Estimation of Lake Ice Thickness with Satellite Radar Altimeter Waveforms
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Résumé
Background and Relevance: The phenology of seasonally ice covered lakes has been altered with anthropogenic climate change; recent studies point out an overall reduction in the number of days in which the lake is covered with ice [1]. Lake ice is essential for many northern communities in fishing and travel. Reductions in the thickness in ice is a major safety risk, especially when those who travel on ice have historically been able to trust it. Remote sensing efforts have majorly focused on sea ice and glacial changes, and little is known about changes in lake ice thickness besides the seasonal length of ice coverage. Previous researchers have determined that the Ku-band (13 to 17 GHz) is capable of penetrating through freshwater ice and is scattered from both the snow/ice and the ice/water interfaces [1]. A radar altimeter operating at the Ku-band holds the potential to measure the height of the sensor above the snow/ice interface and above the ice/water interface. The difference between these two measurements yields the ice thickness. This method has been confirmed with data from the Cryosat-2 satellite [1], but only tested with arctic lakes. There is a gap in knowledge of how midlatitude lakes have responded to changing climates in terms of their seasonal ice thickness. Objectives and Methods: Ku-band radar altimeter measurements from the JASON series of satellites can be used to determine lake ice thickness by calculating the distance between dualpeak waveforms, representative of snow/ice and ice/water interfaces. A study area will be chosen after a review of the available data coverage and an overall analysis of scattering. Snowpack, bubbles, and wetness of the ice adds noise to the waveform and complicates the ice thickness retrieval. A lake that minimizes these factors will be selected for the study area. Data will be extracted from an orbit passing over the lake for each month of a year and in intervals of 5 years. The JASON series has the following advantages to the Cryosat-2 satellite: Improved temporal resolution – CryoSat-2 covers polar regions, while the JASON Series covers the area between N: 66.15° N and S: -66.15°; and greater coverage – Jason-1/2/3 have the shortest revisit cycle (~10 days) among all existing satellite altimeters and have been operating since 1992 [2]. The radar altimeter measurements will be displayed as the travel distance as a function of mean normalized power. The difference between peaks on the waveform will be calculated and logged as the ice thickness during that time. The results will be validated by comparing the estimated lake ice thickness values with ice fishing logs from similar dates. There is potential for the ice thickness data to be interpolated across the entirety of the lake using ArcGIS Pro, but this is contingence on the specifics of the study area. Anticipated Contributions: This study will: (1) estimate ice thickness in areas where in situ drillhole measurements cannot be taken, (2) introduce another factor in climate change discussions and models, (3) further our ability to monitor biophysical factors with remote sensing at global scales. [1] J. F. Beckers, J. Alec Casey and C. Haas, "Retrievals of Lake Ice Thickness From Great Slave Lake and Great Bear Lake Using CryoSat-2," in IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 7, pp. 3708-3720, July 2017, doi: 10.1109/TGRS.2017.2677583. [2] C. J. Donlon et al., “The Copernicus Sentinel-6 mission: Enhanced continuity of satellite sea level measurements from space,” Remote sensing of environment, vol. 258, p. 112395–, 2021, doi: 10.1016/j.rse.2021.112395.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
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