1998
DOI: 10.1175/1520-0450(1998)037<0982:loosba>2.0.co;2
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Lidar Observations of Sea-Breeze and Land-Breeze Aerosol Structure on the Black Sea

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Cited by 18 publications
(12 citation statements)
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“…The variation in the wind direction in Ahtopol: between 9:00 LT and 11:00 LT changed from WS to NE. This change was due to the breeze (Kolev et al 1998), after 12:30 LT the wind direction was SE.…”
Section: Ahtopol and Nao (Rozhen Peak) Regionsmentioning
confidence: 99%
“…The variation in the wind direction in Ahtopol: between 9:00 LT and 11:00 LT changed from WS to NE. This change was due to the breeze (Kolev et al 1998), after 12:30 LT the wind direction was SE.…”
Section: Ahtopol and Nao (Rozhen Peak) Regionsmentioning
confidence: 99%
“…Measurements of the sea breeze using ground-based lidar include the work of Nakane and Sasano (1986), documenting the shape and turbulent structure of the sea-breeze front on the Kanto Plain of Japan (ϳ60 km NE of Tokyo) using an aerosol lidar. Kolev et al (1998) deployed a groundbased aerosol lidar on the shore of the Black Sea, paired with pilot balloon measurements, capturing the transition from offshore to onshore flow. Other studies used ground-based lidar to assess the influence of the sea breeze on the properties of aerosols in coastal regions, including that of Kolev et al (2000), Murayama et al (1999), and Vijayakumar et al (1998).…”
Section: Sea-breeze Observations a Previous Observationsmentioning
confidence: 99%
“…It should be noted that using (6) we can define a large scale correlation time t. From the condition A(a, r) 0, for T > t we derive that the expression for the large correlation time within the considered model is given by: tc = (a -1)k;' (8) The practical importance of approximate self-affinity rest on: (i) it is this symmetry, that seems to be encountered in the nature rather than the exact self-affinity; (ii) unlike the exact self-affinity, using the approximate one allows to obtain finite statistical quantities and on this basis to construct pertinent models of various natural phenomena and structures. In the next section we employ one such model, namely for the autocovariance function, introduced l)y equation (3), to characterize the lidar data.…”
Section: Approximate Self-affinitymentioning
confidence: 99%