Atmospheric Chemistry and Physics (Sep 2019)
EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product
- E. Proestakis,
- V. Amiridis,
- E. Marinou,
- I. Binietoglou,
- A. Ansmann,
- U. Wandinger,
- J. Hofer,
- J. Yorks,
- E. Nowottnick,
- A. Makhmudov,
- A. Papayannis,
- A. Pietruczuk,
- A. Gialitaki,
- A. Apituley,
- A. Szkop,
- C. Muñoz Porcar,
- D. Bortoli,
- D. Dionisi,
- D. Althausen,
- D. Mamali,
- D. Balis,
- D. Nicolae,
- E. Tetoni,
- G. L. Liberti,
- H. Baars,
- I. Mattis,
- I. S. Stachlewska,
- K. A. Voudouri,
- L. Mona,
- M. Mylonaki,
- M. R. Perrone,
- M. R. Perrone,
- M. J. Costa,
- M. Sicard,
- M. Sicard,
- N. Papagiannopoulos,
- N. Papagiannopoulos,
- N. Siomos,
- P. Burlizzi,
- P. Burlizzi,
- R. Pauly,
- R. Engelmann,
- S. Abdullaev,
- G. Pappalardo
Affiliations
- E. Proestakis
- Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens, Athens, 15236, Greece
- V. Amiridis
- Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens, Athens, 15236, Greece
- E. Marinou
- Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft und Raumfahrt (DLR), Oberpfaffenhofen, Germany
- I. Binietoglou
- National Institute of R&D for Optoelectronics, Măgurele, Romania
- A. Ansmann
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
- U. Wandinger
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
- J. Hofer
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
- J. Yorks
- NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, United States
- E. Nowottnick
- GESTAR, Universities Space Research Association, 4254 Stadium Dr., College Park, Maryland 20742, USA
- A. Makhmudov
- Physical Technical Institute, Academy of Sciences of Tajikistan, Dushanbe, Tajikistan
- A. Papayannis
- Laser Remote Sensing Unit (LRSU), Physics Department, National Technical University of Athens, Zografou, 15780, Greece
- A. Pietruczuk
- Institute of Geophysics, Polish Academy of Sciences, 01-452 Warsaw, Poland
- A. Gialitaki
- Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens, Athens, 15236, Greece
- A. Apituley
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
- A. Szkop
- Institute of Geophysics, Polish Academy of Sciences, 01-452 Warsaw, Poland
- C. Muñoz Porcar
- CommSensLab, Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain
- D. Bortoli
- Departamento de Física, Instituto de Ciências da Terra, Escola de Ciências e Tecnologia, Universidade de Évora, Évora, Portugal
- D. Dionisi
- Consiglio Nazionale delle Ricerche, Istituto Scienze Marine (CNR-ISMAR), Tor Vergata, Rome, 00133, Italy
- D. Althausen
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
- D. Mamali
- Department of Geoscience and Remote Sensing, TU Delft, Delft, the Netherlands
- D. Balis
- Laboratory of Atmospheric Physics, Physics Department, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece
- D. Nicolae
- National Institute of R&D for Optoelectronics, Măgurele, Romania
- E. Tetoni
- Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft und Raumfahrt (DLR), Oberpfaffenhofen, Germany
- G. L. Liberti
- Consiglio Nazionale delle Ricerche, Istituto Scienze Marine (CNR-ISMAR), Tor Vergata, Rome, 00133, Italy
- H. Baars
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
- I. Mattis
- Observatory Hohenpeissenberg, German Weather Service, Hohenpeißenberg, Germany
- I. S. Stachlewska
- Institute of Geophysics, Faculty of Physics, University of Warsaw (IGFUW), 02-093 Warsaw, Poland
- K. A. Voudouri
- Laboratory of Atmospheric Physics, Physics Department, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece
- L. Mona
- Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l'Analisi Ambientale (CNR-IMAA), C.da S. Loja, Tito Scalo, Potenza, 85050, Italy
- M. Mylonaki
- Laser Remote Sensing Unit (LRSU), Physics Department, National Technical University of Athens, Zografou, 15780, Greece
- M. R. Perrone
- Dipartimento di Matematica e Fisica, Università del Salento, Lecce, 73100, Italy
- M. R. Perrone
- CNISM – Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia, Lecce, 73100, Italy
- M. J. Costa
- Departamento de Física, Instituto de Ciências da Terra, Escola de Ciências e Tecnologia, Universidade de Évora, Évora, Portugal
- M. Sicard
- CommSensLab, Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain
- M. Sicard
- Ciències i Tecnologies de l'Espai – Centre de Recerca de l'Aeronàutica i de l'Espai/Institut d'Estudis Espacials de Catalunya (CTE-CRAE/IEEC), Barcelona, Spain
- N. Papagiannopoulos
- CommSensLab, Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain
- N. Papagiannopoulos
- Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l'Analisi Ambientale (CNR-IMAA), C.da S. Loja, Tito Scalo, Potenza, 85050, Italy
- N. Siomos
- Laboratory of Atmospheric Physics, Physics Department, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece
- P. Burlizzi
- Dipartimento di Matematica e Fisica, Università del Salento, Lecce, 73100, Italy
- P. Burlizzi
- CNISM – Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia, Lecce, 73100, Italy
- R. Pauly
- Science Systems and Applications Inc., Lanham, 20706 Maryland, USA
- R. Engelmann
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
- S. Abdullaev
- Physical Technical Institute, Academy of Sciences of Tajikistan, Dushanbe, Tajikistan
- G. Pappalardo
- Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l'Analisi Ambientale (CNR-IMAA), C.da S. Loja, Tito Scalo, Potenza, 85050, Italy
- DOI
- https://doi.org/10.5194/acp-19-11743-2019
- Journal volume & issue
-
Vol. 19
pp. 11743 – 11764
Abstract
We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90 min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1 %, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3 %.