1. Introduction
Over the past decade, a large effort has been focused on reconstructing Antarctic surface air temperature (SAT) from in situ, satellite, and reanalysis datasets, in order to gain a better understanding of how this highly sensitive region has been changing (Chapman and Walsh 2007; Monaghan et al. 2008; Steig et al. 2009; O’Donnell et al. 2011; Bromwich et al. 2013; Nicolas and Bromwich 2014). These reconstructions have revealed considerable spatial asymmetry and strong seasonality in SAT trends over the satellite era, including statistically significant warming in West Antarctica in austral spring [September–November (SON)] and, surprisingly, a clear although statistically insignificant cooling in East Antarctica in austral autumn [March–May (MAM)] (Schneider et al. 2012; Nicolas and Bromwich 2014; Smith and Polvani 2017).
A number of mechanisms have been suggested to explain these SAT trends, typically relating to changes in the atmospheric circulation associated either with stratospheric ozone depletion (Thompson and Solomon 2002; Marshall 2007; McLandress et al. 2011; Nicolas and Bromwich 2014) or with tropical teleconnections (Ding et al. 2011; Schneider et al. 2012; Simpkins et al. 2014; Li et al. 2014; Clem and Fogt 2015; Clem and Renwick 2015; Fogt and Wovrosh 2015).









We refer to this as the instantaneous radiative forcing at the TOA (hereafter,
This peculiar negative greenhouse effect, only found over the coldest regions of Antarctica, was originally observed by Hanel et al. (1972, see their Fig. 12d), using an infrared spectrometer aboard one of the early Nimbus-4 meteorological satellites. It has been recently examined in S15, who computed the nearly instantaneous
In this paper we confirm and extend the findings of S15. Specifically, using both an offline radiative transfer model and ensembles of fully coupled atmosphere–ocean–land–sea ice GCM integrations, we demonstrate that the while the
2. Methods
a. Models
The GCM we employ is the Specified Chemistry version of the Whole Atmosphere Community Climate Model (SC-WACCM), a stratosphere-resolving version of the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). The atmospheric component of SC-WACCM has 66 vertical levels with a model top at 140 km, a horizontal resolution of 1.9° × 2.5°, specialized parameterizations for gravity waves, and specified middle atmosphere chemistry [for details, see Smith et al. (2014)]. This atmospheric model is coupled to land, ocean, and sea ice components identical to those described in Marsh et al. (2013).
In addition to SC-WACCM, we use the Parallel Offline Radiative Transfer (PORT) model to calculate the instantaneous radiative forcing at the TOA and tropopause and the stratosphere-adjusted radiative forcing at the TOA following 4×CO2. We note that PORT consists of the radiative transfer component of SC-WACCM, and, when stratospheric temperatures are allowed to adjust radiatively, employs a fixed dynamical heating assumption above the tropopause but with tropospheric and surface properties held fixed (Conley et al. 2013).
b. Integrations
With PORT, we compute the seasonally varying instantaneous radiative forcing as the instantaneous LW flux difference between two PORT integrations with fixed temperatures throughout the troposphere and stratosphere: one with 4×CO2 (1148 ppm) and one with preindustrial CO2 concentrations (287 ppm) using the climatology from a single, 1-yr-long ensemble member of the preindustrial SC-WACCM integrations described below. We compute the instantaneous radiative forcing both at the TOA (
While PORT is an excellent tool for computing radiative forcing, it provides no information about the subsequent response of Antarctic SAT to 4×CO2 in the coupled climate system. To examine that response in the presence of all physically consistent model adjustments and feedbacks, we conduct a suite of 10-member SC-WACCM integration ensembles. To construct the 10-member ensembles, we perturb the initial conditions as in Kay et al. (2015). Specifically, from an existing 500-yr preindustrial control integration (Smith et al. 2014), for each month of the year we branch two 1-yr-long, 10-member ensembles of integrations, one with preindustrial forcings and one with 4×CO2, for a total of 240 integrations. For each pair of integrations, we then calculate the “instantaneous” radiative forcings (for SC-WACCM, we use the average over the first 5 days),
One final note about terminology: in the text below, the average over the 12 responses (one for initialization in each month) will be referred to as the “12-month mean” to distinguish it from the “annual mean,” which we reserve to indicate the mean over one calendar year of model integration, as customary in the climate literature. We also use the term “3-month mean” in an analogous way to describe the average over the responses for specific seasons.
3. Results
We start by illustrating the monthly vertical temperature profiles at the South Pole in SC-WACCM, averaged over the 500-yr preindustrial integration (Fig. 1). Clearly the stratospheric temperatures in the Antarctic exhibit a very large seasonal cycle, with a range of

