3.4 Multi-scale Tropical-Extratropical Interactions Illuminated through Adjoint Studies

Thursday, 26 January 2017: 2:15 PM
2AB (Washington State Convention Center )
Carolyn A. Reynolds, NRL, Monterey, CA; and J. D. Doyle and C. M. Amerault

Adjoint-based tools can provide valuable insight how distinct atmospheric phenomena on various space and time scales, often separated by substantial distances, may evolve to interact and influence and each other.  An adjoint model can be used for the efficient and rigorous computation of forecast sensitivity to changes in the initial state, and for the calculation of leading singular vectors, which are the fastest growing perturbations to a forecast trajectory.  We apply adjoint-based tools from the non-hydrostatic Coupled Atmosphere/Ocean Mesoscale Prediction System (COAMPS) and the Navy Operational Global Atmospheric Prediction System (NOGAPS) to explore interactions between the tropics/subtropics and mid-latitudes that influence the predictability of both tropical and mid-latitude cyclones. The adjoint-based calculations illustrate complex influences on cyclone evolution from phenomenon that are often quite remote, and integration of the adjoint-based perturbation can illustrate rapid downstream energy propagation from the perturbed cyclone itself.

Several examples of tropical-extratropical interactions are presented. Tropical cyclones that are recurving into the mid-latitudes often show sensitivity to mid-latitude troughs several thousand kilometers upstream over a 48-h period, but may also exhibit sensitivity to downstream ridges.  Subsequent evolution of these perturbations exhibits rapid downstream energy growth and propagation, crossing the North Pacific basin in 72 hours. We also explore how the development of mid-latitude cyclones may be very sensitive to the subtropical environment, particularly subtropical moisture. A year-long climatology of daily sensitivity calculations for the region over Japan illustrate how remote influences evolve with the changing season and exhibit high spatial variabiliy. Implications of these findings for the predictability of cyclones will be discussed.

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