five

ALICENET datasets on vertically-resolved aerosol optical and physical properties and layering presented in "Aerosols in the mixed layer and mid-troposphere from long-term data of the Italian Automated Lidar-Ceilometer Network ALICENET and comparison with ERA5 and CAMS models"

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/14419259
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This dataset contains quality-assured aerosol measurements and derived products from the Italian Automated Lidar-Ceilometer network (ALICENET) stations in Aosta, Rome, and Messina, spanning the period 2016-2022. The data are organized into several netCDF files, each focusing on specific aspects of aerosol vertical distribution and characteristics. For each station, the following datasets are present: The "*pm_concentrations.nc" file presents three-dimensional fields (time of day × month × altitude) of particulate matter (PM) concentrations derived from ALICENET measurements. The data covers altitudes from ground level to 5 km, with concentrations expressed in μg/m³. This dataset is particularly valuable for understanding the vertical distribution of aerosols and their temporal evolution. The data are present at both 1 hour and 15-minute resolution. The "*dry_pm_concentrations.nc" file contains similar three-dimensional fields of PM concentrations, but with aerosol concentrations adjusted to account for hygroscopic effects. This dataset enables direct comparison with surface-level PM measurements and model outputs that typically report dry aerosol mass. The "*pm_seasons.nc" file provides seasonal statistics of PM vertical profiles, including median values and interquartile ranges for both ambient and dry conditions. The data is organized by season and altitude, offering insights into the seasonal variability of aerosol vertical distributions. The "*mal_cal_data.nc" file contains statistics of Mixed Aerosol Layer (MAL) and Continuous Aerosol Layer (CAL) heights, including median values and interquartile ranges. These parameters are crucial for understanding boundary layer dynamics and aerosol vertical mixing processes. The "*EAL_MAL.nc" file presents monthly statistics of Elevated Aerosol Layers (EALs) and their relationship with the Mixed Aerosol Layer. The file includes the frequency of EAL occurrence, the percentage of cases where EALs approach the MAL, and associated increases in PM concentrations within the mixed layer. The "*eal_frequency_pm.nc" file contains detailed information about EAL characteristics, including their frequency of occurrence and average PM contribution at different altitudes and months. This dataset is valuable for understanding the impact of transported aerosols on local air quality. The "*aod_perc_profile.nc" file presents the vertical build-up of AOD expressed as percentages, showing how different atmospheric layers contribute to the total column AOD. This information is valuable for understanding the vertical distribution of aerosol optical properties and their impact on radiative transfer. The data are present at both 1 hour and 15-minute resolution. The "*AOD_diurnal_nocturnal.nc" file contains monthly statistics of Aerosol Optical Depth (AOD) at 1064 nm, providing separate diurnal and nocturnal measurements. For each month, the file includes median values along with 25th and 75th percentiles of AOD measurements, enabling analysis of daily and seasonal patterns in aerosol optical properties. The "*pm10_types.nc" file provides speciated PM10 concentrations within the ALICENET-detected EALs, distinguishing between different aerosol components including dust, wildfire emissions, and other sources. The data is organized by month and altitude, offering insights into the composition and origin of elevated aerosol layers. Each file includes appropriate metadata describing variables, units, and coordinate systems. The datasets have undergone rigorous quality assurance procedures as detailed in the associated paper, making them suitable for scientific analysis of aerosol vertical distributions, air quality studies, and model validation.
创建时间:
2024-12-18
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