Monthly vertical temperature profiles at the South Pole averaged over the 500-yr SC-WACCM preindustrial integration. Months that exhibit warmer stratospheric temperatures relative to surface temperatures are shown in the colored curves. All other months are shown as gray curves.
Citation: Journal of Climate 31, 1; 10.1175/JCLI-D-17-0418.1
We now use the PORT model to examine whether these temperature profiles, in combination with increased CO2 concentrations, indeed lead to a negative

(top) Shown are the (a) 12-month mean
Citation: Journal of Climate 31, 1; 10.1175/JCLI-D-17-0418.1
To transcend the limitations of PORT, and confirm the existence of this negative
Figures 2a and 2d, therefore, confirm the findings of S15, and leave little doubt as to the existence of a negative
Figure 2b is identical to Fig. 2a except that we now show
Stratospheric temperatures rapidly cool in response to a quadrupling of CO2 (
The rapid cooling of the stratosphere has a dramatic effect on the response of the TOA LW fluxes to 4×CO2. This is seen in Fig. 2c, where
We, therefore, arrive at the following key result: when the stratosphere is allowed to adjust, the

East Antarctic area-averaged ensemble-mean seasonal cycle of (a)
Citation: Journal of Climate 31, 1; 10.1175/JCLI-D-17-0418.1
We next turn our attention from the TOA to the surface, and ask the question that provides the ultimate motivation for this entire exercise: Can a large increase in CO2 actually lead to a surface cooling anywhere in Antarctica? Based on the above analysis, we do not expect any cooling at the surface in response to 4×CO2. Using our SC-WACCM integrations, we can now verify this directly. In other words, we can ask this: Is there any evidence for surface cooling in the initial few days after we quadruple CO2, when a statistically significant negative
The answer to this question is given in Fig. 4a, where we plot the ensemble mean and 12-month mean SAT response to 4×CO2 in SC-WACCM, averaged over the first five days of the integrations. Despite a negative

Ensemble and 12-month mean
Citation: Journal of Climate 31, 1; 10.1175/JCLI-D-17-0418.1
Finally, to elucidate the surface warming over East Antarctica in spite of the negative

East Antarctic area-averaged ensemble mean and 3-month mean differences in surface energy fluxes between the 4×CO2 and preindustrial SC-WACCM integrations (net surface energy flux:
Citation: Journal of Climate 31, 1; 10.1175/JCLI-D-17-0418.1
4. Conclusions
We have here confirmed the existence of a negative
We have also considered the coupled climate response and the possible impact of rapid climate feedbacks using the fully coupled GCM integrations, and shown that the peculiar negative
In closing, we note that our model integrations with a large and highly idealized forcing were not designed to precisely quantify how the negative
This work is supported by two awards (PLR-13-41657 and AGS-13-22439) from the U.S. National Science Foundation to Columbia University. The authors wish to express their gratitude to Dr. Stephen Warren, of the University of Washington, for bringing to their attention the work of Hanel et al. (1972). It is delightful, and a little humbling, to be able to revisit and expand upon a finding that is nearly half a century old.
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