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Comparison of Macro- and Microphysical Properties in Precipitating and Non-Precipitating Clouds over Central-Eastern China during Warm Season
- Source :
- Remote Sensing, Vol 14, Iss 1, p 152 (2021)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- The macro- and microphysical properties of clouds can reflect their vertical physical structure and evolution and are important indications of the formation and development of precipitation. We used four-year merged CloudSat-CALIPSO-MODIS products to distinguish the macro- and microphysical properties of precipitating and non-precipitating clouds over central-eastern China during the warm season (May–September). Our results showed that the clouds were dominated by single- and double-layer forms with occurrence frequencies > 85%. Clouds with a low probability of precipitation (POP) were usually geometrically thin. The POP showed an increasing trend with increases in the cloud optical depth, liquid water path, and ice water path, reaching maxima of 50%, 60%, and 75%, respectively. However, as cloud effective radius (CER) increased, the POP changed from an increasing to a decreasing trend for a CER > 22 μm, in contrast with our perception that large particles fall more easily against updrafts, but this shift can be attributed to the transition of the cloud phase from mixed clouds to ice clouds. A high POP > 60% usually occurred in mixed clouds with vigorous ice-phase processes. There were clear differences in the microphysical properties of non-precipitating and precipitating clouds. In contrast with the vertical evolution of non-precipitating clouds with weaker reflectivity, precipitating clouds were present above 0 dBZ with a significant downward increase in reflectivity, suggesting inherent differences in cloud dynamical and microphysical processes. Our findings highlight the differences in the POP of warm and mixed clouds, suggesting that the low frequency of precipitation from water clouds should be the focus of future studies.
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 14
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.b996e60820874958bb9e245151bea048
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs14010152