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The assessment and optimization of the MIPA (Morphological Image Processing Approach) algorithm for the retrieval of Atmospheric Boundary Layer Height (ABLH) from Aerosol High-power Lidars (AHL) data are presented. MIPA has been developed at CNR-IMAA in the framework of ACTRIS, and it was tested on several lidar datasets, showing, in general, a good agreement with the traditional ABLH retrieval techniques. The main innovative feature of MIPA with respect to other approaches consists in applying optimized morphological filters and object-oriented analysis on lidar timeseries to obtain ABLH estimates. In this study, we carried out a robust MIPA validation effort based on a dedicated measurement campaign organized at CIAO (CNR-IMAA Atmospheric Observatory) in Spring 2024, where several lidar systems were operating continuously along with a quite complete set of other atmospheric sensors and two radiosounding systems. During the campaign, several case studies were considered for MIPA validation, each characterized by an intensive radiosonde schedule to ensure the establishment of a representative ABLH reference dataset. The ABLH retrieved by MIPA was compared against the corresponding ones obtained by radiosonde data. We observed a good overall agreement under different atmospheric conditions, ranging from intense dust events penetrating the ABL to cleaner atmospheric conditions. The best agreement between MIPA and reference dataset is obtained for longer wavelengths (532 nm and 1064 nm) and during daytime conditions.
Details
; Arienzo Alberto 2
; Gemine, Vivone 2
; Amodeo Aldo 1
; Cardellicchio Francesco 1 ; Gumà-Claramunt Pilar 1
; De Rosa Benedetto 1
; Di Girolamo Paolo 3
; Gandolfi Ilaria 1
; Giunta Aldo 1
; Laurita, Teresa 1
; Marra Fabrizio 1
; Lucia, Mona 1
; Mytilinaios Michail 1
; Papagiannopoulos Nikolaos 1
; Rosoldi Marco 1 ; Summa Donato 1
1 Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l’Analisi Ambientale (CNR-IMAA), 85050 Potenza, Italy; [email protected] (G.D.); [email protected] (G.V.); [email protected] (A.A.); [email protected] (F.C.); [email protected] (P.G.-C.); [email protected] (B.D.R.); [email protected] (I.G.); [email protected] (A.G.); [email protected] (T.L.); [email protected] (F.M.); [email protected] (L.M.); [email protected] (M.M.); [email protected] (N.P.); [email protected] (M.R.); [email protected] (D.S.)
2 Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l’Analisi Ambientale (CNR-IMAA), 85050 Potenza, Italy; [email protected] (G.D.); [email protected] (G.V.); [email protected] (A.A.); [email protected] (F.C.); [email protected] (P.G.-C.); [email protected] (B.D.R.); [email protected] (I.G.); [email protected] (A.G.); [email protected] (T.L.); [email protected] (F.M.); [email protected] (L.M.); [email protected] (M.M.); [email protected] (N.P.); [email protected] (M.R.); [email protected] (D.S.), National Biodiversity Future Center (NBFC), 90133 Palermo, Italy
3 Dipartimento di Scienze della Salute, Università degli Studi della Basilicata (UNIBAS), 85100 Potenza, Italy; [email protected]