上海沿岸海域风场质量控制与预报检验
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摘要
利用2016年上海沿岸海域19个站点的风场资料,进行了风场质量控制,包括完整性检查、内部一致性检查、持续性检查和高度订正。同时挑选10个站点作为实况对2016年风场模式预报进行检验,包括风速预报误差、风速预报准确率和风向预报检验,对比了风场观测资料质量控制前后的检验结果,最后对两次大风过程进行了检验。结果表明:预报检验结果均随着预报时效的增加而变差;整体误差秋季和冬季较小,6月和7月误差较大;分级检验0～5级风速准确率在0.9～1之间,预报值比实况偏大,6级以上风速预报准确率逐渐降低,且预报值比实况偏小;风向检验呈现明显的季节性,冬季12月、1月误差小,准确率最高,夏季6月误差最大,准确率最低;质量控制后检验结果都得到正面提升;两次大风过程预报准确率均在70%以上。
Based on the wind field data of 19 stations in Shanghai coastal waters in 2016,the wind field quality control methods are studied,including the integrity check,internal consistency check,continuity check,and height correction.Meanwhile,10 stations are selected as observation stations of the wind field forecast verification in 2016,including wind speed error,wind speed accuracy and wind direction verification,and compared the results before and after the quality control of the wind field observation data.Finally,two strong wind processes are verified.The main results are as follow:the forecast verification results become worse with the increase of forecast time;the overall error of wind speed forecast in autumn and winter is small,and that in June and July is larger;the accuracy rate of the 0-5 level wind speed verification is between 0.9 and 1,and the forecast value is larger than observation;the accuracy rate of wind speed forecast above level 6 is gradually reduced,and the forecast value is smaller than that of observation.The wind direction verification shows obvious seasonality;in December and January,the error is small and the accuracy rate is the highest;in June,the error is the largest and the accuracy rate is the lowest.After quality control,the verification results are improved positively;the accuracy rates of the two strong wind processes are all above 70%.
Based on the wind field data of 19 stations in Shanghai coastal waters in 2016,the wind field quality control methods are studied,including the integrity check,internal consistency check,continuity check,and height correction.Meanwhile,10 stations are selected as observation stations of the wind field forecast verification in 2016,including wind speed error,wind speed accuracy and wind direction verification,and compared the results before and after the quality control of the wind field observation data.Finally,two strong wind processes are verified.The main results are as follow:the forecast verification results become worse with the increase of forecast time;the overall error of wind speed forecast in autumn and winter is small,and that in June and July is larger;the accuracy rate of the 0-5 level wind speed verification is between 0.9 and 1,and the forecast value is larger than observation;the accuracy rate of wind speed forecast above level 6 is gradually reduced,and the forecast value is smaller than that of observation.The wind direction verification shows obvious seasonality;in December and January,the error is small and the accuracy rate is the highest;in June,the error is the largest and the accuracy rate is the lowest.After quality control,the verification results are improved positively;the accuracy rates of the two strong wind processes are all above 70%.
引文
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[3]王万筠,殷海涛,赵敬红,等.2014-2016年数值降水预报在天津的检验评估[J].气象科技,2018,46(4):718-723.
[4]朱智慧,黄宁立,陈义.光流法在强降水过程预报检验中的应用[J].气象科技,2016,44(4):586-611.
[5]万夫敬,赵传湖,马艳,等.ECMWF模式气温预报在青岛地区的检验与评估[J].气象科技,2018,46(1):112-120.
[6]王波,李民,刘世萱,等.海洋资料浮标观测技术应用现状及发展趋势[J].仪器仪表学报,2014,35(11):2401-2414.
[7]赵聪蛟,周燕.国内海洋浮标监测系统研究概况[J].海洋开发与管理,2013,30(11):13-18.
[8]戴洪磊,牟乃夏,王春玉,等.我国海洋浮标发展现状及趋势[J].气象水文海洋仪器,2014,31(2):118-121.
[9]Monaldo F M,Thompson D R,Beal R C,et al.Comparison of SAR-derived wind speed with model predictions and ocean buoy measurements[J].IEEE Transactions on Geoscience and Remote Sensing,2001,39(12):2587-2600.
[10]Alvarez I,Gomez-Gesteira M,deCastro M,et al.Comparison of different wind products and buoy wind data with seasonality and interannual climate variability in the southern Bay of Biscay(2000-2009)[J].Deep-Sea Research II,2014,106:38-48.
[11]Pensieri S,Bozzano R,Schiano M E.Comparison between QuikSCAT and buoy wind data in the Ligurian Sea[J].Journal of Marine Systems,2010,81(4):286-296.
[12]Jiméne P A,Gonzálezrouco J F,Navarro J,et al.Quality Assurance of Surface Wind Observations from Automated Weather Stations[J].Journal of Atmospheric&Oceanic Technology,2010,27(7):1101-1122.
[13]Bertrand C,Sotelino L G,Journée M.Quality control of the RMI’s AWS wind observations[J].Advances in Science and Research,2016,13:13-19.
[14]何健,王潜梅,钱光明,等.广东省区域自动气象站资料的质量控制与评估[J].广东气象,2011,33(3):37-40.
[15]郭春迓,李天然,胡东明,等.南海北部测站风速质量的控制方法[J].广东气象,2016,38(1):44-48.
[16]江益,王立俊,羊清雯,等.南海区域站气象资料质量控制方法改进[J].气象科技,2018,46(3):474-478.
[17]王超球,许嘉玲.区域自动气象站质量控制参数值高度订正的方法[J].气象研究与应用,2011,32(4):64-66.
[18]植石群,钱光明,罗金铃.广东省沿海风随高度变化研究[J].热带地理,2001,21(2):131-134.
[19]孙莎莎,吴炜,郭俊建.山东沿海测风高度对风速的影响和订正研究[J].海洋预报,2015,32(6):34-39.