Paper Info
Title
Analysis of Diurnal Evolution of Cloud Properties and Convection Tracking over the South China Coastal Area
Abstract
Different diurnal rainfall cycles occur over the offshore and inland regions of the South China coastal area (SCCA). Inspired by these findings, in this study, we investigated the diurnal evolution features of cloud systems and cloud properties inside such systems for both the SCCA offshore and inland regions, using cloud data retrieved from a recently developed deep neural network model. Rainy day data for June 2017 revealed that the ice cloud optical thickness and top height reached their peak intensities at noon (similar to 12 local standard time (LST)) over the offshore region, approximately 2 h later than the rainfall peak. Over the inland region, cloud and rainfall peaks simultaneously appeared from similar to 18 to 20 LST. When further examining the cloud-amount variation of different ice-cloud types, we found a clear diurnal oscillation in the medium-thick cloud amount over the offshore region, while for the inland region, this cloud type had no obvious diurnal peak, showing a low cloud amount throughout the day. This phenomenon suggests different inner structures and intensities between offshore and inland convections. To better elucidate the convection features over different regions, a tracking algorithm was applied to obtain various parameters, such as size, number, and duration of mesoscale convective systems. The strongest convections, which lasted over 12 h, tended to be abundant over the offshore region from similar to 03 to 12 LST, and an inland to offshore migration at similar to 03 LST was facilitated by the beneficial meteorological conditions observed at 113-116 degrees F, 20.5-22.5 degrees N.
Year
DOI
Venue
2022
10.3390/rs14195039
REMOTE SENSING
Keywords
DocType
Volume
South China coastal area, deep neural network, diurnal rainfall cycles
Journal
14
Issue
ISSN
Citations 
19
2072-4292
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Xinyue Wang100.34
Hironobu Iwabuchi200.34
Jean-Baptiste Courbot300.34