Atmospheric Boundary Layer Height Estimation from Lidar Observations: Assessment and Validation of MIPA Algorithm

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.

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Publication Details

Journal
Remote Sensing
Published
2025-08-08
DOI
https://doi.org/10.3390/rs17162748
Citations
2
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
2.21
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Atmospheric Boundary Layer Height Estimation from Lidar Observations: Assessment and Validation of MIPA Algorithm

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2 citations
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2.21
article

Atmospheric Boundary Layer Height Estimation from Lidar Observations: Assessment and Validation of MIPA Algorithm

Michail Mytilinaios, Giuseppe D’Amico, Aldo Giunta, Francesco Cardellicchio, Aldo Amodeo, Gemine Vivone, Pilar Gumà-Claramunt, Marco Rosoldi, Donato Summa, Nikolaos Papagiannopoulos, Fabrizio Marra, Teresa Laurita, Ilaria Gandolfi, Lucia Mona, Alberto Arienzo, Paolo Di Girolamo, Benedetto De Rosa
article en
2 citations

Abstract

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.

Remote SensingVol. 17(16)
University of Basilicata (IT), CNR-IMIOT – Consiglio Nazionale delle Ricerche - Istituto di Metodologie Integrate per l’Osservazione della Terra (IT), University of Palermo (IT)
Openalex Percentile: Top 12%
Atmospheric aerosols and clouds
2.21
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