Climatology of the Boundary Layer Height and of the Wind Field over Greece

Abstract

In this study, a climatology of two key boundary layer features, the Planetary Boundary Layer Height (PBLH) and the wind field over Greece is derived. The climatology is based on daily soundings collected in Athens, Thessaloniki and Heraklion and spanning a 32-year period. The PBLH is estimated using a method based on the gradient of potential temperature and a method based on the bulk Richardson number. The wind field is analyzed by calculating the wind shear and the turning angle of the wind vector between the surface and the top of the boundary layer. The PBLH of the daytime boundary layer over Athens and Thessaloniki is found to exhibit seasonal variability with summer maxima and winter minima and has annual median values in the range of 1.4–1.7 km estimated using the gradient method. The PBLH over Heraklion is found to exhibit weak seasonal variability with a lower median value of 1.2 km. The nighttime boundary layer over all three sites is found to be much shallower with PBLH values in the range of 150–200 m with no seasonal variations. In addition, the bulk Richardson number method is found to systematically underestimate the PBLH compared to the gradient method. The wind field in the daytime boundary layer at all three sites is found to have small shear of the order of 1 ms−1 and wind turning angles that are lower than 15 degrees, while in the nocturnal boundary layer it has larger shear of the order of 5–10 ms−1 with turning angles lower than 20 degrees. In addition, for both the daytime and the nighttime boundary layer there is no general preference for veering or backing.

Climatology of Planetary Boundary Layer Height over Jiangsu, China, Based on ERA5 Reanalysis Data

“…There are many methods to diagnose the PBLH, and the commonly used methods include the potential temperature gradient method [2,35], parcel method [36,37], relative humidity gradient method [21], specific humidity gradient method [21], refractive index gradient method [35,38], and Richardson number method [20,31]. Seidel et al [9,20] compared and evaluated different diagnostic methods and confirmed that the Richardson number method is more suitable for the diagnosis of the PBLH in large-volume datasets, and this method is suitable for both the stable boundary layer (SBL) and convective boundary layer (CBL).…”

“…The Earth's surface exchanges heat, momentum, water vapor, and chemicals with the free atmosphere through the PBL. Since the PBL involves many processes, such as convective activity, turbulent mixing, low-layer cloud formation, pollutant diffusion, and surface energy budget, the PBL plays a key role in many aspects, such as weather, climate, and air pollution [2]. The planetary boundary layer height (PBLH) is an important parameter for characterizing the structural characteristics of the PBL.…”

Thermodynamic and cloud evolution in a cold-air outbreak during HALO-(AC)3: quasi-Lagrangian observations compared to the ERA5 and CARRA reanalyses

“…The profiles of θ are used to derive the atmospheric BLH from dropsonde measurements and reanalyses. The BLH is defined here as the altitude where the largest vertical gradient in θ is found (similar to Seidel et al, 2010;Dai et al, 2014;Bakas et al, 2020;Sinclair et al, 2022). For estimating the cloud top heights (CTHs), the 532 nm backscatter ratio from the water vapor differential absorption (WALES) lidar is used (Wirth et al, 2009).…”

“…The transfer coefficients of heat and humidity are directly calculated using the most recent COARE 3.5 bulk air-sea algorithm (Edson et al, 2013;Bariteau et al, 2021). At winds speeds up to 20 m s −1 , COARE has a reported uncertainty of around 10 % (Fairall et al, 2003;Edson et al, 2013).…”

“…VELOX-derived skin temperature measurements can be obtained from https://doi.org/10.1594/PANGAEA.963401(Schäfer et al, 2023). A Python implementation of the COARE 3.5 bulk air-sea flux algorithm is available from https://doi.org/10.5281/zenodo.5110991(Bariteau et al, 2021). For CARRA, data are available on model levels (https://doi.org/10.24381/cds.d29ad2c6,Schyberg et al, 2020a), pressure levels (https://doi.org/10.24381/cds.e3c841ad,…”