GSTDTAP  > 地球科学
DOI10.1175/JAS-D-20-0007.1
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations
Kneifel, Stefan; Moisseev, Dmitri
2020-10-01
发表期刊Journal of the Atmospheric Sciences
出版年2020
英文摘要

Riming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice particle mass, riming enhances the particle’s terminal velocity, which can be detected by ground-based vertically pointing cloud radars if the effect of vertical air motions can be sufficiently mitigated. In our study, we first revisit a previously published approach to relate the radar mean Doppler velocity (MDV) to rime mass fraction (FR) using a large ground-based in situ dataset. This relation is then applied to multiyear datasets of cloud radar observations collected at four European sites covering polluted central European, clean maritime, and Arctic climatic conditions. We find that riming occurs in 1%–8% of the nonconvective ice containing clouds with median FR between 0.5 and 0.6. Both the frequency of riming and FR reveal relatively small variations for different seasons. In contrast to previous studies, which suggested enhanced riming for clean environments, our statistics indicate the opposite; however, the differences between the locations are overall small. We find a very strong relation between the frequency of riming and temperature. While riming is rare at temperatures lower than −12°C, it strongly increases toward 0°C. Previous studies found a very similar temperature dependence for the amount and droplet size of supercooled liquid water, which might be closely connected to the riming signature found in this study. In contrast to riming frequency, we find almost no temperature dependence for FR.

领域地球科学 ; 气候变化
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/297877
专题地球科学
气候变化
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Kneifel, Stefan,Moisseev, Dmitri. Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations[J]. Journal of the Atmospheric Sciences,2020.
APA Kneifel, Stefan,&Moisseev, Dmitri.(2020).Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations.Journal of the Atmospheric Sciences.
MLA Kneifel, Stefan,et al."Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations".Journal of the Atmospheric Sciences (2020).
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