Articles | Volume 17, issue 19
https://doi.org/10.5194/amt-17-5935-2024
https://doi.org/10.5194/amt-17-5935-2024
Research article
 | 
10 Oct 2024
Research article |  | 10 Oct 2024

Evaluation of Aeolus feature mask and particle extinction coefficient profile products using CALIPSO data

Ping Wang, David Patrick Donovan, Gerd-Jan van Zadelhoff, Jos de Kloe, Dorit Huber, and Katja Reissig

Related authors

MONKI: a three-dimensional Monte Carlo simulator of total and polarised radiation reflected by planetary atmospheres
Victor J. H. Trees, Ping Wang, Job I. Wiltink, Piet Stammes, Daphne M. Stam, David P. Donovan, and A. Pier Siebesma
EGUsphere, https://doi.org/10.5194/egusphere-2025-2197,https://doi.org/10.5194/egusphere-2025-2197, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 18, 73–91, https://doi.org/10.5194/amt-18-73-2025,https://doi.org/10.5194/amt-18-73-2025, 2025
Short summary
The EarthCARE lidar cloud and aerosol profile processor (A-PRO): the A-AER, A-EBD, A-TC, and A-ICE products
David Patrick Donovan, Gerd-Jan van Zadelhoff, and Ping Wang
Atmos. Meas. Tech., 17, 5301–5340, https://doi.org/10.5194/amt-17-5301-2024,https://doi.org/10.5194/amt-17-5301-2024, 2024
Short summary
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023,https://doi.org/10.5194/amt-16-3631-2023, 2023
Short summary
Retrievals of precipitable water vapor and aerosol optical depth from direct sun measurements with EKO MS711 and MS712 spectroradiometers
Congcong Qiao, Song Liu, Juan Huo, Xihan Mu, Ping Wang, Shengjie Jia, Xuehua Fan, and Minzheng Duan
Atmos. Meas. Tech., 16, 1539–1549, https://doi.org/10.5194/amt-16-1539-2023,https://doi.org/10.5194/amt-16-1539-2023, 2023
Short summary

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Validation of the Aeolus L2A products with the eVe reference lidar measurements from the ASKOS/JATAC campaign
Peristera Paschou, Nikolaos Siomos, Eleni Marinou, Antonis Gkikas, Samira Moussa Idrissa, Daniel Tetteh Quaye, Désire Degbe Fiogbe Attannon, Kalliopi Artemis Voudouri, Charikleia Meleti, David Patric Donovan, George Georgoussis, Tommaso Parrinello, Thorsten Fehr, Jonas von Bismarck, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2025-1152,https://doi.org/10.5194/egusphere-2025-1152, 2025
Short summary
Estimating hourly ground-level aerosols using Geostationary Environment Monitoring Spectrometer aerosol optical depth: a machine learning approach
Sungmin O, Ji Won Yoon, and Seon Ki Park
Atmos. Meas. Tech., 18, 1471–1484, https://doi.org/10.5194/amt-18-1471-2025,https://doi.org/10.5194/amt-18-1471-2025, 2025
Short summary
Performance and evaluation of remote sensing satellites for monitoring dust weather in East Asia
Yuanyuan Zhang, Ning Wang, and Shuanggen Jin
EGUsphere, https://doi.org/10.5194/egusphere-2025-992,https://doi.org/10.5194/egusphere-2025-992, 2025
Short summary
Aerosol effects on day-ahead solar radiation forecasting
Xinyuan Hou, Kyriakoula Papachristopoulou, and Stelios Kazadzis
EGUsphere, https://doi.org/10.5194/egusphere-2025-891,https://doi.org/10.5194/egusphere-2025-891, 2025
Short summary
Decoupling the PBL Height, the Mixing Layer Height, and the Aerosol Layer Top in LiDAR Measurements over Chiang Mai, Northern Thailand
Ronald Macatangay, Thiranan Sonkaew, Sherin Hassan Bran, Worapop Thongsame, Titaporn Supasri, Mana Panya, Jeerasak Longmali, Raman Solanki, Ben Svasti Thomson, and Achim Haug
EGUsphere, https://doi.org/10.5194/egusphere-2025-630,https://doi.org/10.5194/egusphere-2025-630, 2025
Short summary

Cited articles

Abril-Gago, J., Guerrero-Rascado, J. L., Costa, M. J., Bravo-Aranda, J. A., Sicard, M., Bermejo-Pantaleón, D., Bortoli, D., Granados-Muñoz, M. J., Rodríguez-Gómez, A., Muñoz-Porcar, C., Comerón, A., Ortiz-Amezcua, P., Salgueiro, V., Jiménez-Martín, M. M., and Alados-Arboledas, L.: Statistical validation of Aeolus L2A particle backscatter coefficient retrievals over ACTRIS/EARLINET stations on the Iberian Peninsula, Atmos. Chem. Phys., 22, 1425–1451, https://doi.org/10.5194/acp-22-1425-2022, 2022. a
Amiridis, V., Marinou, E., Tsekeri, A., Wandinger, U., Schwarz, A., Giannakaki, E., Mamouri, R., Kokkalis, P., Binietoglou, I., Solomos, S., Herekakis, T., Kazadzis, S., Gerasopoulos, E., Proestakis, E., Kottas, M., Balis, D., Papayannis, A., Kontoes, C., Kourtidis, K., Papagiannopoulos, N., Mona, L., Pappalardo, G., Le Rille, O., and Ansmann, A.: LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET, Atmos. Chem. Phys., 15, 7127–7153, https://doi.org/10.5194/acp-15-7127-2015, 2015. a
Donovan, D. P., Kollias, P., Velázquez Blázquez, A., and van Zadelhoff, G.-J.: The generation of EarthCARE L1 test data sets using atmospheric model data sets, Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, 2023. a, b
Donovan, D. P., van Zadelhoff, G.-J., and Wang, P.: The EarthCARE lidar cloud and aerosol profile processor (A-PRO): the A-AER, A-EBD, A-TC, and A-ICE products, Atmos. Meas. Tech., 17, 5301–5340, https://doi.org/https://doi.org/10.5194/amt-17-5301-2024, 2024a. a, b, c, d, e, f
Donovan, D. P., van Zadelhoff, G.-J., and Wang, P.: Aeolus/ALADIN Algorithm Theoretical Basis Document Level 2A products AEL-FM, AEL-PRO, Document Version V2.00, https://earth.esa.int/documents/d/earth-online/aeolus-level-2a- algorithm-theoretical-baseline-document-ael-fm-and-ael-pro- products (last access: 2 August 2024), 2024b. a, b
Download
Short summary
We describe the new feature mask (AEL-FM) and aerosol profile retrieval (AEL-PRO) algorithms developed for Aeolus lidar and present the evaluation of the Aeolus products using CALIPSO data for dust aerosols over Africa. We have found that Aeolus and CALIPSO show similar aerosol patterns in the collocated orbits and have good agreement for the extinction coefficients for the dust aerosols, especially for the cloud-free scenes. The finding is applicable to Aeolus L2A product Baseline 17.
Share