A Case Study of the Physical Processes Associated with the Atmospheric River Initial-Condition Sensitivity from an Adjoint Model

Abstract

Abstract Analysis of a strong landfalling atmospheric river is presented that compares the evolution of a control simulation with that of an adjoint-derived perturbed simulation using the Coupled Ocean–Atmosphere Mesoscale Prediction System. The initial-condition sensitivities are optimized for all state variables to maximize the accumulated precipitation within the majority of California. The water vapor transport is found to be substantially enhanced at the California coast in the perturbed simulation during the time of peak precipitation, demonstrating a strengthened role of the orographic precipitation forcing. Similarly, moisture convergence and vertical velocities derived from the transverse circulation are found to be substantially enhanced during the time of peak precipitation, also demonstrating a strengthened role of the dynamic component of the precipitation. Importantly, both components of precipitation are associated with enhanced latent heating by which (i) a stronger diabatically driven low-level potential vorticity anomaly strengthens the low-level wind (and thereby the orographic precipitation forcing), and (ii) greater moist diabatic forcing enhances the Sawyer–Eliassen transverse circulation and thereby increases ascent and dynamic precipitation. A Lagrangian parcel trajectory analysis demonstrates that a positive moisture perturbation within the atmospheric river increases the moisture transport into the warm conveyor belt offshore, which enhances latent heating in the perturbed simulation. These results suggest that the precipitation forecast in this case is particularly sensitive to the initial moisture content within the atmospheric river due to its role in enhancing both the orographic precipitation forcing and the dynamic component of precipitation.