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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.

Aerosols play an important role in global meteorology and climate, as well as in air transport and human health, but there are still many unknowns on their effects and importance, in particular for the coarser (giant and ultragiant) aerosol particles. In this study, we aim to exploit the synergy between Raman lidar and Ka-band cloud radar to enlarge the size range in which aerosols can be observed and characterized. To this end, we developed an inversion technique that retrieves the aerosol microphysical properties based on cloud radar reflectivity and linear depolarization ratio. We applied this technique to a 6-year-long dataset, which was created using a recently developed methodology for the identification of giant aerosols in cloud radar measurements, with measurements from Potenza in Italy. Similarly, using collocated and concurrent lidar profiles, a dataset of aerosol microphysical properties using a widely used inversion technique complements the radar-retrieved dataset. Hence, we demonstrate that the combined use of lidar- and radar-derived aerosol properties enables the inclusion of particles with radii up to 12 µm, which is twice the size typically observed using atmospheric lidar alone.

Elastic backscatter lidar and ceilometer systems provide continuous observations of aerosol and cloud vertical structure, but the interpretation of conventional attenuated backscatter products is often limited by the dominance of signal amplitude, strong event-to-event variability, and the reduced visibility of subtle internal features. In this study, we present a refinement framework designed to extract additional structural information from elastic lidar measurements through multiscale local diagnostics applied directly to the native backscatter field. The methodology combines standardized residual fields, local gradients, variance-based metrics, space–time decorrelation scales and structure functions to highlight atmospheric boundaries, internal layering, mixing zones, and coherent structures that are not always evident in conventional representations. The approach is evaluated through three contrasting atmospheric case studies observed in 2024. Two spring events are associated with mineral dust intrusions characterized by different vertical coupling with the planetary boundary layer, while a summer case represents a non-dust regime dominated by diurnal boundary-layer evolution. The refined diagnostics consistently reveal features hidden or only weakly visible in the raw backscatter field, including sharp interfaces, embedded stratification, wave-like perturbations and transitions between decoupled and mixed atmospheric states. Results show that the proposed metrics enable a more objective description of aerosol-layer dynamics and boundary–layer interactions without requiring complex inversion procedures or auxiliary measurements. Because the method relies only on standard elastic lidar observations, it is in principle applicable to ceilometer and lidar monitoring networks. However, the present evaluation is based on three contrasting case studies and should therefore be regarded as a proof-of-concept demonstration. The framework offers a candidate pathway for enhanced atmospheric feature detection and improved interpretation of routine profiling observations, with automated regime classification as a longer-term goal requiring validation on larger and more diverse datasets.

This study presents an intercomparison of planetary boundary layer height (PBLH) estimates derived from three distinct approaches: the Morphological Image Processing Approach (MIPA) algorithm applied to ground-based lidar measurements, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) and Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis model outputs, and radiosonde (RS) observations, this latter being taken as reference. The intercomparison was conducted during three measurement episodes, encompassing a total of 153 h (6 days), as part of the Boundary Layer Extensive Campaign with muLti-instrumentaL Analysis (BELLA), carried out in spring and early summer 2024 at the CNR-IMAA Atmospheric Observatory (CIAO) in southern Italy (40.60N, 15.72E). The study provides insights into the performance and reliability of these PBLH estimation approaches under diverse atmospheric scenarios. Visual and statistical analyses of selected case studies indicate that MIPA often tracked the aerosol layering structure and diurnal PBLH evolution more closely than ERA5 and MERRA-2, particularly during convective growth and evening transitions. On the other hand, it is found that ERA5 provides more accurate estimates of the nighttime PBLH, where MIPA shows poor nighttime estimation capabilities. Quantitative comparison against radiosonde data reveals that MIPA reaches a weighted root mean square error (RMSEw) of 380±41 m with a coefficient of determination (R2) of 0.68±0.16, while ERA5 shows an RMSEw of 292±72 m and an R2 of 0.81±0.11; and MERRA-2 shows an RMSEw of 631±124 m and an R2 of 0.34±0.21. By combining MIPA daytime and ERA5 nighttime PBLH, the overall results are improved, obtaining an R2=0.86±0.08 and an RMSEw of 213±40 m. This intercomparison highlights the strengths and limitations of each method and demonstrates the benefits of combining complementary PBLH retrieval techniques. The findings contribute to refining boundary layer monitoring methodologies and provide guidance for operational atmospheric observation networks.

In this study, we present an innovative methodology for the identification of giant aerosols using cloud radar. The methodology makes use of several insects studies in order to separate radar-derived atmospheric plankton signatures into the contributions of insects and giant aerosols. The methodology is then applied to a 6-year-long cloud radar dataset in Potenza, South Italy. Forty giant aerosol events per year were found, which is in good agreement with the site’s climatological record. A sensitivity study on the effects of the giant aerosols on three atmospheric variables and under different atmospheric stability conditions showed that the presence of giant aerosols (a) increased the aerosol optical depth in all the atmospheric stability conditions, (b) decreased the Ångström exponent for the highest and lowest stability conditions and had the opposite effect for the intermediate stability condition, and (c) increased the accumulated precipitation in all the atmospheric conditions, especially in the most unstable ones.

