Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties

By Seiji Kato, Fred G. Rose, S. Sun-Mack, W. Miller, Yan Chen, David A. Rutan, Graeme L. Stephens, Norman G. Loeb, Patrick Minnis, B. Wielicki and 5 more. 2011

272 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/6452ff67120c7d977f9579989617d507fb6e5410

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Citations in the corpus

Climatology of stratocumulus cloud morphologies: microphysical properties and radiative effects (2014, methodology): “As discussed in Sect.2, all radiative flux measurements are taken from the integrated CALIPSO CloudSat CERES and MODIS (CCCM) merged data set (Kato et al., 2010, 2011) and interpolated to the A-train ground track to estimate the radiative effect of low clouds as a function of the MCC type.”
Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model (2018, methodology): “…(MODIS) High cloud fraction MISR Multi-angle Imaging SpectroRadiometer (MISR) Low cloud fraction C3M CERES CALIPSO CloudSat MODIS (C3M) (Kato et al., 2011), in which CALIPSO stands for Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations and CloudSat is a spaceborne…”
Next-generation angular distribution models for top-of-atmosphere radiative flux calculation from CERES instruments: validation (2015, methodology): “CERES data are used by the science community to study the Earth’s energy balance (e.g., Trenberth et al., 2009; Kato et al., 2011; Loeb et al., 2012; Stephens et al., 2012), aerosol direct radiative effects (e.g., Satheesh and Ramanathan, 2000; Zhang et al., 2005; Loeb and Manalo-Smith, 2005; Su et…”
The Non-hydrostatic Icosahedral Atmospheric Model: description and development (2014, methodology): “…and outgoing shortwave radiative flux at the top of the atmosphere that were obtained using the NDW6 scheme, along with the observed outgoing shortwave flux at the top of the atmosphere that was obtained from the satellite product of CERES SYN1deg_Ed3A (Wielicki et al. 1996; Kato et al. 2011).”
A Multisensor Perspective on the Radiative Impacts of Clouds and Aerosols (2013, result): “Although CERES has a larger field of view in comparison withCloudSat, a study by Kato et al. (2011) demonstrated the differences between CERES and CloudSat/CALIPSO cloud fraction decrease when averaged over area and time.”
CERES Synoptic Product: Methodology and Validation of Surface Radiant Flux (2015, methodology): “Using estimates of water vapor uncertainty from Zhang et al. (2006), Kato et al. (2011) suggest a value of 5.2Wm22 for the global uncertainty of DLF due to column water vapor and a value of 4.5Wm22 for the uncertainty in DLF due to surface air temperature.”
Surface Irradiances Consistent With CERES-Derived Top-of-Atmosphere Shortwave and Longwave Irradiances (2013, methodology): “This bias correction is based on computed irradiance using CALIPSO- and CloudSatderived vertical cloud profiles (Kato et al. 2011a).”
The Observed State of the Energy Budget in the Early Twenty-First Century (2015, methodology): “Together, these advances have enabled new reconstructions of energy balance on global (Lin et al. 2008; Trenberth et al. 2009; Kato et al. 2011; Stephens et al. 2012b; Wild et al. 2013, 2015) and regional scales (Fasullo andTrenberth 2008a,b; Trenberth and Fasullo 2013b,c; Brown and Kummerow 2014)…”
Characterizing and understanding radiation budget biases in CMIP3/CMIP5 GCMs, contemporary GCM, and reanalysis (2013, methodology): “This surface flux radiation product is constrained by TOA CERES-derived flux with Energy Balanced and Filled (EBAF) adjustments [Kato et al., 2011, 2012a, 2012b] and is based on two CERES data products.”
Surface Irradiances of Edition 4.0 Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Data Product (2018, background): “Less than 1% heats the ocean at a global annual scale (Loeb et al. 2012; Palmer 2017; Wild et al. 2015).”
The global energy balance from a surface perspective (2013, background): “Depending on the product, they range from 172 to 192 Wm-2 (Zhang et al. 2004; Kato et al. 2011; Hatzianastassiou et al. 2005; Gupta et al. 1999), which may indicate a higher uncertainty range than given in Fig.”