Correcting for Cryoprecipitation in the Calibration of IR Channels of the MSU-MR Radiometer
The presence of cryoprecipitation, which forms a thin film on the input windows of infrared (IR) detectors and distorts the signal, is a major issue in calibration of IR channels of the multispectral scanning imager–radiometer (MSU-MR) aboard Meteor-M No. 2. A model of signal attenuation in transmission through such films and a method for calculating this attenuation were developed. Correction functions for the detected signal were obtained. The developed algorithms were used for cross-calibration between the MSU-MR IR channels and the corresponding channels of the advanced very-high-resolution radiometer of MetOp satellites. An algorithm for calculating the sea surface temperature (SST) based on the non-linear SST technology (split-window technology) was developed and verified by comparison with in situ data. The SST calculation error was less than 0.8°C for the entire sample, which satisfies world quality standards. The stability of calibration parameters within an interval of two years was demonstrated.
Keywords:MSU-MR Meteor-M No. 2 calibration cryoprecipitation sea surface temperature
The development of the optical model of cryoprecipitation was supported by the Russian Science Foundation, project no. 4-50-00034. The study was also supported by the Fundamental Research Program of the Presidium of the Russian Academy of Sciences. Resources of the Satellite Center of the Far Eastern Branch of the Russian Academy of Sciences were employed.
- 1.Akimov, N.P., Badaev, K.V., Gektin, Yu.M., Ryzhakov, A.V., Smelyanskii, M.B., and Frolov, A.G., Low-resolution multi-zone scanning instrument MSU-MR for the space information system “Meteor-M”. Operating principle, evolution, and prospects, Raketno-Kosm. Prib. Inf. Sist., 2015, vol. 2, no. 4, pp. 30–39.Google Scholar
- 2.Aleksanin, A.I. and D’yakov, S.E., Cross-calibration of IR-channels of the MTSAT-1R satellite and algorithm for calculating the sea-surface temperature, Issled. Zemli Kosmosa, 2010, no. 5, pp. 3–10.Google Scholar
- 3.Aleksanin, A.I. and D’yakov, S.E., Cross-calibration of IR-channel data of the MSU-MR radiometer of the “Meteor-M” no. 2 satellite, in Tezisy dokladov 13-i Vserossiiskoi otkrytoi konferentsii “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (Abstracts of Presentations of the 13th All-Russian Open Conference “Current Problems of the Earth’s Remote Sensing from Space”), Moscow: IKI RAN, 2015, p. 8.Google Scholar
- 5.Aleksanin, A.I., D’yakov, S.E., Katamanov, S.N., and Naumkin, Yu.V., Technology of data processing of polar-orbiting satellites FY-1C/1D for monitoring of physical fields of the ocean, Podvod. Issled. Robototekh., 2006, no. 2, pp. 82–91.Google Scholar
- 6.Asmus, V.V., Krovotyntsev, V.A., Makridenko, L.A., Milekhin, O.E., Solov’ev, V.I., Uspensky, A.B., Frolov, A.V., and Khailov, M.N., The system of hydrometeorological satellites of “Meteor-M” series and the results of summer tests of the “Meteor-M” satellite no. 2, in Tezisy dokladov Mezhdunarodnoi nauchno-tekhnicheskloi konferentsii “Aktual’ne problemy sozdaniya kosmicheskikh sistem distantsionnogo zondirovaniya Zemli” (Abstracts of Presentations of the International Scientific and Practical Conference “Key Problems in the Development of Space Systems of the Earth’s Remote Sensing”), Moscow: VNIIEM, 2015, pp. 4–5.Google Scholar
- 7.Donlon, C., Robinson, I., Casey, K.S., Vazquez-Cuervo, J., Armstrong, E., Arino, O., Gentemann, C., May, D., LeBorgne, P., Piollé, J., Barton, I.J., Beggs, H., Poulter, D.J.S., Merchant, C.J., Bingham, A., Heinz, S., Harris, A., Wick, G., Emery, B., Minnett, P., Evans, R., Lewellyn-Jones, D., Mutlow, C., Reynolds, R.W., Kawamura, H., and Rayner, N., The global ocean data assimilation experiment high-resolution sea surface temperature pilot project, Bull. Am. Meteorol. Soc., 2007, vol. 88, no. 8, pp. 1197–1213.CrossRefGoogle Scholar
- 8.Goodrum, G., Kidwell, K.B., and Winston, W., NOAA KLM user’s guide, 1999. http://www2.ncdc.noaa.gov/ docs/klm.Google Scholar
- 9.Katamanov, S.N., Development of an automatic method of geo-referencing for MSU-MR images of the polar-orbiting satellite “Meteor-M” no. 1, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2014, vol. 11, no. 4, pp. 276–285.Google Scholar
- 10.Katamanov, S.N., Automatic image navigation method for AVHRR/3 imagery from polar-orbiting MetOp satellites, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2015, vol. 12, no. 3, pp. 63–74.Google Scholar
- 11.OSCAR observing systems capability analysis and review tool, observation requirements, sea surface temperature, 2011. https://www.wmo-sat.info/oscar/variables/ view/134.Google Scholar
- 12.Tsentry kollektivnogo pol’zovaniya Rossiyskoi akademii nauk (Common Use Centers of the Russian Academy of Sciences), Moscow: Nauka, 2004.Google Scholar