# Last millennium climate changes over the Antarctic Peninsula and southern Patagonia in CESM-LME simulations: Differences between Medieval Climate Anomaly and present-day temperatures

Gabriel Silvestri, Ana Laura Berman, Francois de Vleeschouwer, Ilana Wainer

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Gabriel Silvestri, Ana Laura Berman, Francois de Vleeschouwer, Ilana Wainer. Last millennium climate changes over the Antarctic Peninsula and southern Patagonia in CESM-LME simulations: Differences between Medieval Climate Anomaly and present-day temperatures. Quaternary Science Reviews, 2021, 274, pp.107273. 10.1016/j.quascirev.2021.107273. hal-03835366

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1 Last millennium climate changes over the Antarctic Peninsula and southern Patagonia

2 in CESM-LME simulations: differences between Medieval Climate Anomaly and

3 present-day temperatures

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Gabriel Silvestri ¹,²,³ – Ana Laura Berman ¹,²,³ – Francois De Vleeschouwer ³ – Ilana Wainer ⁴

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(1) Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales. Buenos Aires, Argentina.

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(2) CONICET – Universidad de Buenos Aires. Centro de Investigaciones del Mar y la Atmósfera (CIMA). Buenos Aires, Argentina.

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**Corresponding author:**

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Gabriel E. Silvestri

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E-mail: gabriels@cima.fcen.uba.ar

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**Abstract**

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This paper describes differences between Medieval Climate Anomaly (MCA) and present-day temperatures in the area composed of the Antarctic Peninsula, southern Patagonia, and the surrounding southern oceans. The investigation is conducted with the simulation results from the Community Earth System Model Last Millennium Ensemble (CESM-LME) considering the impact of each natural (volcanic activity and solar variability) and anthropogenic (greenhouse gas, ozone-aerosols and land use/land cover) individual forcing relative to the full forced simulations. Model results show generalized warming during the MCA in the study area.

However, the simulated MCA temperatures are significantly colder than present-day mean values due to the influence of increased atmospheric greenhouse gas concentrations since the beginning of the modern Industrial Era in the ~1850s. In fact, model runs in which only natural forcings were applied show that, in the absence of greenhouse gas forcing, present-day temperatures in the Antarctic Peninsula and southern Patagonia would be lower than or similar to those during the MCA. The study demonstrates the value of paleoclimate proxy-model comparisons but also highlights the limitations of current available proxy information to perform that integration in the study area.

**Keywords:** Antarctic Peninsula; Patagonia; Medieval Climate Anomaly; Little Ice Age; last millennium; CESM-LME simulations
1. Introduction

The Antarctic Peninsula (AP) is a narrow stretch of land of complex topography surrounded by the Southern Ocean (Fig. 1). Continuous long-term observational records of surface temperature in the AP are only available from a very few meteorological stations. The longest record is Orcadas, which started in 1903, while continuous records from other scientific stations started around the middle of the 20th century. Based on this information, several studies reported unusual warming through the second half of the twentieth century. In fact, the available meteorological information reveals significant warming across the AP since the 1950s representing the largest increases in near-surface air temperature in the Southern Hemisphere (e.g., Vaughan et al., 2003; Turner et al., 2005; Richard et al., 2013). This exceptional 50-year warming is not just a local phenomenon but part of a significant 100-year regional warming trend that began around the 1900s (e.g., Thomas et al., 2009; Jones et al., 2016). Additionally, paleoclimatic reconstructions suggest that this 100-year trend in the AP is unusual in the context of natural century-scale trends over the last 2000 years (Stenni et al., 2017). Changes in large-scale atmospheric circulation modes, regional pressure/wind systems, stratospheric ozone depletion, and local sea ice loss have been suggested as forcings of the pronounced 20th century warming in the AP (e.g., Thompson and Solomon, 2002; Marshall et al., 2006; Ding et al., 2011; Schneider et al., 2012; Turner et al., 2012; Ding and Steig, 2013; Goodwin et al., 2016; Raphael et al., 2016). Significant accelerated increase of temperature was also detected in the upper ocean west of the AP indicating that the pronounced warming registered in the region is not restricted to the atmosphere but also includes the adjacent upper-layer oceanic waters (Meredith and King, 2005). After this pronounced warming, AP temperature decreased during the first part of the twenty-first century (e.g., Carrasco, 2013; Turner et al., 2016; Oliva et al., 2017; Jones et al., 2019; Turner et al., 2019), but it is still unclear if this cooling represents robust evidence of change of sign in the long-term evolution of regional temperature (Gonzalez
and Fortuny, 2018; Carrasco et al., 2021). For the Antarctic continent, evaluations of station data since ~1950 show uneven distribution of temperature trends, with heating of 0.55°C/decade at the San Martin meteorological station in the western AP and cooling of ~0.06°C/decade registered at the Zhongshan meteorological station in the Larsemann Hills of East Antarctica (Silva et al., 2019). Supplementary Material 1 provides additional information regarding linear trends in the AP during the last decades of the 20th century.

Separated from the AP by the Drake Passage, southern Patagonia (SPat) is the continental landmass nearest to the AP (Fig. 1). Here the complex topography of the southern Andes has a significant impact on the regional climate (e.g., Berman et al., 2012, 2013). Long-term information of temperature in SPat is scarce. Although there are several meteorological stations located in this region, their records have large gaps or only cover short periods making it difficult to detect significant changes and/or trends at regional scale. With this limitation, the few available meteorological records suggest a moderate increase in temperature during the last decades of the 20th century with a linear trend markedly lower than that detected in the AP (see more details in Supplementary Material 1).

Although the increase in temperature through the second half of the twentieth century is unusual since meteorological records in many regions of the world began, paleoclimatic studies suggest that it is not the only relatively warm period that has occurred during the last millennium (e.g., Neukom et al., 2014; Ljungqvist et al., 2019). In fact, last-millennium temperature evolution at global, regional and local scales has been reconstructed from a wide variety of climate proxy data and coupled atmosphere-ocean general circulation models (AOGCMs). Among other useful climate information, these reconstructions have focused in particular on the characteristics of two significant time-periods: the Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA). In general terms, proxy-based reconstructions and model simulations of temperature during the past millennium characterize the MCA as a relatively
warm period developed between ca. 950 and ca. 1250 and the LIA as a relatively cold period
which extended from ca. 1450 to ca. 1850 (e.g., Mann et al., 2009; Neukom et al., 2011; Diaz
et al., 2011; Landrum et al., 2013; Ljungqvist et al., 2019; Neukom et al., 2019). However, there
is evidence that the specific timing of peak MCA warmth and LIA cold intervals varies
regionally resulting in regionally specific temperature departures from a global mean state in
each period (e.g., PAGES2k Consortium, 2013).

