A comparison of ASOS near-surface winds and WSR-88D-derived wind speed profiles measured in landfalling tropical cyclones

Richard J. Krupar, John L. Schroeder, Douglas A. Smith, Song Lak Kang, Sylvie Lorsolo

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

A set of velocity-azimuth display (VAD) wind speed profiles derived from coastal Weather Surveillance Radar-1988 Doppler (WSR-88D) systems was paired with Automated Surface Observing System (ASOS) 10-m standardized mean and nonstandardized gust wind speeds measured within 10 km of nearby WSR-88Ds. The goal was to formulate an appropriate methodology and empirical relationships to estimate overland near-surface wind conditions in landfalling tropical cyclones (TCs) using VAD tropical cyclone boundary layer (TCBL) lower-tropospheric wind measurements. A total of 17 TCs and seven ASOS/WSR-88D sites were used to construct a unique comparative dataset. Four estimation methods including the log and power laws, mean and gust wind speed ratio (WSR) methods, and curve fitting with linear regression and polynomial fits were evaluated. Results from the evaluation show that WSR-88D site-specific linear regression equations using a VAD 0-200-m layer average wind speed and nonzero intercepts provided the most accurate predictions of the ASOS 10-m standardized mean wind speed. Results also show that a non-site-specific linear regression model using a VAD 0-500-m mean boundary layer (MBL) wind speed and nonzero intercept is 1.07% more accurate than using a single-gust WSR to predict ASOS 10-m nonstandardized gust wind speeds. Only 2.15% of the ASOS 10-m nonstandardized maximum 3-s gust wind speeds were found to exceed the VAD 0-500-m MBL wind speed, indicating that the VAD 0-500-m MBL wind speed represents a viable source of momentum available for transport to the surface in the form of a gust.

Original languageEnglish
Pages (from-to)1343-1361
Number of pages19
JournalWeather and Forecasting
Volume31
Issue number4
DOIs
StatePublished - Aug 1 2016

Keywords

  • Atm/ocean structure/ phenomena
  • Mathematical and statistical techniques
  • Observational techniques and algorithms
  • Radars/radar observations
  • Regression analysis
  • Statistical techniques
  • Surface observations
  • Tropical cyclones

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