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Solving Challenges of Assimilating Microwave Remote Sensing Signatures With a Physical Model to Estimate Snow Water
Ioanna Merkouriadi1, Juha Lemmetyinen1, Glen E Liston2
1Finnish Meteorological Institute Helsinki Finland.
Water Resources Research
|November 26, 2021
Summary
Accurate snow water equivalent (SWE) estimation using microwave data is challenging due to snow microstructure. Physical snow models can improve SWE retrievals by accounting for these microstructural relationships.
Area of Science:
- Earth Science
- Remote Sensing
- Hydrology
Background:
- Global monitoring of seasonal snow water equivalent (SWE) has advanced, but microwave-based SWE estimation faces challenges.
- Accurate a priori characterization of snow properties is crucial for reliable SWE retrievals from passive and active microwave signatures.
Purpose of the Study:
- To identify challenges in assimilating microwave signatures with physical snow models for SWE estimation.
- To examine potential solutions for improving microwave-based SWE retrievals by integrating physical snow models.
Main Methods:
- Designed a sensitivity experiment based on a point-based study.
- Quantified the effects of changes in physically modeled SWE and snowpack properties on microwave-based SWE retrievals.
Main Results:
- Assimilating microwave signatures with physical snow models presents critical challenges related to the physical relationship between SWE and snow microstructure.
- Sensitivity experiments revealed the impact of snow microstructure on microwave SWE retrieval accuracy.
Conclusions:
- Challenges in microwave-based SWE estimation can be overcome.
- Microwave algorithms must account for the physical relationships between SWE and snow microstructure for improved accuracy.
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