While the AP and SPat are the only continental landmasses in the Western Hemisphere
between 45°S and 70°S and contain several sites with valuable information regarding past
climate conditions at high Southern Hemisphere latitudes, there is still a lack of studies that aim
to evaluate their past millennial changes in the absence of anthropogenic forcing. This
knowledge is essential to better understanding past climate evolution and might provide useful
information to improve scenarios of future climate change in both regions as well as the
surrounding Southern Ocean that comprise the widest present-day oceanic areas of ecological
significance in austral latitudes (e.g., Hindell et al., 2020). In this context, numerical simulations
performed with the most advanced AOGCMs contain complete representations of climate
system components allowing detailed descriptions of past and present temperature at global
and/or regional scale. In particular, the Community Earth System Model Last Millennium
Ensemble (CESM-LME) modeling project (Otto-Bliesner et al., 2016) provides a description
of climate evolution since the year 850 considering the influence of all natural (volcanic
eruptions, orbital changes, solar irradiance) and anthropogenic (greenhouse gas emissions,
ozone and tropospheric aerosols, land use/land cover changes) forcings simultaneously, as well
as the impact of each forcing individually (see Section 2). In other words, CESM-LME
simulations provide crucial information to describe differences between past and present-day
temperatures identifying which forcing might be responsible for temperature changes from the
MCA to the present. At middle and high latitudes of the Southern Hemisphere, CESM-LME
outputs were first employed by Marcello et al. (2019), Tonelli et al. (2019), Verona et al. (2019), and Wainer and Gent (2019) providing innovative pictures of changes in waters of the southern South Atlantic and the Weddell Sea through the last millennium. Consequently, we aim to use the available set of CESM-LME simulations to answer the following two specific questions: 1) How different were MCA temperatures from present-day mean values in the AP and SPat? 2) What was the contribution of each individual forcing (natural and anthropogenic)? Answering these questions is essential for a better understanding of the influence of natural and anthropogenic forcings on past climate changes documented in the region. Although CESM-LME simulations provide crucial information for this research, it is important to mention that AOGCMs with coarse spatial resolutions prevent a correct reproduction of climate processes at a local scale in areas of complex topography such as the AP and SPat. As a result, modeled regional climate conditions may differ from those provided by models with higher spatial resolution (e.g., Bozkurt et al., 2021). In this context, information from proxy records is included in the study to provide a more complete picture of past regional temperatures and, in particular, to evaluate the performance of the model in reproducing those conditions.

The manuscript is organized as follows. Section 2 describes model simulations and methodology. Section 3 shows temperature changes between the MCA and the present isolating the influence of individual forcings on those changes and also on anomalies involving LIA mean conditions. Section 4 discusses available proxy-based reconstructions and how well model results agree with that information. Section 5 summarizes the main conclusions.

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## 2. Model simulations and methodology

In this study, the simulation results from the Community Earth System Model Last Millennium Ensemble experiment (CESM-LME) are used
(http://www.cesm.ucar.edu/projects/community-projects/LME). CESM is a fully coupled general circulation model linking atmosphere, ocean, land, and sea ice components of the climate system developed at the National Center for Atmospheric Research (NCAR). This model uses the version 1.1 of CESM with the Community Atmosphere Model version 5 (CESM1-CAM5) run at ~2° resolution in the atmosphere and land components and ~1° resolution in the ocean and sea ice components. Detailed descriptions of the model can be found in Danabasoglu et al. (2012), Hurrell et al. (2013) and Otto-Bliesner et al. (2016). Simulations span the years 850 to 2005 providing an ensemble of last millennium conditions based on the fifth Coupled Model Intercomparison Project (CMIP5) climate forcing reconstructions (Schmidt et al., 2011, 2012). Characteristics of each climate forcing are listed in Otto-Bliesner et al. (2016). However, some relevant issues are briefly mentioned here in order to simplify descriptions of model-based results.

The prescribed forcings associated with drivers of climate through the last millennium consist of variations in greenhouse gas concentrations, stratospheric ozone, atmospheric aerosols, volcanic activity, land use and land cover, Earth's orbital parameters (eccentricity, obliquity and precession) and solar radiance. Although there are uncertainties in the estimation of each individual forcing during the last millennium, all of them were determined by the availability of data and the current state of knowledge intending to have the most realistic description of natural and anthropogenic past climate drivers. The set of CESM-LME experiments comprises simulations containing all documented forcings simultaneously as well as single-forcing simulations. The single-forcing experiments describe the influence of one specific forcing on the simulated climate variability and changes through the millennium while the others remain fixed at their level in the year 850. For example, the "volcanic experiment" describes climate evolution from the year 850 to the present associated only with the action of volcanic activity without the influence of any other external forcing.
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Model outputs employed in this paper consist of an ensemble of thirteen simulations with the full-set of external forcings, three simulations forced only with changes in greenhouse gas concentrations, five forced only with changes in ozone and aerosols, five forced only with volcanic eruptions, three forced only with changes in land use and land cover, three forced only with orbital changes, and four forced only with changes in solar activity. Differences among ensemble members of each specific forcing are produced by the application of small random round-off difference in the air temperature field at the start of each ensemble member. Details of the simulations can be found in Otto-Bliesner et al. (2016).

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The analysis is focused on annual mean surface temperature in the AP and SPat but also includes the surrounding Southern Ocean (Fig. 1). Hereafter, “last millennium” (LM) refers to the period 850-1850, MCA refers to the period 950-1250, LIA refers to the period 1450-1850, L19C refers to the late 19th century (1850-1899), E20C refers to the early 20th century (1900-1949), and “present-day” (PD) refers to the modern period 1970-2005. The statistical significance of differences of temperature and linear trends are assessed using the Student's t-test (Wilks, 2006).

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Validations of model outputs against observed records is essential in order to ensure reliability of information provided by simulations. However, results displayed in Section 4 demonstrate that detailed comparisons between simulated past climate conditions and proxy-based reconstructions from the AP and SPat are difficult because paleorecords from these regions exhibit a lack of regional coherency in the sign and intensity of temperature changes through the last millennium. In contrast, available present-day meteorological information shows that CESM-LME simulations reproduce the linear trends in annual mean surface temperature over the AP and SPat observed during the last decades of the 20th century (see Supplementary Material 1). The model is also able to reproduce the observed annual sea ice limit (Fig. 1a) and the annual mean sea level pressure field (Fig. 1c) over the study region.
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## 3. Results of CESM-LME simulations

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CESM-LME results show clear evidence of generalized warm climate conditions during the MCA with respect to mean conditions during the LM (Fig. 2a) and LIA (Fig. 2b) over the entire study area. Modeled MCA temperatures in the AP and SPat are, respectively, 0.18°C and 0.06°C warmer than the LM mean value and 0.34°C and 0.11°C warmer than during the LIA.

