Articles | Volume 8, issue 10
https://doi.org/10.5194/amt-8-4561-2015
https://doi.org/10.5194/amt-8-4561-2015
Research article
 | 
30 Oct 2015
Research article |  | 30 Oct 2015

Quality assessment and improvement of the EUMETSAT Meteosat Surface Albedo Climate Data Record

A. Lattanzio, F. Fell, R. Bennartz, I. F. Trigo, and J. Schulz

Related authors

A database of global reference sites to support validation of satellite surface albedo datasets (SAVS 1.0)
Alexander Loew, Ralf Bennartz, Frank Fell, Alessio Lattanzio, Marie Doutriaux-Boucher, and Jörg Schulz
Earth Syst. Sci. Data, 8, 425–438, https://doi.org/10.5194/essd-8-425-2016,https://doi.org/10.5194/essd-8-425-2016, 2016
Short summary
LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis
M. J. Wooster, G. Roberts, P. H. Freeborn, W. Xu, Y. Govaerts, R. Beeby, J. He, A. Lattanzio, D. Fisher, and R. Mullen
Atmos. Chem. Phys., 15, 13217–13239, https://doi.org/10.5194/acp-15-13217-2015,https://doi.org/10.5194/acp-15-13217-2015, 2015
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024,https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024,https://doi.org/10.5194/amt-17-2721-2024, 2024
Short summary
Application of Doppler sodar in short-term forecasting of PM10 concentration in the air in Krakow (Poland)
Ewa Agnieszka Krajny, Leszek Ośródka, and Marek Jan Wojtylak
Atmos. Meas. Tech., 17, 2451–2464, https://doi.org/10.5194/amt-17-2451-2024,https://doi.org/10.5194/amt-17-2451-2024, 2024
Short summary
Radiative closure tests of collocated hyperspectral microwave and infrared radiometers
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233, https://doi.org/10.5194/amt-17-2219-2024,https://doi.org/10.5194/amt-17-2219-2024, 2024
Short summary
Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-term forecasting
Kyriakoula Papachristopoulou, Ilias Fountoulakis, Alkiviadis F. Bais, Basil E. Psiloglou, Nikolaos Papadimitriou, Ioannis-Panagiotis Raptis, Andreas Kazantzidis, Charalampos Kontoes, Maria Hatzaki, and Stelios Kazadzis
Atmos. Meas. Tech., 17, 1851–1877, https://doi.org/10.5194/amt-17-1851-2024,https://doi.org/10.5194/amt-17-1851-2024, 2024
Short summary

Cited articles

Cescatti, A., Marcolla, B., Vannan, S. K. S., Pan, J. Y., Roman, M. O., Yang, X., Ciais, P., Cook, R. B., Law, B. E., Matteucci, G., Migliavacca, M., Moors, E., Richardson, A. D., Seufert, G., and Schaaf, C. B.: Intercomparison of MODIS albedo retrievals and in situ measurements across the global FLUXNET network, Remote Sens. Environ. 121, 323–334, 2012.
EUMETSAT: Meteosat First Generation User Handbook, available at: http://www.eumetsat.int/website/home/Data/TechnicalDocuments/index.html?lang=EN (last access: July 2015), 40 pp., 2011.
Fang, H., Liang, S., Kim, H.-Y., Townshend, J. R., Schaaf, C. L., Strahler, A. H., and Dickinson, R. E.: Developing a spatially continuous 1 km surface albedo data set over North America from Terra MODIS products, J. Geophys. Res., 112, D20206, https://doi.org/10.1029/2006JD008377, 2007.
Fell, F., Bennartz, R., Cahill, B., Lattanzio, A., Muller, J.-P., Schulz, J., Shane, N., Trigo, I., and Watson, G.: Evaluation of the Meteosat Surface Albedo Climate Data Record (ALBEDOVAL), Final Report, 119 pp., available at: http://www.eumetsat.int/website/home/Data/ClimateService/index.html (last access: July 2015), 2012.
Fontana, F.: Evaluation of a probabilistic cloud masking algorithm for climate data record processing: Sparc: a new scene identification algorithm for msg seviri, Visiting Scientist Report 14, EUMETSAT Satellite Application Facility on Climate Monitoring, 2010.
Download
Short summary
EUMETSAT has generated a surface albedo data set climate data record, spanning over more than 2 decades, from measurements acquired by Meteosat First Generation satellites. EUMETSAT coordinated a study for the validation of such a data record. In the validation report, the full set of results, including comparison with in situ measurements and satellites, was presented. A method of increasing the quality of the data set, removing cloud-contaminated pixels, is presented.