Confronting Models with Data: The Gewex Cloud Systems Study

By David, Randall, Judith, Curry, Peter, Duynkerke, Steven, Krueger, Mitchell, Moncrieff and 11 more. 2003

178 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/e180b2bc86993b0c3e7c2900e96bb466555850be

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. M. Webb
2. Sandrine Bony
3. Brian J. Soden
4. K. Taylor
5. M. Zelinka
6. Hugh Morrison
7. Stephen A. Klein
8. J. Gregory

In Global and Planetary Change

1. M. Webb
2. Sandrine Bony
3. Brian J. Soden
4. K. Taylor
5. M. Zelinka
6. Hugh Morrison
7. Stephen A. Klein
8. J. Gregory

Citations in the corpus

• Intercomparison of cloud model simulations of Arctic mixed‐phase boundary layer clouds observed during SHEBA/FIRE‐ACE (2011, background): “Hugh Morrison, National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO, 80307 morrison@ucar.edu #National Center for Atmospheric Research is sponsored by the National Science Foundation”
• The Cumulus Parameterization Problem: Past, Present, and Future (2004, methodology): “Khairoutdinov and Randall (2001; see also Randall et al. 2003b) applied CRCP, which they called superparameterization, to the climate simulation problem and presented very encouraging results.”
• A Comparison of TWP-ICE Observational Data with Cloud-Resolving Model Results (2012, background): “…2D Cloud Resolving Model (ISUCRM) [Wu et al., 2008], the Meso-NH Atmospheric Simulation System (MESONH) [Lafore et al., 1998], the System for Atmospheric Modeling (SAM) [Khairoutdinov and Randall, 2003], and the UK Met Office Large Eddy Model (UKMO) [Shutts and Gray, 1994; Petch and Gray, 2001].”
• Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction (2004, methodology): “For example, data sets of this type have been centralized for investigations conducted by participants in the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS 2002, Randall et al. 2003).”
• Evaluation of cloud‐resolving and limited area model intercomparison simulations using TWP‐ICE observations: 1. Deep convective updraft properties (2014, background): “D CRMs in GCM grid boxes, a process known as superparameterization [Grabowski, 2001; Khairoutdinov and Randall, 2001; Randall et al., 2003].”
• Stable Atmospheric Boundary Layers and Diurnal Cycles: Challenges for Weather and Climate Models (2013, background): “Such a strategy has also been found to be very useful for cloudy boundary layers (e.g., Randall et al. 2003; Neggers et al. 2012).”
• On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles (2006, methodology): “HadSM3 is a version of the Hadley Centre climate model and is described by Pope et al. (2000) and Williams et al. (2001a, b). Atmospheric resolution is N48/L19, and the model has prognostic equations for total water (vapour plus liquid/ice) and liquid/ice water temperature.”