Using a high-resolution snow process model to inform microwave forward and retrieval models on the physical relationship of snow properties ...
Previous studies have investigated the synergies between snow process models and passive microwave (PMW) remote sensing to fill the lack of information in the PMW obser-vations to retrieve the snow properties, especially the snow mass. We present a case study that expands the previous work, performe...
| Main Authors: | , , |
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| Format: | Conference Object |
| Language: | unknown |
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Zenodo
2024
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5281/zenodo.12750418 https://zenodo.org/doi/10.5281/zenodo.12750418 |
| Summary: | Previous studies have investigated the synergies between snow process models and passive microwave (PMW) remote sensing to fill the lack of information in the PMW obser-vations to retrieve the snow properties, especially the snow mass. We present a case study that expands the previous work, performed in a tower setting, to a satellite case. We use a state-of-the-art snow process model with high spatial resolution, to produce a time series of snow states over a study area in the northern Finland, and we simulate the vertically polarized brightness temperature (BT) time series at the frequencies 18.7 GHz and 36.5 GHz. We compare the modeled BTs against the satellite observations. We identify factors, on one hand, in the snow process modeling, and on the other hand, in the radiative transfer modeling, that are responsible for the errors. We also analyze the effect of spatial heterogeneity of the modeled snow properties on the coarse resolution satellite observed BT and conclude that itdoes not play a ... |
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