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The Applicability of NCEP Reanalysis Data to Severe Convection Environment Analysis
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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。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.
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Key words:
- NCEP reanalysis data;
- sounding;
- supercell;
- severe convection
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图 1 NCEP再分析资料与探空资料的0~6 km风垂直切变散点图 (a) 及风垂直切变差分布图 (b)
Fig. 1 The scatter diagram of 0—6 km vertical wind shear (a) and the shear difference (b) between NCEP reanalysis data and observations
图 2 NCEP再分析资料与探空资料的风速差值 (a) 和风向 (b) 分布
Fig. 2 The differences of wind direction (a) and speed (b) between NCEP reanalysis data and observations
图 3 NCEP再分析资料与探空资料各层风速 (a) 和温度、露点 (b) 的平均差
Fig. 3 Mean differences of temerature, dew point and wind speed between NCEP reanalysis data and observations
图 4 NCEP再分析资料与探空资料计算的对流有效位能散点图 (a) 及对流有效位能差值分布 (b)
Fig. 4 Same as in Fig. 1, exept for CAPE
图 5 NCEP再分析资料与探空资料的温度差 (a) 和露点温度差 (b) 分布
Fig. 5 Same as in Fig. 2, except for temperature (a) and dew temperature (b)
图 6 NCEP再分析资料与探空资料K指数计算的热力参数散点图
(a)850 hPa与500 hPa温度差，(b)K指数
Fig. 6 Scattlerplot of thermodynamical parameters between NCEP reanalysis data and observations
(a) temperature difference between 850 hPa and 500 hPa, (b)Kindex
表 1 不同资料及不同方式得到的对流有效位能及其与探空资料计算结果差值 (单位: J·kg-1)
Table 1 Average CAPE and CAPE deviation calculated by different dataset and different methods (unit: J·kg-1)
统计量 探空资料计算结果 底层温度加1℃ 底层露点温度加1℃ MICAPS探空分析结果 NCEP再分析资料计算结果 NCEP直接输出量 平均值 1511 1705 1970 1390 1536 848 均值差 194 459 -121 25 -663 最大差值 348 1074 826 3672 949 3/4值 228 576 -52 622 7 中值 198 472 -136 -188 -599 1/4值 162 298 -201 -787 -1223 最小差值 0 0 -844 -2497 -3229 注:中值，1/4值和3/4值分别指对流有效位能差值 (不同资料、不同方式得到的对流有效位能减去探空资料计算结果) 构成的序列按由小到大排列，位于50%，25%和75%处的值。 
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[1] 廖晓农, 俞小鼎, 谭一洲. 14时探空在改进北京地区对流天气潜势预报中的作用.气象, 2007, 33(3):28-32. doi: 10.7519/j.issn.1000-0526.2007.03.004 [2] 何立富, 周庆亮, 陈涛, 等.北京"7.10"暴雨中尺度对流系统分析.应用气象学报, 2007, 18(5):655-664. doi: 10.11898/1001-7313.20070501 [3] 徐文慧, 倪允琪.登陆台风环流内的一次中尺度强度对流过程.应用气象学报, 2009, 20(3):267-275. doi: 10.11898/1001-7313.20090302 [4] 王瑾, 蒋建莹, 江吉喜. "7.18"济南突发性大暴雨特征.应用气象学报, 2009, 20(3):295-302. doi: 10.11898/1001-7313.20090305 [5] 何立富, 周庆亮, 陈涛. "05.6"华南暴雨中低纬度系统活动及其相互作用.应用气象学报, 2010, 21(4):385-394. http://cdmd.cnki.com.cn/Article/CDMD-90030-2005089451.htm [6] 谢建标, 林良勋, 颜文胜, 等.广州2005年"3.22"强飑线天气过程分析.应用气象学报, 2007, 18(3):321-329. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070354&flag=1 [7] 纪晓玲, 王式功, 穆建华, 等.宁夏雷暴天气过程划分及环流分型和环境场特征.应用气象学报, 2010, 21(3):329-334. doi: 10.11898/1001-7313.20100308 [8] 王秀明, 钟青.环境与强对流 (暴) 云相互作用的个例模拟.高原气象, 2009, 28(2): 366-373. http://cdmd.cnki.com.cn/Article/CDMD-10300-2006066399.htm [9] 慕熙昱, 徐琪, 夏文梅, 等.准线形对流系统中强度-速度负相关性的特征研究.气象学报, 2009, 67(4):631-639. doi: 10.11676/qxxb2009.063 [10] 廖晓农, 王华, 石增云.北京地区雷暴大风日θe平均廓线特征.气象, 2004, 30(11):35-37. doi: 10.3969/j.issn.1000-0526.2004.11.008 [11] 梁爱民, 张庆红, 申红喜, 等.北京地区雷暴大风预报研究.气象, 2006, 32(11):73-81. doi: 10.3969/j.issn.1000-0526.2006.11.012 [12] 郑永光, 张喜春, 陈炯, 等. 用NCEP资料分析华北暖季对流性天气的气候背景. 北京大学学报: 自然科学版, 2007, 43(5): 600-608. [13] Thompson R L, Edwards R, Hart J A, et al. Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Wea Forecasting, 2003, 18: 1243-1261. doi: 10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2 [14] Moller A R, Doswell III C A, Foster M P, et al. The operational recognition of supercell thunderstorm environments and storm structures. Wea Forecasting, 1994, 9: 327-347. doi: 10.1175/1520-0434(1994)009<0327:TOROST>2.0.CO;2 [15] [2011-02-01]. http://www.ofcm.gov/fmh3/text/chapter2.htm. [16] 魏东, 尤凤春, 范水勇, 等.北京快速更新循环预报系统_BJ_RUC_模式探空质量评估分析.气象, 2010, 36(8):72-80. doi: 10.7519/j.issn.1000-0526.2010.08.010 [17] 李佳英, 俞小鼎, 王迎春.用探空资料检验中尺度数值模式对强对流天气的诊断分析能力.气象, 2006, 32(7):13-17. doi: 10.7519/j.issn.1000-0526.2006.07.002 [18] 陈子通, 闫敬华, 苏耀墀.模式探空的评估分析及其在强对流天气预报中的应用研究.大气科学, 2006, 32(2):235-247. http://www.cnki.com.cn/Article/CJFDTOTAL-DQXK200602005.htm -
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