River ice phenology and thickness from satellite altimetry: potential for ice bridge road operation and climate studies

Abstract

Abstract. River ice is a key component of the cryosphere. Satellite monitoring of river ice is a rapidly developing area of scientific enquiry, which has wide-ranging implications for climate, environmental and socioeconomic applications. Spaceborne radar altimetry is widely used for monitoring river water regimes; however, its potential for the observation of river ice processes and properties has not been demonstrated yet. Using Ku-band backscatter measurements from the Jason-2 and Jason-3 satellite missions (2008–2019), we demonstrate the potential of radar altimetry for the retrieval of river ice phenology dates and ice thickness for the first time. The altimetric measurements were determined to be sensitive enough to detect the first appearance of ice and the beginning of thermal breakup on the lower Ob River (Western Siberia). The uncertainties in the retrieval of ice event timing were within the 10 d repeat cycle of Jason-2 and Jason-3 in 88 %–90 % of the cases analysed. The uncertainties in the river ice thickness retrievals made via empirical relations between the satellite backscatter measurements and in situ observations, expressed as the root mean square error (RMSE), were of 0.07–0.18 m. A novel application of radar altimetry is the prediction of ice bridge road operations, which is demonstrated herein. We established that the dates of ferry closing and ice road opening and closing in the city of Salekhard can be predicted with an accuracy (expressed as RMSE) of 3–5 d.

Ice thickness and water level estimation for ice-covered lakes with satellite altimetry waveforms and backscattering coefficients

“…4 associated with ice growth and is dependent on in situ measurements, which limits a wider application of the method. In addition, we found that the performance of LIT estimation using only one regression model with one set of model parameters can be fairly unstable from year to year and from lake to lake, partially because the initial ice and snow conditions can be very different for each winter and each lake, which is also mentioned by Zakharova et al (2021).…”

“…To evaluate the performance of the logarithmic model we proposed (equation ( 10)) to convert backscattering coefficients into LIT, we compared it with the power function model used by Zakharova et al (2021). To evaluate the feasibility of both models, we directly used in situ LIT in Baker Lake instead of waveform-based LIT to generate model parameters, which could represent the best performance of both models ideally.…”

“…To evaluate the feasibility of both models, we directly used in situ LIT in Baker Lake instead of waveform-based LIT to generate model parameters, which could represent the best performance of both models ideally. In addition, Zakharova et al (2021) used parameters derived from training data sets and applied to all ice-covered seasons. Here we derived separate parameters for each ice-covered season for both models due to the large variability of optimal parameter sets in different ice-covered seasons.…”

“…Backscattering coefficients from satellite altimeters were also used in lake ice phenology. A recent study (Zakharova et al, 2021) investigated the relationship between the altimetry-based backscattering coefficients and in situ river ice thickness, suggesting the great potential of altimetry-based backscattering coefficients in estimating LIT for thin ice. However, in situ ice thickness data are necessary to derive regression models, which greatly limits applications of the method developed by Zakharova et al (2021).…”

“…A recent study (Zakharova et al, 2021) investigated the relationship between the altimetry-based backscattering coefficients and in situ river ice thickness, suggesting the great potential of altimetry-based backscattering coefficients in estimating LIT for thin ice. However, in situ ice thickness data are necessary to derive regression models, which greatly limits applications of the method developed by Zakharova et al (2021). To avoid confusion, the term "backscattering coefficients" refers to altimetrybased backscattering coefficients in the following context, unless otherwise stated.…”