The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs

Zhao, Ming; Golaz, Jean‐Christophe; Held, Isaac M.; Guo, Huan; Balaji, V.; Benson, Rusty; Chen, J. H.; Chen, X.; Donner, Leo J.; Dunne, John; Dunne, Krista A.; Durachta, J.; Fan, Song‐Miao; Freidenreich, S. M.; Garner, Stephen T.; Ginoux, Paul; Harris, Lucas; Horowitz, Larry W.; Krasting, John P.; Langenhorst, A. R.; Zhi, Liang; Lin, Pu; Lin, S. J.; Malyshev, Sergey; Mason, Erik; Milly, P. C. D.; Ming, Yi; Naik, Vaishali; Paulot, Fabien; Paynter, David; Phillipps, Peter J.; Radhakrishnan, Aparna; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, Charles J.; Shevliakova, Elena; Shen, Zhencai; Shin, Hyeyum Hailey; Silvers, Levi G.; Wilson, J. R.; Winton, Michael; Wittenberg, Andrew T.; Wyman, Bruce; Xiang, Baoqiang

doi:10.1002/2017ms001208

Cited by 181 publications

(221 citation statements)

References 89 publications

Supporting

Mentioning

216

Contrasting

Order By: Relevance

“…Monthly mean data from CERES EBAF Ed4.1 (Loeb et al, and Kato et al, ), ERA‐Interim (Dee et al, ), and GFDL AM4 (Zhao et al, ) are used to study the temporal variability of Δ G from March 2000 to August 2016. Within Edition 4.1 of CERES EBAF, we use the “t” version: clear sky fluxes from the total area of a region.…”

Section: Methodsmentioning

confidence: 99%

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

2019

Self Cite

View full text Add to dashboard Cite

The clear sky greenhouse effect (G) is defined as the trapping of infrared radiation by the atmosphere in the absence of clouds. The magnitude and variability of G is an important element in the understanding of Earth's energy balance; yet the quantification of the governing factors of G is poor. The global mean G averaged over 2000 to 2016 is 130–133 W m−2 across data sets. We use satellite observations from Clouds and the Earth's Radiant Energy System Energy Balance and Filled (CERES EBAF) to calculate the monthly anomalies in the clear sky greenhouse effect (ΔG). We quantify the contributions to ΔG due to changes in surface temperature, atmospheric temperature, and water vapor by performing partial radiation perturbation experiments using ERA‐Interim and Geophysical Fluid Dynamics Laboratory's Atmospheric Model 4.0 climatological data. Water vapor in the middle troposphere and upper troposphere is found to contribute equally to the global mean and tropical mean ΔG. Holding relative humidity (RH) fixed in the radiative transfer calculations captures the temporal variability of global mean ΔG while variations in RH control the regional ΔG signal. The variations in RH are found to help generate the clear sky super greenhouse effect (SGE). Thirty‐six percent of Earth's area exhibits SGE, and this disproportionately contributes to 70% of the globally averaged magnitude of ΔG. In the global mean, G's sensitivity to surface temperature is 3.1–4.0 W m−2 K−1, and the clear sky longwave feedback parameter is 1.5–2.0 W m−2 K−1. Observations from CERES EBAF lie at the more sensitive ends of these ranges and the spread arises from its cloud removal treatment, suggesting that it is difficult to constrain clear sky feedbacks.

show abstract

Section: Methodsmentioning

confidence: 99%

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is conceivable that some of the tropical Pacific climate improvements seen in the 55‐km FLOR could also have been attained with a 100‐km grid (midway between LOAR1 and FLOR), though we have not tested this in the FLOR lineage which has focused on improving simulations of regional and extreme phenomena that clearly benefit from higher atmospheric resolution. However, analyses of the 100‐km GFDL‐AM4 atmosphere model (Zhao et al, ; ) and its coupled counterpart GFDL‐Coupled Model version 4 confirm that excellent simulations of tropical Pacific climate are indeed possible with a 100‐km atmosphere grid.…”

Section: Discussionmentioning

confidence: 99%

“…Beyond its utility for the present study, LOAR1 has also contributed to the development of a new GFDL coupled model (Seamless system for Prediction and EArth system Research [SPEAR]) which is optimized for seasonal‐to‐decadal applications and forecasting. SPEAR leverages the new technology and parameterizations developed for the Coupled Model version 4 CGCM (Zhao et al, , ) that is GFDL's main model contribution to Coupled Model Intercomparison Project phase 6. SPEAR will be documented in a future study.…”

