This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F0 using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F0, around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors. The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for λ ≥ 500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03. Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences. It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.
Bibliographical noteFunding Information:
Financial support. This research has been supported by the
Acknowledgements. We are grateful for the support from the JAXA (Japan Aerospace Exploration Agency) SGLI, MOEJ (Ministry of the Environment Japan)-NIES (National Institute for Environmental Studies)-JAXA GOSAT and GOSAT2, ERCA (Environmental Restoration and Conservation Agency) ERDF/S-12, and JST (Japan Science and Technology Agency)/CREST/TEEDDA (JP- MJCR15K4) projects. Kazuhiko Miura of Tokyo University of Science is gratefully acknowledged for providing us with Langley plot data. A group of the co-authors were supported by ERCA/ERDF/2-1901, JSPS (Japan Society for the Promotion of Science) /KAKENHI/JP19H04235, P17K00529, and the JAXA 2nd research announcement on the Earth Observations (grant number 19RT000351). ESR is grateful for the support of the Spanish Ministry of Economy and Competitiveness and European Regional Development Fund through funding to the University of Valencia within several projects, such as CGL2015-70432-R and CGL2017-86966-R. The SAVEX-D campaign was funded by EUFAR TNA (European Union Seventh Framework Programme, grant agreement no. 312609), making use of airborne data obtained using the BAe-146-301 Atmospheric Research Aircraft operated by Airtask Ltd and managed by the Facility for Airborne Atmospheric Measurements (FAAM). It was a success thanks to many staff at the Met Office, the University of Leeds, the University of Manchester, the University of Hertsfordshire, FAAM, Directflight Ltd, Avalon Engineering and BAE Systems. ESR also thanks Emanuele Costantini of the Research Area of Tor Vergata for the data center and server maintenance, Dr. Igor Bertello for his help on the development of the ESR system, and Dr. Henri Diémoz from ARPA Valle d’Aosta for continuous support of ESR activities.
Jhoon Kim was supported by the “Technology development for Practical Applications of Multi-Satellite data to maritime issues” project, funded by the Ministry of Ocean and Fisheries, South Korea.
All Science Journal Classification (ASJC) codes
- Atmospheric Science