8.6 Environmental Predictors Related to the Subseasonal Prediction of West Pacific Tropical Cyclone Activity

Tuesday, 30 January 2024: 5:45 PM
342 (The Baltimore Convention Center)
Kurt A. Hansen, NRL, Monterey, CA; NRL, Monterey, CA; and M. Janiga, S. Rushley, and C. A. Reynolds

Subseasonal prediction of tropical cyclones (TCs) has many potential applications in energy, emergency response, and defense sectors; however, subseasonal TC prediction remains a challenge due to biases in both large-scale conditions and TCs in coupled global models. Subseasonal forecasts of large-scale environmental conditions, such as vertical wind shear, are generally more skillful than forecasts of smaller scale phenomenon, such as TCs themselves. Thus, model forecasts of environmental parameters can be linked to TC activity and then be used to extend the horizon of useful skill through statistical-dynamical models. The aim of this work is to assess the utility of incorporating model forecasted environmental fields in a statistical model compared to skill coming from model forecasted MJO state and TC activity.

In this study we evaluate The European Centre for Medium-Range Weather Forecasts (ECMWF) model from the Subseasonal-to-Seasonal (S2S) database and the Navy Earth System Prediction Capability (ESPC) as part of the Subseasonal Experiment (SubX) on their ability to predict West Pacific TC activity using environmental fields (e.g., shear, humidity, low-level vorticity, upper-level velocity potential). To isolate the environmental signals associated with subseasonal variability of TC activity we examine events of anomalous accumulated cyclone energy (ACE) and TC days relative to each season. These events are used to create composites in ERA5 reanalysis fields of the environmental conditions related to West Pacific TC activity. These composites are used to select predictors to be fed into a statistical dynamical hybrid model. ECMWF and Navy-ESPC forecasts of these environmental predictors are combined and compared to model predictions of TC activity and MJO state to assess if an improvement in skill can be accomplished by considering these model forecasted environmental fields.

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