Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Transactions of Atmospheric Sciences》 2018-05
Add to Favorite Get Latest Update

Extended range probabilistic forecast of surface air temperature using Bayesian model averaging

ZHI Xiefei;PENG Ting;WANG Yuhong;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory of Meteorological Disasters,Ministry of Education (KLME),Nanjing University of Information Science & Technology;Nanjing Joint Center for Atmospheric Research (NJCAR);Hebei Meteorological Observatory;  
In this study,based on the 10—15 day extended range ensemble forecasts of European Centre for MediumRange Weather Forecasts(ECMWF),National Centers for Environmental Prediction(NCEP)and United Kingdom Met Office(UKMO)in the TIGGE dataset,the probabilistic forecasts of surface air temperature during the period from 1 June to 31 August 2013 were conducted using BMA(Bayesian Model Averaging).The results showed that the forecasting skill changed with the length of the training period,reaching its optimal value when the length of the training period was 30 days.BMA could provide full PDF(Probability Density Function),and quantitatively describe the forecast variance and uncertainty.The uncertainty and error on the land(higher latitude)were larger than those on the sea(lower latitude).Moving average methods improved the forecast skill of surface air temperature,and the longer the moving average period was,the better of the forecast performance would be.
【Fund】: 国家自然科学基金资助项目(41575104);; 北极阁开放研究基金南京大气科学联合研究中心(NJCAR)重点项目(NJCAR2016ZD04)
【CateGory Index】: P456
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved