The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3

By L. Donner, B. Wyman, Richard S. Hemler, L. Horowitz, Yi Ming, Ming Zhao, J. Golaz, Paul Ginoux, Shian-Jiann Lin, M. Schwarzkopf and 31 more. 2011

996 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/9b34b3da5dfba04f452a6a90a0d013937ab115fd

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. Andrew Gettelman
2. J. Golaz
3. Stephen A. Klein
4. Bjorn Stevens
5. V. Larson
6. Peter M. Caldwell
7. Xiaohong Liu
8. Hugh Morrison

In Global and Planetary Change

1. Andrew Gettelman
2. J. Golaz
3. Stephen A. Klein
4. Bjorn Stevens
5. Peter M. Caldwell
6. Xiaohong Liu
7. V. Larson
8. F. Brient

Citations in the corpus

• Evaluation of CMIP5 models for west and southwest Iran using TOPSIS-based method (2018, background): “0 M8 Donner et al. (2011) NOAA GFDL GFDL-CM3 M9 Dunne et al. (2012) NOAA GFDL GFDL-ESM2M M10 Dunne et al. (2012) NOAA GFDL GFDL-ESM2G M11 Volodin et al. (2010) INM INM-CM4 M12 Dufresne et al.”
• Structure and Performance of GFDL's CM4.0 Climate Model (2019, methodology): “0 trends are −0.34 and −0.09 × 106 km2 per decade in September and March, respectively, which can be compared to the CMIP5 multimodel ensemble mean trends of −0.40 in September and −0.25 in March (Turner et al., 2013).”
• Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions (2014, background): “The presence of ice can lead to a rapid depletion of cloud liquid water via the Wegener–Bergeron–Findeisen process (Wegener 1911; Bergeron 1935; Findeisen 1938), and it has been suggested that low in-cloud concentrations of ice nuclei limit ice formation and thus contribute to the persistence of…”
• Quantifying Progress Across Different CMIP Phases With the ESMValTool (2020, background): “(2012) FGOALS‐g2 FGOALS‐s2 National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) /Institute of Atmospheric Physics, China Li et al. (2013); http://www.”
• An Overview of the Atmospheric Component of the Energy Exascale Earth System Model (2019, methodology): “An informal look at climate models being used today indicate many put 22–28 layers between the surface and 18 km (e.g., Donner et al., 2011; Martin et al., 2011; Roeckner et al., 2006).”
• Climatological Characteristics of Arctic and Antarctic Surface-Based Inversions* (2011, background): “The IGRA is a quality-controlled compilation of radiosonde observations from the global network of more than 1500 stations and includes the observed temperature, geopotential height, humidity, wind direction, and wind speed at standard (mandatory) levels (including the surface level and 1000, 925,…”
• The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies (2018, background): “1 (GFDL-GAMDT, 2004), AM3 (Donner et al., 2011), and HiRAM (Zhao et al., 2009).”
• The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs (2018, methodology): “GFDL AM2 and AM3 are no exceptions (Donner et al., 2011; GFDL-GAMDT, 2004).”