Articles | Volume 13, issue 9
Atmos. Meas. Tech., 13, 4995–5012, 2020
https://doi.org/10.5194/amt-13-4995-2020
Atmos. Meas. Tech., 13, 4995–5012, 2020
https://doi.org/10.5194/amt-13-4995-2020

Research article 25 Sep 2020

Research article | 25 Sep 2020

Calibration of global MODIS cloud amount using CALIOP cloud profiles

Andrzej Z. Kotarba

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Dissecting effects of orbital drift of polar-orbiting satellites on accuracy and trends of climate data records of cloud fractional cover
Jędrzej S. Bojanowski and Jan P. Musiał
Atmos. Meas. Tech., 13, 6771–6788, https://doi.org/10.5194/amt-13-6771-2020,https://doi.org/10.5194/amt-13-6771-2020, 2020
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Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O2-O2, MODIS and Suomi-NPP VIIRS
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-122,https://doi.org/10.5194/amt-2020-122, 2020
Revised manuscript accepted for AMT
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Evaluation of the MODIS Collection 6 multilayer cloud detection algorithm through comparisons with CloudSat Cloud Profiling Radar and CALIPSO CALIOP products
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020,https://doi.org/10.5194/amt-13-3263-2020, 2020
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An extended radar relative calibration adjustment (eRCA) technique for higher-frequency radars and range–height indicator (RHI) scans
Alexis Hunzinger, Joseph C. Hardin, Nitin Bharadwaj, Adam Varble, and Alyssa Matthews
Atmos. Meas. Tech., 13, 3147–3166, https://doi.org/10.5194/amt-13-3147-2020,https://doi.org/10.5194/amt-13-3147-2020, 2020
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Comparing lightning observations of the ground-based European lightning location system EUCLID and the space-based Lightning Imaging Sensor (LIS) on the International Space Station (ISS)
Dieter R. Poelman and Wolfgang Schulz
Atmos. Meas. Tech., 13, 2965–2977, https://doi.org/10.5194/amt-13-2965-2020,https://doi.org/10.5194/amt-13-2965-2020, 2020
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Cited articles

Ackerman, S. A., Strabala, K. I., Menzel, W. P., Frey, R. A., Moeller, C. C., and Gumley, L. E.: Discriminating clear sky from clouds with MODIS, J. Geophys. Res., 103, 32141–32157, https://doi.org/10.1029/1998JD200032, 1998. 
Ackerman, S. A., Holz, R. E., Frey, R., Eloranta, E. W., Maddux, B. C., and McGill, M.: Cloud detection with MODIS. Part II: Validation, J. Atmos. Ocean. Tech., 25, 1073–1086, https://doi.org/10.1175/2007JTECHA1053.1, 2008. 
Ackerman, S., Frey, R., Kathleen Strabala, K., Liu, Y., Gumley, L., Baum, B., and Menzel, P: MYD35_L2 - MODIS/Aqua Cloud Mask and Spectral Test Results 5-Min L2 Swath 250m and 1km, MODIS Atmosphere L2 Cloud Mask Product, NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA, https://doi.org/10.5067/MODIS/MYD35_L2.061, 2017. 
Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E., Ackerman, S. A., Heidinger, A. K., and Yang, P.: MODIS cloud-top property refinements for collection 6, J. Appl. Meteorol. Clim., 51, 1145–1163, https://doi.org/10.1175/JAMC-D-11-0203.1, 2012. 
Chan, M. A. and Comiso, J. C.: Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat, J. Climate, 26, 3285–3306, https://doi.org/10.1175/JCLI-D-12-00204.1, 2013. 
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Short summary
This paper evaluates the operational approach for producing global (Level 3) cloud amount based on MODIS cloud masks (Level 2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 %, and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/local scale. A method of how to correct and calibrate MODIS global data using CALIPSO detections is suggested.