ECMWF高分辨率模式对陕西2017年7月高温预报的检验及订正
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摘要
2017年7月陕西累计出现26 d日最高气温≥35℃的高温天气,其中14 d日最高气温突破40℃,7月7～14日和17～27日出现2次区域性持续高温天气。利用陕西99个国家站的最高气温逐时观测和ECMWF高分辨率模式的定时最高气温预报资料,检验ECMWF高分辨率模式对2017年7月陕西极端高温天气的预报能力和一元线性回归方法对气温预报的订正能力。结果表明:144 h之前模式较好地预报出了陕西2次区域性持续高温天气,但是高温日数的预报值在陕西大部分地区较观测值偏少,漏报了陕南大部分地区的高温日,与14:00～17:00时段最高气温的预报值在陕西大部分地区较观测值偏低,其中陕南地区的预报平均绝对误差明显大于其他地区有关。一元线性回归方法对168 h之前的最高气温预报为正订正效果,订正后陕西大部分地区最高气温的预报准确率上升,平均绝对误差减小,日最高气温≥35℃或≥40℃的高温预报较订正前更接近实况。
There were 26 days of high temperature when the daily maximum air temperature( MAT) was above35 ℃ in Shaanxi Province,China in July 2017,and out of the 26 days there were 14 days with the MAT being even above 40 ℃. The continuous hot weather in this region in the month occurred twice during the periods from July 7th to 14 thand from July 17 thto 27threspectively. Based on hourly observation of MAT at 99 stations in Shaanxi Province reported by CMA( Chinese Meteorological Administration) and fixed time forecast of ECMWF( European Center for Medium Weather Forecasting) high-resolution model,the performance of ECMWF model for the hot weather forecast and temperature correction by linear regression method were evaluated. The evaluation methods included average error,average absolute error and accuracy with absolute error less than 1 ℃ and 2 ℃. The results showed an obvious regional difference in forecast ability of the model,whose accuracy of the MAT is higher in Guanzhong and lower in Southern Shaanxi. The regional continuous hot weather could have been better forecasted by the model during the forecast time of 144 hours,but the number of hot weather days predicted was less than the observation days in most areas of Shaanxi Province,and it failed to forecast the hot weather days in most areas of southern Shaanxi.This was because that the values of MAT from prediction were less than the observation in most areas of Shaanxi,and the MAE( mean absolute error) in southern Shaanxi was more than that in other areas of Shaanxi from 14: 00 to17: 00 BST. With the extension of forecast hours,the capability of the linear regression method to correct air temperature was decreased in wave mode. The linear regression method had positive function to correct air temperature during the forecast time of 168 hours,which is better between 14: 00 PM and 01: 00 AM the next day than that in any other times,and there was a significant negative correlation relationship between the correction ability of the method and forecast ability of the model. The linear regression method could increase the accuracy and decrease the MAE of MAT. The ME( mean error) of MAT was closer to zero,and the hot weather forecast with a daily MAT being above35 ℃ or 40 ℃ was closer to the observation after correction. The research provides a rational reference for hot weather forecasts from ECMWF model in summer,and it is noted further studies during other time periods are needed to verify the universality of the conclusion as this study was focused on the period of July 2017.
There were 26 days of high temperature when the daily maximum air temperature( MAT) was above35 ℃ in Shaanxi Province,China in July 2017,and out of the 26 days there were 14 days with the MAT being even above 40 ℃. The continuous hot weather in this region in the month occurred twice during the periods from July 7th to 14 thand from July 17 thto 27threspectively. Based on hourly observation of MAT at 99 stations in Shaanxi Province reported by CMA( Chinese Meteorological Administration) and fixed time forecast of ECMWF( European Center for Medium Weather Forecasting) high-resolution model,the performance of ECMWF model for the hot weather forecast and temperature correction by linear regression method were evaluated. The evaluation methods included average error,average absolute error and accuracy with absolute error less than 1 ℃ and 2 ℃. The results showed an obvious regional difference in forecast ability of the model,whose accuracy of the MAT is higher in Guanzhong and lower in Southern Shaanxi. The regional continuous hot weather could have been better forecasted by the model during the forecast time of 144 hours,but the number of hot weather days predicted was less than the observation days in most areas of Shaanxi Province,and it failed to forecast the hot weather days in most areas of southern Shaanxi.This was because that the values of MAT from prediction were less than the observation in most areas of Shaanxi,and the MAE( mean absolute error) in southern Shaanxi was more than that in other areas of Shaanxi from 14: 00 to17: 00 BST. With the extension of forecast hours,the capability of the linear regression method to correct air temperature was decreased in wave mode. The linear regression method had positive function to correct air temperature during the forecast time of 168 hours,which is better between 14: 00 PM and 01: 00 AM the next day than that in any other times,and there was a significant negative correlation relationship between the correction ability of the method and forecast ability of the model. The linear regression method could increase the accuracy and decrease the MAE of MAT. The ME( mean error) of MAT was closer to zero,and the hot weather forecast with a daily MAT being above35 ℃ or 40 ℃ was closer to the observation after correction. The research provides a rational reference for hot weather forecasts from ECMWF model in summer,and it is noted further studies during other time periods are needed to verify the universality of the conclusion as this study was focused on the period of July 2017.
