Improving Assimilation of Polar-Orbiting Satellite Microwave Radiances over the Tibetan Plateau Using a Gaussian–Flat Variational Quality Control.

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Title: Improving Assimilation of Polar-Orbiting Satellite Microwave Radiances over the Tibetan Plateau Using a Gaussian–Flat Variational Quality Control.
Authors: Yang, Jiarui1 (AUTHOR), Hao, Bingjie2 (AUTHOR), He, Jie3 (AUTHOR), Deng, Hua3,4 (AUTHOR), Chen, Hua1,4 (AUTHOR), Ma, Xulin1,2 (AUTHOR) xulinma@nuist.edu.cn
Source: Remote Sensing. Jun2026, Vol. 18 Issue 12, p2029. 22p.
Subjects: Data assimilation, Microwave remote sensing, Meteorological satellites, Weather forecasting, Distribution (Probability theory), Rainfall
Geographic Terms: Tibet (China)
Abstract: Highlights: What are the main findings? The Flat-VarQC significantly increases the effective assimilation rate of polar-orbiting satellite microwave observations over the Tibetan Plateau (by approximately 4–28%) by recovering observations rejected by conventional quality control. The differences in the analysis weights of the temperature channel and the humidity channel in Flat-VarQC are revealed. The scheme shows better applicability and effectiveness for microwave temperature sounders than for microwave humidity sounders, with more reasonable weights for temperature observations. A Gaussian–Flat variational quality control suitable for improving the assimilation of satellite data over the Tibetan Plateau is developed. Optimizing the key parameters enables more effective use of multi-channel microwave observations from multiple polar-orbiting satellites under complex terrain conditions over the Tibetan Plateau, providing reference parameter schemes in operational assimilation systems. What are the implications of the main findings? The improved assimilation of satellite observations enhances the analysis of key dynamic and moisture fields, thereby improving forecasts of heavy precipitation over the Tibetan Plateau. The parameter optimization for Flat-VarQC provides a practical reference for assimilating satellite observations over data-sparse regions with complex terrain. The evolution of weather systems over the Tibetan Plateau (hereinafter referred to as the Plateau) significantly affects the quality of numerical weather prediction in its surrounding areas and downstream regions. Given the scarcity and relatively low quality of conventional observations over the Plateau, satellite observations with high spatial and temporal resolution are particularly important. However, the complex surface conditions of the Plateau severely limit the effective application and assimilation performance of satellite observations. The variational quality control (VarQC) scheme has demonstrated strong capability to reasonably utilize observations of varying quality to improve assimilation analyses. In view of this, this study developed a variational quality control scheme based on the non-Gaussian characteristics of observation errors, specifically a scheme based on a "Gaussian + flat" distribution (Flat-VarQC), tailored for satellite observations over the Plateau. Key parameters of the scheme are optimized for polar-orbiting satellite microwave sounders, enabling more appropriate adjustment of the observation weights in the assimilation process based on the innovations, thereby increasing the effective assimilation rate of polar-orbiting satellite microwave sounding data over the Plateau and improving the quality of analyses. Experimental results indicate that observation errors of satellite observations over the Plateau exhibit pronounced fat-tailed distribution characteristics. The conventional Gaussian assumption in variational assimilation schemes leads to a low effective assimilation rate of observations, thereby reducing the contribution of polar-orbiting satellite microwave sounding data to the analyses over the Plateau. The proposed Flat-VarQC scheme significantly improves the effective assimilation rate of both conventional and satellite observations over the Plateau, incorporates more beneficial observational information, and eliminates harmful observational information, thereby enhancing the positive contribution of observations to assimilation analyses. This scheme leads to particularly significant improvements in the assimilation of spaceborne microwave temperature sounder observations over the Plateau and in forecasts of heavy precipitation associated with meso- and micro-scale weather systems. [ABSTRACT FROM AUTHOR]
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Abstract:Highlights: What are the main findings? The Flat-VarQC significantly increases the effective assimilation rate of polar-orbiting satellite microwave observations over the Tibetan Plateau (by approximately 4–28%) by recovering observations rejected by conventional quality control. The differences in the analysis weights of the temperature channel and the humidity channel in Flat-VarQC are revealed. The scheme shows better applicability and effectiveness for microwave temperature sounders than for microwave humidity sounders, with more reasonable weights for temperature observations. A Gaussian–Flat variational quality control suitable for improving the assimilation of satellite data over the Tibetan Plateau is developed. Optimizing the key parameters enables more effective use of multi-channel microwave observations from multiple polar-orbiting satellites under complex terrain conditions over the Tibetan Plateau, providing reference parameter schemes in operational assimilation systems. What are the implications of the main findings? The improved assimilation of satellite observations enhances the analysis of key dynamic and moisture fields, thereby improving forecasts of heavy precipitation over the Tibetan Plateau. The parameter optimization for Flat-VarQC provides a practical reference for assimilating satellite observations over data-sparse regions with complex terrain. The evolution of weather systems over the Tibetan Plateau (hereinafter referred to as the Plateau) significantly affects the quality of numerical weather prediction in its surrounding areas and downstream regions. Given the scarcity and relatively low quality of conventional observations over the Plateau, satellite observations with high spatial and temporal resolution are particularly important. However, the complex surface conditions of the Plateau severely limit the effective application and assimilation performance of satellite observations. The variational quality control (VarQC) scheme has demonstrated strong capability to reasonably utilize observations of varying quality to improve assimilation analyses. In view of this, this study developed a variational quality control scheme based on the non-Gaussian characteristics of observation errors, specifically a scheme based on a "Gaussian + flat" distribution (Flat-VarQC), tailored for satellite observations over the Plateau. Key parameters of the scheme are optimized for polar-orbiting satellite microwave sounders, enabling more appropriate adjustment of the observation weights in the assimilation process based on the innovations, thereby increasing the effective assimilation rate of polar-orbiting satellite microwave sounding data over the Plateau and improving the quality of analyses. Experimental results indicate that observation errors of satellite observations over the Plateau exhibit pronounced fat-tailed distribution characteristics. The conventional Gaussian assumption in variational assimilation schemes leads to a low effective assimilation rate of observations, thereby reducing the contribution of polar-orbiting satellite microwave sounding data to the analyses over the Plateau. The proposed Flat-VarQC scheme significantly improves the effective assimilation rate of both conventional and satellite observations over the Plateau, incorporates more beneficial observational information, and eliminates harmful observational information, thereby enhancing the positive contribution of observations to assimilation analyses. This scheme leads to particularly significant improvements in the assimilation of spaceborne microwave temperature sounder observations over the Plateau and in forecasts of heavy precipitation associated with meso- and micro-scale weather systems. [ABSTRACT FROM AUTHOR]
ISSN:20724292
DOI:10.3390/rs18122029