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In both regions, modeled temperature evolution imply that the LM is colder than [$M_{MCA} - 1\sigma_{MCA}$] and that the LIA is colder than [$M_{MCA} - 2\sigma_{MCA}$] where $M_{MCA}$ and $\sigma_{MCA}$ are, respectively, the statistical mean and standard deviation of decadal mean temperature in the MCA period. Additionally, the more pronounced MCA warming with respect to the LIA rather than with respect to the LM is consequence of generalized LIA cooling (Fig. 2c). In this context, modeled LIA temperatures in the AP and SPat are, respectively, 0.16°C and 0.04°C colder than LM mean values being also colder than [$M_{LM} - 0.5 \sigma_{LM}$]. Long-term negative linear trends in surface temperature developed through the LM are closely related to the climate differences showed in Fig. 2. In fact, modeled temperatures show slight negative trends in the period 850-1849 (Fig. 3a) contrasting with pronounced positive trends in 1850-2005 (Fig. 3b). The sign and intensity of trends in each period explain the significant present-day warming in the context of the past millennium climate evolution (Fig. 3c).

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Since the set of CESM-LME experiments contains simulations involving full and single forcing runs, the evolution of the climate system (represented by simulations containing all forcings simultaneously) can be compared with their single-forcing equivalent. This information is essential in order to infer causes of temperature changes since medieval times documented in the study area. Differences between MCA and PD surface temperatures

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extracted from all available CESM-LME simulations are shown in figures 4 and 5. The main
aspects of these differences are described in the following paragraphs.

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221 3.1. All forcings simultaneously (full-forcing simulation)

222 In the context of climate variability through the last millennium, the pronounced
223 increase of temperature since the beginning of the Industrial Era in ~1850s produced unusually
224 warm conditions in the entire study area (Fig. 3c, Table 1a). This regional warming is reflected
225 in the mean temperatures during late 19th century (1850-1899 period), early 20th century (1900-
226 1949 period) and PD (1970-2005 period) in the AP and SPat (Fig. 4). CESM-LME simulations
227 indicate that PD temperatures are 0.85°C and 0.40°C warmer than during the MCA in the AP
228 and SPat respectively. In both cases, PD temperatures clearly exceeds the value [M<sub>MCA</sub> +
229 2σ<sub>MCA</sub>] (Fig. 4). The spatial field of differences between PD and MCA temperatures also shows
230 statistically significant warming over most of the surrounding Southern Ocean (Fig. 5a). The
231 most intense temperature anomalies (~1.3°C) developed at latitudes of the AP (~60°-70°S)
232 could be a consequence of reduced sea ice during the PD compared to the MCA (e.g., Landrum
233 et al., 2013; Otto-Bliesner et al., 2016; Tonelli et al., 2019). Cold and statistically non-
234 significant anomalies suggested by the model in part of the Drake Passage indicate that the
235 pronounced warming through the last century has not yet reversed the long-term preindustrial
236 cooling in that area.
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238 3.2. Volcanic eruptions (VOLC simulation)

239 Volcanic aerosols reflect incident solar radiation back to space affecting net solar flux
240 at the surface and, in consequence, modify surface and near-surface temperature. Explosive
241 volcanism appears to exert a significant influence on the temporal evolution of hemispheric and
242 regional temperature changes through the LM (e.g., Diaz et al., 2011 and references therein).

243 In particular, volcanic eruptions can induce significant warming in the Weddell Sea side of the
244 AP due to changes in high-latitude westerlies and interactions with the Weddell Gyre (Verona
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246 Under the influence of this only forcing, CESM-LME simulations suggest that PD
247 temperatures are markedly lower than those simulated with all forcings (Table 2 and
248 Supplementary Fig. S2a in Supplementary Material 2). The lack of significant linear trends
249 since the ~1850s (Fig. 6b) indicates that the long-term LM cooling (Fig. 3a) was not reversed
250 by the action of only volcanic activity in the last century. As a result, PD temperatures are lower
251 than MCA values over the entire region (Figs. 4 and 5b, Table 1b), and are also slightly lower
252 than or similar to LIA mean conditions (Figs. 4 and 7b, Table 1c). In other words, present-day
253 climate would be colder than the MCA and also colder than, or similar to, the LIA if the only
254 forcing of climate change since ~1850s was the volcanic activity. This feature indicates that it
255 is unlikely that changes only in volcanic activity since the ~1850s provoked temperature
256 changes between the MCA and PD (and also between the LIA and PD) as those inferred in the
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259 3.3. Orbital position and solar irradiance (ORB and SOL simulations)

260 Changes in the Earth's orbital position (eccentricity, obliquity and precession) and solar
261 irradiance affect the seasonal distribution and latitudinal intensity of insolation. CESM-LME
262 simulations suggest that only changes in each of these forcings, that imply increased insolation
263 through the last century (Otto-Bliesner et al., 2016), induce a slight temperature increase since
264 ~1850s. However, the corresponding linear trends are not statistically significant at the 95%
265 level over wide parts of the study area, especially in the ORB simulation (Figs. 6c-d).
Temperature trends are statistically significant in regions where sea ice exists for at least part of the year (see sea ice limit in Fig. 1a). This feature suggests an important role for positive sea ice-albedo feedback. In fact, increased insolation associated with both individual forcings promotes warm surface conditions that, in turn, might induce sea ice melting. Reduced sea ice cover is associated with reduced surface albedo and, as consequence, increased absorption of solar energy leading to warmer conditions in the upper water column of Antarctic seas. Taking into account that the sea ice cover around the AP has a marked annual cycle (e.g., King et al., 2003), detailed descriptions of sea ice-albedo feedbacks should be done at a seasonal scale but that analysis is beyond the scope of this paper.

Considering the influence of each of these forcings, PD temperatures are colder than real values (Table 2, Supplementary Figs. S2b-c) but the slight increase of temperature since ~1850s is sufficient to reverse the LM cooling. In fact, PD temperatures would be similar to the MCA (Figs. 4 and 5c-d, Table 1b) and warmer than the LIA (Figs. 4 and 7c-d, Table 1c) over most of the region if the only forcing of climate change through the last century were changes in orbital parameters or solar irradiance. These results indicate that the simulated increase of temperature during the last century is partly forced by changes in these individual forcings. However, the corresponding temperature anomalies (Table 1a) demonstrate that the contribution of both forcings is very small. In other words, CESM-LME simulations suggest that changes in orbital position and solar irradiance reversed the last-millennium cold trend but it is unlikely that the action of each of these two forcings alone since the ~1850s produced significant differences of temperature between the MCA and PD (and also between the LIA and PD) as those inferred in the study area.

