Investigating the MJO-TC connection and its role in subseasonal US precipitation prediction

Tropical cyclones (TCs) are a major source of extreme precipitation in tropical and subtropical regions. Accurate TC forecasts are key to predicting precipitation at the subseasonal time scale in the CONUS as landfalling TCs often bring extreme rain, especially to the coastal regions. Given the potentially catastrophic societal impacts of torrential TC precipitation and their potentially negative influence on a model’s subseasonal precipitation prediction skill, if not simulated correctly, there is a clear need to evaluate subseasonal TC prediction and understand its skill in models.
We propose a project focused on the subseasonal prediction of TCs and their associated precipitation in the CONUS in the Unified Forecast System (UFS) and other models. We aim to identify and understand model biases and systematic errors in the representation of the Madden-Julian Oscillation (MJO)-TC relationship, a key source of predictability for subseasonal TC prediction. Under the proposed research, we will first conduct performance-based analyses to objectively evaluate the performance of UFS and other models at predicting the MJO and its circulation anomalies during boreal summer, as well as the modulation of TC precursor disturbances and TC activity at subseasonal timescales in the Northeast Pacific and North Atlantic basins. We will then perform process-based analyses targeting the dynamics and thermodynamics of precursor disturbances and their conversion into TCs (i.e., tropical cyclogenesis) and precipitation associated with TCs and TC remnants in the CONUS coastal and inland regions, which will provide insights into the origins of precipitation forecast error. This will include a diagnosis of errors in the subseasonal modulation of TC precursors and TCs, even if a model is able to produce good MJO predictions.