Distribution and Variability of Satellite‐Derived Signals of Isolated Convection Initiation Events Over Central Eastern China

Abstract

This study combined measurements from the Chinese operational geostationary satellite Fengyun‐2E (FY‐2E) and ground‐based weather radars to conduct a statistical survey of isolated convection initiation (CI) over central eastern China (CEC). The convective environment in CEC is modulated by the complex topography and monsoon climate. From May to August 2010, a total of 1,630 isolated CI signals were derived from FY‐2E using a semiautomated method. The formation of these satellite‐derived CI signals peaks in the early afternoon and occurs with high frequency in areas with remarkable terrain inhomogeneity (e.g., mountain, water, and mountain‐water areas). The high signal frequency areas shift from northwest CEC (dry, high altitude) in early summer to southeast CEC (humid, low altitude) in midsummer along with an increasing monthly mean frequency. The satellite‐derived CI signals tend to have longer lead times (the time difference between satellite‐derived signal formation and radar‐based CI) in the late morning and afternoon than in the early morning and night. During the early morning and night, the distinction between cloud top signatures and background terrestrial radiation becomes less apparent, resulting in delayed identification of the signals and thus short and even negative lead times. A decline in the lead time is observed from May to August, likely due to the increasing cloud growth rate and warm‐rain processes. Results show increasing lead times with increasing landscape elevation, likely due to more warm‐rain processes over the coastal sea and plain, along with a decreasing cloud growth rate from hill and mountain to the plateau.

Convection Initiation Resulting From the Interaction Between a Quasi‐Stationary Dryline and Intersecting Gust Fronts: A Case Study

“…This high‐impact squall line produced strong downbursts and widespread wind damage ranging from eastern Henan Province to the neighboring regions of Shandong, Henan, Anhui, and Jiangsu provinces on the evening of 3 June 2009, causing 27 fatalities (Zhang et al, ). In fact, this region has the highest recorded rate of squall line incidents in China (He et al, ; Huang et al, ; Meng et al, , ). The bow echo reached its peak intensity at ~1422 UTC, with a maximum radial velocity of 42.5 m/s at the 0.5° elevation angle (~800 m above ground level) over Yongcheng City (Figure a).…”

Analysis of Livorno Heavy Rainfall Event: Examples of Satellite-Based Observation Techniques in Support of Numerical Weather Prediction

“…In order to get around lacks and inadequacies in the radar and gauges coverage, a recent study [16] proposes an algorithm that blends the radar, gauges, and satellite quantitative precipitation estimation over areas immediately outside the effective radar coverage. Moreover, the importance of the fusion between WRN and satellite observations in supporting now-casting is investigated in [17], where measurements from the Chinese operational geostationary satellite Fengyun-2E, providing cloud top information at frequent intervals (<1 h), and ground-based weather radars, have been combined to conduct a study of the isolated convection initiation over central eastern China. A different approach has been followed in this study, the application of three satellite-based techniques to the Livorno extreme rainfall event will be shown with the purpose of investigating their usefulness in supplying information about cloud classification and in characterizing rainy areas when WRN information is missing.…”

Retrieval of the vertical profile of the cloud effective radius from the Chinese FY-4 next-generation geostationary satellite

“…The occurrence, development and dissipation of cloud clusters results in changes in their location, area, cloud-top temperature, average temperature and precipitation. The process of these changes is relatively continuous (Zhang and Fu, 2018) and 115 continuous pixels with a certain feature are often used to identify a "cloud cluster" or convective system Chen and Fu, 2017;Huang et al, 2017;Mapes and Houze, 1993;Zuidema, 2003). For example, Williams and Houze (1987) only considered continuous areas in which the brightness temperature was <213 K when identifying and tracking cloud clusters.…”