The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved.Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2°latitude ϫ 2.5°longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1°in latitude and longitude, with meridional resolution equatorward of 30°becoming progressively finer, such that the meridional resolution is 1/3°at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments.The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic. Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO 2 . The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).

A new version of the Community Atmosphere Model (CAM) has been developed and released to the climate community. CAM Version 3 (CAM3) is an atmospheric general circulation model that includes the Community Land Model (CLM3), an optional slab ocean model, and a thermodynamic sea ice model. The dynamics and physics in CAM3 have been changed substantially compared to implementations in previous versions. CAM3 includes options for Eulerian spectral, semi-Lagrangian, and finite-volume formulations of the dynamical equations. It supports coupled simulations using either finite-volume or Eulerian dynamics through an explicit set of adjustable parameters governing the model time step, cloud parameterizations, and condensation processes. The model includes major modifications to the parameterizations of moist processes, radiation processes, and aerosols. These changes have improved several aspects of the simulated climate, including more realistic tropical tropopause temperatures, boreal winter land surface temperatures, surface insolation, and clear-sky surface radiation in polar regions. The variation of cloud radiative forcing during ENSO events exhibits much better agreement with satellite observations. Despite these improvements, several systematic biases reduce the fidelity of the simulations. These biases include underestimation of tropical variability, errors in tropical oceanic surface fluxes, underestimation of implied ocean heat transport in the Southern Hemisphere, excessive surface stress in the storm tracks, and offsets in the 500-mb height field and the Aleutian low.

A global atmospheric model with roughly 50-km horizontal grid spacing is used to simulate the interannual variability of tropical cyclones using observed sea surface temperatures (SSTs) as the lower boundary condition. The model’s convective parameterization is based on a closure for shallow convection, with much of the deep convection allowed to occur on resolved scales. Four realizations of the period 1981–2005 are generated. The correlation of yearly Atlantic hurricane counts with observations is greater than 0.8 when the model is averaged over the four realizations, supporting the view that the random part of this annual Atlantic hurricane frequency (the part not predictable given the SSTs) is relatively small (<2 hurricanes per year). Correlations with observations are lower in the east, west, and South Pacific (roughly 0.6, 0.5, and 0.3, respectively) and insignificant in the Indian Ocean. The model trends in Northern Hemisphere basin-wide frequency are consistent with the observed trends in the International Best Track Archive for Climate Stewardship (IBTrACS) database. The model generates an upward trend of hurricane frequency in the Atlantic and downward trends in the east and west Pacific over this time frame. The model produces a negative trend in the Southern Hemisphere that is larger than that in the IBTrACS. The same model is used to simulate the response to the SST anomalies generated by coupled models in the World Climate Research Program Coupled Model Intercomparison Project 3 (CMIP3) archive, using the late-twenty-first century in the A1B scenario. Results are presented for SST anomalies computed by averaging over 18 CMIP3 models and from individual realizations from 3 models. A modest reduction of global and Southern Hemisphere tropical cyclone frequency is obtained in each case, but the results in individual Northern Hemisphere basins differ among the models. The vertical shear in the Atlantic Main Development Region (MDR) and the difference between the MDR SST and the tropical mean SST are well correlated with the model’s Atlantic storm frequency, both for interannual variability and for the intermodel spread in global warming projections.

Abstract. The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model is used to simulate the atmospheric sulfur cycle. The model uses the assimilated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). Global sulfur budgets from a 6-year simulation for SOe, sulfate, dimethylsulfide (DMS), and methanesulfonic acid (MSA) are presented in this paper. In a normal year without major volcanic perturbations, about 20% of the sulfate precursor emission is from natural sources (biogenic and volcanic), and 80% is anthropogenic; the same sources contribute 33% and 67%, respectively, to the total sulfate burden. A sulfate production efficiency of 0.41-0.42 is estimated in the model, an efficiency which is defined as a ratio of the amount of sulfate produced to the total amount of SOe emitted and produced in the atmosphere. This value indicates that less than half of the SOe entering the atmosphere contributes to the sulfate production, the rest being removed by dry and wet depositions. In a simulation for 1990 we estimate a total sulfate production of 39 Tg S yr -•, with 36% and 64% from in-air and in-cloud oxidation, respectively, of SOe. We also demonstrate that major volcanic eruptions, such as the Mount Pinatubo eruption in 1991, can significantly change the sulfate formation pathways, distributions, abundance, and lifetime. Comparison with other models shows that the parameterizations for wet removal or wet production of sulfate are the most critical factors in determining the burdens of SO2 and sulfate. Therefore a priority for future research should be to reduce the large uncertainties associated with the wet physical and chemical processes.

In this two‐part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea‐ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top‐of‐atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.

Responses of tropical cyclones (TCs) to CO 2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3-4-5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model's transient fullycoupled 2 × CO 2 TC activity response is largely recovered by "time-slice" experiments using time-invariant SST perturbations added to each model's own SST climatology. The TC response to SST forcing depends on each model's background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO 2 -induced warming patterns and CO 2 doubling. Isolated CO 2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC "seeds", which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO 2 concentrations, and (2) less efficient development of these"seeds" into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.

[1] The ability to reliably estimate CO 2 fluxes from current in situ atmospheric CO 2 measurements and future satellite CO 2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO 2 ) at 280 locations. We extracted synoptic-scale variability from daily averaged CO 2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO 2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO 2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.

SUMMARYA global shallow-water model based on the flux-form semi-lagrangian scheme is described. The massconserving flux-form semi-Lagrangian scheme is a multidimensional semi-lagrangian extension of the higher order Godunov-type finite-volume schemes (e.g., the piece-wise parabolic method). Unlike the piece-wise parabolic methodology, neither directional splitting nor a Riemann solver is involved. A reverse engineering procedure is introduced to achieve the goal of consistent transport of the absolute vorticity and the mass, and hence, the potential vorticity. Gravity waves are treated explicitly, in a manner that is consistent with the forward-in-time flux-form semi-Lagrangian transport scheme. Due to the finite-volume nature of the flux-form semi-lagrangian scheme and the application of the monotonicity constraint, which can be regarded as a subgrid-scale flux parametrization, essentially noise-free solutions are obtained without additional diffusion. Two selected shallow-water test cases proposed by Williamson et al. (1992) and a stratospheric vortex erosion simulation are presented. Discussions on the accuracy and computational efficiency are given based on the comparisons with a Eulerian spectral model and two advective-form semi-implicit semi-Lagrangian models.