Evaluation of Hurricane Wind Speed Analyses in a Simulation of Hurricane Earl (2010) Using Low-Order Wavenumbers

George Andrew Soukup NOAA/AOML/Hurricane Research Division, Miami, Florida

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Frank D. Marks NOAA/AOML/Hurricane Research Division, Miami, Florida

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Abstract

To determine how well a low-order wavenumber representation describes a hurricane wind speed field, given its natural variability in space and time, low-order wavenumber representations were calculated for hourly “snapshots” of the 10-m wind speed field generated by the current operational hurricane model. Two distinct periods were examined: the first when the storm is in a reasonably steady state over 7–8 h and the second where the storm is changing its internal structure over a similar time interval. Observing system sensitivity experiments were also performed using wind speed field time series obtained from interpolation of the model snapshots for each of the two periods. The time series were sampled along the flight legs of a typical “figure four” aircraft flight pattern to simulate the surface wind data collection process to ascertain the effects of the wind speed field’s temporal and spatial variability upon the low-order wavenumber analyses.

The comparison between the model wind speed field at any time and the wavenumber representations during the “steady state” period shows that the essential features of the wind speed field are captured by wavenumbers 0 and 1 and that including up to wavenumber 3 practically reproduces the model field. However, in the “nonsteady” period the wavenumber 0 and 1 representation is frequently unable to capture the essential characteristics of the wind speed field. The observing system sensitivity experiments suggest that when the primary circulation is rapidly changing in amplitude and/or structure during the data collection period, the low-order wavenumbers analysis of the wind speed field will only represent the temporal mean structure.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Frank D. Marks, frank.marks@noaa.gov

Abstract

To determine how well a low-order wavenumber representation describes a hurricane wind speed field, given its natural variability in space and time, low-order wavenumber representations were calculated for hourly “snapshots” of the 10-m wind speed field generated by the current operational hurricane model. Two distinct periods were examined: the first when the storm is in a reasonably steady state over 7–8 h and the second where the storm is changing its internal structure over a similar time interval. Observing system sensitivity experiments were also performed using wind speed field time series obtained from interpolation of the model snapshots for each of the two periods. The time series were sampled along the flight legs of a typical “figure four” aircraft flight pattern to simulate the surface wind data collection process to ascertain the effects of the wind speed field’s temporal and spatial variability upon the low-order wavenumber analyses.

The comparison between the model wind speed field at any time and the wavenumber representations during the “steady state” period shows that the essential features of the wind speed field are captured by wavenumbers 0 and 1 and that including up to wavenumber 3 practically reproduces the model field. However, in the “nonsteady” period the wavenumber 0 and 1 representation is frequently unable to capture the essential characteristics of the wind speed field. The observing system sensitivity experiments suggest that when the primary circulation is rapidly changing in amplitude and/or structure during the data collection period, the low-order wavenumbers analysis of the wind speed field will only represent the temporal mean structure.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Frank D. Marks, frank.marks@noaa.gov
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