Articles | Volume 10, issue 1
Atmos. Meas. Tech., 10, 83–107, 2017
https://doi.org/10.5194/amt-10-83-2017
Atmos. Meas. Tech., 10, 83–107, 2017
https://doi.org/10.5194/amt-10-83-2017

Research article 06 Jan 2017

Research article | 06 Jan 2017

Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing

Alexandra Tsekeri et al.

Data sets

FAAM B638 ACEMED and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft Facility for Airborne Atmospheric Measurements (FAAM) http://catalogue.ceda.ac.uk/uuid/f014fe1ff19f40d78c83223458d82aee

CALIPSO/CALIOP Level 1B, Lidar Profile Data, version 3.01 CALIPSO Science Team https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L1-ValStage1-V3-01_L1B-003.01

CALIPSO/CALIOP Level 2, Lidar Aerosol Layer Data, version 3.01 CALIPSO Science Team https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmAPro-Prov-V3-01_L2-003.01

CALIPSO data ICARE Data Center http://www.icare.univ-lille1.fr/

The MODIS Active Fire Detections, MCD14ML NASA FIRMS https://earthdata.nasa.gov/active-fire-data

Operational Model Global Tropospheric Analyses NCEP FNL https://doi.org/10.5065/D6FB50XD

Sea surface temperature (SST) data NOAA/OAR/ESRL PSD http://www.esrl.noaa.gov/psd//

Download
Short summary
The In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) provides vertical profiles of aerosol optical, microphysical and hygroscopic properties from airborne in situ and remote sensing measurements. The algorithm is highly advantageous for aerosol characterization in humid conditions, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. IRRA can find valuable applications in aerosol–cloud interaction schemes and in validation of active space-borne sensors.