The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow
<p>The accurate representation of ice particles is essential for both remotely sensed estimates of clouds and precipitation and numerical models of the atmosphere. As it is typical in radar retrievals to assume that all snow is composed of aggregate snowflakes, both denser rimed snow and the m...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-09-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://www.atmos-meas-tech.net/12/4993/2019/amt-12-4993-2019.pdf |
| _version_ | 1811208700434579456 |
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| author | S. L. Mason S. L. Mason R. J. Hogan R. J. Hogan C. D. Westbrook S. Kneifel D. Moisseev D. Moisseev L. von Terzi |
| author_facet | S. L. Mason S. L. Mason R. J. Hogan R. J. Hogan C. D. Westbrook S. Kneifel D. Moisseev D. Moisseev L. von Terzi |
| author_sort | S. L. Mason |
| collection | DOAJ |
| description | <p>The accurate representation of ice particles is essential for both remotely sensed estimates of clouds and precipitation and numerical models of the atmosphere.
As it is typical in radar retrievals to assume that all snow is composed of aggregate snowflakes, both denser rimed snow and the mixed-phase cloud in which riming occurs may be under-diagnosed in retrievals and therefore difficult to evaluate in weather and climate models.
Recent experimental and numerical studies have yielded methods for using triple-frequency radar measurements to interrogate the internal structure of aggregate snowflakes and to distinguish more dense and homogeneous rimed particles from aggregates.</p>
<p>In this study we investigate which parameters of the morphology and size distribution of ice particles most affect the triple-frequency radar signature and must therefore be accounted for in order to carry out triple-frequency radar retrievals of snow.
A range of ice particle morphologies are represented, using a fractal representation for the internal structure of aggregate snowflakes and homogeneous spheroids to represent graupel-like particles;
the mass–size and area–size relations are modulated by a density factor.
We find that the particle size distribution (PSD) shape parameter and the parameters controlling the internal structure of aggregate snowflakes both have significant influences on triple-frequency radar signature and are at least as important as that of the density factor.
We explore how these parameters may be allowed to vary in order to prevent triple-frequency radar retrievals of snow from being over-constrained, using two case studies from the Biogenic Aerosols – Effects of Clouds and Climate (BAECC) 2014 field campaign at Hyytiälä, Finland.
In a case including heavily rimed snow followed by large aggregate snowflakes, we show that triple-frequency radar measurements provide a strong constraint on the PSD shape parameter, which can be estimated from an ensemble of retrievals;
however, resolving variations in the PSD shape parameter has a limited impact on estimates of snowfall rate from radar.
Particle density is more effectively constrained by the Doppler velocity than triple-frequency radar measurements, due to the strong dependence of particle fall speed on density.
Due to the characteristic signatures of aggregate snowflakes, a third radar frequency is essential for effectively constraining the size of large aggregates.
In a case featuring rime splintering, differences in the internal structures of aggregate snowflakes are revealed in the triple-frequency radar measurements. We compare retrievals assuming different aggregate snowflake models against in situ measurements at the surface and show significant uncertainties in radar retrievals of snow rate due to changes in the internal structure of aggregates.
The importance of the PSD shape parameter and snowflake internal structure to triple-frequency radar retrievals of snow highlights that the processes by which ice particles interact may need to be better understood and parameterized before triple-frequency radar measurements can be used to constrain retrievals of ice particle morphology.</p> |
| first_indexed | 2024-04-12T04:26:00Z |
| format | Article |
| id | doaj.art-bd97419c0b7e4681adfde24df5769bc4 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-04-12T04:26:00Z |
| publishDate | 2019-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-bd97419c0b7e4681adfde24df5769bc42022-12-22T03:48:05ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482019-09-01124993501810.5194/amt-12-4993-2019The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snowS. L. Mason0S. L. Mason1R. J. Hogan2R. J. Hogan3C. D. Westbrook4S. Kneifel5D. Moisseev6D. Moisseev7L. von Terzi8Department of Meteorology, University of Reading, Reading, UKNational Centre for Earth Observation, University of Reading, Reading, UKDepartment of Meteorology, University of Reading, Reading, UKEuropean Centre for Medium-range Weather Forecasts, Reading, UKDepartment of Meteorology, University of Reading, Reading, UKDepartment of Geophysics and Meteorology, University of Cologne, Cologne, GermanyInstitute for Atmospheric and Earth System Research, University of Helsinki, Helsinki, FinlandFinnish Meteorological Institute, Helsinki, FinlandDepartment of Geophysics and Meteorology, University of Cologne, Cologne, Germany<p>The accurate representation of ice particles is essential for both remotely sensed estimates of clouds and precipitation and numerical models of the atmosphere. As it is typical in radar retrievals to assume that all snow is composed of aggregate snowflakes, both denser rimed snow and the mixed-phase cloud in which riming occurs may be under-diagnosed in retrievals and therefore difficult to evaluate in weather and climate models. Recent experimental and numerical studies have yielded methods for using triple-frequency radar measurements to interrogate the internal structure of aggregate snowflakes and to distinguish more dense and homogeneous rimed particles from aggregates.</p> <p>In this study we investigate which parameters of the morphology and size distribution of ice particles most affect the triple-frequency radar signature and must therefore be accounted for in order to carry out triple-frequency radar retrievals of snow. A range of ice particle morphologies are represented, using a fractal representation for the internal structure of aggregate snowflakes and homogeneous spheroids to represent graupel-like particles; the mass–size and area–size relations are modulated by a density factor. We find that the particle size distribution (PSD) shape parameter and the parameters controlling the internal structure of aggregate snowflakes both have significant influences on triple-frequency radar signature and are at least as important as that of the density factor. We explore how these parameters may be allowed to vary in order to prevent triple-frequency radar retrievals of snow from being over-constrained, using two case studies from the Biogenic Aerosols – Effects of Clouds and Climate (BAECC) 2014 field campaign at Hyytiälä, Finland. In a case including heavily rimed snow followed by large aggregate snowflakes, we show that triple-frequency radar measurements provide a strong constraint on the PSD shape parameter, which can be estimated from an ensemble of retrievals; however, resolving variations in the PSD shape parameter has a limited impact on estimates of snowfall rate from radar. Particle density is more effectively constrained by the Doppler velocity than triple-frequency radar measurements, due to the strong dependence of particle fall speed on density. Due to the characteristic signatures of aggregate snowflakes, a third radar frequency is essential for effectively constraining the size of large aggregates. In a case featuring rime splintering, differences in the internal structures of aggregate snowflakes are revealed in the triple-frequency radar measurements. We compare retrievals assuming different aggregate snowflake models against in situ measurements at the surface and show significant uncertainties in radar retrievals of snow rate due to changes in the internal structure of aggregates. The importance of the PSD shape parameter and snowflake internal structure to triple-frequency radar retrievals of snow highlights that the processes by which ice particles interact may need to be better understood and parameterized before triple-frequency radar measurements can be used to constrain retrievals of ice particle morphology.</p>https://www.atmos-meas-tech.net/12/4993/2019/amt-12-4993-2019.pdf |
| spellingShingle | S. L. Mason S. L. Mason R. J. Hogan R. J. Hogan C. D. Westbrook S. Kneifel D. Moisseev D. Moisseev L. von Terzi The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow Atmospheric Measurement Techniques |
| title | The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow |
| title_full | The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow |
| title_fullStr | The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow |
| title_full_unstemmed | The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow |
| title_short | The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow |
| title_sort | importance of particle size distribution and internal structure for triple frequency radar retrievals of the morphology of snow |
| url | https://www.atmos-meas-tech.net/12/4993/2019/amt-12-4993-2019.pdf |
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