Section: Observational and Model Data Setsmentioning

confidence: 99%

Improved Simulations of Tropical Pacific Annual‐Mean Climate in the GFDL FLOR and HiFLOR Coupled GCMs

Wittenberg

Vecchi

Delworth

et al. 2018

J Adv Model Earth Syst

Self Cite

View full text Add to dashboard Cite

The National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory has recently developed two global coupled general circulation models, the Forecast‐oriented Low Ocean Resolution (FLOR) model and the High atmospheric resolution Forecast‐oriented Low Ocean Resolution (HiFLOR) model, which are now being utilized for climate research and seasonal predictions. Compared to their predecessor Coupled Model version 2.1 (CM2.1), the new versions have improved ocean/atmosphere physics and numerics and refinement of the atmospheric horizontal grid from 220 km (CM2.1) to 55 km (FLOR) and 26 km (HiFLOR). Both FLOR and HiFLOR demonstrate greatly improved simulations of the tropical Pacific annual‐mean climatology, with FLOR practically eliminating any equatorial cold bias in sea surface temperature. An additional model experiment (Low Ocean Atmosphere Resolution version 1) using FLOR's ocean/atmosphere physics, but with the atmospheric grid coarsened toward that of CM2.1, is used to further isolate the impacts of the refined atmospheric grid versus the improved physics and numerics. The improved ocean/atmosphere formulations are found to produce more realistic tropical Pacific patterns of sea surface temperature and rainfall, surface heat fluxes, ocean mixed layer depths, surface currents, and tropical instability wave activity; enhance the near‐surface equatorial upwelling; and reduce the intercentennial warm drift of the tropical Pacific upper ocean. The atmospheric grid refinement further improves these features and also improves the tropical Pacific surface wind stress, implied Ekman and Sverdrup transports, subsurface temperature and salinity structure, and heat advection in the equatorial upper ocean. The results highlight the importance of nonlocal air‐sea interactions in the tropical Pacific climate system, including the influence of off‐equatorial surface fluxes on the equatorial annual‐mean state. Implications are discussed for improving future simulations, observations, and predictions of tropical Pacific climate.

show abstract

“…This is similar to the range chosen in Zhao et al (). The values of n = 4, c = 0.16 are used in the AM4.0 version of the model (Zhao et al, , ). However, in our simulations, for c > 0.15, the model becomes numerically unstable, which limits our choice of the strength of the damping coefficients designating weak and strong damping for c = 0.05 and c = 0.15, respectively.…”

Section: Model and Experimental Designmentioning

confidence: 99%

Sensitivity of Radiative‐Convection Equilibrium to Divergence Damping in GFDL‐FV3‐Based Cloud‐Resolving Model Simulations

Anber

Jeevanjee

Harris

et al. 2018

J Adv Model Earth Syst

Self Cite

View full text Add to dashboard Cite

Using a nonhydrostatic model based on a version of Geophysical Fluid Dynamics Laboratory's FV3 dynamical core at a cloud‐resolving resolution in radiative‐convective equilibrium (RCE) configuration, the sensitivity of the mean RCE climate to the magnitude and scale‐selectivity of the divergence damping is explored. Divergence damping is used to reduce small‐scale noise in more realistic configurations of this model. This sensitivity is tied to the strength (and width) of the convective updrafts, which decreases (increases) with increased damping and acts to organize the convection, dramatically drying out the troposphere and increasing the outgoing longwave radiation. Increased damping also results in a much‐broadened precipitation probability distribution and larger extreme values, as well as reduction in cloud fraction, which correspondingly decreases the magnitude of shortwave and longwave cloud radiative effects. Solutions exhibit a monotonic dependence on the strength of the damping and asymptotically converge to the inviscid limit. While the potential dependence of RCE simulations on resolution and microphysical assumptions are generally appreciated, these results highlight the potential significance of the choice of subgrid numerical diffusion in the dynamical core.

show abstract

The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs

Cited by 181 publications

References 89 publications

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

Improved Simulations of Tropical Pacific Annual‐Mean Climate in the GFDL FLOR and HiFLOR Coupled GCMs

Sensitivity of Radiative‐Convection Equilibrium to Divergence Damping in GFDL‐FV3‐Based Cloud‐Resolving Model Simulations

Contact Info

Product

Resources

About