引文
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[14]肖红茹,王灿伟,周秋雪,等. T639、ECMWF细网格模式对2012年5~8月四川盆地降水预报的天气学检验[J].高原山地气象研究,2013,33(1):80-85.[XIAO Hongru,WANG Canwei,ZHOU Qiuxue,et al. Synoptic meteorology verification of precipitation forecast for T639 ECMWF fine grid models from May to August 2012 in Sichuan Basin[J]. Plateau and Mountain Meteorology Research,2013,33(1):80-85.]
[15]熊世为,郁凌华,胡姗姗,等.基于ECMWF细网格产品的一种优化BP-MOS气温预报方法[J].干旱气象,2017,35(4):668-673.[XIONG Shiwei,YU Linghua,HU Shanshan,et al. An optimized BP-MOS temperature forecast method based on the finemesh products of ECMWF[J]. Journal of Arid Meteorology,2017,35(4):668-673.]
[16]罗菊英,周建山,闫永财.基于数值预报及上级指导产品的本地气温MOS预报方法.气象科技,2014,42(3):443-450.[LUO Juying,ZHOU Jianshan,YAN Yongcai. Local temperature MOS forecast method based on numerical forecast products and superior guidance[J]. Meteorological Science and Technology,2014,42(3):443-450.]
[17]余晖,陈国民,万日金.数值模式的热带气旋强度预报订正及其集成应用[J].气象学报,2015,73(4):667-678.[YU Hui,CHEN Guomin,WAN Rijin. A multi-model consensus forecast technique for tropical cyclone intensity based on model output calibration[J]. Acta Meteorological Sinica,2015,73(4):667-678.]
[18]李佰平,智协飞. ECWRF模式地面气温预报的四种误差订正方法的比较研究[J].气象,2012,38(8):897-902.[LI Baiping,ZHI Xiefei. Comparative study of four correction schemes of the ECMWF surface temperature forecasts[J]. Meteorological Monthly,2012,38(8):897-902.]
[2]潘留杰,张宏芳,王建鹏.数值天气预报检验方法研究进展[J].地球科学进展,2014,29(3):327-335.[PAN Liujie,ZHANG Hongfang,WANG Jianpeng. Progress on verification methods of numerical weather prediction[J]. Advances in Earth Science,2014,29(3):327-335.]
[3]董全,金荣花,代刊,等. ECMWF集合预报和确定性预报对淮河流域暴雨预报的对比分析[J].气象,2016,42(9):1146-1153.[DONG Quan,JIN Ronghua,DAI Kan,et al. Comparison between ECMWF ensemble and deterministic forecast for heavy rainfall in the Huaihe River Basin of China[J]. Meteorological Monthly,2016,42(9):1146-1153.]
[4]王海燕,田刚,徐卫立,等. ECMWF模式在长江上游流域调度关键期的预报检验评估[J].干旱气象,2017,35(1):142-147.[WANG Haiyan,TIAN Gang,XU Weili,et al. Evaluation and inspection of ECMWF model forecast product during dispatch key periods in upper reaches of the Yangtze River Basin[J]. Journal of Arid Meteorology,2017,35(1):142-147.]
[5]潘留杰,张宏芳,陈小婷,等. ECMWF集合预报在中国中部地区的降水概率预报性能评估[J].高原气象,2017,36(1):138-147.[PAN Liujie,ZHANG Hongfang,CHEN Xiaoting,et al. Evaluation of precipitation probability forecasts of ECMWF ensemble prediction system in central China[J]. Plateau Meteorology,2017,36(1):138-147.]
