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Conference Paper

GEWEX cloud assessment: A review

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Kinne,  Stefan
Observations and Process Studies, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Citation

Stubenrauch, C., Rossow, W., Kinne, S., Ackerman, S., Cesana, G., Chepfer, H., et al. (2013). GEWEX cloud assessment: A review. In R. F. Cahalan, & J. Fischer (Eds.), Radiation Processes in the Atmosphere and Ocean (IRS 2012): Proceedings of the International Radiation Symposium (IRC/IAMAS) (pp. 404-407).


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-75BE-9
Abstract
Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our
planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and
across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data
records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit
systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy
and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides
the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved
from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders
and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude),
cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties
(effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level
clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically
thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires
consideration of many factors. The monthly, gridded database presented here facilitates further assessments, climate
studies, and the evaluation of climate models.