Browsing by Subject "MELTING LAYER"

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  • Li, Haoran; Korolev, Alexei; Moisseev, Dmitri (2021)
    Mixed-phase clouds are globally omnipresent and play a major role in the Earth's radiation budget and precipitation formation. The existence of liquid droplets in the presence of ice particles is microphysically unstable and depends on a delicate balance of several competing processes. Understanding mechanisms that govern ice initiation and moisture supply are important to understand the life cycle of such clouds. This study presents observations that reveal the onset of drizzle inside a similar to 600m deep mixed-phase layer embedded in a stratiform precipitation system. Using Doppler spectral analysis, we show how large supercooled liquid droplets are generated in Kelvin-Helmholtz (K-H) instability despite ice particles falling from upper cloud layers. The spectral width of the supercooled liquid water mode in the radar Doppler spectrum is used to identify a region of increased turbulence. The observations show that large liquid droplets, characterized by reflectivity values larger than 20 dBZ, are generated in this region. In addition to cloud droplets, Doppler spectral analysis reveals the production of columnar ice crystals in the K-H billows. The modeling study estimates that the concentration of these ice crystals is 3-8 L-1, which is at least 1 order of magnitude higher than that of primary ice-nucleating particles. Given the detail of the observations, we show that multiple populations of secondary ice particles are generated in regions where larger cloud droplets are produced and not at some constant level within the cloud. It is, therefore, hypothesized that K-H in- stability provides conditions favorable for enhanced droplet growth and formation of secondary ice particles.
  • Li, Haoran; Möhler, Ottmar; Petäjä, Tuukka; Moisseev, Dmitri (2021)
    Formation of ice particles in clouds at temperatures of 10 ffiC or warmer was documented by using ground-based radar observations. At these temperatures, the number concentration of ice-nucleating particles (INPs) is not only expected to be small, but this number is also highly uncertain. In addition, there are a number of studies reporting that the observed number concentration of ice particles exceeds expected INP concentrations, indicating that other ice generation mechanisms, such as secondary ice production (SIP), may play an important role in such clouds. To identify formation of ice crystals and report conditions in which they are generated, W-band cloud radar Doppler spectra observations collected at the Hyytiala station for more than 2 years were used. Given that at these temperatures ice crystals grow mainly as columns, which have distinct linear depolarization ratio (LDR) values, the spectral LDR was utilized to identify newly formed ice particles. It is found that in 5 %-13% of clouds, where cloud top temperatures are 12 degrees C or warmer, production of columnar ice is detected. For colder clouds, this percentage can be as high as 33 %; 40 %-50% of columnar-ice-producing events last less than 1 h, while 5 %-15% can persist for more than 6 h. By comparing clouds where columnar crystals are produced and to the ones where these crystals are absent, the columnar-ice-producing clouds tend to have larger values of liquid water path and precipitation intensity. The columnarice-producing clouds were subdivided into three categories, using the temperature difference, Delta T, between the altitudes where columns are first detected and cloud top. The cases where Delta T is less than 2K are typically single-layer shallow clouds where needles are produced at the cloud top. In multilayered clouds where 2K
  • Tiira, Jussi; Moisseev, Dmitri (2020)
    Vertical profiles of polarimetric radar variables can be used to identify fingerprints of snow growth processes. In order to systematically study such manifestations of precipitation processes, we have developed an unsupervised classification method. The method is based on k-means clustering of vertical profiles of polarimetric radar variables, namely reflectivity, differential reflectivity and specific differential phase. For rain events, the classification is applied to radar profiles truncated at the melting layer top. For the snowfall cases, the surface air temperature is used as an additional input parameter. The proposed unsupervised classification was applied to 3.5 years of data collected by the Finnish Meteorological Institute Ikaalinen radar. The vertical profiles of radar variables were computed above the University of Helsinki Hyytiala station, located 64 km east of the radar. Using these data, we show that the profiles of radar variables can be grouped into 10 and 16 classes for rainfall and snowfall events, respectively. These classes seem to capture most important snow growth and ice cloud processes. Using this classification, the main features of the precipitation formation processes, as observed in Finland, are presented.