[6]潘留杰,张宏芳,朱伟军,等. ECMWF模式对东北半球气象要素场预报能力的检验[J].气候与环境研究,2013,18(1):111-123.[PAN Liujie,ZHANG Hongfang,ZHU Weijun,et al. Forecast performance verification of the ECMWF model over the Northeast Hemisphere[J]. Climatic and Environmental Research,2013,18(1):111-123.]
[7]周昆,郝元甲,姚晨,等. 6种数值模式在安徽区域天气预报中的检验[J].气象科学,2010,30(6):801-805.[ZHOU Kun,HAO Yuanjia,YAO Chen,et al. The verification of six numerical models for weather forecast in Anhui Province[J]. Journal of the Meteorological Sciences,2010,30(6):801-805.]
[8]王丹,高红燕,马磊,等. SCMOC温度精细化指导预报在陕西区域的质量检验[J].气象科技,2014,42(5):839-846.[WANG Dan,GAO Hongyan,MA Lei,et al. Quality test of refined guidance SCMOC temperature prediction in Shaanxi Province[J].Meteorological Science and Technology,2014,42(5):839-846.]
[9] PINSON P,HAGEDORN R. Verification of the ECMWF ensemble forecasts of wind speed against observations[J]. Meteorological Applications,2012,19(4):484-500.
[10] WANG Y,QIAN H,SONG J J,et al. Verification of the T213 global spectral model of China National Meteorology Center over the East-Asia area[J]. Journal of Geophysical Researh Atmospheres,2008,113(D10110):1-7.
[11]龚伟伟,师春香,张涛,等.中国区域多种数值模式资料的地面气象要素评估[J].气候与环境研究,2015,20(1):53-62.[GONG Weiwei,SHI Chunxiang,ZHANG Tao,et al. Evaluation of surface meteorological elements from several numerical models in China[J]. Climatic and Environmental Research,2015,20(1):53-62.]
[12]张峰. 2015年9~11月T639、ECMWF及日本模式中期预报性能检验[J].气象,2016,42(2):246-253.[ZHANG Feng. Performance verification of medium-range forecast by T639 and ECMWF and Japan models from September to November[J]. Meteorological Monthly,2016,42(2):246-253.]
[13]涂小萍,姚日升. ECMWF数值产品在热带气旋(TC)路径预报中的应用分析[J].热带气象学报,2010,26(6):759-764.[TU Xiaoping,YAO Risheng. Analysis on ECMWF NWP products in TC track forecasting[J]. Journal of Tropical Meteorology,2010,26(6):759-764.]
[14]肖红茹,王灿伟,周秋雪,等. T639、ECMWF细网格模式对2012年5~8月四川盆地降水预报的天气学检验[J].高原山地气象研究,2013,33(1):80-85.[XIAO Hongru,WANG Canwei,ZHOU Qiuxue,et al. Synoptic meteorology verification of precipitation forecast for T639 ECMWF fine grid models from May to August 2012 in Sichuan Basin[J]. Plateau and Mountain Meteorology Research,2013,33(1):80-85.]
[15]熊世为,郁凌华,胡姗姗,等.基于ECMWF细网格产品的一种优化BP-MOS气温预报方法[J].干旱气象,2017,35(4):668-673.[XIONG Shiwei,YU Linghua,HU Shanshan,et al. An optimized BP-MOS temperature forecast method based on the finemesh products of ECMWF[J]. Journal of Arid Meteorology,2017,35(4):668-673.]
[16]罗菊英,周建山,闫永财.基于数值预报及上级指导产品的本地气温MOS预报方法.气象科技,2014,42(3):443-450.[LUO Juying,ZHOU Jianshan,YAN Yongcai. Local temperature MOS forecast method based on numerical forecast products and superior guidance[J]. Meteorological Science and Technology,2014,42(3):443-450.]
[17]余晖,陈国民,万日金.数值模式的热带气旋强度预报订正及其集成应用[J].气象学报,2015,73(4):667-678.[YU Hui,CHEN Guomin,WAN Rijin. A multi-model consensus forecast technique for tropical cyclone intensity based on model output calibration[J]. Acta Meteorological Sinica,2015,73(4):667-678.]
[18]李佰平,智协飞. ECWRF模式地面气温预报的四种误差订正方法的比较研究[J].气象,2012,38(8):897-902.[LI Baiping,ZHI Xiefei. Comparative study of four correction schemes of the ECMWF surface temperature forecasts[J]. Meteorological Monthly,2012,38(8):897-902.]