Track Uncertainty in High-Resolution HWRF Ensemble Forecasts of Hurricane Joaquin

Alaka, Ghassan J.; Zhang, Xuejin; Gopalakrishnan, Sundararaman; Zhang, Zhan; Marks, Frank D.; Atlas, Robert

doi:10.1175/waf-d-19-0028.1

Cited by 23 publications

(7 citation statements)

References 58 publications

(72 reference statements)

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“…To address the TC-centric limitation of the operational HWRF, an experimental version of HWRF, known as the Basin-scale HWRF (HWRF-B; Table 1; X. Alaka et al 2017Alaka et al , 2019Alaka et al , 2020 12 within a large, static parent domain that includes most of the areas of responsibility of NHC and NOAA's Central Pacific Hurricane Center (CPHC) (Fig. 2).…”

Section: The Basin-scale Hwrf Modeling System and Experimental Designmentioning

confidence: 99%

High-Definition Hurricanes: Improving Forecasts with Storm-Following Nests

Alaka

Zhang

Gopalakrishnan

2022

Bulletin of the American Meteorological Society

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To forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition”, i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. However, resolutions in operational global models remain too coarse to accurately predict these structures that are critical to TC intensity. Storm-following nests are a solution to this problem because they are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Program, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC-TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multi-storm nesting approach to improve the simulation of TC-TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multi-storm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multi-storm approach demonstrated TC intensity forecast improvements, including more realistic TC-TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System.

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Section: The Basin-scale Hwrf Modeling System and Experimental Designmentioning

confidence: 99%

High-Definition Hurricanes: Improving Forecasts with Storm-Following Nests

Alaka

Zhang

Gopalakrishnan

2022

Bulletin of the American Meteorological Society

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“…Here, and for this hindcasted case, the deterministic run and mean of ensembles are quite close to each other. However, it has been proven that a welldesigned ensemble system will not only help represent the uncertainty (and spread) well but it will also give us better products (Alaka et al 2019;Zhang et al 2014) compared to deterministic simulation, especially in forecast. Although the uncertainty is small at the beginning, the errors can grow fast due to the aforementioned key roles; therefore, the simulated results will diverge from observation.…”

Section: Atmospheric Modelmentioning

confidence: 99%

Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

Abdolali

Westhuysen

et al. 2021

Ocean Dynamics

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Various uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.

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“…Some research [12,36] indicated that the forecast uncertainty of a TC track has a great influence on its intensity. After a TC makes landfall, it will often stop intensifying and even decay rapidly.…”

Section: Tc Track Sensitivitymentioning

confidence: 99%

Forecast Uncertainty of Rapid Intensification of Typhoon Dujuan (201521) Induced by Uncertainty in the Boundary Layer

Qin

Duan

2020

Atmosphere

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Using ensemble forecast experiments generated by the weather research and forecasting model, the forecast uncertainties of intensity and its rapid intensification (RI) induced by the uncertainty occurring in the boundary layer are investigated for Typhoon Dujuan (201521). The results show that the uncertainty in the boundary layer in the typhoon area, compared with that in other areas of the model domain, not only leads to a much larger forecast uncertainty of the typhoon intensity but also considerably perturbs the RI forecast uncertainty. Particularly, the uncertainty in the gale area in the boundary layer, compared with that in the inner-core and other areas, makes a much larger contribution to the forecast uncertainty of typhoon intensity, with the perturbations including moisture component being most strongly correlated with the occurrence of RI. Further analyses show that such perturbations increase the maximum tangential wind in the boundary layer and enhance the vorticity in the eyewall, which then facilitate the spin-up of the inner-core and induce the occurrence of RI. It is inferred that more observations, especially those associated with the moisture, should be preferentially assimilated in the gale area within the boundary layer of a tropical cyclone, which will help improve the forecast skill of the RI. These results also tell us that the boundary layer parameterization scheme should be further developed to improve the forecast skill of tropical cyclone intensity and its RI behavior.

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Track Uncertainty in High-Resolution HWRF Ensemble Forecasts of Hurricane Joaquin

Cited by 23 publications

References 58 publications

High-Definition Hurricanes: Improving Forecasts with Storm-Following Nests

High-Definition Hurricanes: Improving Forecasts with Storm-Following Nests

Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

Forecast Uncertainty of Rapid Intensification of Typhoon Dujuan (201521) Induced by Uncertainty in the Boundary Layer

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