Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-961-2021
https://doi.org/10.5194/amt-14-961-2021
Research article
 | 
08 Feb 2021
Research article |  | 08 Feb 2021

Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument

Nick Gorkavyi, Zachary Fasnacht, David Haffner, Sergey Marchenko, Joanna Joiner, and Alexander Vasilkov

Related authors

Earth observations from the Moon's surface: dependence on lunar libration
Nick Gorkavyi, Nickolay Krotkov, and Alexander Marshak
Atmos. Meas. Tech., 16, 1527–1537, https://doi.org/10.5194/amt-16-1527-2023,https://doi.org/10.5194/amt-16-1527-2023, 2023
Short summary
Tracking aerosols and SO2 clouds from the Raikoke eruption: 3D view from satellite observations
Nick Gorkavyi, Nickolay Krotkov, Can Li, Leslie Lait, Peter Colarco, Simon Carn, Matthew DeLand, Paul Newman, Mark Schoeberl, Ghassan Taha, Omar Torres, Alexander Vasilkov, and Joanna Joiner
Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021,https://doi.org/10.5194/amt-14-7545-2021, 2021
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Gravity waves above the northern Atlantic and Europe during streamer events using Aeolus
Sabine Wüst, Lisa Küchelbacher, Franziska Trinkl, and Michael Bittner
Atmos. Meas. Tech., 18, 1591–1607, https://doi.org/10.5194/amt-18-1591-2025,https://doi.org/10.5194/amt-18-1591-2025, 2025
Short summary
Observations of tall-building wakes using a scanning Doppler lidar
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025,https://doi.org/10.5194/amt-18-1355-2025, 2025
Short summary
Mid-Atlantic nocturnal low-level jet characteristics: a machine learning analysis of radar wind profiles
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech., 18, 1269–1282, https://doi.org/10.5194/amt-18-1269-2025,https://doi.org/10.5194/amt-18-1269-2025, 2025
Short summary
Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm
Padmanabhan Thiruvengadam, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech., 18, 1185–1191, https://doi.org/10.5194/amt-18-1185-2025,https://doi.org/10.5194/amt-18-1185-2025, 2025
Short summary
GNSS-RO residual ionospheric error (RIE): a new method and assessment
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025,https://doi.org/10.5194/amt-18-843-2025, 2025
Short summary

Cited articles

Butz, A., Guerlet, S., Hasekamp, O. P., Kuze, A., and Suto, H.: Using ocean-glint scattered sunlight as a diagnostic tool for satellite remote sensing of greenhouse gases, Atmos. Meas. Tech., 6, 2509–2520, https://doi.org/10.5194/amt-6-2509-2013, 2013. 
Cao, X., Hu, Y., Zhu, X., Shi, F., Zhuo, L., and Chen, J.: A simple self-adjusting model for correcting the blooming effects in DMSP-OLS nighttime light images, Remote Sens. Environ., 224, 401–411, https://doi.org/10.1016/j.rse.2019.02.019, 2019. 
Chan Miller, C., Gonzalez Abad, G., Wang, H., Liu, X., Kurosu, T., Jacob, D. J., and Chance, K.: Glyoxal retrieval from the Ozone Monitoring Instrument, Atmos. Meas. Tech., 7, 3891–3907, https://doi.org/10.5194/amt-7-3891-2014, 2014. 
Cheng, L., Tao, J., Valks, P., Yu, Ch., Liu, S., Wang, Y., Xiong, X., Wang, Z., and Chen, L.: NO2 retrieval from the Environmental trace gases Monitoring Instrument (EMI): preliminary results and intercomparison with OMI and TROPOMI, Remote Sens.-Basel, 11, 3017, https://doi.org/10.3390/rs11243017, 2019. 
Cox, C. and Munk, W.: Measurement of the roughness of the sea surface from photographs of the Sun's glitter, J. Opt. Soc. Am., 44, 838–850, https://doi.org/10.1364/JOSA.44.000838, 1954. 
Download
Short summary
Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as DI of 1–r.
Share