本文利用2013年7月12〜13日蘇力(Soulik)颱風侵襲期間，根據地面自動測報系統(AWOS)測報資 料，就松山機場跑道兩頭（R10和R28)之風速、氣壓和氣壓梯度等跳動情形，與機場低空風切警告系 統(LLWAS)發出的風切警告加以分析。
研究結果顯示颱風暴風圈接近、籠罩和遠離台灣北部地區之際，松山機場最大風速、最大風速差和 風速等最大跳動幅度分別> 17KT、> 11KT和> +6 / < -6 kt，飛行員在起降時就有可能遭遇風切的危險； 分別> 32KT、> 29KT和>+12 / < -12KT，機場就可能有多且強的風切現象發生。當風速越大，其風速、 氣壓和氣壓梯度等跳動幅度越大；反之，則越小。尤其在最大風速發生之前1〜5分鐘，氣壓和氣壓梯 度等跳動幅度都有很強。
機場跑道(R10與R28)風速、氣壓和氣壓梯度等跳動幅度超過一個標準差(1ff)之時段和頻率，與機場 低空風切警告系統發出風切警告者有相當的一致性，跳動幅度超過1ff之頻率越多，引發風切警告次數 越多且越強。因此，利用機場跑道風速、氣壓和氣壓梯度等跳動幅度超過1ff之頻率和時段，就可偵測 到低空風切的發生，或許也可以彌補機場低空風切警告系統還有10%以下的風切警告失敗率。本研究成 果可提供研發機場低空風切簡易警告系統參考。

In this study, we focus on the estimation and identification of low level wind shear phenomena. We based on the existing Sung-Shan airport Automatic weather observation(AWOS), every second storage data, adopting the ground weather parameters, wind speed (on 10 meter Tower), pressure and pressure gradient fluctuation at both runway threshold, i.e. R10 & R28. analyzing the time variation of these parameters and their correlation with the wind shear alert that issued by the existing low level wind shear system(LLWAS), hereafter. The result shows when the typhoon storm circle is close to, or on the northern Taiwan, or leaving Taiwan, the Song-San airport wind speed exceeds 20 kt frequently, and then the low level wind shear is prone to occur. The wind speed is stronger, the greater the fluctuation amplitude of its wind, barometric pressure and pressure gradient. When the max wind speed > 17 kt or the max wind speed variation > 11 kt or the wind speed fluctuation > +6 / -6 kt , the airplane will probably encounter the wind shear phenomena, and if the max wind speed > 32 kt or the max wind speed variation > 29 kt or the wind speed fluctuation > +12 / -12 kt , The airplane will encounter with serious wind burst, especially within 1〜5 minutes before the occurrence of the maximum wind speed, the wind speed, barometric pressure and air pressure, such as these three parameters have a greater fluctuation amplitude. The Fluctuation amplitude of wind speed, pressure and pressure gradient which exceeds one statistics sigma (standard deviation, 1 a) that the time span and frequencies are very close to the existing LLWAS system alerts in the Song-San airport. With the aid of this research, we believe the wind shear false alarm rate will be reduced and be able to compensate the 10% false alarm prediction to some extent.