气象学报
氣象學報
기상학보
ACTA METEOROLOGICA SINICA
2014年
1期
168-181
,共14页
李国翠%刘黎平%连志鸾%周淼%李哲
李國翠%劉黎平%連誌鸞%週淼%李哲
리국취%류려평%련지란%주묘%리철
雷暴大风%识别方法%雷达拼图数据%模糊逻辑%统计分析
雷暴大風%識彆方法%雷達拼圖數據%模糊邏輯%統計分析
뇌폭대풍%식별방법%뢰체병도수거%모호라집%통계분석
Thunderstorm gale%Identification method%Radar mosaic data%Fuzzy-logical principle%Statistical study
应用雷达回波三维组网拼图数据、加密自动站和地面灾害大风资料,对2008-2012年京津冀地区20次区域性雷暴大风天气过程进行了统计。检验了基于模糊逻辑建立的利用回波强度识别大风的算法,分析了大风出现的位置。该大风识别算法确定了雷暴大风的6个雷达识别指标及其对应的权重系数和不同季节的隶属函数。检验分析块状回波、带状回波和片状回波3类大风过程的识别效果,结果表明:块状回波类大风是由孤立的强单体风暴引发的,风暴单体具有回波强、回波顶高、垂直积分液态水含量大和移动快等特点,雷暴大风多出现在风暴单体附近且二者移动路径一致;带状回波的长度远大于宽度,主要包含飑线和弓状回波,大风影响范围广且多位于带状回波的前沿一带;片状回波多指大面积层云回波中镶嵌着强回波单体块的混合回波,对应出现的雷暴大风多位于风暴单体的周边区域。3类回波识别到的可能出现大风区域与实测大风范围基本吻合,块状、带状和片状3种类型的雷暴大风命中率分别为96.2%、68.6%和45.3%,漏报率分别为3.8%、31.4%和54.7%。由于垂直积分液态水含量偏低和回波强度弱,片状雷暴大风识别漏报相对较多;空报原因除了与测站分布稀疏有很大关系外,也与识别算法本身有关。识别检验证明雷暴大风综合识别方法是合理可靠、切实可行的,可以为雷暴大风的短时临近预警业务和系统开发提供技术支撑,这一工作也为进一步预警大风出现的位置提供了基础。
應用雷達迴波三維組網拼圖數據、加密自動站和地麵災害大風資料,對2008-2012年京津冀地區20次區域性雷暴大風天氣過程進行瞭統計。檢驗瞭基于模糊邏輯建立的利用迴波彊度識彆大風的算法,分析瞭大風齣現的位置。該大風識彆算法確定瞭雷暴大風的6箇雷達識彆指標及其對應的權重繫數和不同季節的隸屬函數。檢驗分析塊狀迴波、帶狀迴波和片狀迴波3類大風過程的識彆效果,結果錶明:塊狀迴波類大風是由孤立的彊單體風暴引髮的,風暴單體具有迴波彊、迴波頂高、垂直積分液態水含量大和移動快等特點,雷暴大風多齣現在風暴單體附近且二者移動路徑一緻;帶狀迴波的長度遠大于寬度,主要包含颮線和弓狀迴波,大風影響範圍廣且多位于帶狀迴波的前沿一帶;片狀迴波多指大麵積層雲迴波中鑲嵌著彊迴波單體塊的混閤迴波,對應齣現的雷暴大風多位于風暴單體的週邊區域。3類迴波識彆到的可能齣現大風區域與實測大風範圍基本吻閤,塊狀、帶狀和片狀3種類型的雷暴大風命中率分彆為96.2%、68.6%和45.3%,漏報率分彆為3.8%、31.4%和54.7%。由于垂直積分液態水含量偏低和迴波彊度弱,片狀雷暴大風識彆漏報相對較多;空報原因除瞭與測站分佈稀疏有很大關繫外,也與識彆算法本身有關。識彆檢驗證明雷暴大風綜閤識彆方法是閤理可靠、切實可行的,可以為雷暴大風的短時臨近預警業務和繫統開髮提供技術支撐,這一工作也為進一步預警大風齣現的位置提供瞭基礎。
응용뢰체회파삼유조망병도수거、가밀자동참화지면재해대풍자료,대2008-2012년경진기지구20차구역성뇌폭대풍천기과정진행료통계。검험료기우모호라집건립적이용회파강도식별대풍적산법,분석료대풍출현적위치。해대풍식별산법학정료뇌폭대풍적6개뢰체식별지표급기대응적권중계수화불동계절적대속함수。검험분석괴상회파、대상회파화편상회파3류대풍과정적식별효과,결과표명:괴상회파류대풍시유고립적강단체풍폭인발적,풍폭단체구유회파강、회파정고、수직적분액태수함량대화이동쾌등특점,뇌폭대풍다출현재풍폭단체부근차이자이동로경일치;대상회파적장도원대우관도,주요포함박선화궁상회파,대풍영향범위엄차다위우대상회파적전연일대;편상회파다지대면적층운회파중양감착강회파단체괴적혼합회파,대응출현적뇌폭대풍다위우풍폭단체적주변구역。3류회파식별도적가능출현대풍구역여실측대풍범위기본문합,괴상、대상화편상3충류형적뇌폭대풍명중솔분별위96.2%、68.6%화45.3%,루보솔분별위3.8%、31.4%화54.7%。유우수직적분액태수함량편저화회파강도약,편상뇌폭대풍식별루보상대교다;공보원인제료여측참분포희소유흔대관계외,야여식별산법본신유관。식별검험증명뇌폭대풍종합식별방법시합리가고、절실가행적,가이위뇌폭대풍적단시림근예경업무화계통개발제공기술지탱,저일공작야위진일보예경대풍출현적위치제공료기출。
Based on the radar mosaic 3D data,automatic weather stations observations and disaster wind data,twenty cases of thunderstorm gale from 2008 to 2012 in the Beijing-Tianjin-Hebei region are statistically analyzed to develop an automated de-tection of thunderstorm gale with the fuzzy logical based algorithm.The capability of the algorithm is examined.In the meth-od,the six main radar identification indices of ground gale are given with the corresponding membership functions and weight coefficients determined.All the gale is tested and analyzed,including the three types of echo,i.e.the massive echo,banding echo and floccus echo.The results show that the massive echo is triggered by the strong storm monomer with strong echo, higher echo top,bigger vertical integrated liquid water content (VIL)value and faster moving speed,and in this case the gale occurs nearby the thunderstorm cell with the same route as that of the cell;the banding echo mainly contains the squall line and the bow echo with its length greater than the width and the impact range of strong wind located at the forefront of the band ech-o;the floccus echo generally refers to the mixed echo with large area layer echo embedded by the isolated massive echo,and the strong wind area situated around the storm monomer.The wind range for the three types identified is generally consistent with the real wind,and the hit rate of massive echo,banding echo and floccus echo is respectively 96.2%,68.6% and 45.3% with the missing rate of respectively 3.8%,31.4%and 54.7%.Lower omission rate of floccus echos gale is because of weak echo intensity and lower VIL and missing rate is caused by the sparse station distribution and algorithm.This also proved that the automatic identification method is efficiently and feasible,it has important practical guiding significance for an operational system in short-term forecasting and nowcast warning.The work also provides a foundation in warning the position of surface gale.