4.7 Article

Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors

期刊

GEOPHYSICAL RESEARCH LETTERS
卷 48, 期 2, 页码 -

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2020GL089863

关键词

avhrr; caliop; mixed-phase clouds; remote sensing; satellite data; validation

资金

  1. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme [714062]
  2. Ministry of Science, Research and the Arts Baden-Wurttemberg
  3. Federal Ministry of Education and Research
  4. European Space Agency (ESA) through the Cloud_cci project [4000128637/20/I-NB]
  5. EUMETSAT
  6. CM SAF

向作者/读者索取更多资源

The study examines the distribution of supercooled liquid fraction in clouds with different temperatures, geographical locations, and cloud types using four satellite-based datasets. Despite discrepancies in phase and temperature between passive and active satellite sensors, all datasets show an increase in SLF with cloud optical thickness and generally larger SLF in the Southern Hemisphere compared to the Northern Hemisphere, except for continental low-level clouds.
One of the largest uncertainties in numerical weather prediction and climate models is the representation of mixed-phase clouds. With the aim of understanding how the supercooled liquid fraction (SLF) in clouds with temperature from -40 degrees C to 0 degrees C is related to temperature, geographical location, and cloud type, our analysis contains a comparison of four satellite-based datasets (one derived from active and three from passive satellite sensors), and focuses on SLF distribution near-globally, but also stratified by latitude and continental/maritime regions. Despite the warm bias in cloud top temperature of the passive sensor compared to the active sensor and the phase mismatch in collocated data, all datasets indicate, at the same height-level, an increase of SLF with cloud optical thickness, and generally larger SLF in the Southern Hemisphere than in the Northern Hemisphere (up to about 20% difference), with the exception of continental low-level clouds, for which the opposite is true. Plain Language Summary In mixed-phase clouds, hydrometeors consisting of ice and supercooled liquid water (i.e., water below 0 degrees C) can exist simultaneously. In the mixed-phase temperature range (-40 degrees C to 0 degrees C), ice-nucleating particles (e.g., mineral dusts, biological aerosol particles) are needed for glaciation to be possible. The partitioning into liquid and ice depends not only on the ice-nucleating particles, but also, for example, on cloud dynamics and ice multiplication processes, influencing in turn the lifetime and the precipitation type of these clouds, and the Earth-atmosphere energy balance locally and globally. In this study, we show ice and liquid partitioning for different cloud types, comparing four satellite-based datasets. This allows us to identify robustly their common trends despite their differences. Our results show on average less ice in the Northern than in the Southern Hemisphere when considering all clouds together, and that the larger the cloud optical thickness, the less ice when treating the cloud types separately. The partitioning of cloud types over sea and over land in both hemispheres show less ice in the Southern than in the Northern Hemisphere for high-level and mid-level clouds, but the opposite for low-level clouds over land. This might be due to differences in aerosol composition and distribution. Key Points . Despite phase and temperature mismatches, the retrievals based on passive and active satellite sensors qualitatively agree on the following Supercooled liquid fraction is larger in the Southern Hemisphere than in the Northern Hemisphere, except for continental low-level clouds In clouds with temperatures from -40 degrees C to 0 degrees C at the same height-level, supercooled liquid fraction increases with cloud optical thickness

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据