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- 저자 : Li-Shan Tseng (검색결과 4 건)
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Wu Sing-Shan,Tseng Ching-Tzu,Yang Yu-Hung,Liu Yao-Chia,Chang Ju-Chun,Gyawali Purushottam,Li Yi-Hsuan,Yang Tzu-Hao,Tsai Yi-Fang,Tang Li-Cheng,Nai Yu-Shin 한국응용곤충학회 2022 Journal of Asia-Pacific Entomology Vol.25 No.4
The fall armyworm, Spodoptera frugiperda, is an emerging invasive pest in Taiwan that feeds on a wide range of crops and causes serious damage. Herein, an entomopathogenic fungal library (EFLib) was constructed to identify potential microbes to control FAW. Twenty-eight indigenous entomopathogenic fungi (EPF) were iso lated and investigated for their potential pathogenicity, with Metarhizium pinghaense (Mp-NCHU-124) and Beauveria bassiana (Bb-NCHU-157) exerting dose-dependent effects on the 4th instar FAW larvae. The non-ionic surfactant Silwet L-77 rapidly killed FAW larvae after spraying at a concentration of 300 mg/kg and the toxic effect of Silwet L-77 on FAW larvae was dose-dependent. When the EPF isolates (10 6 conidia/mL) were applied to FAW larvae in combination with the non-ionic surfactant Silwet L-77 (30–90 mg/kg), the mortality rate dramatically increased and the LT 50 reduced, with increased fungal mycosis (Mp-NCHU-124: 38% to 72% and Bb-NCHU-157: 20 to 62%), indicating the high compatibility of EPF with the non-ionic surfactant. Thus, the Silwet L-77+EPF combined formulation has potential for practical field application for FAW pest control and sustainable agriculture in the future.
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Wei-Teh Li,Jau-Ming Chen,Ruo-Shan Tseng,Tzu-Ling Lai 한국기상학회 2022 Asia-Pacific Journal of Atmospheric Sciences Vol.58 No.1
September 2016 harbored record-breaking three tropical cyclones (TCs) affecting Taiwan within a month. Multiple modulating processes governing these three TC events and associated rainfall and intensification features are examined. September 2016 fell in a La Niña phase. For interannual variability, major warm sea surface temperature (SST) anomalies in September 2016 shifted eastward toward the tropical western North Pacific (WNP) compared to the Maritime Continent during other La Niña events. These SST anomalies induced strong convergence and convection anomalies facilitating TC formation. The TCs formed in the joint region between a northern anticyclonic anomaly over the northern WNP and a southern cyclonic anomaly extending from the tropical WNP toward Taiwan. They were steered by anomalous easterly/southeasterly flows northwestward toward an anomalous cyclonic center overlying Taiwan, leading to intensive TC activity affecting Taiwan. For intraseasonal variability, the three TCs of September 2016 were steered by anomalous easterly/southeasterly flows in the southern section of a 30–60-day anomalous anticyclone over the subtropical WNP northwestward toward a 30–60-day anomalous cyclone that lay over Taiwan. During these events, local rainfall in Taiwan was mainly affected by moisture convergence due to 3–10-day transient anomalies, rather than intraseasonal anomalies. For TC intensification processes, faster intensification was assisted by decreases in vertical wind shear and increases in upward motion, moisture convergence, upper-level divergence, and SST. Intensification processes were mainly affected by transient anomalies. Overall, interannual and intraseasonal anomalies modulated TC genesis and movement, while transient anomalies influenced local rainfall and intensification processes.
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Climatic Factors Suppressing Tropical Cyclone Activity around Taiwan during October
Wei‑Teh Li,Jau‑Ming Chen,Ruo‑Shan Tseng 한국기상학회 2023 Asia-Pacific Journal of Atmospheric Sciences Vol.59 No.4
During Octobers of 1970–2019, no tropical cyclones (TCs) affected Taiwan in 32 out of 50 years (64%). Suppressed TCactivity in these years results from different modulating processes imposed by various climatic features. During Octobersof El Niño years, TC genesis in the western North Pacific (WNP) shifts eastward and decreases in the western WNP to thesoutheast of Taiwan. An anomalous anticyclone across the South China Sea (SCS) and Taiwan hinders TC movement towardTaiwan. In La Niña years, TC genesis increases in the region southeast of Taiwan. These TCs are guided by an anomalouscyclone centering in the SCS to have major TC tracks to the southwest of Taiwan toward the SCS. A year with a September–November value on the Oceanic Niño Index (ONI) of between 0°-0.5 °C (-0.5°-0 °C) is categorized as a positive (negative)Normal year. During the positive Normal years, an anomalous cyclone over the WNP enhances TC genesis in its southernsection and guides these TCs northward along the regions east of Taiwan. An anomalous anticyclone across the SCS andTaiwan hinders TC movement toward Taiwan. During the negative Normal years, a westward elongation of warm sea surfacetemperature anomalies from the WNP into the eastern Indian Ocean forces an anomalous anticyclone to extend westwardfrom the WNP toward the SCS. TC genesis to the south of this anomalous anticyclone decreases and is accompanied byreduced TC movement toward Taiwan.
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Sahana Paul,Chung-Chieh Wang,Li-Shan Tseng,이동인,Jing-Shan Hong,Tzay-Ming Leou 한국기상학회 2021 Asia-Pacific Journal of Atmospheric Sciences Vol.57 No.4
This study assesses relative merit of three mesoscale models – the Cloud-Resolving Storm Simulator (CReSS), the Central Weather Bureau (CWB) Weather Research and Forecasting (WRF) model, and the CWB Non-hydrostatic Forecast System (NFS) – that participated in the Southwest Monsoon Experiment (SoWMEX) in 2008. The Mei-yu quantitative precipitation forecasts (QPFs) in May–June of the three models are compared against merged data from ~400 rain gauges and the Tropical Rainfall Measuring Mission (TRMM). The three models have a grid size of 3.5 or 5 km, and their QPFs over the forecast range of 12–36 h are verified by subjective means, with particular foci on rainfall spatial pattern, intra-seasonal variability, and diurnal cycle during the entire season, its sub-periods, and Intensive Observation Periods (IOPs). The three models each has advantages and disadvantages. The CReSS performs best in seasonal and diurnal characteristics of rainfall. Despite higher resolution, it suffers from over-forecast and location error problems. Without a data assimilation system, its single domain with a limited size fabricates it more sensitive to errors in initial and boundary conditions (IC/BCs) from the global model. Although theCWBWRF is most stable among three and performs well in simulating spatial distribution of rainfall, it exhibits under-prediction with an inadequate intra-seasonal variation. In both the entire period and IOPs, the CWB NFS simulates rainfall pattern closest to observation with only slight under-prediction. However, the diurnal cycle captured by the CWB NFS has a phase lag of 12 h and thus a timing error that is likely associated with delayed development of convection due to systematic bias.
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