资源环境科技发展态势分析平台

Two-year observations of a Ka-band Zenith Radar at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) are used to document the midlatitude cirrus cloud macroproperties. Generally, cirrus occurs 41.6% of the observation time and most frequently appear at about 7.2 km above ground level. The cirrus macroproperties are strongly coupled with large-scale atmospheric states; thus, its occurrence and location over the SACOL have significant seasonal variations. A k-mean clustering method is used to classify cirrus into four distinct regimes without a prior knowledge about the meteorological process. Contrasting to the different cirrus physical properties in each regime, the cirrus event of each regime has a distinct seasonal distribution and the synoptic conditions from the ERA-Interim reanalysis responsible for each cirrus regime are also quite different. Since global climate models typically overestimate cirrus cloud thickness due to inadequate parameterization or coarse grid resolution, we examined the probability density functions of large-scale vertical velocity associated with each cirrus regime and the relationship between cirrus thickness and vertical velocity. It is found that the differences of the vertical velocity probability density functions among the cirrus regimes are as distinct as their macroproperties and a significant correlation exists between cirrus thickness and the vertical velocity, although the large-scale vertical motion is nearly as likely to be descending as ascending when cirrus clouds are observed. This may imply that large-scale vertical velocity can be used to constrain the variations of cirrus thickness simulated by global climate models.

Plain Language Summary Cirrus clouds are composed of large amount of ice crystals, most frequently distributed in the midlatitude storm track regions and the tropics, and cover about 30% of the Earth surface. They have significant impact on water cycle and radiative balance and thus play an important role in our climate system. These processes strongly depend on the cirrus properties such as top height and vertical distribution. However, cirrus clouds are still a great challenge to be accurately represented in climate models due to incomplete knowledge of their occurrence and physical and dynamical properties that can cause large uncertainties in climate prediction. We obtained the cirrus macroproperties from the cloud radar observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (a midlatitude site in western China) and found that the cirrus macroproperties are strongly coupled with large-scale atmospheric states. This may help us to better understand the connection between cirrus properties and dynamic processes.