Convection Initiation Associated With Ambient Winds and Local Circulations Over a Tropical Island in South China

Abstract

One of the most challenging aspects of severe weather forecasting is to predict when and where a convective storm will develop, also known as convection initiation (CI). CI is commonly deemed to have occurred when the first radar echo of a convective storm appears. It is usually the result of multiscale interactions between large-scale atmospheric circulations, local circulations, and the terrain (Wilson & Roberts, 2006). The forecast errors regarding CI timing and location are two of the major factors that limit the predictability of subsequent severe weather and quantitative precipitation forecasts (Weckwerth et al., 2011). Improving our understanding of CI mechanisms would be of great help for disaster prevention and mitigation.Convection over tropical islands is particularly active, which makes tropical islands among the rainiest regions on Earth (Carbone et al., 2000). In the presence of moisture pooling and instability, the locally enhanced lift associated with boundary-layer convergence zones, such as sea-breeze fronts (SBFs) and

Characteristics of Deep Convective Systems and Initiation during Warm Seasons over China and Its Vicinity

“…), weather radars or other ground-based observing systems provide us new opportunities to further study the characteristics of DCSI and improve DCSI forecast. Although the genesis environment of mesoscale convective systems is very similar and many convective systems display similar dynamic and thermodynamic structures around the world [67], the understanding of convective initiation in different regions, particularly in complex terrain, remains a great challenge [37,39]. Further research is needed to explore the impact of the atmospheric environment factors on the convective systems, the direct and indirect influence of dynamic and thermodynamic forcing from land surface, terrain and sea breezes, and in particular, their daytime and nighttime initiation, by using these modern observing systems, as well as high-resolution numerical weather models and machine learning/deep learning technologies.…”

“…In addition, the DCSI activity expands further northward from July to August (Figure 7), corresponding to the moist monsoon flows [6,27]. Obviously, the summer monsoon, land-sea breeze circulations and terrain work together to drive the monthly and diurnal variations of DCSI in this region [39].…”

“…Much work has been done to study the physical mechanisms of DCSI based on numerical weather models, and/or multi-platform measurements over the North China, South China and Eastern China, respectively [35][36][37][38]. Several statistical studies of DCSI have also been done in these regions in recent years using satellite and/or Doppler weather radar measurements [19,26,27,[39][40][41]. However, there is no work done to explore the systematic features of DCSI over the nation-wide region across China and its vicinity, nor comparison of DCSI in the subregions with different climates.…”

Terrain Effects on Regional Precipitation in a Warm Season over Qinling-Daba Mountains in Central China

“…Except for the height change, all other terrain related settings are the default settings in the WRF mode. This is a similar methodology on terrain sensitivity experiment with some previous studies [12,36], where sensitivity simulations modify the height of terrain in the same region but retains the same land properties as those in the CTRL.…”

“…The diversity of mountains and coastlines across mainland China results in a broad spectrum of rainfall effects [27], proving an effective way to investigate the effects of the terrain on reginal precipitation by numerical sensitivity simulations. Most of these previous studies have shown that Weather Research and Forecasting (WRF) model has the capability in accurately simulating the rainfall events with complex terrain by convection-permitting simulations [12,16,18,22,26,27,35,36], as well as in terrain sensitivity experiment [12,13,27,31,36]. The widely used method of reinitialization by subdividing a long-term continuous integration into shorter ones has been proved an effective way to alleviate the problem of systematic model error [35,37].…”