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## 3.4. Greenhouse gas (GHG simulation)

CESM-LME simulations indicate that the accelerated warming since the beginning of the Industrial Era would have been even more pronounced if climate variability were produced only by changes in GHG concentrations. In fact, PD temperatures associated only with GHG forcing are warmer than those produced by the action of all forcings simultaneously (Table 2, Supplementary Fig. S2d). This feature is associated with the more pronounced positive linear trends since the ~1850s in response to only GHG forcing compared to trends induced by simultaneous action of all forcings (Figs. 6a and 6e). In light of these results, the intensity of modern warming due to the increase of GHG concentrations alone must be weakened by the influence of the other forcings in order to have regional temperatures similar to the real values defined by the full-forcing experiment. More pronounced warming due to only changes in GHG concentrations since the ~1850s would produce more intense PD warming with respect to the MCA (Figs. 4, 5a and 5e, Table 1b) and the LIA (Figs. 4, 7a and 7e, Table 1c). In other words, CESM-LME simulations indicate that it is likely that the other forcings reduce the impact of exclusive changes in GHG concentrations since the ~1850s in order to have differences of temperature between the MCA and PD (and also between the LIA and PD) as those inferred in the study area.

## 3.5. Ozone and aerosols (O3/AER simulation)

It is well-known that atmospheric ozone absorbs incoming solar shortwave radiation as well as longwave radiation emitted by the Earth's surface. Consequently, ozone losses (increases) induce tropospheric cooling (warming) that affect surface climates, especially in middle and high latitudes of the Southern Hemisphere. In this context, anthropogenic activities produced significant reduction of stratospheric ozone over the Antarctic from the 1970s through
the mid-2000s (period considered as “the present” in this study), that, in turn, led to significant radiative cooling of the stratosphere in the Southern Hemisphere (e.g., Randel et al., 2009).

Previous studies (e.g., Bandoro et al., 2014 and references therein) have proposed that changes in Antarctic ozone concentration modify stratospheric meridional gradients of temperature that, in turn, produce changes in stratospheric flows. Due to dynamical stratospheric-tropospheric coupling, circulation changes extend to the Earth’s surface inducing changes in surface temperatures. In other words, stratospheric temperature changes propagate to the surface but this is largely an indirect effect through coupled stratospheric-tropospheric circulation processes. Descriptions of temperature changes at seasonal scale and lagged tropospheric responses to stratospheric changes are beyond the scope of this paper. As an example of changes at seasonal scale, the stratospheric cooling during 1970s-2000s in response to ozone depletion was detected in austral spring-summer having a lack of significant temperature change in autumn-winter (Previdi and Polvani, 2014). This feature is consistent with the fact that changes in stratospheric ozone is unlikely to have played a significant role in the large winter warming observed in western Antarctic Peninsula during the late 20th century (Roscoe et al., 2006).

In addition to the impact of changes in ozone concentrations, changes in stratospheric aerosols concentrations also affect the global energy balance because these particles absorb both shortwave and longwave radiation. With these considerations, CESM-LME simulation results suggest that PD temperature would be colder than real values if the only forcing of climate variability were changes in ozone and stratospheric aerosols (Table 2, Supplementary Fig. S2e). Negative trends for the 1850–2005 period can be seen in Fig. 6f. As a consequence of this cooling, PD temperatures would be lower than MCA values over the entire study area (Figs. 4 and 5f, Table 1b). Furthermore, PD temperatures would be colder than LIA conditions (Figs. 4 and 7f, Table 1c). These results indicate that reconstructed temperature changes in the last millennium were not produced only by the influence of this forcing on the climate system.
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## 3.6. Land use/land cover (LAND simulation)

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Human activities through the last millennium have markedly changed the Earth's surface due to the adoption of agriculture and the transformation of natural forests, grasslands, and shrublands into agricultural areas. As consequence, it is expected that some land surface properties, like albedo and latent-sensible heat fluxes, were locally affected. In order to describe this anthropogenic influence on the climate system, CESM-LME simulations include experiments that consider changes in plant functional types for crops and pasture. In response to the influence of this individual forcing, the LM long-term cooling was not reversed due to the lack of significant linear trends in temperature since the ~1850s (Fig. 6g). Consequently, PD climate in the study area would be colder than real mean conditions (Table 2, Supplementary Fig. S2f) as well as colder than the MCA (Figs. 4 and 5g, Table 1b). Moreover, PD temperature would be slightly colder than and similar to the LIA in the AP and SPat respectively (Figs. 4 and 7g, Table 1c). These results suggest that reconstructed temperature changes between the MCA and PD (and also between the LIA and PD) were not produced by the action of this individual forcing alone.

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Results summarized in the previous paragraphs describe the influence of each individual forcing on temperature evolution through the past millennium. However, the present-day warming with respect to MCA mean conditions, and also with respect to LIA mean conditions, inferred from simulations that consider all forcings simultaneously is substantially different to the sum of temperature changes produced by the individual forcings (Table 3). In other words, results provided by the full-forcing simulation differ from a linear additivity of responses to single-forcing simulations. This feature is a consequence of nonlinear interactions between sub-
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systems of the climate system that are captured in model simulations. Nonlinearities may arise
from different processes as positive ice-temperature feedbacks in polar regions (e.g., Goosse et
al., 2018; Frew et al., 2019) and the opposite radiative effect of GHG and anthropogenic
aerosols forcings (e.g., Feichter et al., 2004; Deng et al., 2020).

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4. Comparison between model results and paleotemperature proxy data

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Paleoclimate proxies and climate models constitute two complementary sources of
information on past climate conditions. However, performing detailed evaluations on the
realism of numerical model simulations of temperature changes and trends against proxy-based
reconstructions is a challenge due to the lack of continuous quality-controlled temperature-
sensitive records distributed over the AP and SPat. Although there is a marked scarcity of
information from both areas, significant progress has been made in using the available proxy
data to reconstruct climate changes and trends through past centuries. These reconstructions are
extrapolated from a variety of archives (e.g., marine, ice, lake and peat sediments, tree-rings,
speleothems, glacial dynamics) which diversifies the source of palaeoclimatic information over
the last millennium. Nevertheless, compilations of proxy information show regional
incoherencies in the sign and intensity of reconstructed temperature changes. In consequence,
the available proxy data has limitations to performing detailed proxy-model comparisons.
Disagreements among different proxy-based temperature reconstructions can be summarized
as follows.

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Mann et al. (2009) used a global climate proxy network to reconstruct annual surface
temperature patterns over the last 1500 years. Although this reconstruction allows description
of temperature evolution at a regional scale, the authors mention that reconstructions are most
reliable over the Northern Hemisphere and the Tropics, and least reliable in the Southern
387 Hemisphere, particularly in the extra-tropical areas. In this context, temperature reconstructions
388 for the AP and SPat are shown in Fig. 8a and Tables 4a-b. In the AP, the MCA was colder than
389 the PD (and also colder than the LIA and LM) and positive linear trend through the LM (i.e.,
390 the 850-1849 period) became more pronounced since the ~1850s. In SPat, the MCA was colder
391 than the PD (and warmer than the LIA and LM) but negative linear trends through the LM
392 reversed since the ~1850s.

