by observations.