We present a multi-year study of Saharan dust intrusions on a mountainous site located in the central Mediterranean Basin regarding their aerosol optical and geometrical properties. The observations were carried out at the Consiglio Nazionale delle Ricerche-Istituto di Metodologie per l’Analisi Ambientale (CNR-IMAA) located in Potenza (40,360N, 15,440E), Italy, from March 2010 to October 2022, using ACTRIS (Aerosol Clouds and Trace Gases Research InfraStructure). A total of 101 night-time lidar measurements of dust intrusions were identified. The following properties were calculated for the periods December, January, February (DJF), March, April, May (MAM), June, July, August (JJA) and September, October, November (SON): aerosol layer center of mass altitude, particle lidar ratio at 355 and 532 nm, particle depolarization ratio at 532 nm and backscattering Ångström exponent at 532–1064 nm. Both geometrical and optical aerosol properties vary considerably with the seasons. During SON and DJF, air masses transporting dust travel at lower altitudes, and become contaminated with local continental particles. In MAM and JJA, dust is also likely to travel at higher altitudes and rarely mix with other aerosol types. As a result, aerosols are larger in size and irregular in shape during the warm months. The ratio of the lidar ratios at 355 and 532 nm is 1.11 ± 0.15 in DJF, 1.12 ± 0.07 in SON, 0.94 ± 0.12 in MAM, and 0.92 ± 0.08 in JJA. The seasonal radiative effect estimated using the Fu–Liou–Gu (FLG) radiative transfer model indicates the most significant impact during the JJA period. A negative dust radiative effect is observed both at the surface (SRF) and at the top of the atmosphere (TOA) in all the seasons, and this could be related to a minimal contribution from black carbon. Specifically, the SRF radiative effect estimation is −14.48 ± 1.32 W/m2 in DJF, −18.00 ± 0.89 W/m2 in MAM, −22.08 ± 1.36 W/m2 in JJA, and −13.47 ± 1.12 W/m2 in SON. Instead, radiative effect estimation at the TOA is −22.23 ± 2.06 W/m2 in DJF, −38.23 ± 2.16 W/m2 in MAM, −51.36 ± 3.53 W/m2 in JJA, and −22.57 ± 2.11 W/m2 in SON. The results highlight how the radiative effects of the particles depend on the complex relationship between the dust load, their altitude in the troposphere, and their optical properties. Accordingly, the knowledge of aerosols optical property profiles is of primary importance to understand the radiative impact of dust.

In March 2019, the PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite was launched by the Italian Space Agency (ASI), and it is currently operational on a global basis. The mission includes the hyperspectral imager PRISMA working in the 400–2500 nm spectral range with 237 bands and a panchromatic (PAN) camera (400–750 nm). This paper presents an evaluation of the PRISMA top-of-atmosphere (TOA) L1 products using different in situ measurements acquired over a fragmented rural area in Southern Italy (Pignola) between October 2019 and July 2021. L1 radiance values were compared with the TOA radiances simulated with a radiative transfer code configured using measurements of the atmospheric profile and the surface spectral characteristics. The L2 reflectance products were also compared with the data obtained by using the ImACor code atmospheric correction tool. A preliminary assessment to identify PRISMA noise characteristics was also conducted. The results showed that: (i) the PRISMA performance, as measured at the Pignola site over different seasons, is characterized by relative mean absolute differences (RMAD) of about 5–7% up to 1800 nm, while a decrease in accuracy was observed in the SWIR; (ii) a coherent noise could be observed in all the analyzed images below the 630th scan line, with a frequency of about 0.3–0.4 cycles/pixel; (iii) the most recent version of the standard reflectance L2 product (i.e., Version 2.05) matched well the reflectance values obtained by using the ImACor atmospheric correction tool. All these preliminary results confirm that PRISMA imagery is suitable for an accurate retrieval of the bio-geochemical variables pertaining to a complex fragmented ecosystem such as that of the Southern Apennines. Further studies are needed to confirm and monitor PRISMA data performance on different land-cover areas and on the Radiometric Calibration Network (RadCalNet) targets.

