An application of the A-4DEnVar to coupled parameter optimization

Gong, Yan; Liang, Kangzhuang; Wu, Xinrong; Shao, Qi; Li, Wei; Liu, Siyuan; Han, Guijun; Liu, Hanyu

doi:10.1007/s13131-022-1997-1

Cited by 1 publication

(1 citation statement)

References 35 publications

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“…However, the 4D-Var method also has some drawbacks. In the first place, the background forecast's fixed covariance matrix is not as efficient in capturing the flow-dependent errors compared to the ensemble Kalman filter techniques [26]. In the second place, the 4D-Var method is extremely time-consuming and labor-intensive, requiring multiple iterations of the tangent linear adjoint model to be operated on the powerful parallel computer, as well as the maintenance and development of these models [27].…”

Section: Introductionmentioning

confidence: 99%

A Hurricane Initialization Scheme with 4DEnVAR Satellite Ozone and Bogus Data Assimilation (SOBDA) and Its Application: Case Study

Liu

2023

Atmosphere

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The aim of this study is to joint assimilate the ozone product from the satellite Atmospheric Infrared Sounder (AIRS) and bogus data using the four-dimensional ensemble-variational (4DEnVar) method, and demonstrate the potential benefits of this initialization technique in improving hurricane forecasting through a case study. Firstly, the quality control scheme is employed to enhance the ozone product quality from the satellite AIRS; a bogus sea level pressure (SLP) at the hurricane center is constructed simultaneously based on Fujita’s mathematical model for subsequent assimilation. Secondly, a 4DEnVar satellite ozone and bogus data assimilation (SOBDA) model is established, incorporating an observation operator of satellite ozone that utilizes the relationship between satellite ozone and potential vorticity (PV) from the lower level of 400 hPa to the upper level of 50 hPa. Finally, several comparative experiments are performed to assess the influence of assimilating satellite ozone and/or bogus data, the 4DEnVAR method and four-dimensional variational (4D-Var) method, and ensemble size on hurricane prediction. It is found that assimilating satellite ozone and bogus data with the 4DEnVar method concurrently brings about significant alterations to the initial conditions (ICs) of the hurricane vortex, resulting in a more homogeneous and deeper vortex with a larger, warmer, and more humid core as opposed to assimilating only one type of data. As the duration of integration increases, the initial perturbations in the upper levels gradually propagate downwards, giving rise to significant disparities in the hurricane prediction when satellite ozone and/or bogus information is incorporated. The results demonstrate that utilizing the 4DEnVar approach to assimilate both satellite ozone and bogus data leads to the maximum enhancement in reducing track error and central SLP error of hurricane simulation throughout the entire 72 h forecasting period, compared to assimilating a single dataset. Furthermore, comparative experiments have indicated that the performance of 4DEnVar SOBDA in hurricane forecasting is influenced by the ensemble size. Generally, selecting an appropriate number of ensemble members can not only effectively improve the accuracy of hurricane prediction but can also significantly reduce the demand for computational resources relative to the 4D-Var method. This study can also serve as an advantageous technical reference for numerical applications of ozone products from other satellites and hurricane initialization.

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Section: Introductionmentioning

confidence: 99%

A Hurricane Initialization Scheme with 4DEnVAR Satellite Ozone and Bogus Data Assimilation (SOBDA) and Its Application: Case Study

Liu

2023

Atmosphere

View full text Add to dashboard Cite

show abstract

An application of the A-4DEnVar to coupled parameter optimization

Cited by 1 publication

References 35 publications

A Hurricane Initialization Scheme with 4DEnVAR Satellite Ozone and Bogus Data Assimilation (SOBDA) and Its Application: Case Study

A Hurricane Initialization Scheme with 4DEnVAR Satellite Ozone and Bogus Data Assimilation (SOBDA) and Its Application: Case Study

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