Simultaneous Multiscale 4DEnVar With Scale Dependent Localization (SDL) in Hurricane Analysis and Forecast System (HAFS)

Abstract

This study presents the implementation and evaluation of scale‐dependent localization (SDL) in the hurricane analysis and forecast system 4D Ensemble Variational (4DEnVar) Data Assimilation (DA) system. The SDL capability is compared with the traditional Single‐Scale Localization (SSL) method to assess its benefits and necessity for hurricane prediction. The experiments focus on Hurricane Laura (2020) and involve single observation experiments as well as real observation DA cycling experiments. The results indicate that the SDL experiment, which incorporates the Fast Almost Gaussian Filtering approach for scale decomposition, consistently outperforms the corresponding SSL configurations in almost all aspects. Further diagnostics show that due to its multiscale nature, the SDL approach demonstrates better track prediction over small‐scale SSL due to improved environmental analysis and better analyzed vortex position and structure, and superior intensity prediction during the rapid intensification over both the large‐scale SSL and the small‐scale SSL owing to enhanced inner‐core thermodynamic analysis.