Plateau Meteorology

Plateau Meteorology >

2016 , Vol. 35 >Issue 2: 397 - 405

DOI: https://doi.org/10.7522/j.issn.1000-0534.2014.00147

Impact of Different Covariance Inflation Schemes of ETKF on WRFDA Hybrid Assimilation and Forecast

  • WANG Yuanbing ,
  • CHEN Yaodeng ,
  • MIN Jinzhong ,
  • GAO Yufang ,
  • HUANG Xiangyu ,
  • WANG Hongli ,
  • XU Dongmei ,
  • LIU Jianyu
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  • Key Laboratory of Meteorological Disaster of Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;2. Meteorological Service Singapore, Centre for Climate Research Singapore, Singapore 537054, Singapore;3. Cooperative Institute for Research in the Atmosphere, Colorado State Univeisity, Fort Collins CO 80553, USA;4. Global Systems Division, NOAA/Earth System Research Laboratory, Boulder CO 80302, USA

Received date: 2014-06-11

  Online published: 2016-04-28

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Abstract

To study the impact of different ETKF(Ensemble Transform Kalman Filter)covariance inflation schemes on Hybrid data assimilation and forecast, five experiments are conducted over most China area from 10 to 20 July 2011. These five experiments include four experiments with different covariance inflation schemes and one experiment without any covariance inflation schemes. The results show that:All the experiments with covariance inflation perform better than experiment without covariance inflation. The inflation sheme which averages the inflation factors performs worst; The performance of the other three experiments with covariance inflation shows similar results, but differences still exsit:For wind, the scheme which uses projection factor in ensemble subspace and the scheme which uses averaged innovation value show the better results than the other two. For temperature, humidity and preciptation, the sheme which uses the ratio of the spread between previous and current cycle and the scheme uses averaged innovation value perform the best.

Key words： NWP; Data assimilation; Hybrid; Covariance inflation

Cite this article

WANG Yuanbing , CHEN Yaodeng , MIN Jinzhong , GAO Yufang , HUANG Xiangyu , WANG Hongli , XU Dongmei , LIU Jianyu . Impact of Different Covariance Inflation Schemes of ETKF on WRFDA Hybrid Assimilation and Forecast[J]. Plateau Meteorology, 2016 , 35(2) : 397 -405 . DOI: 10.7522/j.issn.1000-0534.2014.00147

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