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NCEP再分析资料在强对流环境分析中的应用
引用本文:王秀明,俞小鼎,朱禾.NCEP再分析资料在强对流环境分析中的应用[J].应用气象学报,2012,23(2):139-146.
作者姓名:王秀明  俞小鼎  朱禾
作者单位:中国气象局气象干部培训学院,北京 100081
基金项目:国家自然科学基金项目(41005002,40875029),公益性行业(气象)科研专项(GYHY200906003)
摘    要:为考察NCEP再分析资料在我国强对流天气产生环境分析中的适用性,选取2002—2009年多普勒天气雷达识别的60例超级单体风暴个例,对比分析常规探空资料和NCEP再分析资料提取的温、湿、风垂直廓线,结果表明:NCEP再分析资料计算的对流有效位能因对抬升气团湿度敏感而与观测间差异较大,宜用K指数、温度直减率分析大气层结稳定度;因对流层中高层风与探空差异不大,其中500~700 hPa的风与探空近乎一致,因此NCEP再分析资料计算的深层、中层风垂直切变参量可靠性较高;NCEP再分析资料水汽参数与探空资料差异大,特别是在大气边界层,需用观测资料订正;边界层物理量,特别是风向与探空差异显著,因此不宜用NCEP再分析资料讨论雷暴触发问题;平均而言,NCEP再分析资料湿度廓线低层偏干而中层偏湿,925 hPa以上风速偏小,降低了强对流发生概率。

关 键 词:NCEP再分析资料    探空资料    超级单体    强对流
收稿时间:2011-05-23

The Applicability of NCEP Reanalysis Data to Severe Convection Environment Analysis
Wang Xiuming,Yu Xiaoding and Zhu He.The Applicability of NCEP Reanalysis Data to Severe Convection Environment Analysis[J].Quarterly Journal of Applied Meteorology,2012,23(2):139-146.
Authors:Wang Xiuming  Yu Xiaoding and Zhu He
Affiliation:China Meteorological Administration Training Center, Beijing 100081
Abstract:Operational sounding observation is carried out twice per day, but four similar vertical profiles can be obtained from NCEP reanalysis data. Therefore, the vertical profiles obtained from NCEP reanalysis data are assessed and its applicability in diagnosing severe convection environment is analyzed. Sixty soundings in close proximity to supercell storms are investigated. These supercell storms are observed in China and identified by Doppler weather radar. The soundings which may be polluted by storm are replaced by soundings from its downstream area or upstream area. The profiles obtained from NCEP data are at the same time and as close to the observation soundings as possible. The vertical profile data that obtained from NCEP reanalysis data are compared with soundings. The ingredients-based methodology is used to discuss the potential for severe convection. Vertical wind shear is the first element to check. NCEP wind in middle and high troposphere is almost consistent with observation, so the deep and middle vertical wind shear (0—6 km, 0—8 km and 0—3 km) and other related dynamical parameters can be calculated from NCEP data except for 0—1 km low vertical wind shear, because wind difference is significant in planet boundary layer (PBL). To study instability of storms, convective available potential energy (CAPE), temperature lapse rate (temperature difference between 850 hPa and 500 hPa), and K index are investigated. The statistic results show that the difference of CAPE between observation and NCEP profiles is significant, because CAPE is sensitive to dewpoint and temperature of lifting air mass. On average, 1℃ temperature increment of lifting airmass brings 200 J·kg-1CAPE augmentation, 1℃ dewpoint increases CAPE by nearly 500 J·kg-1, and the augmentation can vary from 0 to 1000 J·kg-1. Moisture is one of the three ingredients for thunderstorm. The error of NCEP moisture parameter is significant, especially within planet boundary layer, the average dewpoint difference between NCEP and observation is 2℃ in low troposphere, which results in nearly 1000 J·kg-1CAPE difference. To calculate CAPE from NCEP data, moisture should be corrected according to observation. Temperature lapse rate can be used to diagnose atmospheric instability instead of CAPE, as temperature profile can be used to analysis severe convection. The difference of K index is small in most cases. NCEP output variable CAPEsfc (surface CAPE) is unreasonably small, but the tendency can indicate the change of CAPE. Most lifting processes are within PBL, where the difference of the atmospheric parameters especially the wind direction between observation and NCEP data is significant, so it's not suitable to use NCEP data to study lifting mechanism of thunderstorm. On average, the NECP moisture profile is much drier at low level and wetter at middle level than observation, and wind speed above 925 hPa is weaker than observation, which lowers the possibility of severe convection.
Keywords:NCEP reanalysis data  sounding  supercell  severe convection
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