Publication Date:
2022-05-25
Description:
This paper is not subject to U.S. copyright. The definitive version was published in Journal of Geophysical Research: Oceans 122 (2017): 3505–3518, doi:10.1002/2017JC012727.
Description:
A 3-D variational ocean data assimilation adjoint approach is used to examine the impact of ocean observations on coupled tropical cyclone (TC) model forecast error for three recent hurricanes: Isaac (2012), Hilda (2015), and Matthew (2016). In addition, this methodology is applied to develop an innovative ocean observation targeting tool validated using TC model simulations that assimilate ocean temperature observed by Airborne eXpendable Bathy Thermographs and Air-Launched Autonomous Micro-Observer floats. Comparison between the simulated targeted and real observation data assimilation impacts reveals a positive maximum mean linear correlation of 0.53 at 400–500 m, which implies some skill in the targeting application. Targeted ocean observation regions from these three hurricanes, however, show that the largest positive impacts in reducing the TC model forecast errors are sensitive to the initial prestorm ocean conditions such as the location and magnitude of preexisting ocean eddies, storm-induced ocean cold wake, and model track errors.
Description:
ONR Grant Numbers: N0001416WX01949, N0001416WX01384, N0001416WX01262;
NOAA Grant Number: NA13OAR4830233
Keywords:
Tropical cyclone
;
Ocean data assimilation
;
Ocean sampling
;
Air-sea interaction
Repository Name:
Woods Hole Open Access Server
Type:
Article
Permalink
