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高原气象  2018, Vol. 37 Issue (4): 1042-1050    DOI: 10.7522/j.issn.1000-0534.2017.00090
徐岩岩, 常军
河南省气候中心, 河南 郑州 450003
Evaluation of the Minimum Temperature Forecast of 1~52 Days Based on DERF2.0 Model
XU Yanyan, CHANG Jun
Climate Center of Henan Province, Zhengzhou 450003, Henan, China
 全文: PDF 
摘要: 利用国家气候中心第二代月动力延伸预报模式系统(DERF2.0)1983-2013年历史回算数据中20个全样本集合平均的最低温度数据,对3月中国中纬度地区模式最低温度1~52天逐日预报能力进行了评估。结果表明,通过计算绝对误差的绝对值AE、均方根误差RMSE和相关系数R发现前10天预报可信度较高,预报时效越短,可信度越高,超过10天之后预报可信度越来越低。为了分析模式误差的深层次原因,利用集合经验模态分解方法(EEMD)对数据进行分解,DERF2.0模式和观测数据的高频分量IMF1和趋势项R为主要分量,低频分量IMF2占的比重较少。分析发现,DERF2.0模式在10天之后预报能力下降的主要原因是高频分量IMF1的预报能力下降。通过分析历年的结果,发现各项方差贡献率年际变化不大,比较稳定,高频分量IMF1和低频分量IMF2方差贡献率和观测数据相比普遍偏低,趋势项R方差贡献率和观测数据相比每年都偏高。DERF2.0模式应该针对高频扰动继续加强研究,提高DERF2.0预报升温降温过程的能力。
关键词: DERF2.0模式逐日最低温度EEMD高频扰动方差贡献率    
Abstract: On the basis of the lowest temperature data for the average of 20 full sample of the National Climate Centre second-generation monthly Dynamic Extended Range Forecast operational system 2.0 (DERF2.0) from 1983 to 2013, the forecast capacity of the lowest temperature in mid-latitudes of China in march from 1 to 52 days was evaluated. The first ten days of the minimum temperature were more credible, and the shorter the forecast time was, the higher the credibility was, but over the 10 days, the credibility of the forecast was getting worse and worse by evaluating the absolute value of the absolute error (AE), root mean square error (RMSE) and correlation coefficient (R). In order to analyze the deep reasons of the model error, the data was decomposed by the ensemble empirical mode decomposition (EEMD). The high frequency component IMF1 and the trend item R were the main components, while the low frequency component IMF2 account for a small proportion in DERF2.0 data and observation data. The main reason for the decline in predictive ability after ten days was the decline in the predictive ability of the high frequency IMF1 by analyzing. In the DERF2.0 model, the variance contribution rate and observation data of the high frequency components of the high frequency components were generally low compared with the observed data. The contribution rate and observation data of the trend item R variance were higher than that of each year. The DERF2.0 model should focus on the study of high frequency disturbances to improve the ability of DERF2.0 in predicting the temperature changing process.
Key words: DERF2.0 model    minimum temperature of day    EEMD    high frequency components    ratio of variance
收稿日期: 2017-08-12 出版日期: 2018-08-22
:  P456.3  
基金资助: 河南省气象局气象科学研究项目(KQ201730,Z201406);河南省气象局气候与气候变化创新团队项目
作者简介: 徐岩岩(1988-),男,河南栾川人,工程师,主要从事气候预测方面研究
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徐岩岩, 常军. 基于DERF2.0模式1~52天最低温度逐日预报的检验评估[J]. 高原气象, 2018, 37(4): 1042-1050.

XU Yanyan, CHANG Jun. Evaluation of the Minimum Temperature Forecast of 1~52 Days Based on DERF2.0 Model. Plateau Meteorology, 2018, 37(4): 1042-1050.


Baldwin M P, Stephenson D B, Thompson D W J, et al, 2003. Stratospheric memory and skill of extended-range weather forecasts[J]. Science, 301(5633):636-640.
Huang N E, Wu Z H, 2008. A review on Hilbert-Huang transform:Method and its applications to geophysical studies[J]. Rev Geophys, 46(2):1-23.
Huang N E, Shen Z, Long S R, et al, 1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]//Proceedings of the Royal Society of London A:Mathematical, physical and engineering sciences. The Royal Society, 454(1971):903-995.
Overpeck J T, Meehl G A, Bony S, et al, 2011. Climate data challenges in the 21st century[J]. Science, 331(6018):700-702.
Saha S, Nadiga S, Thiaw C, et al, 2005. The NCEP climate forecast system[J]. J Climate, 19(15):3483-3517.
Sue N, 2008. Big data:The Harvard computers[J]. Nature, 455(7209):36-37.
Vitart F, 2004. Monthly forecasting at ECMWF[J]. Mon Wea Rev, 132(132):2761-2779.
Wheeler M, Hendon H, 2004. An all-season real-time multivariate MJO index:Development of an index for monitoring and prediction[J]. Mon Wea Rev, 132(8):1917-1932.
Woolnough S J, Vitart F, Balmaseda M A, 2007. The role of the ocean in the Madden-Julian Oscillation:Implications for MJO prediction[J]. Quart J Roy Meteor Soc, 133(622):117-128.
Wu T W, Yu R C, Zhang F, et al, 2010. The Beijing Climate Center atmospheric general circulation model:Description and its performance for the present-day climate[J]. Climate Dyn, 34(1):123-147.
Zhang X F, Zhang Y F, Wang C Y, et al, 2011. Spatial distribution and temporal variation of the winter wheat late frost disaster in Henan, China[J]. Acta Meteor Sinica, 25(2):249-259.
陈官军, 魏凤英, 巩远发, 2010. NCEP/CFS模式对东亚夏季延伸预报的检验评估[J]. 应用气象学报, 21(6):659-670. Chen G J, Wei F Y, Gong Y F, 2010. Assessing the extended range forecast error of NCEP/CFS in the summer of East Asia[J]. Quart J Appl Meteor, 21(6):659-670.
陈桂英, 赵振国, 1998. 短期气候预测评估方法和业务初估[J]. 应用气象学报, 9 (2):178-185. Chen G Y, Zhao Z G, 1998. Assessment methods of short range climate prediction and their operational application[J]. Quart J Appl Meteor, 9 (2):178-185.
陈乾金, 张永山, 1995. 华北异常初终霜冻气候特征研究[J]. 自然灾害学报, 4(3):33-39. Chen Q J, Zhang Y S, 1995. Study on climatic features of unusual first and last frost in north China[J]. J Natural Disaster, 4(3):33-39.
丑纪范, 2012. 一个创新研究——大气数值模式变量的物理分解及其在极端事件预报中的应用[J]. 地球物理学报, 55(5):1433-1438. Chou J F, 2012. An innovation study on the physical decomposition of numerical model atmospheric variables and their application in weather extreme events[J]. Chinese J Geophys, 55(5):1433-1438.
单机坤, 梁潇云, 孙林海, 等, 2016. 冬季极端低温日数预测方法研究[J]. 高原气象, 35(6):1609-1614. Shan J K, Liang X Y, Sun L H, et al, 2016. Prediction of extreme winter cold days[J]. Plateau Meteor, 35(6):1609-1614. DOI:10.7522/j. issn. 1000-0534.2015.00112.
丁一汇, 李清泉, 李维京, 等, 2004. 中国业务动力季节预报的进展[J]. 气象学报, 62 (5):598-612. Ding Y H, Li Q Q, Li W J, et al, 2004. Advance in seasonal dynamical prediction operation in china[J]. Acta Meteor Sinica, 62 (5):598-612.
丁一汇, 刘一鸣, 宋永加, 等, 2002. 我国短期气候动力预测模式系统的研究及试验[J]. 气候与环境研究, 7 (2):236-246. Ding Y H, Liu Y M, Song Y J, et al, 2002. Research and experiments of the dynamical model system for short-term climate prediction[J]. Climatic Environ Res, 7 (2):236-246.
冯玉香, 何维勋, 孙忠富, 等, 1999. 我国冬小麦霜冻害的气候分析[J]. 作物学报, 25(3):335-340. Feng Y X, He W X, Sun Z F, et al, 1999. Climatological study on frost damage of winter wheat in China[J]. Acta Agronomica Sinica, 25(3):335-340.
顾伟宗, 陈丽娟, 张培群, 等, 2009. 基于月动力延伸预报最优信息的中国降水降尺度预测模型[J]. 气象学报, 67(2):280-287. Gu W Z, Chen L J, Zhang P Q, et al, 2009. Downscaling precipitation prediction in China based on optimization information extracted from monthly dynamic extended range forecast[J]. Acta Meteor Sinica, 67(2):280-287.
何慧根, 李巧萍, 吴统文, 等, 2014. 月动力延伸预测模式业务系统DERF2.0对中国气温和降水的预测性能评估[J]. 大气科学, 38(5):950-964. He H G, Li Q P, Wu T W, et al, 2014. Temperature and precipitation evaluation of monthly dynamic extended range forecast operational system DERF2.0 in China[J]. Chinese J Atmos Sci, 38(5):950-964.
金荣花, 马杰, 毕宝贵, 2010.10~30 d延伸期预报研究进展和业务现状[J]. 沙漠与绿洲气象, 4(2):1-5. Jin R H, Ma J, Bi B G, 2010. Research advancement and operation status about the extended range forecast from10 to 30 days[J]. Desert Oasis Meteor, 4(2):1-5.
李茂松, 王道龙, 张强, 等, 2005.2004-2005年黄淮海地区冬小麦冻害成因分析[J]. 自然灾害学报, 14(4):51-55. Li M S, Wang D L, Zhang Q, et al, 2005. Cause analysis of frost damage to winter wheat in Huang-Huai-Hai plain during 2004-2005[J]. J Natural Disaster, 14(4):51-55.
马柱国, 2003. 中国北方地区霜冻日的变化与区域增暖相互关系[J]. 地理学报, 58(增刊):31-37. Ma Z G, 2003. Variation of frost days and its relationship to regional warming in northern China[J]. Acta Geograp Sinica, 58(Suppl):31-37.
孟纯纯, 马耀明, 马伟强, 等, 2016. 中国东部秋冬季极端干旱事件的数值模拟研究[J]. 高原气象, 35(5):1327-1338. Meng C C, Ma Y M, Ma W Q, et al, 2016. Modeling analysis of a severe autumn/winter drought in eastern China by using Regional Atmospheric Modeling System(RAMS)[J]. Plateau Meteor, 35(5):1327-1338. DOI:10.7522/j. issn. 1000-0534.2015.00082.
唐红玉, 董新宁, 周秀华, 等, 2016. 基于DERF2.0产品的重庆月动力延伸期预测分析及应用[J]. 沙漠与绿洲气象, 10(3):1-8. Tang H Y, Dong X N, Zhou X H, et al, 2016. Analysis and application of monthly dynamic extension forecast in Chongqing based on DERF2.0 data[J]. Desert Oasis Meteor, 10(3):1-8.
伍荣生, 谈哲敏, 王元, 2007. 我国业务天气预报发展的若干问题思考[J]. 气象科学, 27(1):112-118. Wu R S, Tan Z M, Wang Y, 2007. Discussions on the scientific and technological development of Chinese operation weather forcast[J]. Scientia Meteor Sinica, 27(1):112-118.
叶殿秀, 张勇, 2008.1961-2007年我国霜冻变化特征[J]. 应用气象学报, 19(6):661-665. Ye D X, Zhang Y, 2008. Characteristics of frost changes from 1961 to 2007 over China[J]. Quart J Appl Meteor, 19(6):661-665.
翟盘茂, 任福民, 1997. 中国近40年最高最低温度变化[J]. 气象学报, 55(4):418-429. Zhai P M, Ren F M, 1997. On changes of China's maximum and minimum temperatures in the recent 40 years[J]. Acta Meteor Sinica, 55(4):418-429.
钟秀丽, 王道龙, 李玉中, 等, 2007. 黄淮麦区小麦拔节后霜害的风险评估[J]. 应用气象学报, 18(1):102-107. Zhong X L, Wang D L, Li Y Z, et al, 2007. Risk assessment of forst damage in wheat[J]. Quart J Appli Meteor, 18(1):102-107.
庄照荣, 薛纪善, 李兴良, 等, 2010. GRAPES全球模式的模式误差估计[J]. 大气科学, 34(3):591-598. Zhuang Z R, Xue J S, Li X L, et al, 2010. Estimation of model error for the global GRAPES model[J]. Chinese J Atmos Sci, 34(3):591-598.
[1] 郝立生, 向亮, 周须文. 华北平原夏季降水准双周振荡与低频环流演变特征[J]. , 2015, 34(2): 486-493.
[2] 叶月珍, 方之芳. 青藏高原热力状况与四川盆地汛期降水的联系[J]. 高原气象, 1999, 18(2): 162-170.
[3] 方之芳, 李超, 李贤琅. 青藏高原温度场与贵州干旱的联系[J]. 高原气象, 1996, 15(4): 496-502.