TY - JOUR
T1 - Direct assimilation of satellite radiance data in GRAPES variational assimilation system
AU - Zhu, Guofu
AU - Xue, Jishan
AU - Zhang, Hua
AU - Liu, Zhiquan
AU - Zhuang, Shiyu
AU - Huang, Liping
AU - Dong, Peiming
PY - 2008/11
Y1 - 2008/11
N2 - Variational method is capable of dealing with observations that have a complicated nonlinear relation with model variables representative of the atmospheric state, and so make it possible to directly assimilate such measured variables as satellite radiance, which have a nonlinear relation with the model variables. Assimilation of any type of observations requires a corresponding observation operator, which establishes a specific mapping from the space of the model state to the space of observation. This paper presents in detail how the direct assimilation of real satellite radiance data is implemented in the GRAPES-3DVar analysis system. It focuses on all the components of the observation operator for direct assimilation of real satellite radiance data, including a spatial interpolation operator that transforms variables from model grid points to observation locations, a physical transformation from model variables to observed elements with different choices of model variables, and a data quality control. Assimilation experiments, using satellite radiances such as NOAA17 AMSU-A and AMSU-B (Advanced Microwave Sounding Unit), are carried out with two different schemes. The results from these experiments can be physically understood and clearly reflect a rational effect of direct assimilation of satellite radiance data in GRAPES-3DVar analysis system.
AB - Variational method is capable of dealing with observations that have a complicated nonlinear relation with model variables representative of the atmospheric state, and so make it possible to directly assimilate such measured variables as satellite radiance, which have a nonlinear relation with the model variables. Assimilation of any type of observations requires a corresponding observation operator, which establishes a specific mapping from the space of the model state to the space of observation. This paper presents in detail how the direct assimilation of real satellite radiance data is implemented in the GRAPES-3DVar analysis system. It focuses on all the components of the observation operator for direct assimilation of real satellite radiance data, including a spatial interpolation operator that transforms variables from model grid points to observation locations, a physical transformation from model variables to observed elements with different choices of model variables, and a data quality control. Assimilation experiments, using satellite radiances such as NOAA17 AMSU-A and AMSU-B (Advanced Microwave Sounding Unit), are carried out with two different schemes. The results from these experiments can be physically understood and clearly reflect a rational effect of direct assimilation of satellite radiance data in GRAPES-3DVar analysis system.
KW - Advanced Microwave Sounding Unit
KW - Data assimilation
KW - Observation operator
KW - Satellite radiance data
KW - Variational method
UR - https://www.scopus.com/pages/publications/56349102708
U2 - 10.1007/s11434-008-0419-x
DO - 10.1007/s11434-008-0419-x
M3 - Article
AN - SCOPUS:56349102708
SN - 1001-6538
VL - 53
SP - 3465
EP - 3469
JO - Chinese Science Bulletin
JF - Chinese Science Bulletin
IS - 22
ER -