Articles | Volume 10, issue 4
Earth Syst. Sci. Data, 10, 2279–2293, 2018
Earth Syst. Sci. Data, 10, 2279–2293, 2018

  14 Dec 2018

14 Dec 2018

Using CALIOP to estimate cloud-field base height and its uncertainty: the Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm and dataset

Johannes Mülmenstädt et al.

Related authors

Constraining the Twomey effect from satellite observations: issues and perspectives
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099,,, 2020
Short summary
Radiative forcing of climate change from the Copernicus reanalysis of atmospheric composition
Nicolas Bellouin, Will Davies, Keith P. Shine, Johannes Quaas, Johannes Mülmenstädt, Piers M. Forster, Chris Smith, Lindsay Lee, Leighton Regayre, Guy Brasseur, Natalia Sudarchikova, Idir Bouarar, Olivier Boucher, and Gunnar Myhre
Earth Syst. Sci. Data, 12, 1649–1677,,, 2020
Short summary
A new classification of satellite-derived liquid water cloud regimes at cloud scale
Claudia Unglaub, Karoline Block, Johannes Mülmenstädt, Odran Sourdeval, and Johannes Quaas
Atmos. Chem. Phys., 20, 2407–2418,,, 2020
Short summary
Surprising similarities in model and observational aerosol radiative forcing estimates
Edward Gryspeerdt, Johannes Mülmenstädt, Andrew Gettelman, Florent F. Malavelle, Hugh Morrison, David Neubauer, Daniel G. Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, Minghuai Wang, and Kai Zhang
Atmos. Chem. Phys., 20, 613–623,,, 2020
Short summary
Separating radiative forcing by aerosol–cloud interactions and rapid cloud adjustments in the ECHAM–HAMMOZ aerosol–climate model using the method of partial radiative perturbations
Johannes Mülmenstädt, Edward Gryspeerdt, Marc Salzmann, Po-Lun Ma, Sudhakar Dipu, and Johannes Quaas
Atmos. Chem. Phys., 19, 15415–15429,,, 2019
Short summary

Related subject area

Atmosphere – Meteorology
HydroGFD3.0 (Hydrological Global Forcing Data): a 25 km global precipitation and temperature data set updated in near-real time
Peter Berg, Fredrik Almén, and Denica Bozhinova
Earth Syst. Sci. Data, 13, 1531–1545,,, 2021
Short summary
Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A
Pierre Bosser, Olivier Bock, Cyrille Flamant, Sandrine Bony, and Sabrina Speich
Earth Syst. Sci. Data, 13, 1499–1517,,, 2021
Short summary
Hydrometeorological data from a Remotely Operated Multi-Parameter Station network in Central Asia
Cornelia Zech, Tilo Schöne, Julia Illigner, Nico Stolarczuk, Torsten Queißer, Matthias Köppl, Heiko Thoss, Alexander Zubovich, Azamat Sharshebaev, Kakhramon Zakhidov, Khurshid Toshpulatov, Yusufjon Tillayev, Sukhrob Olimov, Zabihullah Paiman, Katy Unger-Shayesteh, Abror Gafurov, and Bolot Moldobekov
Earth Syst. Sci. Data, 13, 1289–1306,,, 2021
Short summary
WegenerNet high-resolution weather and climate data from 2007 to 2020
Jürgen Fuchsberger, Gottfried Kirchengast, and Thomas Kabas
Earth Syst. Sci. Data, 13, 1307–1334,,, 2021
Short summary
G2DC-PL+: a gridded 2 km daily climate dataset for the union of the Polish territory and the Vistula and Odra basins
Mikołaj Piniewski, Mateusz Szcześniak, Ignacy Kardel, Somsubhra Chattopadhyay, and Tomasz Berezowski
Earth Syst. Sci. Data, 13, 1273–1288,,, 2021
Short summary

Cited articles

An, N., Wang, K., Zhou, C., and Pinker, R. T.: Observed Variability of Cloud Frequency and Cloud-Base Height within 3600 m above the Surface over the Contiguous United States, J. Climate, 30, 3725–3742,, 2017. a
Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C. R., Smirnova, T. G., Olson, J. B., James, E. P., Dowell, D. C., Grell, G. A., Lin, H., Peckham, S. E., Smith, T. L., Moninger, W. R., Kenyon, J. S., and Manikin, G. S.: A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh, Mon. Weather Rev., 144, 1669–1694,, 2016. a
Böhm, C., Sourdeval, O., Mülmenstädt, J., Quaas, J., and Crewell, S.: Cloud base height retrieval from multi-angle satellite data, Atmos. Meas. Tech. Discuss.,, in review, 2018. a
CALIPSO Science Team: CALIPSO/CALIOP Level 2, Vertical Feature Mask Data, version 4.10,, 2016. a
Cao, C., De Luccia, F. J., Xiong, X., Wolfe, R., and Weng, F.: Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite, IEEE Trans. Geosci. Remote Sens., 52, 1142–1156,, 2014. a
Short summary
One of the key pieces of information about a cloud is how high its base is. Unlike cloud top, cloud base is hard to observe from a satellite perspective – the cloud blocks the view. But without using satellites, it is difficult to compile global datasets. Here we describe how we worked around the limitations of a cloud-detecting laser satellite to observe global cloud base heights. This dataset will expand our knowledge of the cloudy atmosphere and its interaction with the planetary surface.