Identification

Title

Predictability of tropical cyclone intensity: scale-dependent forecast error growth in high-resolution stochastic kinetic-energy backscatter ensembles

Abstract

A systematic study of the intrinsic predictability of tropical cyclone (TC) intensity is conducted using a set of cloud-resolving model ensembles of Hurricane Earl (2010). The ensembles are perturbed with a stochastic kinetic-energy backscatter scheme (SKEBS) and started from identical initial conditions. Scale-dependent error growth is investigated by imposing stochastic perturbations with various spatial scales on the TC and its environment. Predictability limits (upper bound) are determined by computing the error magnitude associated with each component of the Fourier-decomposed TC wind fields at forecast times up to 7 days. Three SKEBS ensembles with different perturbation scales are used to investigate the effects of small-scale, mesoscale and large-scale uncertainties on the predictability of TC intensity. In addition, the influence of the environmental flow is investigated by perturbing the lateral boundary conditions. It is found that forecast errors grow rapidly on small scales (azimuthal wave numbers > 20), which saturate within 6-12 h in all four ensembles, regardless of perturbation scale. Errors grow relatively slower on scales corresponding to rain bands (wave numbers 2-5), limiting the predictability of these features to 1-5 days. Earl's mean vortex and the wave number-1 asymmetry are comparatively resistant to error growth and remain predictable for at least 7 days. Forecast uncertainty of the mean vortex and wave number-1 asymmetry is greater in the large-scale perturbation and perturbed lateral boundary condition ensembles. The results from this case indicate that the predictability of the mean vortex and wave number-1 asymmetry is predominately associated with the predictability of the large-scale environment, which is generally much longer than that of convective-scale processes within the TC.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.org/ark:/85065/d7t72jzx

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Copyright 2016 Royal Meteorological Society.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata date

2025-07-11T20:52:19.858321

Metadata language

eng; USA