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Assimilation of Radio Occultation Data Using Measurement-based Observation Error Specification: Preliminary Results

Hailing ZhangUniversity Corporation for Atmospheric Research, Boulder, CO

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Ying-Hwa KuoUniversity Corporation for Atmospheric Research, Boulder, CO

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Sergey SokolovskiyUniversity Corporation for Atmospheric Research, Boulder, CO

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Abstract

The local spectral width (LSW) of a radio occultation (RO) observation in impact parameter representation is a useful parameter for providing information on the uncertainty associated with the RO bending angle measurement. The LSW can potentially be used to specify the bending angle observation error (BaOE) in the lower troposphere for each individual sounding. This study assesses the usefulness and limitations of LSW in representing BaOE for a global data assimilation system. A two-step scheme is proposed to derive profile-dependent BaOE from LSW. Since the LSW-based BaOE varies with each individual RO observation, it is here designated as a dynamic BaOE (DBOE) in contrast to the traditional statistics-based BaOE specification. A benchmark control run and two sensitivity experiments are conducted with continuous cycling data assimilation using the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) and Global Forecast System (GFS). The usefulness and impact of the LSW-based DBOE are evaluated using radiosonde observations and global analyses. Results show that DBOE is able to improve the assimilation of RO data, leading to better forecast skill scores. Another experiment, in which the GSI statistical observation error of the benchmark run is replaced by the average of LSW-based DBOE, shows that the ability to assign larger weighting for high-quality observation and lower weighting for low-quality observation is the key factor for the success of the LSW-based DBOE.

Corresponding Author: Hailing Zhang, hailingz@ucar.edu

Abstract

The local spectral width (LSW) of a radio occultation (RO) observation in impact parameter representation is a useful parameter for providing information on the uncertainty associated with the RO bending angle measurement. The LSW can potentially be used to specify the bending angle observation error (BaOE) in the lower troposphere for each individual sounding. This study assesses the usefulness and limitations of LSW in representing BaOE for a global data assimilation system. A two-step scheme is proposed to derive profile-dependent BaOE from LSW. Since the LSW-based BaOE varies with each individual RO observation, it is here designated as a dynamic BaOE (DBOE) in contrast to the traditional statistics-based BaOE specification. A benchmark control run and two sensitivity experiments are conducted with continuous cycling data assimilation using the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) and Global Forecast System (GFS). The usefulness and impact of the LSW-based DBOE are evaluated using radiosonde observations and global analyses. Results show that DBOE is able to improve the assimilation of RO data, leading to better forecast skill scores. Another experiment, in which the GSI statistical observation error of the benchmark run is replaced by the average of LSW-based DBOE, shows that the ability to assign larger weighting for high-quality observation and lower weighting for low-quality observation is the key factor for the success of the LSW-based DBOE.

Corresponding Author: Hailing Zhang, hailingz@ucar.edu
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