393 Neukom et al. (2011) reconstructed austral summer surface air temperature fields in the
394 period 900-1995 using annually resolved predictors from natural and human archives in
395 southern South America. Reconstructed conditions in SPat suggest that the MCA was colder
396 than PD (and warmer than the LIA but similar to the LM) and negative linear trends developed
397 through the LM reversed since the ~1850s (Fig. 8b and Table 4c).

398 Stenni et al. (2017) used a paleoclimate database of Antarctic ice core isotope records
399 to reconstruct regional temperatures of the past 2000 years on a decadal scale. Results for the
400 AP are shown in Fig. 8c and Table 4a. These reconstructions suggest a lack of significant
401 difference between the MCA, LIA and LM conditions which is coherent with the lack of
402 significant linear trend through the LM. In contrast, positive linear trends since the ~1850s
403 produce significant PD warming with respect to the MCA, LIA and LM mean conditions.

404 Climate reconstructions from individual proxies also provide useful descriptions of past
405 temperature conditions in the AP and SPat. A group of available reconstructions are
406 summarized in Fig. 9 and Supplementary Material 3. Site descriptions, illustrations and
407 references are detailed in the Supplements of Lüning et al. 2019a and Lüning et al. 2019b. Proxy
408 information in the AP suggests: MCA warmer than LIA in sites 1, 2, 4, 6 and 9; MCA colder
409 than LIA in site 5; MCA similar to or warmer than PD in sites 1, 3, 7 and 8. Proxy information
410

in SPat suggests: MCA warmer than LIA in sites 10, 11, 13, 14, 15, 16, 17 and 18; MCA warmer
than PD in sites 10 and 11; MCA colder than PD in site 12.

411

412

The results summarized above clearly point to marked disagreements among different
proxy-based reconstructions of the temperature changes during the last millennium in the study
area. In fact, past temperature in the AP extracted from Mann's and Stenni's reconstructions
disagree in the sign of changes through pre-Industrial times, but agree in describing MCA (and
LIA) temperatures colder than those of the PD. Clear discrepancies also exist between
information extracted from both reconstructions and climate conditions inferred from
individual proxies due to it having been suggested that the MCA was warmer than the LIA and
similar to or warmer than PD in some specific sites (see Fig. 9a). Disagreements among proxy
records make it difficult to compare against model results because the proxy-based information
turn into unclear. In this context, temperature evolution in the AP described by the CESM-LME
full-forcing simulation (synthetized in Table 4a) indicates MCA mean conditions warmer than
those of the LIA and LM but colder than PD which is consistent with negative linear trends
through LM reversed since the ~1850s. These features are qualitatively similar to the
information extracted from sites 2, 4, 6 and 9 (which describe the MCA warmer than LIA; see
Fig. 9a) but disagree with paleorecords of sites 1, 3, 5, 7 and 8 (Fig. 9a) and also disagree with
reconstructions of Mann and Stenni (Table 4a).

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

Regarding past temperature in SPat, individual proxies describing the MCA colder than
PD but warmer than the LIA (Fig. 9b) agree with reconstructions of Mann and Neukom but
individual proxies suggesting an MCA warmer than PD disagree with those reconstructions.
Although intensities of changes in annual temperature reconstructed by Mann tend to be higher
than those simulated by the model (Table 4b), there are qualitative agreements in the sign of
annual changes and trends in all considered time-periods. Additionally, qualitative agreements
are observed between summer changes and trends reconstructed by Neukom and simulated by

429

430

431

432

433

434
the model (Table 4c) being differences of MCA and LIA with respect to LM the most noticeable disagreement between proxy records and modeled temperatures.

Although proxy records provide crucial information to validate numerical model simulations, palaeotemperature reconstructions based on natural archives display a certain degree of uncertainty inherent to the reconstruction process. Furthermore, information extracted from palaeoproxies located in mountainous areas (as those of the AP and SPat) may be affected by local atmospheric dynamics (e.g., katabatic winds). In this context, the complex topography of the AP generates uncertainties with respect to the spatial representativeness of information extracted from each individual site as local temperature may change significantly over short distances (e.g., van Wessem et al., 2015). Likewise, most sites with palaeotemperature information in SPat are located in the hinterland of the southern Andes Cordillera that induces pronounced temperature gradients through the mountains (e.g., Garreaud et al., 2013). In addition, part of available proxy information in the AP and SPat is extracted from marine and lake cores (see Supplementary Material 3) that may be affected by specific processes (e.g., upwelling, meltwater input) and, as a result, these records may not reflect atmospheric temperature conditions. Consequently, information from available individual proxies should be treated with caution when comparing proxy-based to model-based results in the AP and SPat. In other words, the available proxy network makes it challenging to infer high-quality and reliable reconstructions of mean temperature to contrast against numerical simulations in both study regions.

Discrepancies among different proxy-based reconstructions affect validations of the CESM-LME simulations but also affect validations of numerical simulations performed with any other global (e.g., PMIP4 in https://pmip.lsce.ipsl.fr) or regional model that can be used to study climate evolution through the last millennium in the study area. Coherency among different proxy-based reconstructions of last millennium temperature over the AP, SPat and
460

surrounding Southern Ocean is essential in order to have the opportunity to perform detailed
validations of paleoclimatic numerical simulations in the region.

461

462

463

5. Conclusions and final remarks

464

This paper shows the contribution of individual natural and anthropogenic forcing to
465
466 differences between the MCA and PD surface temperatures over the Antarctic Peninsula,
southern Patagonia and the surrounding Southern Ocean based on simulations of the CESM-
467
468 LME project. Model simulations suggest that MCA temperatures were warmer than mean
conditions during the LM and LIA periods in the entire study area. Furthermore, there is a
469
470 pronounced PD warming with respect to MCA conditions which is a consequence of increased
GHG concentrations since the beginning of the Industrial Era in the ~1850s. Although changes
471
472 in orbital parameters and solar irradiance induced a slight increase in regional temperature
reversing the last-millennium cold trends, this impact remains low and it is unlikely that each
473
474 of these two forcings alone has had a significant contribution to the real difference between
medieval and present-day temperature in the study area. Model results also show that the action
475
476 of volcanic eruptions, changes in ozone and stratospheric aerosols, and changes in land
cover/land use tended to reduce the modern increment of temperatures. In summary, CESM-
477
478 LME simulations indicate that present-day climate is warmer than MCA mean conditions due
479 to the increase in GHG concentrations since the ~1850s. Furthermore, it is very likely that
modern temperatures would be colder than those of medieval times if this anthropogenic forcing
480
481 were absent.

