Abstract
The visible infrared radiometer (VIRR) is the first instrument with longest measurements equipped on the Fengyun (FY) polar-orbiting satellites. Through re-processing of the historic VIRR measurements, long-term (over 20 yr) global data can be integrated from multiple participating VIRRs on a consistent radiometric scale, which are valuable to climate and climate change studies. Due to lack of an onboard calibration system for VIRR, the reflective solar bands must be vicariously calibrated. This study applied the multi-site vicarious approach for consistent calibration of the VIRR visible (VIS) and near-infrared (NIR) data, and produced calibration coefficients for five VIRRs on FY-1C/D and FY-3A/B/C. The data quality was then evaluated with observations. The reflectance predicted by using the radiative transfer model over multiple invariant desert and ocean targets was used to derive the calibration slope via a weighted fitting scheme, in which the weights are the inverse of the variance from a radiative transfer simulation evaluated with reference to Aqua moderate resolution imaging spectroradiometer (MODIS). The sensor-specific calibration coefficients were derived on a daily basis by using piecewise polynomials. The calibration reference of the VIRR solar band record was further traced to the Aqua MODIS Collection 6.1 reference calibration with a systematic correction derived from the Libya4 desert. The VIRR record was compared with the Aqua MODIS C6.1 calibration over the polar region based on simultaneous nadir overpass observations. The lifetime relative difference for each sensor are within 3.3% and 4.5% for channels 1 and 2. Invariant deserts were also employed to evaluate the stability and consistency of the VIRR record. In general, the means of the directional and spectral corrected reflectance for each sensor are within 1% of the 20-yr average, implying that the VIRR reflectance of the invariant targets is consistent to within 1% among the sensors for channels 1 and 2. The VIRR data thus derived are reliable.
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References
Bacour, C., X. Briottet, F.-M. Bréon, et al., 2019: Revisiting pseudo invariant calibration sites (PICS) over sand deserts for vicarious calibration of optical imagers at 20 km and 100 km scales. Remote Sens., 11, 1166, doi: https://doi.org/10.3390/rs11101166.
Bhatt, R., D. R. Doelling, D. Morstad, et al., 2014: Desert-based absolute calibration of successive geostationary visible sensors using a daily exoatmospheric radiance model. IEEE Trans. Geosci. Remote Sens., 52, 3670–3682, doi: https://doi.org/10.1109/TGRS.2013.2274594.
Bhatt, R., D. R. Doelling, B. R. Scarino, et al., 2015: Toward consistent radiometric calibration of the NOAA AVHRR visible and near-infrared data record. Proc. Volume 9607, Earth Observing Systems XX, SPIE, San Diego, 960703, doi: https://doi.org/10.1117/12.2186816. Accessed on 17 November 2021.
Bhatt, R., D. R. Doelling, B. R. Scarino, et al., 2016: A consistent AVHRR visible calibration record based on multiple methods applicable for the NOAA degrading orbits. Part I: Methodology. J. Atmos. Oceanic Technol., 33, 2499–2515, doi: https://doi.org/10.1175/JTECH-D-16-0044.1.
Chen, L., X. Q. Hu, N. Xu, et al., 2013: The application of deep convective clouds in the calibration and response monitoring of the reflective solar bands of FY-3A/MERSI (Medium Resolution Spectral Imager). Remote Sens., 5, 6958–6975, doi: https://doi.org/10.3390/rs5126958.
Cosnefroy, H., M. Leroy, and X. Briottet, 1996: Selection and characterization of Saharan and Arabian desert sites for the calibration of optical satellite sensors. Remote Sens. Environ., 58, 101–114, doi: https://doi.org/10.1016/0034-4257(95)00211-1.
Doelling, D. R., C. Lukashin, P. Minnis, et al., 2012: Spectral reflectance corrections for satellite intercalibrations using SCIAMACHY data. IEEE Geosci. Remote Sens. Lett., 9, 119–123, doi: https://doi.org/10.1109/LGRS.2011.2161751.
Doelling, D. R., A. S. Wu, X. X. Xiong, et al., 2015: The radiometric stability and scaling of collection 6 Terra- and Aqua-MODIS VIS, NIR, and SWIR spectral bands. IEEE Trans. Geosci. Remote Sens., 53, 4520–4535, doi: https://doi.org/10.1109/TGRS.2015.2400928.
Doelling, D. R., R. Bhatt, B. R. Scarino, et al., 2016: A consistent AVHRR visible calibration record based on multiple methods applicable for the NOAA degrading orbits. Part II: Validation. J. Atmos. Oceanic Technol., 33, 2517–2534, doi: https://doi.org/10.1175/JTECH-D-16-0042.1.
Heidinger, A. K., W. C. Straka III, C. C. Molling, et al., 2010: Deriving an inter-sensor consistent calibration for the AVHRR solar reflectance data record. Int. J. Remote Sens., 31, 6493–6517, doi: https://doi.org/10.1080/01431161.2010.496472.
Helder, D. L., B. Basnet, and D. L. Morstad, 2010: Optimized identification of worldwide radiometric pseudo-invariant calibration sites. Can. J. Remote Sens., 36, 527–539, doi: https://doi.org/10.5589/m10-085.
