Understanding Error Distributions of Hurricane Intensity Forecasts during Rapid Intensity Changes

Trabing, Benjamin C.; Bell, Michael M.

doi:10.1175/waf-d-19-0253.1

Cited by 28 publications

(30 citation statements)

References 24 publications

(41 reference statements)

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“…The documented relationship between TC intensification and the storm environment is supported by theory and numerous modeling experiments 39 – 43 . Although internal dynamical processes of TCs are also important for RI 44 , they are challenging to quantify and predict even with high-resolution numerical weather prediction models 3 . Additionally, it is not currently possible to assess how the internal dynamical processes will change with global warming using global climate models while large-scale environmental conditions are well-observed and captured by global climate models.…”

Section: Resultsmentioning

confidence: 99%

“…Over the last five years, guidance models and National Hurricane Center (NHC) forecasts have exhibited more skill in forecasting RI in the east Pacific and North Atlantic (hereafter, Atlantic refers to the North Atlantic) basins 2 . However, the intensity forecast errors for RI events are still approximately 2–3 times larger than non-RI events, depending on forecast lead time 3 . The forecasting challenges associated with these RI events were likely exacerbated by the recent upward trend in the proportion of storms that achieved RI 4 – 10 .…”

Section: Introductionmentioning

confidence: 95%

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A potential explanation for the global increase in tropical cyclone rapid intensification

Bhatia¹,

Baker

Yang

et al. 2022

Nat Commun

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Tropical cyclone rapid intensification events often cause destructive hurricane landfalls because they are associated with the strongest storms and forecasts with the highest errors. Multi-decade observational datasets of tropical cyclone behavior have recently enabled documentation of upward trends in tropical cyclone rapid intensification in several basins. However, a robust anthropogenic signal in global intensification trends and the physical drivers of intensification trends have yet to be identified. To address these knowledge gaps, here we compare the observed trends in intensification and tropical cyclone environmental parameters to simulated natural variability in a high-resolution global climate model. In multiple basins and the global dataset, we detect a significant increase in intensification rates with a positive contribution from anthropogenic forcing. Furthermore, thermodynamic environments around tropical cyclones have become more favorable for intensification, and climate models show anthropogenic warming has significantly increased the probability of these changes.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

A potential explanation for the global increase in tropical cyclone rapid intensification

Bhatia¹,

Baker

Yang

et al. 2022

Nat Commun

View full text Add to dashboard Cite

show abstract

“…

After lagging improvements in track forecasts over the last few decades, tropical cyclone (TC) intensity change prediction has recently improved (Cangialosi et al, 2020) led by progress in numerical weather prediction and our fundamental understanding of TC processes. Rapid intensification (RI, defined by an increase in maximum-sustained wind ≥30 kt in 24 hr; Kaplan & DeMaria, 2003), however, still has comparatively poor forecasts (Cangialosi et al, 2020;Fischer et al, 2019;Trabing & Bell, 2020). More than 75% of all RI events initially have intensities of 55 kt or less (Wang & Jiang, 2021; cf., Figure 6).

…”

mentioning

confidence: 99%

How Do Weak, Misaligned Tropical Cyclones Evolve Toward Alignment? A Multi‐Case Study Using the Hurricane Analysis and Forecast System

Alvey

Hazelton

2022

JGR Atmospheres

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This study simulates five initially weak, moderately sheared tropical cyclones (TCs) from the 2020–2021 North Atlantic basin hurricane seasons using the Hurricane Analysis and Forecast System (HAFS). Four of the five simulations rapidly evolve from misaligned vortices with asymmetric precipitation and thermodynamic distributions toward more aligned and symmetric configurations. The displaced low‐level (LLC) and mid‐level circulations (MLC) non‐monotonically progress toward alignment with periods of reformation, precession, and advection. Beginning 12–18 hr pre‐alignment, TCs have increasingly greater mid‐tropospheric humidity and areal coverages of precipitation downshear left than the simulation that fails to align. Alignment precedes the most sustained symmetrization of favorable thermodynamics and precipitation, but deep convection (not necessarily symmetric) plays a critical role in alignment. Ida (2021), a high impact US storm, undergoes a vortex‐scale evolution where an increase in areal coverage and intensity of deep convection promotes a reformation of the vortex into a smaller compact core with a closed MLC (a closed LLC does not immediately form). This convective behavior downtilt helps to reshape the irrotational velocity field in the lower troposphere toward the reformed vortex. The increasingly convergent flow of favorable boundary layer thermodynamics within the inflow region thereby increases the instability, which maintains the persistent intense convection. The confluent flow ultimately promotes an advection of the pre‐existing LLC toward the reformed vortex resulting in alignment. Tilt reductions are also shown to be temporally linked with the diurnal cycle, wherein convection preferentially increases near the center during the early morning hours (local time).

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“…While the forecasting toward hurricane track and intensity improves greatly in previous years, evidences still show comparability large yearly mean absolute errors due to the complexity of air-sea interactions and thermodynamic process [27], especially the long-term forecasting of hurricane intensity [28]. Therefore, this DIU should be incorporated to maintain the robustness of the SWDD-ASs.…”

Section: Decision-dependent Intensity-related Intervalmentioning

confidence: 99%

A Distributionally Robust Resilience Enhancement Strategy for Distribution Grids Considering Decision-Dependent Contingencies

Li¹,

Lei²,

Sun³

et al. 2022

Preprint

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When performing resilience enhancement for distribution grids, suboptimal strategies induced by misspecified contingency models may lead to unanticipated regrets in retrospective analyses.However, there are two obstacles for reliably modeling uncertain contingencies: 1) decision-dependent uncertainty (DDU) resulting from different line hardening decisions, and 2) distributional ambiguity due to limited outage information under extreme weather events (EWEs). To address these two challenges, this paper constructs scenario-wise decision-dependent ambiguity sets (SWDD-ASs), where the DDU and distributional ambiguity inherent in EWE-induced contingencies are simultaneously captured under each possible EWE scenario. Then, a two-stage trilevel decisiondependent distributionally robust resilient enhancement (DD-DRRE) model is formulated, whose outputs include the optimal line hardening, distributed generation (DG) allocation, and proactive network reconfiguration strategy under the worst-case distributions in SWDD-ASs. Then, the DD-DRRE model are equivalently recast to a MILP-based master problem and multiple scenario-wise subproblems, facilitating the utilization of a customized column-and-constraint generation (C&CG) algorithm. Finally, numerical tests demonstrate a remarkable improvement in the out-of-sample performance of our model, compared to its prevailing stochastic and robust counterparts. Moreover, the potential values of incorporating the ambiguity and distributional information are quantitatively estimated, which can serve as a useful reference for planners with different budgets and risk-aversion levels.

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Understanding Error Distributions of Hurricane Intensity Forecasts during Rapid Intensity Changes

Cited by 28 publications

References 24 publications

A potential explanation for the global increase in tropical cyclone rapid intensification

A potential explanation for the global increase in tropical cyclone rapid intensification

How Do Weak, Misaligned Tropical Cyclones Evolve Toward Alignment? A Multi‐Case Study Using the Hurricane Analysis and Forecast System

A Distributionally Robust Resilience Enhancement Strategy for Distribution Grids Considering Decision-Dependent Contingencies

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