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

Although proxy records provide crucial information to validate numerical model
simulations, paleotemperature reconstructions available in the AP and SPat contain
uncertainties inherent to the reconstruction process but also exhibit a lack of regional coherency

482

483
484 in the sign and intensity of temperature changes through the last millennium. Temperature
485 changes described by the CESM-LME simulations partly agree with the available paleorecords.

486 However, disagreements among proxy reconstructions make it difficult to validate model
487 results. In consequence, further analyses should be done in order to improve descriptions of
488 temperature evolution through the last millennium in the study area. In particular, to have a
489 high-quality network of climate proxy records providing coherent reconstructions of
490 temperature through the entire millennium is crucial to evaluate the validity of numerical model
491 simulations. It is also essential that proxy information captures the spatial configuration of
492 temperature changes through the whole millennium avoiding masking significant aspects of
493 that spatial variation. Regarding numerical simulations of last millennium climate evolution,
494 upcoming studies based on state-of-the-art multimodel experiments from the Paleoclimate
495 Modelling Intercomparison Project – Phase 4 (PMIP4) will allow quantifications of inter-model
496 differences in defining MCA temperature anomalies with respect to PD conditions, as well as
497 the influence of natural and anthropogenic forcings on those anomalies. However, simulations
498 performed with high-resolution regional models might be ideal to capture climate conditions in
499 this challenging study region.

500

501

502 Acknowledgments

503 The authors appreciate comments and suggestions provided by Professor Colm O'Cofaigh, Dr.

504 John King and an anonymous reviewer which were very helpful in improving this paper.

505 Authors also acknowledge the CESM1 (CAM5) Last Millennium Ensemble Community

506 Project and supercomputing resources provided by NSF/CISL/Yellowstone for producing and

507 making available their model output. Francois De Vleeschouwer acknowledges support from
508 the CNRS International Emerging Actions and the Climat AmSud Programme. Ilana Wainer
509 was supported in part by FAPESP; CNPq-MCT-INCT-594 CRIOSFERA 573720/2008-8 and
510 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil (CAPES)-Finance
511 Code 001.

512
513

514 References

515 Bandoro, J., Solomon, S., Donohoe, A., Thompson, D.W.J., Santer, B.D., 2014. Influences of
516 the Antarctic ozone hole on Southern Hemisphere summer climate change. J. Clim. 27, 6245-
517 6264.

518
519 Berman, A.L., Silvestri, G., Compagnucci, R., 2012. Eastern Patagonia seasonal precipitation: influence of southern hemisphere circulation and links with subtropical South American precipitation. J. Clim. 25, 6781-6795.
520
521

522
523 Berman, A.L., Silvestri, G., Compagnucci, R., 2013. On the variability of seasonal temperature
524 in southern South America. Clim. Dyn. 40, 1863-1878.

525
526 Bozkurt, D., Bromwich, D.H., Carrasco, J., Rondanelli, R., 2021. Temperature and precipitation
527 projections for the Antarctic Peninsula over the next two decades: contrasting global and
528 regional climate model simulations. Clim. Dyn. 56, 3853-3874.

529
Carrasco, J.F., 2013. Decadal changes in the near-surface air temperature in the western side of the Antarctic Peninsula. Atmos. Climate. Sci. 3, 275-281.

Carrasco, J.F., Bozkurt, D., Cordero, R.R., 2021. A review of the observed air temperature in the Antarctic Peninsula. Did the warming trend come back after the early 21st hiatus? Polar Sci. https://doi.org/10.1016/j.polar.2021.100653.

Danabasoglu, G., Bates, S.C., Briegleb, B.P., Jayne, S.R., Jochum, M., Large, W.G., Peacock, S., Yeager, S.G., 2012. The CCSM4 ocean component. J. Clim. 25, 1361-1389.

Deng, J., Dai, A., Xu, H., 2020. Nonlinear climate responses to increasing CO2 and anthropogenic aerosols simulated by CESM1. J. Clim. 33, 281-301.

Diaz, H.F., Trigo, R.M., Hughes, M.K., Mann, M.E., Xoplaki, E., Barriopedro, D., 2011. Spatial and temporal characteristics of climate in medieval times revisited. Bull. Amer. Meteor. Soc. 92, 1487-1500.

Ding, Q., Steig, E.J., Battisti, D.S., Kuttel, M., 2011. Winter warming in West Antarctica caused by central tropical Pacific warming. Nature Geosci. 4, 398-403. https://doi.org/10.1038/ngeo1129.
551 Ding, Q., Steig, E.J., 2013. Temperature change on the Antarctic Peninsula linked to the tropical
552 Pacific. J. Clim. 26, 7570–7585.

553
554 Feichter, J., Roeckner, E., Lohmann, U., Liepert, B., 2004. Nonlinear aspects of the climate
555 response to greenhouse gas and aerosol forcing. J. Clim. 17, 2384–2398.

556
557 Frew, R.C., Feltham, D.L., Holland, P.R., Petty, A.A., 2019. Sea ice – ocean feedbacks in the
558 antarctic shelf seas. J. Phys. Oceanogr. 49, 2423–2446.

559
600 Garreaud, R.D., Lopez, P., Minvielle, M., Rojas, M., 2013. Large scale control on the Patagonia
561 climate. J. Clim. 26, 215–230.

562
563 Gonzalez, S., Fortuny, D., 2018. How robust are the Antarctic Peninsula trends? Antarct. Sci.
564 30, 322–328.

565
566 Goodwin, B.P., Mosley-Thompson, E., Wilson, A.B., Porter, S.E., Sierra-Hernandez, M.R.,
567 2016. Accumulation variability in the Antarctic Peninsula: The role of large-scale atmospheric
568 oscillations and their interactions. J. Clim. 29(7), 2579–2596.

569
570 Goosse, H., Kay, J.E., Armour, K.C., et al. 2018. Quantifying climate feedbacks in polar
571 regions. Nat. Commun. 9, 1919. https://doi.org/10.1038/s41467-018-04173-0.

572
573 Hindell, M.A., Reinsinger, R.R., Ropert-Coudert, Y., et al., 2020. Tracking of marine predators
to protect Southern Ocean ecosystems. Nature. 580, 87–92. https://doi.org/10.1038/s41586-
020-2126-y.

576
577 Hurrell, J.W., Holland, M.M., Gent, P.R., et al., 2013. The Community Earth System Model: A framework for collaborative research. Bull. Amer. Meteor. Soc. 94, 1339–1360.

579
580 Jones, J.M., Gille, S.T., Goosse, H., et al., 2016. Assessing recent trends in high-latitude
581 Southern Hemisphere surface climate. Nature Clim. Change. 6, 917–926.

