Nonlinear forecast error growth of rapidly intensifying hurricane harvey (2017) examined through convection-permitting ensemble assimilation of GOES-16 all-sky radiances

The dynamics and predictability of the rapid intensification (RI) of Hurricane Harvey (2017) were examined using convection-permitting initialization, analysis, and prediction from a cycling ensemble Kalman filter (EnKF) that assimilated all-sky infrared radiances from the Advanced Baseline Imager on GOES-16. The EnKF analyses were able to evolve the various scales of the radiance fields associated with Harvey close to those observed, including those associated with scattered individual convective cells before the onset of rapid intensification (RI) and the organized vortex-scale convective system during and after RI. This was true for more than 3 days of a continuous assimilation cycling. Deterministic forecasts initialized from the EnKF analyses captured the rapidly deepening intensity of Harvey more than 24 h prior to its onset. To explore the predictability of Harvey's intensity during RI, ensemble probabilistic forecasts and sensitivity analyses were conducted. It was found that significant ensemble spread growth was induced by initial perturbations individually in either the wind or moisture fields. The nonlinear interactions between wind and moisture perturbations further limited the predictability of the intensification process of Harvey by increasing the uncertainty in the simulated wind and moisture distributions and modifying the convective activity and its feedback on vortex flow. This study highlights both the importance of better initializing the dynamic and moisture state variables simultaneously and the potential contribution of satellite all-sky radiance assimilation on constraining them and their associated convective activity that impacts RI of tropical cyclones.

Files

Metadata

Work Title Nonlinear forecast error growth of rapidly intensifying hurricane harvey (2017) examined through convection-permitting ensemble assimilation of GOES-16 all-sky radiances
Access
Open Access
Creators
  1. Masashi Minamide
  2. Fuqing Zhang
  3. Eugene E. Clothiaux
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Journals of the Atmospheric Sciences
Publication Date December 1, 2020
Publisher Identifier (DOI)
  1. https://doi.org/10.1175/JAS-D-19-0279.1
Deposited July 26, 2021

Versions

Analytics

Collections

This resource is currently not in any collection.

Work History

Version 1
published

  • Created
  • Added Minamideetal.2020.JAS.NonlinearErrorGrowth.pdf
  • Added Creator Masashi Minamide
  • Added Creator Fuqing Zhang
  • Added Creator Eugene E. Clothiaux
  • Published
  • Updated
  • Updated
  • Updated