Fractal geometry of aggregate snowflakes revealed by triple wavelength radar measurements

[thumbnail of Open Access]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.
| Preview
Available under license: Creative Commons Attribution
[thumbnail of triplew_rev.pdf]
Text - Accepted Version
· Restricted to Repository staff only
Restricted to Repository staff only

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Stein, T. H. M. orcid id iconORCID: https://orcid.org/0000-0002-9215-5397, Westbrook, C. D. orcid id iconORCID: https://orcid.org/0000-0002-2889-8815 and Nicol, J. (2015) Fractal geometry of aggregate snowflakes revealed by triple wavelength radar measurements. Geophysical Research Letters, 42 (1). pp. 176-183. ISSN 0094-8276 doi: 10.1002/2014GL062170

Abstract/Summary

Radar reflectivity measurements from three different wavelengths are used to retrieve information about the shape of aggregate snowflakes in deep stratiform ice clouds. Dual-wavelength ratios are calculated for different shape models and compared to observations at 3, 35 and 94 GHz. It is demonstrated that many scattering models, including spherical and spheroidal models, do not adequately describe the aggregate snowflakes that are observed. The observations are consistent with fractal aggregate geometries generated by a physically-based aggregation model. It is demonstrated that the fractal dimension of large aggregates can be inferred directly from the radar data. Fractal dimensions close to 2 are retrieved, consistent with previous theoretical models and in-situ observations.

Altmetric Badge

Additional Information 2014GL062170
Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/38672
Identification Number/DOI 10.1002/2014GL062170
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Uncontrolled Keywords Cloud physics and chemistry, Snow, Remote sensing, snow, radar, scattering
Additional Information 2014GL062170
Publisher American Geophysical Union
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar