通过对AMDAR（Aircraft Meteorological Data Relay）温度资料进行了偏差订正来改善数值预报同化预报效果。方法是以NECP（National Centers for Environmental Prediction）的GFS（Global Forecast System）的6 h预报场作为参考场来统计AMDAR观测温度减去参考场的偏差，根据飞机上升率和下降率，应用最小二乘法拟合温度资料偏差的线性回归方程，然后用回归方程结合探空资料对温度观测进行偏差订正。AMDAR资料来源是国家气象信息中心数据库，偏差统计时间为冬季（2014年12月到2015年1-2月）和夏季（2014年6-8月）。另外，应用GRAPES（Global Regional Assimilation and Prediction System）系统对订正后的AMDAR温度资料进行了1个月（2013年12月）的同化预报影响试验，结果表明，同NCEP的FNL（Final Operational Global Analysis data）资料相比，加入订正后的AMDAR温度资料可以减小高度分析场的偏差和均方根误差，尤其在平飞阶段（300~150 hPa），其偏差、均方根误差减小了2 gpm，对温度分析场的影响也有正效果，偏差和均方根误差最多减小0.15℃。高度场和温度场的预报距平相关系数在250 hPa以上也比温度资料订正前有所提高，温度场的预报时效提高了0.5天。
Bias correction of AMDAR(Aircraft Meteorological Data Relay) temperature data is used to improve numerical weather forecast effect in this paper.6 hour forecast of global forecast system in national center for environmental prediction is as reference field, and bias statistic of AMDAR temperature data minus reference filed has been done.The equation of linear regression of bias of AMDAR temperature is fitted by the method of least square method according to the rate of rise and descend, and bias of AMDAR temperature can be corrected by combing the radiosonde data.The AMDAR data is from real-time database in National Meteorological Information Centre (NMIC), and the two period for the data is from June to August 2014 and from December 2014 to February 2015.One month numerical experiment has been done by the use of corrected AMDAR temperature data in GRAPES (Global Regional Assimilation and Prediction System).The results show that Bias and RMSE (root mean square error) of height analysis are decreased by assimilating corrected AMDAR temperature data than uncorrected data.Bias and RMSE of height decrease 2 gpm on 300~150 hPa.The maximum reduction of bias and RMSE of temperature is close to 0.15℃.Forecast anomaly correlation of height and temperature is increased above 250 hPa than before correction.The period of validity of temperature improve 0.5 days.
[1]Ballish B A, Kumar K V. 2008. Systematic differences in aircraft and radiosonde temperatures[J]. Bull Amer Meteor Soc, 89:1689-1707.
[2]Cardinali C, Isaksen L, Andersson E. 2003. Use and impact of automated aircraft data in a global 4DVAR data assimilation system[J]. Mon Wea Rev, 131:1865-1877.
[3]Dee D P. 2004. Variational bias correction of radiance data in the ECMWF system. Proc. ECMWF Workshop on Assimilation of High Spectral Resolution Sounders in NWP, Reading, United Kingdom, ECMWF, 97-112.
[4]Fournier C, Holden S D. 2005. Development of the Canadian Aircraft Meteorological Data Relay (AMDAR) Program and Plans for the Future[C] 13th Symposium on Meteorological Observations and Instrumentation. Savannah, GA.
[5]Harris B A, Kelly G. 2001. A satellite radiance-bias correction shceme for data assimilation[J]. Quart JRoy Meteor Soc, 127:1453-1468.
[6]Isaksen L, Vasiljevic D, Dee D, et al. 2012. Bias correction of aircraft data implemented in November 2011[D]. ECMWF Newsletter, No. 131, ECMWF, Reading, United Kingdom.
[7]Pouponneau B, Ayrault F, Bergot T, et al. 1999. The impact of aircraft data on an Atlantic cyclone analyzed in terms of sensitivities and trajectories[J]. Wea Forecasting, 14:67-83.
[8]Rukhovets L, Tenenbaum J, Geller M. 1998. The impact of additional aircraft data on the Goddard earth observing system analyses[J]. Mon Wea Rev, 126:2927-2941.
[9]Schwartz B, Benjamin S G. 1995. A comparison of temperature and wind measurements from ACARS-equipped aircraft and radiosondes[J]. Wea Forecasting, 10:528-544.
[10]Zhu Y Q, Derber J C, Purser R J, et al. 2015. Variational Correction of Aircraft Temperature Bias in the NCEP's GSI Analysis System[J]. Mon Wea Rev, 143(9):3774-3803.
[11]Chen Dehui, Xue Jishan, Yang Xuesheng, et al. 2008. GRAPES Design and Research of New Generation Global/Regional Multi Scale Numerical Prediction Model[J]. Chinese Sci Bull, 53(20):2396-2407.<br/>陈德辉, 薛纪善, 杨学胜, 等. 2008. GRAPES新一代全球/区域多尺度统一数值预报模式总体设计研究[J].科学通报, 53(20):2396-2407.
[12]Liao Jie, Ren Zhihua. 2011. Comparative Analysis on Aircraft and Radiosonde Temperatures in China[J]. Meteor Mon, 37(3):263-269.<br/>廖捷, 任芝花. 2011.我国飞机观测气温和常规观测气温的对比分析[J].气象, 37(3):263-269.
[13]Qiao Xiaoyan, Ma Shuqing, Tao Shiwei, et al. 2010. Error Analyses of Temperature and Wind of Aircraft Meteorological Data[J], Journal of Chengdu University of Information Technology, 25(2):201-205.<br/>乔晓燕, 马舒庆, 陶士伟, 等. 2010.商用飞机气象观测温度、风场随机误差分析[J].成都信息工程学院学报, 25(2):201-205.
[14]Tao Shiwei, Hao Min, Xue Jishan, et al. 2008. Analyses of Observation Data Error in Numerical Forecasting Assimilation System[J], Meteor Mon, 34(7):34-40.<br/>陶士伟, 郝民, 薛纪善, 等. 2008.数值预报同化系统中观测资料误差分析[J].气象, 34(7):34-40.
[15]Tao Shiwei, Hao Min, Zhao Linna. 2009. Quality control procedures and its application in AMDAR observation data[J]. Meteor Mon, 35(12):66-73.<br/>陶士伟, 郝民, 赵琳娜. 2009. AMDAR观测资料分析及质量控制[J].气象, 35(12):66-73.
[16]Xue Jishan, Liu Yan, Zhang Lin, et al. 2012. Mode Variable analysis in GRAPES Global Three-Dimensional Variational Assimilation System[R]. 12-15.<br/>薛纪善, 刘艳, 张林, 等. 2012. GRAPES全球三维变分同化系统模式变量分析版[R]. 12-15.
