The spatial and temporal characteristics and distributions of thunderstorms in Taiwan during the warm season (May-October) from 2005 to 2008 and under weak synoptic-scale forcing are documented using radar reflectivity, lightning, radiosonde, and surface data. Average hourly rainfall amounts peaked in midafternoon (1500-1600 local solar time, LST). The maximum frequency of rain was located in a narrow strip, parallel to the orientation of the mountains, along the lower slopes of the mountains. Significant diurnal variations were found in surface wind, temperature, and dewpoint temperature between days with and without afternoon thunderstorms (TS A and non-TS A days). Before thunderstorms occurred, on TS A days, the surface temperature was warmer (about 0.58-1.58C) and the surface dewpoint temperature was moister (about 0.58-28C) than on non-TS A days. Sounding observations from northern Taiwan also showed warmer and higher moisture conditions on TS A days relative to non-TS A days. The largest average difference was in the 750-550-hPa layer where the non-TS A days averaged 2.58-3.58C drier. These preconvective factors associated with the occurrences of afternoon thunderstorms could be integrated into nowcasting tools to enhance warning systems and decision-making capabilities in real-time operations.
Three years' worth of radar reflectivity data from four radars in an area of complex terrain (Taiwan) from 2005 to 2007 were analyzed and a reflectivity climatology was developed. The climatology was applied in the construction of new hybrid scans to minimize the impacts of ground clutter and beam blockages. The reflectivity climatology showed significant seasonal variations and captured distributions of ground/sea clutters, beam blockages, and anomalous propagations in addition to precipitation systems in the radar domains.By comparing the reflectivity climatology with gauge observations, it was found that 15 (20) dBZ was a good approximation for rain/no-rain segregation during cool (warm) seasons. Comparisons between the standard (i.e., based on terrain and scan strategies only with the assumption of standard propagations) and nonstandard (i.e., standard plus the clutter and blockage mitigation using the reflectivity climatology) hybrid scans showed that the former did not accurately reflect the clutter and blockage distributions in the real atmosphere. The application of the reflectivity climatology was shown to significantly reduce the impacts of clutter and blockages and provided improved radar quantitative precipitation estimates (QPEs) in the complex terrain.
In this study, a fuzzy logic algorithm is developed to provide objective guidance for the prediction of afternoon thunderstorms in northern Taiwan using preconvective predictors during the warm season (May-October) from 2005 to 2008. The predictors are derived from surface stations and sounding measurements. The study is limited to 277 days when synoptic forcing was weak and thermal instability produced by the solar heating is primarily responsible for thunderstorm initiation. The fuzzy algorithm contains 29 predictors and associated weights. The weights are based on the maximum of the critical success index (CSI) to forecast afternoon thunderstorms. The most important predictors illustrate that under relatively warm and moist synoptic conditions, sea-breeze transport of moisture into the Taipei Basin along with weak winds inland provide favorable conditions for the occurrence of afternoon convective storms. In addition, persistence of yesterday's convective storm activity contributed to improving today's forecast. Skill score comparison between the fuzzy algorithm and forecasters from the Taiwan Central Weather Bureau showed that for forecasting afternoon thunderstorms, the fuzzy logic algorithm outperformed the operational forecasters. This was the case for both the calibration and independent datasets. There was a tendency for the forecasters to overforecast the number of afternoon thunderstorm days. The fuzzy logic algorithm is able to integrate the preconvective predictors and provide probability guidance for the prediction of afternoon thunderstorms under weak synoptic-scale conditions, and could be implemented in real-time operations as a forecaster aid.
Capsule Summary The operational system provides a suite of QPE products at 1-km resolution and 10-min update cycle over Taiwan and adjacent ocean based on multi-wavelength radar, gauge and atmospheric environmental and climatological data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.