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A Three-Step Method for Estimating the Mixing Height Using Ceilometer Data from the Helsinki Testbed

A new three-step idealized-profile method to estimate the mixing height from vertical profiles of ceilometer backscattering coefficient is developed to address the weaknesses found with such estimates that are based on the one-step idealized-profile method. This three-step idealized-profile method f...

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Bibliographic Details
Published in:Journal of applied meteorology and climatology 2012-12, Vol.51 (12), p.2172-2187
Main Authors: Eresmaa, Noora, Härkönen, Jari, Joffre, Sylvain M., Schultz, David M., Karppinen, Ari, Kukkonen, Jaakko
Format: Article
Language:English
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Summary:A new three-step idealized-profile method to estimate the mixing height from vertical profiles of ceilometer backscattering coefficient is developed to address the weaknesses found with such estimates that are based on the one-step idealized-profile method. This three-step idealized-profile method fits the backscattering coefficient profile of ceilometer measurements into an idealized scaled vertical profile of three error functions, thus having the potential to determine three aerosol layers (one for the surface layer, one for the mixing height, and one for the artificial layer caused by the weakened signal). This three-step idealized-profile method is tested with ceilometer and radiosounding data collected during the Helsinki Testbed campaign (2 January 2006–13 March 2007). Excluding cases with low aerosol concentration in the boundary layer, cases with clouds present, and cases with precipitation present, the resulting dataset consists of 97 simultaneous backscattering coefficient profiles and radiosoundings. The three-step method is compared with the one-step method and other commonly employed algorithms. A strong correlation (correlation coefficientr= 0.91) between the mixing heights as determined by the three-step method using ceilometer data and those determined from radiosoundings is an improvement over the same correlation using the one-step method (r= 0.28), as well as the other algorithms.
ISSN:1558-8424
1558-8432
DOI:10.1175/JAMC-D-12-058.1