Wind Direction Bias in Generating Wind Roses and Conducting Sector-Based Air-Dispersion Modeling
Certain widely used wind rose programs and air dispersion models use an overly-simple data-transfer algorithm that induces a directional bias in their output products. The purpose of this paper is to provide a revised algorithm that corrects the aliasing bias that occurs when the internals in reported wind direction data are on the same order of magnitude, but not equal to the intervals used in the wind direction summaries. The directional bias issue arises when output products in 22.5-degree sectors are produced from 10-degree wind direction data, which affects the results of simulations of air and surface concentrations using widely applied air-dispersion models. Datasets or models with the bias discussed here give consistent positive biases (approximately 30%) for cardinal direction sectors (north, south, east, and west) and consistent negative biases for all the other sectors (approximately -10%). Data summary and air dispersion programs providing outputs in directions sectors that do not match the observational sectors need to be checked for this bias. A revised data-transfer algorithm is provided that corrects the aliasing bias that can occur in transferring wind direction data between different sectors widths.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 943391
- Report Number(s):
- PNNL-SA-54826; JAWAEB; TRN: US200902%%25
- Journal Information:
- Journal of the Air and Waste Management Association, 58(7):913-918, Vol. 58, Issue 7; ISSN 1047-3289
- Country of Publication:
- United States
- Language:
- English
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