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The Impact of Incremental Analysis Update on Regional Simulations for Typhoons

The analyses produced by intermittent data assimilation methods can be dynamically inconsistent and unbalanced. By gradually distributing the analysis increment along model integration, the incremental analysis update (IAU) is effective to combat the inconsistences and imbalances. Different implementations of IAU with time constant or time‐varying increments using different increment frequencies are systematically evaluated for regional simulations, especially for fast‐moving typhoons. Results show that experiments with IAU generally produce smaller forecast errors of temperature, specific humidity, and wind speed than experiment CTRL without initialization. Three‐dimensional IAUs (3DIAUs) with time‐constant increments have smaller errors than four‐dimensional IAUs (4DIAUs) with time‐varying increments interpolated from 3‐hr and hourly increments. Thus, for regional simulations, 3DIAU that imposes stronger filtering has advantages over 4DIAUs with different increment frequencies. For two typhoon cases, experiments with IAU obtain better intensity and structure of vortex than experiment CTRL; thus, the application of IAU can better retain the observation information and build the improved TC structure. But due to the displacement errors in priors and posteriors, the advantage of 4DIAU that considers the propagation of increment is limited compared to 3DIAU. As a trade‐off between the filtering and time‐varying increment, 4DIAU with 3‐hr increment that considers time‐varying increments compared to 3DIAU but imposes stronger filtering than 4DIAU with hourly increment could be preferred for TCs.