The impact of hybrid oceanic data assimilation in a coupled model: A case study of a tropical cyclone

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• Tsz Yan Leung (Met Office)
• Friday 23 September 2022, 14:30-14:50
• No Room Required.

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GFDW02 - Forecast Verification and Data Assimilation in intermediate and large scale models of geophysical fluid dynamics, with applications to medium range and seasonal forecasting

Tropical cyclones tend to result in distinctive spatial and temporal characteristics in the upper ocean, which suggests that traditional, parametrisation-based background-error covariances in oceanic data assimilation (DA) may not be suitable.  Using the case study of Cyclone Titli, which affected the Bay of Bengal in October 2018, we explore hybrid methods that combine the traditional covariance modelling strategy used in variational methods with flow-dependent estimates of the ocean’s error covariance structures based on a short-range ensemble forecast.  This hybrid approach is investigated in the UK Met Office’s state-of-the-art system.  Single-observation experiments in the ocean reveal that the hybrid approach is capable of producing analysis increments that are time-varying, more anisotropic and vertically less uniform.  When the hybrid oceanic covariances are incorporated into a weakly coupled DA system, the sea-surface temperature (SST) in the path of the cyclone is changed, not only through the different specifications of background-error covariances used in the SST assimilation, but also through the propagation of subsurface temperature differences to the surface as a result of vertical mixing associated with the cyclone’s strong winds.  The coupling with the atmosphere then leads to a discrepancy in the cyclone’s central pressure, which brings forth further SST differences due to the different representations of the cyclone’s emerging cold wake. Tsz Yan Leung, Amos S. Lawless, Nancy K. Nichols, Daniel J. Lea, Matthew J. Martin

This talk is part of the Isaac Newton Institute Seminar Series series.

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