Abstract
This paper reports results from an inter-comparison effort involving different sensors/techniques used to measure the Atmospheric Boundary Layer (ABL) height. The effort took place in the framework of the first Special Observing Period of the Hydrological cycle of the Mediterranean Experiment (HyMeX-SOP1). Elastic backscatter and rotational Raman signals collected by the Raman lidar system BASIL were used to determine the ABL height and characterize its internal structure. These techniques were compared with co-located measurements from a wind profiler and radiosondes and with ECMWF-ERA5 data. In the effort we consider radiosondes launched in the proximity of the lidar site, as well as radiosondes launched from the closest radiosonde station included in the Integrated Global Radiosonde archive (IGRA). The inter-comparison effort considers data from October 2012. Results reveal a good agreement between the different approaches, with values of the correlation coefficient R2 in the range 0.52 to 0.94. Results clearly reveals that the combined application of different techniques to distinct sensors’ and model datasets allow getting accurate and cross-validated estimates of the ABL height over a variety of weather conditions. Furthermore, correlations between the ABL height and other atmospheric dynamic and thermodynamic variables as CAPE, friction velocity and relative humidity are also assessed to infer possible mutual dependences.
Highlights
The Atmospheric Boundary Layer (ABL) is lowest portion of the atmosphere, directly in contact and influence by the Earth’s surface, which reacts to the combined action of mechanical and thermal forcing factors
The results in the figure 2a reveal a quite 235 good agreement between the five different approaches/sensors/models, all of the them being capable to capture the major features associated with ABL height (ABLH) monthly variability, with the only exception of ERA5 model reanalyses which underestimate the ALBH over an extended portion of the considered period (16-31 October 2012)
A linear fit is applied to the data points, using a linear regression function through zero with the form Y = A × X, with X being again the values of the mean reference ABLH obtained from the 5 different sensors/models and Y being ABLH values from each 260 single sensor/model
Summary
The ABL is lowest portion of the atmosphere, directly in contact and influence by the Earth’s surface , which reacts to the combined action of mechanical and thermal forcing factors In this layer, as a result of turbulent air motion and vertical 25 mixing induced by shear and buoyancy forces (Stull, 1988), physical quantities such as flow velocity, temperature and moisture are characterized by rapid fluctuations. Ribc at height z can be calculated from the wind speed and the potential temperature values at z and at surface level, as originally reported in Hanna (1969) and 95 extensively described in e.g., Stull (1988) and Garratt (1994) Such gradients can be revealed in wind lidar, wind profiler, radiosonde and aircraft in- situ sensors’ profile data (Sicard et al, 2006).
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