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 m...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.展开更多
Reconciling upper-air temperature trends derived from radiosonde and satellite observations is a necessary step to confidently determine the global warming rate. This study examines the raw and homogenized radiosonde ...Reconciling upper-air temperature trends derived from radiosonde and satellite observations is a necessary step to confidently determine the global warming rate. This study examines the raw and homogenized radiosonde observations over China and compares them with layer-mean atmospheric temperatures derived from satellite microwave observations for the lower-troposphere(TLT), mid-troposphere(TMT), upper-troposphere(TUT), and lower-stratosphere(TLS) by three research groups. Comparisons are for averages over China, excluding the Tibetan Plateau, and at individual stations where metadata contain information on radiosonde instrument changes. It is found that major differences between the satellite and radiosonde observations are related to artificial systematic changes. The radiosonde system updates in the early 2000 s over China caused significant discontinuities and led the radiosonde temperature trends to exhibit less warming in the middle and upper troposphere and more cooling in the lower stratosphere than satellite temperatures. Homogenized radiosonde data have been further adjusted by using the shift-point adjustment approaches to match with satellite products for China averages. The obtained trends during 1979–2015 from the re-adjusted radiosonde observation are respectively 0.203 ± 0.066, 0.128 ± 0.044, 0.034 ± 0.039, and –0.329 ± 0.135 K decade^(–1) for TLT, TMT, TUT, and TLS equivalents. Compared to satellite trends, the re-adjusted radiosonde trends are within 0.01 K decade^(–1) for TMT and TUT, 0.054 K decade^(–1) warmer for TLT, and 0.051 K decade^(–1) cooler for TLS. The results suggest that the use of satellite data as a reference is helpful in identifying and removing inhomogeneities of radiosonde temperatures over China and reconciling their trends to satellite microwave observations. Future efforts are to homogenize radiosonde temperatures at individual stations over China by using similar approaches.展开更多
基金Key Technologies Research and Development Program (Grant No. 2001BA607B02)National Natural Science Foundation of China (Grant No. 40475042)
文摘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.
基金Supported by the National Key Research and Development Progtam of China(2018YFC1509002 and 2016YFA0600301-05)China Meteorological Administration Special Public Welfare Research Fund(GYHY201406017,GYHY201506002,and GYHY201506019)+1 种基金National Natural Science Foundation of China(41675094 and 41775082)Climate Change Special Fund of China Meteorological Administration(CCSF201803)
文摘Reconciling upper-air temperature trends derived from radiosonde and satellite observations is a necessary step to confidently determine the global warming rate. This study examines the raw and homogenized radiosonde observations over China and compares them with layer-mean atmospheric temperatures derived from satellite microwave observations for the lower-troposphere(TLT), mid-troposphere(TMT), upper-troposphere(TUT), and lower-stratosphere(TLS) by three research groups. Comparisons are for averages over China, excluding the Tibetan Plateau, and at individual stations where metadata contain information on radiosonde instrument changes. It is found that major differences between the satellite and radiosonde observations are related to artificial systematic changes. The radiosonde system updates in the early 2000 s over China caused significant discontinuities and led the radiosonde temperature trends to exhibit less warming in the middle and upper troposphere and more cooling in the lower stratosphere than satellite temperatures. Homogenized radiosonde data have been further adjusted by using the shift-point adjustment approaches to match with satellite products for China averages. The obtained trends during 1979–2015 from the re-adjusted radiosonde observation are respectively 0.203 ± 0.066, 0.128 ± 0.044, 0.034 ± 0.039, and –0.329 ± 0.135 K decade^(–1) for TLT, TMT, TUT, and TLS equivalents. Compared to satellite trends, the re-adjusted radiosonde trends are within 0.01 K decade^(–1) for TMT and TUT, 0.054 K decade^(–1) warmer for TLT, and 0.051 K decade^(–1) cooler for TLS. The results suggest that the use of satellite data as a reference is helpful in identifying and removing inhomogeneities of radiosonde temperatures over China and reconciling their trends to satellite microwave observations. Future efforts are to homogenize radiosonde temperatures at individual stations over China by using similar approaches.
