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Open AccessJournal ArticleDOI

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

TLDR
The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment as discussed by the authors provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities).
Abstract
Clouds cover about 70% of 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 compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR soun...

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Citations
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Journal ArticleDOI

Rapid and highly variable warming of lake surface waters around the globe

Catherine M. O'Reilly, +63 more
TL;DR: In the first worldwide synthesis of in situ and satellite-derived lake data, this paper found that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009.
Journal ArticleDOI

The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy

TL;DR: The Global Climate Observing System (GCOS) developed the concept of essential climate variables (ECVs) as mentioned in this paper, which is used to provide reliable, traceable, observation-based evidence for a range of applications, including monitoring, mitigating, adapting to, and attributing climate changes.
References
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Journal ArticleDOI

Advances in understanding clouds from ISCCP

TL;DR: The progress report on the International Satellite Cloud Climatology Project (ISCCP) describes changes made to produce new cloud data products (D data), examines the evidence that these changes are improvements over the previous version (C data), summarizes some results, and discusses plans for the ISCCP through 2005.
Journal ArticleDOI

The CloudSat mission and the A-train: a new dimension of space-based observations of clouds and precipitation

TL;DR: CloudSat as discussed by the authors is a satellite experiment designed to measure the vertical structure of clouds from space, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASA's Aqua and Aura satellites, a NASA-CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL).
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Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms

TL;DR: Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is a two-wavelength polarization lidar that performs global profiling of aerosols and clouds in the troposphere and lower stratosphere as discussed by the authors.
Journal ArticleDOI

The MODIS cloud products: algorithms and examples from Terra

TL;DR: The various algorithms being used for the remote sensing of cloud properties from MODIS data with an emphasis on the pixel-level retrievals (referred to as Level-2 products), with 1-km or 5-km spatial resolution at nadir are described.
Journal ArticleDOI

Discriminating clear sky from clouds with MODIS

TL;DR: The MODIS cloud mask algorithm as discussed by the authors uses several cloud detection tests to indicate a level of confidence that the MEDIS is observing clear skies, which is ancillary input to MEDIS land, ocean, and atmosphere science algorithms to suggest processing options.
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