Triple-frequency radar retrieval of microphysical properties of snow
<p>An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underp...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/48621ed5b580429ea63b7ff3f1b614c1 |
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| Sumario: | <p>An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is
presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin
better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming
parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic
snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign,
in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ
measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous
validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and
mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for <span class="inline-formula">log <sub>10</sub>IWC</span> and
<span class="inline-formula">log <sub>10</sub><i>D</i><sub>m</sub></span>. The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains
results that are highly correlated with the in situ data.</p> |
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