582
583 Jones, M.E., Bromwich, D.H., Nicolas, J.P., Carrasco, J., Plavcová, E., Zou, X., Wang, S.-H.,
584 2019. Sixty years of widespread warming in the southern mid- and high-latitudes (1957–2016).
585 J. Clim. 32, 6875–6898.

586
587 King, J.C., Turner, J., Marshall, G.J., Connolley, W.M., Lachlan-Cope, T.A., 2003. Antarctic
588 Peninsula climate variability and its causes as revealed by analysis of instrumental records, in:
589 Domack, E., Levente, A., Burnet, A., Bindschadler, R., Convey, P., Kirby, M. (Eds.), Antarctic
590 Peninsula climate variability: historical and paleoenvironmental perspectives. American
591 Geophysical Union, Washington, pp. 17–30.

592
593 Landrum, L., Otto-Bliesner, B.L., Wahl, E.R., Conley, A., Lawrence, P.J., Teng, H., 2013. Last
594 millennium climate and its variability in CCSM4. J. Clim. 26, 1085–1111.
595

596

Ljungqvist, F.C., Zhang, Q., Brattstrom, G., Krusic, P.J., Seim, A., Li, Q., Zhang, Q., Moberg, A., 2019. Centennial-scale temperature change in last millennium simulations and proxy-based reconstructions. J. Clim. 32, 2441–2482.

597

598

599

600

Lüning, S., Gałka, M., Vahrenholt, F., 2019a. The Medieval Climate Anomaly in Antarctica. Palaeogeogr. Palaeoclimatol. Palaeoecol. 532, 109251.
https://doi.org/10.1016/j.palaeo.2019.109251.

601

602

603

604

Lüning, S., Gałka, M., Bamonte, F.P., Rodríguez, F.G., Vahrenholt, F., 2019b. The Medieval Climate anomaly in South America. Quat. Int. 508, 70–87.

605

606

607

Mann, M.E., Zhang, Z., Rutherford, S., Bradley, R.S., Hughes, M.K., Shindell, D., Ammann, C., Faluvegi, G., Ni, F., 2009. Global signatures and dynamical origins of the Little Ice Age and Medieval Climate Anomaly. Science. 326, 1256–1260.

608

609

610

611

Marcello, F., Wainer, I., Gent, P.R., Otto-Bliesner, B.L., Brady, E.C., 2019. South Atlantic surface boundary current system during the Last Millennium in the CESM-LME: The Medieval Climate Anomaly and Little Ice Age. Geosciences. 9(7), 299.
https://doi.org/10.3390/geosciences9070299.

612

613

614

615
616 Marshall, G.J., Orr, A., van Lipzig, N.P.M., King, J.C., 2006. The impact of a changing 617 Southern Hemisphere Annular Mode on Antarctic Peninsula summer temperatures. J. Clim. 19, 618 5388–5404.

619
620 Meredith, M.P., King, J.C., 2005. Rapid climate change in the ocean west of the Antarctic 621 Peninsula during the second half of the 20th century. Geophys. Res. Lett. 32, L19604.
622 doi:10.1029/2005GL024042.

623
624 Neukom, R., Luterbacher, J., Villalba, R., et al., 2011. Multiproxy summer and winter surface 625 air temperature field reconstructions for southern South America covering the past centuries. 626 Clim. Dyn. 37, 35–51.

627
628 Neukom, R., Gergis, J., Karoly, D., et al., 2014. Inter-hemispheric temperature variability over 629 the past millennium. Nature Clim. Change. 4, 362–367. https://doi.org/10.1038/nclimate2174

630
631 Neukom, R., Steiger, N., Gómez-Navarro, J.J., Wang, J., Werner, J.P., 2019. No evidence for 632 globally coherent warm and cold periods over the pre-industrial Common Era. Nature. 571, 633 550–554.

634
635 Oliva, M., Navarro, F., Hrbácek, F., Hernández, A., Nývlt, D., Pereira, P., Ruiz-Fernández, J., 636 Trigo, R., 2017. Recent regional climate cooling on the Antarctic Peninsula and associated 637 impacts on the cryosphere. Sci. Total Environ. 580, 210–223.
638

639

Otto-Bliesner, B.L., Brady, E.C., Fasullo, J., Jahn, A., Landrum, L., Stevenson, S., Rosenbloom, N., Mai, A., Strand, G., 2016. Climate variability and change since 850 CE: An ensemble approach with the Community Earth System Model (CESM). Bull. Amer. Meteor. Soc. 97, 735-754.

640

641

642

643

644

PAGES 2k Consortium, 2013. Continental-scale temperature variability during the last two millennia. Nat. Geosci. 6, 339-346.

645

646

647

Previdi, M., Polvani, L.M., 2014. Climate system response to stratospheric ozone depletion and recovery. Q. J. R. Meteorol. Soc. 140(685), 2401-2419.

648

649

650

Randel, W.J., Shine, K.P., Austin, J., et al., 2009. An update of observed stratospheric temperature trends. J. Geophys. Res. 114, D02107. doi:10.1029/2008JD010421.

651

652

653

Raphael, M.N., Marshall, G.J., Turner, J., et al., 2016. The Amundsen Sea low: Variability, change, and impact on Antarctic climate. Bull. Amer. Meteor. Soc. 97, 111-121.

654

655

656

Richard, Y., Rouault, M., Pohl, B., Crétat, J., Duclot, I., Taboulot, S., Reason, C.J.C., Macron, C., Buiron, D., 2013. Temperature changes in the mid- and high-latitudes of the Southern Hemisphere. Int. J. Climatol. 33, 1948-1963.

657

658

659
660 Roscoe, H.K., Marshall, G.J., King, J.C., 2006. Low potential for stratospheric dynamical
661 change to be implicated in the large winter warming in the central Antarctic Peninsula. Q.J.R.
662 Meteorol. Soc. 132, 803-820.

663
664 Schmidt, G.A., Jungclaus, J.H., Ammann, C.M., et al., 2011. Climate forcing reconstructions
665 for use in PMIP simulations of the Last Millennium (v1.0). Geosci. Model Dev. 4, 33-45.

666
667 Schmidt, G.A., Jungclaus, J.H., Ammann, C.M., et al., 2012. Climate forcing reconstructions
668 for use in PMIP simulations of the Last Millennium (v1.1). Geosci. Model Dev. 5, 185-191.

669
670 Schneider, D.P., Deser, C., Okumura, Y., 2012. An assessment and interpretation of the
671 observed warming of West Antarctica in the austral spring. Clim. Dyn. 38, 323-347.

672
673 Silva, N., Wainer, I., Tonelli, M., 2019. Caracterização de Mudanças Climáticas na Antártica a
674 partir da Segunda Metade do Século XX. Rev. Bras. Geogr. Fís. 12(6), 2091-2107.
675 https://doi.org/10.26848/rbgf.v12.6.p2091-2107.

