E’ aperto il bando per una posizione di postdoc della durata di 2 anni presso l’Università dell’Aquila, avente come titolo “P20224AT3W – PBLHsat-Machine learning-based improvement of planetary boundary layer height from atmospheric model simulations using CALIOP satellite and ACTRIS Earlinet ground-based lidar observations”.

La domanda va presentata entro il 15 gennaio al seguente link.

Il bando è invece disponibile a questo link.

SI riporta di seguito una breve descrizione del progetto di ricerca: “In this project, we aim at improving the accuracy of estimating Planetary Boundary Layer Height (PBLH) simulated by atmospheric models using a machine learning approach. The basic underlying idea is to train different machine learning algorithms using data from CALIPSO satellite and EUMETNET ground-based lidars and ceilometers to obtain an optimal estimated of PBLH, and then test the benefit in bias correcting model simulation of PBLH on the meteorological forecast. The specific work of the candidate will include preparation of ERA5 reanalyses, high-resolution simulations with WRF mesoscale model, and testing of different methods of bias correction and physical parameterization of PBL dynamics.