Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators
By Jennifer E. Kay, B. Hillman, Stephen A. Klein, Yuying Zhang, B. Medeiros, Robert Pincus, Andrew Gettelman, Brian Eaton, J. Boyle, Roger Marchand and 1 more. 2012
296 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/0ba8362e0ee5615323259b56f27b34375bcd3a5a
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
- Sungsu Park
- Stephen A. Klein
- J. Golaz
- David L. Williamson
- V. Larson
- Richard B. Neale
- Sandrine Bony
- B. Medeiros
In Global and Planetary Change
- Sungsu Park
- J. Golaz
- Stephen A. Klein
- David L. Williamson
- V. Larson
- Richard B. Neale
- Sandrine Bony
- B. Medeiros
Citations in the corpus
- On the Correspondence between Mean Forecast Errors and Climate Errors in CMIP5 Models (2013, background): “This suggests biases in the cloud condensate simulations (cloud liquid and ice) as the cloud optical depth is important in affecting the net radiation budget (Kay et al. 2012; Nam et al. 2012).”
- Ubiquitous low‐level liquid‐containing Arctic clouds: New observations and climate model constraints from CALIPSO‐GOCCP (2012, background): “…clouds frequently occur in the Arctic and exert a large influence on Arctic surface radiative fluxes [e.g., Shupe and Intrieri , 2004; Shupe , 2011; de Boer et al. , 2009; Morrison et al. , 2012] and Arctic climate feedbacks [e.g., Winton , 2006; Kay and Gettelman , 2009; Kay et al. , 2012a].”
- Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model (2018, methodology): “Note that output from the MISR simulator (Marchand & Ackerman, 2010) is used in Figure 2 to facilitate model-observation comparison of low-level clouds, as MISR provides the most accurate retrievals of cloud top heights for low-level clouds among the available satellite cloud simulators contained in”
- The Mean Climate of the Community Atmosphere Model (CAM4) in Forced SST and Fully Coupled Experiments (2013, background): “…in cloud the extensive physics parameterization developments in the model’s successor CAM5 provides a much improved simulation of cloud and cloud optical properties, particularly when analyzed through the Cloud Observation Simulator Package (COSP) diagnostics available in CAM (Kay et al. 2012).”