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A New Typhoon Bogus Data Assimilation and its Sampling Method: A Case Study

Abstract In this study, the authors introduce a new bogus data assimilation method based on the dimension-reduced projection 4-DVar, which can resolve the cost function directly in low-dimensional space. The authors also try a new method to improve the quality of samples, which are the base of dimension-reduced space projection bogus data assimilation (DRP-BDA). By running a number of numerical weather models with different model parameterization combinations on the typhoon Sinlaku, the authors obtained two groups of samples with different spreads and similarities. After DRP-BDA, the results show that, compared with the control runs, the simulated typhoon center pressure can be deepened by more than 20 hPa to 30 hPa and that the intensity can last as long as 60 hours. The mean track error is improved after DRP-BDA, and the structure of the typhoon is also improved. The wind near the typhoon center is enhanced dramatically, while the warm core is moderate.