Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models

By M. Webb, C. Senior, Sandrine Bony, J. Morcrette. 2001

427 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/c608ae0ed0eaf338c5ac8467c181a3267e00739b

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In Atmospheric Science

In Global and Planetary Change

Citations in the corpus

Cloud Feedbacks in the Climate System: A Critical Review (2005, methodology): “Webb et al. (2001) use this same analysis approach in an attempt to examine the nature of the differences in cloud radiative processes implicit in the ERBE cloud forcing data and the forcings derived from three global models.”
The Geostationary Earth Radiation Budget project (2005, methodology): “…years) from the Earth Radiation Budget Experiment (Harrison et al. 1990), with the Scanning Radiation Budget sensor (Kandel et al. 1998), and with simulations by version 4 of the Hadley Centre for Climate Prediction and Research Atmospheric Model (HadAM4) (Pope et al. 2000; Webb et al. 2001).”
How Well Do We Understand and Evaluate Climate Change Feedback Processes (2006, methodology): “Moreover, it has been pointed out that models exhibit systematic biases in tropical and midlatitude regions by simulating clouds generally too optically thick, and not abundant enough in the midtroposphere and in large-scale subsidence regimes (Klein and Jakob 1999; Norris and Weaver 2001; Webb et a”
Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models (2005, result): “[16] As stressed by other studies [Webb et al., 2001; Volodin, 2004], it is thus crucial to improve the representation of MBL clouds in climate models.”
Objective identification of cloud regimes in the Tropical Western Pacific (2003, methodology): “Citation: Jakob, C., and G. Tselioudis, Objective identification of cloud regimes in the Tropical Western Pacific, Geophys.”
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. (2016, background): “Such approaches enable more quantitative comparisons to the satellite record (e.g. Yu et al., 1996; Klein and Jakob, 1999; Webb et al., 2001; Bodas-Salcedo et al., 2008; Cesana and Chepfer, 2013).”
GCM intercomparison of global cloud regimes: present-day evaluation and climate change response (2007, methodology): “amongst contemporary GCMs (Webb et al. 2001; Zhang et al. 2005) and is likely to be mainly due to a lack of midlevel convective detrainment and poor simulation of multilayer cloud structures (Tselioudis and Jakob 2002).”
Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels (2012, methodology): “In all of the CFMIP models, the ISCCP simulator (Klein and Jakob 1999; Webb et al. 2001) is run inline during integration.”
The Non-hydrostatic Icosahedral Atmospheric Model: description and development (2014, background): “NICAM also introduces the ISCCP simulator (Klein and Jakob 1999; Webb et al. 2001), with which the distribution of every cloud category can be calculated online.”
Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators (2012, methodology): “The ISCCP observations (Rossow and Schiffer 1999) and corresponding ISCCP simulator (Klein and Jakob 1999; Webb et al. 2001) have now been applied for over a decade (e.g., Norris and Weaver 2001; Lin and Zhang 2004; Zhang et al. 2005, hereafter Z05; Schmidt et al. 2006; Cole et al. 2011).”