Evaluation of ice particle growth in ICON using statistics of multi‐frequency Doppler cloud radar observations
Evaluation of ice particle growth in ICON using statistics of multi‐frequency Doppler cloud radar observations
复制标题
使用多频多普勒云雷达观测统计数据评估 ICON 中的冰粒生长
DOI:
10.1002/qj.3875
复制
发表时间:
--
影响因子:
8.9
通讯作者:
S. Kneifel
中科院分区:
文献类型:
--
作者:
V. Schemann;M. Karrer;J. Dias Neto;L. von Terzi;A. Seifert;S. Kneifel
Vertically pointing radar observations combining multiple frequencies and Doppler measurements have been recently shown to contain valuable information about ice particle growth processes, such as aggregation and riming. In this study, we use a two‐months X, Ka, W‐Band Doppler radar dataset of midlatitude winter clouds to infer statistical growth signatures of ice and snow particles. The observational statistics are compared to forward‐simulated radar moments based on simulations of the campaign time period with a high‐resolution version of the ICON model and a two‐moment microphysical scheme. The statistical comparison shows very good agreement of the simulated vertical structure of radar reflectivity and surface precipitation rate. The dual‐wavelength ratios, which are closely related to the mean particle size, also show consistently a major increase at temperatures higher than –15 °C. However, at temperatures higher than –7 °C, ICON increasingly overestimates the mean particle size. The statistics of mean Doppler velocities also reveal that the model overestimates the terminal velocity of snow particles, especially at larger sizes. We discuss possible reasons for the identified discrepancies, such as an unrealistic temperature dependence of the sticking efficiency or the non‐saturation of terminal velocities at larger sizes caused by the implemented power law relations. Our study demonstrates examples of the importance of combining various radar techniques for identifying issues in simulated microphysical processes, which can otherwise be hidden due to compensating errors.
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DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
Mengtao Yin;Guosheng Liu;R. Honeyager;F. Turk
通讯作者:
F. Turk
DOI:
--
发表时间:
2011
期刊:
影响因子:
--
作者:
G. Petty;Wei Huang
通讯作者:
Wei Huang
影响因子:
6.8
作者:
A. Seifert;J. Leinonen;C. Siewert;S. Kneifel
通讯作者:
S. Kneifel
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
S. Brdar;A. Seifert
通讯作者:
A. Seifert
影响因子:
5.1
作者:
Reitter;K. Fröhlich;A. Seifert;S. Crewell;M. Mech
通讯作者:
M. Mech