This study describes a quite special and interesting atmospheric event characterized by the simultaneous presence of fresh and aged smoke layers. These peculiar conditions occurred on 16 July 2024 at the CNR-IMAA atmospheric observatory (CIAO) in Potenza (Italy), and represent an ideal case for the evaluation of the impact of aging and transport mechanisms on both the optical and microphysical properties of biomass burning aerosol. The fresh smoke was originated by a local wildfire about 2 km from the measurement site and observed about one hour after its ignition. The other smoke layer was due to a wide wildfire occurring in Canada that, according to backward trajectory analysis, traveled for about 5–6 days before reaching the observatory. Synergetic use of lidar, ceilometer, radar, and microwave radiometer measurements revealed that particles from the local wildfire, located at about 3 km a.s.l., acted as condensation nuclei for cloud formation as a result of high humidity concentrations at this altitude range. Optical characterization of the fresh smoke layer based on Raman lidar measurements provided lidar ratio (LR) values of 46 ± 4 sr and 34 ± 3 sr, at 355 and 532 nm, respectively. The particle linear depolarization ratio (PLDR) at 532 nm was 0.067 ± 0.002, while backscatter-related Ångström exponent (AEβ) values were 1.21 ± 0.03, 1.23 ± 0.03, and 1.22 ± 0.04 in the spectral ranges of 355–532 nm, 355–1064 nm and 532–1064 nm, respectively. Microphysical inversion caused by these intensive optical parameters indicates a low contribution of black carbon (BC) and, despite their small size, particles remained outside the ultrafine range. Moreover, a combined use of CIAO remote sensing and in situ instrumentation shows that the particle properties are affected by humidity variations, thus suggesting a marked particle hygroscopic behavior. In contrast, the smoke plume from the Canadian wildfire traveled at altitudes between 6 and 8 km a.s.l., remaining unaffected by local humidity. Absorption in this case was higher, and, as observed in other aged wildfires, the LR at 532 nm was larger than that at 355 nm. Specifically, the LR at 355 nm was 55 ± 2 sr, while at 532 nm it was 82 ± 3 sr. The AEβ values were 1.77 ± 0.13 and 1.41 ± 0.07 at 355–532 nm and 532–1064 nm, respectively and the PLDR at 532 nm was 0.040 ± 0.003. Microphysical analysis suggests the presence of larger, yet much more absorbent particles. This analysis indicates that both optical and microphysical properties of smoke can vary significantly depending on its origin, persistence, and transport in the atmosphere. These factors that must be carefully incorporated into future climate models, especially considering the frequent occurrences of fire events worldwide.

In this paper, characterization of the optical and microphysical properties of extremely fresh biomass burning aerosol is presented. This work aims to characterize, for the first time to our knowledge, freshly formed smoke particles observed only a few minutes after they were emitted from a nearby forest fire. The smoke particles were detected by combining passive (sun-photometer) and active (Raman lidar) techniques. On 14 August 2021, an EARLINET (European Aerosol Research Lidar Network) multi-wavelength Raman lidar and a co-located AERONET sun-photometer in Potenza, South Italy, observed an extremely fresh smoke plume. The lidar measurements, carried out from 22:27 to 02:16 UTC, revealed a thick biomass burning layer below 2.7 km. The particle depolarization ratio at 532 nm was 0.025, and lidar ratios at 355 and 532 nm were, respectively, 40 and 38 sr. The mean value of the Ångström exponent was 1.5. The derived size distribution was bimodal with a peak at 0.13 µm, an effective radius mean value of 0.15 µm, and a single scattering albedo of 0.96 at all wavelengths. The real part of the refractive index was 1.58 and the imaginary was 0.006. The AERONET measurements at 5:34 UTC confirmed the lidar measurements.

A strategy for European Aerosol Research Lidar Network (EARLINET) correlative measurements for Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) has been developed. These EARLINET correlative measurements started in June 2006 and are still in progress. Up to now, more than 4500 correlative files are available in the EARLINET database. Independent extinction and backscatter measurements carried out at high‐performance EARLINET stations have been used for a quantitative comparison with CALIPSO level 1 data. Results demonstrate the good performance of CALIPSO and the absence of evident biases in the CALIPSO raw signals. The agreement is also good for the distribution of the differences for the attenuated backscatter at 532 nm ((CALIPSO‐EARLINET)/EARLINET (%)), calculated in the 1–10 km altitude range, with a mean relative difference of 4.6%, a standard deviation of 50%, and a median value of 0.6%. A major Saharan dust outbreak lasting from 26 to 31 May 2008 has been used as a case study for showing first results in terms of comparison with CALIPSO level 2 data. A statistical analysis of dust properties, in terms of intensive optical properties (lidar ratios, Ångström exponents, and color ratios), has been performed for this observational period. We obtained typical lidar ratios of the dust event of 49 ± 10 sr and 56 ± 7 sr at 355 and 532 nm, respectively. The extinction‐related and backscatter‐related Ångström exponents were on the order of 0.15–0.17, which corresponds to respective color ratios of 0.91–0.95. This dust event has been used to show the methodology used for the investigation of spatial and temporal representativeness of measurements with polar‐orbiting satellites.