Mixing layer height (MLH) is a crucial parameter for air quality modelling that is still not routinely measured. Common methods for MLH determination use atmospheric profiles recorded by radiosonde but this process suffers from coarse temporal resolution since the balloon is usually launched only twice a day. Recently, cheap ceilometers are gaining popularity in the retrieval of MLH diurnal evolution based on aerosol profiles. This study presents a comparison between proprietary (Jenoptik) and freely available (STRAT) algorithms to retrieve MLH diurnal cycle over an urban area. The comparison was conducted in the summer season when MLH is above the full overlapping height of the ceilometer in order to minimize negative impact of the biaxial LiDAR’s drawback. Moreover, fogs or very low clouds which can deteriorate the ceilometer retrieval accuracy are very unlikely to be present in summer. The MLHs determined from the ceilometer were verified against those measured from the radiosonde, which were estimated using the parcel, lapse rate, and Richardson methods (the Richardson method was used as a reference in this study). We found that the STRAT and Jenoptik methods gave lower MLH values than radiosonde with an underestimation of about 150 m and 650 m, respectively. Additionally, STRAT showed some potential in tracking the MLH diurnal evolution, especially during the day. A daily MLH maximum of about 2000 m was found in the late afternoon (18–19 LT). The Jenoptik algorithm showed comparable results to the STRAT algorithm during the night (although both methods sometimes misleadingly reported residual or advected layers as the mixing layer (ML)). During the morning transition the Jenoptik algorithm outperformed STRAT, which suffers from abrupt changes in MLH due to integrated layer attribution. However, daytime performance of Jenoptik was worse, especially in the afternoon when the algorithm often cannot estimate any MLH (in the period 13–16 LT the method reports MLHs in only 15–30% of all cases). This makes day-to-day tracing of MLH diurnal evolution virtually impracticable. This problem is possibly due to its early version (JO-CloVis 8.80, 2009) and issues with real-time processing of a single profile combined with the low signal-to-noise ratio of the ceilometer. Both LiDAR-based algorithms have trouble in the evening transition since they rely on aerosol signature which is more affected by the mixing processes in the past hours than the current turbulent mixing.
Increasing urbanization impacts the local meteorology and the quality of life for residents. Urban surface characteristics and anthropogenic heat stress lead to urban heat island effects, changes in local circulations, precipitation alteration, and amendment of the local fluxes. These modifications have a direct effect on the life and health of residents. In this study, we assessed the impact of urbanization in Sofia (Bulgaria) using the Weather Research and Forecasting (WRF) model at 500 m resolution for the summer period of 2016. We utilized the CORINE (coordination of information on the environment) 2012 land cover database to represent the urban areas in four detailed land cover types, i.e., high-intensity residential areas, low-intensity residential areas, medium/industrial areas, and developed open spaces. We performed two experiments; in the first, we substituted an urban area with the most representative rural land cover to delineate the current impact of urbanization, while in the second, we replaced the existing built-up area (all four categories) with a hypothetical scenario of high-density residential land cover showing aggressive urban development. These experiments addressed the impact of land use changes as well as the extreme effects of ongoing high-density construction on the local meteorological conditions. The results showed that urban temperatures can increase by 5 °C and that moisture can decrease by 2 g/kg in the central part of Sofia in comparison to surrounding rural areas. The results also showed that building higher and dense urban areas can significantly increase heat flux and add additional stress to the environment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.