Understanding the mechanisms driving the development of the Planetary Boundary Layer (PBL) and the Subtropical Subsidence Inversion (SSI) over Qatar is essential for accurate prediction of surface meteorology and air quality. Using the vertical backscatter profile of the atmosphere from a ceilometer located at Qatar Foundation, coupled with a novel Layer Identification Algorithm (LIA) developed by scientists at QEERI, a continuous time series of the PBL and SSI has been constructed. LIA was developed in response to limitations in the original software from the ceilometer, that was only able to analyze data up to 4 km altitude, but radiosonde observations indicated the existence of the SSI at higher altitudes (between 4.5 and 8 km above sea level). LIA has been validated against in-situ measurements through spatial and temporal coincident radiosonde launches by QEERI (more than two years of weekly measurements). The LIA algorithm uses image recognition methods to identify boundary layers not only by their vertical characteristics; but also by their temporal and spatial signatures. The algorithm was written in Python and is designed to process the ceilometer's output data in real time or as a post-processing step. A short conceptual description of the algorithm's structure will be included in the methodology.

During the winter months the mean PBL depth in Doha was found to be higher compared to the summer months; in addition, the diurnal amplitude was higher during winter. Apart from seasonal variations in the PBL depth behavior, short term ?uctuations in the daily signature of the PBL structure were observed; with some days exhibiting a well-developed PBL followed by a day with no significant PBL variation. This behavior of the summer PBL (lower daily mean depth and lower diurnal amplitude relative to winter) is explained by two factors. An increase in the intensity of the sea breeze circulation; coupled with intense temperatures and humidity, the latter increases the energy ?ux towards latent heat. As a consequence, the development of the PBL is diminished during the summer. On the other hand, It was observed that the SSI is strongest during the summer months. The strength was established quantitatively via temperature inversion from the weekly radiosondes and qualitatively by continuity via LIA output. In addition to seasonal variations, the SSI exhibits short term fluctuations; in some occasions with height variations on the order of 2 km in three days. The details of the mechanism driving the SSI behavior are been studied using global circulation meteorological models.

The behavior of the PBL can exacerbate poor air quality events. This can be even worse in the case of Qatar; since during the months of higher photochemical activity (because of increased surface insolation, temperature and humidity) the PBL depth tends to be lower, therefore increasing the concentration of emitted pollutants (either anthropogenic or biogenic). Therefore, understanding the PBL and SSI seasonal and diurnal behavior is critical for predicting surface atmospheric conditions, as well as occurrences of poor air quality. This knowledge will help define possible mitigation strategies and inform urban planning and sustainable development.


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