Hu, X. Q., L. Sun, J. Liu, et al., 2012: Calibration for the solar reflective bands of medium resolution spectral imager onboard FY-3A. IEEE Trans. Geosci. Remote Sens., 50, 4915–4928, doi: https://doi.org/10.1109/TGRS.2012.2214226.
Hu, X. Q., L. Wang, J. W. Wang, et al., 2020: Preliminary selection and characterization of pseudo-invariant calibration sites in Northwest China. Remote Sens., 12, 2517, doi: https://doi.org/10.3390/rs12162517.
Karlsson, K.-G., and E. Johansson, 2014: Multi-sensor calibration studies of AVHRR-heritage channel radiances using the simultaneous nadir observation approach. Remote Sens., 6, 1845–1862, doi: https://doi.org/10.3390/rs6031845.
Li, C., Y. Xue, Q. H. Liu, et al., 2014: Post calibration of channels 1 and 2 of long-term AVHRR data record based on SeaWiFS data and pseudo-invariant targets. Remote Sens. Environ., 150, 104–119, doi: https://doi.org/10.1016/j.rse.2014.04.020.
Lyu, J.-Y., L. Chen, M.-Y. He, et al., 2017: Degradation analysis for FY3B/VIRR reflective solar bands based on the Dunhuang radiometric calibration site. Spectrosc. Spectral Anal., 37, 2397–2401, doi: https://doi.org/10.3964/j.issn.1000-0593(2017)08-2397-05. (in Chinese)
Scarino, B. R., D. R. Doelling, P. Minnis, et al., 2016: A web-based tool for calculating spectral band difference adjustment factors derived from SCIAMACHY hyperspectral data. IEEE Trans. Geosci. Remote Sens., 54, 2529–2542, doi: https://doi.org/10.1109/TGRS.2015.2502904.
Sun, L., X. Q. Hu, M. H. Guo, et al., 2012a: Multisite calibration tracking for FY-3A MERSI solar bands. IEEE Trans. Geosci. Remote Sens., 50, 4929–4942, doi: https://doi.org/10.1199/TGRS.2012.2215613.
Sun, L., M.-H. Guo, N. Xu, et al., 2012b: On-orbit response variation analysis of FY-3 MERSI reflective solar bands based on Dunhuang site calibration. Spectrosc. Spectral Anal., 32, 1869–1877, doi: https://doi.org/10.3964/j.issn.1000-0593(2012)07-1869-09. (in Chinese)
Sun, L., H. Qiu, R. H. Wu, et al., 2021: FY-1 and FY-3 VIRR FCDR for reflective solar bands. National Satellite Meteorological Center, China Meteorological Administration, doi: https://doi.org/10.12185/NSMC.RICHCEOS.FCDR.VIRRRSBsRecalCoef.FY.VFRR.LLGBAL.POAD.NUL.TXT.202LLV1.
Teillet, P. M., J. A. Barsi, G. Chander, et al., 2007: Prime candidate Earth targets for the post-launch radiometric calibration of space-based optical imaging instruments. Proc. Volume 6677, Earth Observing Systems XII, SPIE, San Diego, 66770S, doi: https://doi.org/10.1117/12.733156. Accessed on 17 November 2021.
Wang, L., X. Q. Hu, Z. J. Zheng, et al, 2018: Radiometric calibration tracking detection for FY-3A/MERSI by joint use of snow targets in South and North Pole. Acta Opt. Sinica, 38, 0212003, doi: https://doi.org/10.3788/AOS201838.0212003. (in Chinese)
Xu, N., L. Chen, R. H. Wu, et al., 2014: In-flight intercalibration of FY-3C visible channels with AQUA MODIS. Proc. Volume 9264, Earth Observing Missions and Sensors: Development, Implementation, and Characterization III, SPIE, Beijing, 926408, doi: https://doi.org/10.1117/12.2071185. Accessed on 17 November 2021.
Xu, N., R. H. Wu, X. Q. Hu, et al., 2015: Integrated method for on-obit wide dynamic vicarious calibration of FY-3C MERSI reflective solar bands. Acta Opt. Sinica, 3, 1228001, doi: https://doi.org/10.3788/AOS201535.1228001. (in Chinese)
Zhang, P., L. Chen, D. Xian, et al., 2018: Recent progress of Fengyun meteorology satellites. Chinese J. Space Sci., 38, 788–796, doi: https://doi.org/10.11728/cjss2018.05.788.
Zhang, P., Q. F. Lu, X. Q. Hu, et al., 2019: Latest progress of the Chinese meteorological satellite program and core data processing technologies. Adv. Atmos. Sci., 36, 1027–1045, doi: https://doi.org/10.1007/s00376-019-8215-x.
Acknowledgments
The authors would like to thank Mingge Yuan, Ya Shen, and Xin Zheng for their help with data processing, and Hongbo Pan, Taoyang Wang, Chengbao Liu, and Lei Yang for FY-1 VIRR re-geolocation.
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Supported by the National Key Research and Development Program of China (2018YFB0504905 and 2018YFB0504900).
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Sun, L., Qiu, H., Wu, R. et al. Long-Term Consistent Recalibration of VIRR Solar Reflectance Data Record for Fengyun Polar-Orbiting Satellites. J Meteorol Res 35, 926–942 (2021). https://doi.org/10.1007/s13351-021-1049-3
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DOI: https://doi.org/10.1007/s13351-021-1049-3