In Part 2 of this two‐part paper, documentation is provided of key aspects 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). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

We describe the Geophysical Fluid Dynamics Laboratory's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the preindustrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high‐quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasiperiodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.

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.

A suite of the historical simulations run with the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models forced by greenhouse gases, aerosols, stratospheric ozone depletion, and volcanic eruptions and a second suite of simulations forced by increasing CO 2 concentrations alone are compared with observations for the reference interval 1965-2000. Surface air temperature trends are disaggregated by boreal cold (November-April) versus warm (May-October) seasons and by high latitude northern (N: 40°-90°N) versus southern (S: 60°S-40°N) domains. A dynamical adjustment is applied to remove the component of the coldseason surface air temperature trends (over land areas poleward of 40°N) that are attributable to changing atmospheric circulation patterns. The model simulations do not simulate the full extent of the wintertime warming over the high-latitude Northern Hemisphere continents during the later 20th century, much of which was dynamically induced. Expressed as fractions of the concurrent trend in global-mean sea surface temperature, the relative magnitude of the dynamically induced wintertime warming over domain N in the observations, the simulations with multiple forcings, and the runs forced by the buildup of greenhouse gases only is 7∶2∶1, and roughly comparable to the relative magnitude of the concurrent sea-level pressure trends. These results support the notion that the enhanced wintertime warming over high northern latitudes from 1965 to 2000 was mainly a reflection of unforced variability of the coupled climate system. Some of the simulations exhibit an enhancement of the warming along the Arctic coast, suggestive of exaggerated feedbacks.spatial patterns of warming | climate model diagnostics | dynamically-induced warming | polar amplification

[1] We analyzed the changes of simulated Brewer-Dobson circulation (BDC) for 1960-2099 from 12 chemistry climate models participating the Chemistry-Climate Model Validation activity phase 2 (CCMVal-2). We decomposed the BDC into transition, shallow, and deep branches with vertical extent of 100-70, 70-30, and above 30 hPa, respectively. Models consistently simulate the acceleration in all three BDC branches over 140 years, but the acceleration rate of the deep branches is much smaller. The acceleration rate of the transition and shallow branches in general shows weak seasonal or hemispheric dependence and increases with time, consistent with the continuous and homogeneous increase of greenhouse gas concentrations. The trend magnitudes of shallow and transition branches differ from model to model, which are found to be associated with the simulated changes in subtropical jets and tropical upper tropospheric temperature. The acceleration of the deep branch is also a response to the increase of greenhouse gas concentrations but is modulated by the changes in ozone concentrations. The effect of ozone changes is particularly prominent in the southern deep branch during austral summer: almost all models simulated strong significant acceleration during the ozone depletion era, weak deceleration during the ozone recovery era, and near-zero trends during the stable ozone era. However, the ozone effect is less evident in other seasons and in other branches.Citation: Lin, P. and Q. Fu (2013), Changes in various branches of the Brewer-Dobson circulation from an ensemble of chemistry climate models,

Abstract. This study examines the seasonality of tropical lower-stratospheric temperature trends using the Microwave Sounding Unit lower-stratospheric channel (T 4 ) for 1980-2008. We present evidence that this seasonality is largely a response to changes in the Brewer-Dobson circulation (BDC) driven by extratropical wave forcing. We show how the tropical T

Robust stratospheric temperature trend patterns are suggested in the winter and spring seasons in the Southern Hemisphere high latitudes from the satellite-borne Microwave Sounding Unit (MSU) measurement for 1979–2007. These patterns serve as indicators of key processes governing temperature and ozone changes in the Antarctic. The observed patterns are characterized by cooling and warming regions of comparable magnitudes, with the strongest local trends occurring in September and October. In September, ozone depletion induces radiative cooling, and strengthening of the Brewer–Dobson circulation (BDC) induces dynamical warming. Because the trends induced by these two processes are centered in different locations in September, they do not cancel each other, but rather produce a wavelike structure. In contrast, during October, the ozone-induced radiative cooling and the BDC-induced warming exhibit a more zonally symmetric structure than in September, and hence largely cancel each other. However, the October quasi-stationary planetary wavenumber 1 has shifted eastward from 1979 to 2007, producing a zonal wavenumber-1 trend structure, which dominates the observed temperature trend pattern. Simulated temperature changes for 1979–2007 from coupled atmosphere–ocean general circulation model (AOGCM) experiments run for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) are compared with the observations. In general, the simulated temperature changes are dominated by zonally symmetric ozone-induced radiative cooling. The models fail to simulate the warming in the southern polar stratosphere, implying a lack of the BDC strengthening in these models. They also fail to simulate the quasi-stationary planetary wave changes observed in October and November.

The influence of atmospheric circulation changes reflected in spontaneously occurring sea level pressure (SLP) anomalies upon surface air temperature (SAT) variability and trends is investigated using partial least squares (PLS) regression, a statistical method that seeks to maximally explain covariance between a predictand time series or field and a predictor field. Applying PLS regression in any one of the three variants described in this study (pointwise, PC-wise, and fieldwise), the method yields a dynamical adjustment to the observed NH SAT field that accounts for approximately 50% of the variance in monthly mean, cold season data. It is shown that PLS regression provides a more parsimonious and statistically robust dynamical adjustment than an adjustment method based on the leading principal components of the extratropical SLP field. The usefulness of dynamical adjustment is demonstrated by applying it to the attribution of cold season SAT trends in two reference intervals: 1965–2000 and 1920–2011. The adjustment is shown to reconcile much of the spatial structure and seasonal differences in the observed SAT trends. The dynamically adjusted SAT fields obtained from this analysis provide datasets capable of being analyzed for residual variability and trends associated with thermodynamic and radiative processes.