Study of the atmospheric boundary layer evening transitions using two different datasets: An observational and numerical approach

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Wednesday, 11 June 2014: 5:00 PM
John Charles Suite (Queens Hotel)
Mariano Sastre, University Complutense of Madrid (UCM), Madrid, Spain; and C. Yagüe, C. Román-Cascón, and G. Maqueda

In this work it is studied the temporal evolution of the Atmospheric Boundary Layer (ABL) along the transition period from a diurnal typical convection to a nocturnal more frequently stable situation, so called late afternoon or evening transition. In order to obtain a proper characterization, we try to learn whether or not the behaviour of these transitional boundary layers is strongly dependent on local conditions. For this reason, two sets of evening transitions are studied from data collected at two different experimental sites. These locations correspond to research facilities named CIBA (Spain) and CRA (France), which are the places where atmospheric field campaigns have been conducted during the last years, such as CIBA2008 and BLLAST 2011, respectively. A statistical analysis has been carried out for both locations, and it will be shown the average behaviour as well as extreme values according to the timing, considering sunset as a reference. A similar pattern in the qualitative evolution of many variables is found. Nevertheless, several relevant differences in the progress of key variables are obtained too. Some case studies are explored, focusing on the role played by the atmospheric turbulence. Complementary, numerical experiments are also performed using the Weather Research and Forecast (WRF) mesoscale model. Special attention has been paid to the discrepancies previously noticed between the two sites from the experimental data global picture. It is checked if these discrepancies are also found in the model simulations. Moisture, both from the soil and the air, is thought to have great relevance in order to explain many of the differences found in the model simulations as well as in the observed data.