Hindcasts of Integrated Kinetic Energy in Atlantic Tropical Cyclones: A Neural Network Prediction Scheme

Kozar, Michael E.; Misra, Vasubandhu; Powell, Mark D.

doi:10.1175/MWR-D-16-0030.1

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Hindcasts of Integrated Kinetic Energy in Atlantic Tropical Cyclones: A Neural Network Prediction Scheme

2016
By Kozar, Michael E. ; Misra, Vasubandhu ; Powell, Mark D.
Source: Monthly Weather Review, 144(12), 4591-4603.

[PDF-597.65 KB]

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Details:

Journal Title:

Monthly Weather Review
Personal Author:

Kozar, Michael E. ; Misra, Vasubandhu ; Powell, Mark D.

Kozar, Michael E. ; Misra, Vasubandhu ; Powell, Mark D. Less -
Corporate Authors:

United States. National Oceanic and Atmospheric Administration. Office of Oceanic and Atmospheric Research ; Modeling, Analysis, Predictions, and Projections Program (U.S.)

United States. National Oceanic and Atmospheric Administration. Office of Oceanic and Atmospheric Research ; Modeling, Analysis, Predictions, and Projections Program (U.S.) Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office)

OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office) Less -
Description:

A new statistical–dynamical scheme is presented for predicting integrated kinetic energy (IKE) in North Atlantic tropical cyclones from a series of environmental input parameters. Predicting IKE is desirable because the metric quantifies the energy across a storm’s entire wind field, allowing it to respond to changes in storm structure and size. As such, IKE is especially useful for quantifying risks in large, low-intensity, high-impact storms such as Sandy in 2012. The prediction scheme, named the Statistical Prediction of Integrated Kinetic Energy, version 2 (SPIKE2), builds upon a previous statistical IKE scheme, by using a series of artificial neural networks instead of more basic linear regression models. By using a more complex statistical scheme, SPIKE2 is able to distinguish nonlinear signals in the environment that could cause fluctuations in IKE. In an effort to evaluate SPIKE2’s performance in a future operational setting, the model is calibrated using archived input parameters from Global Ensemble Forecast System (GEFS) control analyses, and is run in a hindcast mode from 1990 to 2011 using archived GEFS reforecasts. The hindcast results indicate that SPIKE2 performs significantly better than both persistence and climatological benchmarks.
Keywords:

[+]

Cyclones—Tropics Hindcasts Hurricanes Neural Networks Typhoons
Source:

Monthly Weather Review, 144(12), 4591-4603.
DOI:

https://doi.org/10.1175/MWR-D-16-0030.1
Document Type:

Journal Article
Funding:

Grant no. NA12OAR4310078 ; Grant no. NA10OAR4310215 ; Grant no. NA10OAR4320143

Grant no. NA12OAR4310078 ; Grant no. NA10OAR4310215 ; Grant no. NA10OAR4320143 Less -
Place as Subject:

Atlantic Ocean
Rights Information:

Other
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:626bde29d359321aa137d477db848cb7df56ae107503ad1e216e402dd88bdcd1
Download URL:

https://repository.library.noaa.gov/view/noaa/28356/noaa_28356_DS1.pdf
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Hindcasts of Integrated Kinetic Energy in Atlantic Tropical Cyclones: A Neural Network Prediction Scheme

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