676
677 Stenni, B., Curran, M.A.J., Abram, N.J., et al., 2017. Antarctic climate variability on regional
678 and continental scales over the last 2000 years. Clim. Past. 13, 1609-1634.

679
Thomas, E.R., Dennis, P.F., Bracegirdle, T.J., Franzke, C., 2009. Ice core evidence for significant 100-year regional warming on the Antarctic Peninsula. Geophys. Res. Lett. 36, L20704. doi:10.1029/2009GL040104.

683

Thompson, D.W.J., Solomon, S., 2002. Interpretation of recent Southern Hemisphere climate change. Science. 296, 895–899.

686

Tonelli, M., Marcello, F., Ferrero, B., Wainer, I., 2019. Warm deep water variability during the Last Millennium in the CESM–LME: pre-Industrial scenario versus late 20th century changes. Geosciences. 9, 346. doi:10.3390/geosciences9080346.

690

Turner, J., Colwell, S.R., Marshall, G.J., Lachlan-Cope, T.A., Carleton, A.M., Jones, P.D., Lagun, V., Reid, P.A., Iagovkina, S., 2005. Antarctic climate change during the last 50 years. Int. J. Climatol. 25, 279–294.

694

Turner, J., Maksym, T., Phillips, T., Marshall, G.J., Meredith, M.P., 2012. Impact of changes in sea ice advance on the large winter warming on the western Antarctic Peninsula. Int. J. Climatol. 33, 852–861.

698

Turner, J., Lu, H., White, I., King, J.C., Phillips, T., Hosking, J.S., Bracegirdle, T.J., Marshall, G.J., Mulvaney, R., Deb, P., 2016. Absence of 21st century warming on Antarctic Peninsula consistent with natural variability. Nature. 535, 411–415.
702

703

704

705

Turner, J., Marshall, G.J., Clem, K., Colwell, S., Phillips, T., Lu, H., 2019. Antarctic temperature variability and change from station data. Int. J. Climatol. 40, 2986–3007. https://doi.org/10.1002/joc.6378.

706

707

708

709

van Wessem, J.M., Reijmer, C.H., van de Berg, W.J., van den Broeke, M.R., Cook, A.J., van Ulft, L.H., van Meijgaard, E., 2015. Temperature and wind climate of the Antarctic Peninsula as simulated by a high-resolution regional atmospheric climate model. J. Clim. 28, 7306–7326.

710

711

712

713

Vaughan, D.G., Marshall, G.J., Connolley, W.M., Parkinson, C., Mulvaney, R., Hodgson, D.A., King, J.C., Pudsey, C.J., Turner, J., 2003. Recent rapid regional climate warming on the Antarctic Peninsula. Clim. Chang. 60, 243–274.

714

715

716

Verona, L.S., Wainer, I., Stevenson, S., 2019. Volcanically triggered ocean warming near the Antarctic Peninsula. Sci. Rep. 9, 9462. https://doi.org/10.1038/s41598-019-45190-3.

717

718

719

Wainer, I., Gent, P.R., 2019. Changes in the Atlantic sector of the Southern Ocean estimated from the CESM Last Millennium Ensemble. Antarct. Sci. 31(1), 37–51.

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Wilks, D.S., 2006. Statistical Methods in the Atmospheric Sciences, second ed. International Geophysics Series. Elsevier Academic Press, St. Louis.

723
724

725 **Figure and Table captions**

726 **Fig. 1.** Study area. **a)** Continental regions referred as the Antarctic Peninsula (AP) and southern
727 Patagonia (SPat) are delimited by green squares. Acronyms identify South Pacific Ocean
728 (SPO), South Atlantic Ocean (SAO), Drake Passage (Dp), Scotia Sea (Sco), Bellingshausen
729 Sea (Bel), and Weddell Sea (Wed). Red (blue) contour shows the annual average ice extent for
730 1979–2005 in CESM-LME full-forcing simulation (observed NOAA/NSIDC data;
731 https://nsidc.org/data/G02202) plotted as the 15% ice concentration limit. **b)** Observed 0.25-
732 degree latitude-longitude resolution topography
733 (http://research.jisao.washington.edu/data_sets/elevation) in the AP and SPat. Unit: meters. **c)**
734 Modeled and observed 1979–2005 annual mean sea level pressure. Red (blue) contours
735 correspond to 986 hPa, 996 hPa and 1006 hPa in CESM-LME full-forcing simulation (ERA5
736 reanalysis).

737

738 **Fig. 2.** Differences of annual mean temperature in the CESM-LME full-forcing simulations. **a)** MCA minus LM. **b)** MCA minus LIA. **c)** LIA minus LM. Differences are significant at 95% level in all grid points.

741

742 **Fig. 3.** **a)** Linear trends in annual mean surface temperature from the full-forcing simulation for 743 850-1849 period. Trends are significant at 95% level in all grid points. **b)** As **a)** but for 1850-744 2005 period. Color scale is different to that of **a)** because trends in 850-1849 are markedly lower 745 than those of 1850-2005. **c)** Differences between annual mean surface temperatures from the 746 full-forcing simulation in PD and LM periods (i.e., differences PD minus LM). Stippling 747 indicates differences not statistically significant at the 95% level.

748

749 **Fig. 4.** Mean temperature in the AP and SPat during the MCA, LIA, L19C, E20C and each PD
750 experiment (see details in the text). Red points (●) indicate MCA; blue points (●) indicate LIA;
751 white points (o) indicate LM; black points (●) indicate L19C, E20C and PD of full-forcing
752 simulation; green points (●) indicate PD of each single natural forcing; grey points (●) indicate
753 PD of each single anthropogenic forcing. Horizontal black lines indicate the limits M<sub>MCA</sub> ±
754

$2\sigma_{MCA}$ being $M_{MCA}$ and $\sigma_{MCA}$ the statistics mean and standard deviation of decadal mean temperature in the MCA period of the full-forcing simulation. Unit: °C.

755

756

757

**Fig. 5.** Differences between simulated annual mean temperatures in PD and MCA periods (i.e., differences PD minus MCA). Forcings involved in PD simulations are indicated in each figure: **a)** all forcings, **b)** only volcanic, **c)** only orbital, **d)** only solar, **e)** only GHG, **f)** only ozone/aerosol, **g)** only land use/land cover. Stippling indicates differences not statistically significant at the 95% level.

758

759

760

761

762

763

**Fig. 6.** Linear trends in annual mean surface temperature for 1850-2005 period. Forcings involved in the simulation are indicated in each figure: **a)** all forcings, **b)** only volcanic, **c)** only orbital, **d)** only solar, **e)** only GHG, **f)** only ozone/aerosol, **g)** only land use/land cover. Stippling indicates trends not statistically significant at the 95% level.

764

765

766

767

768

**Fig. 7.** Differences between simulated annual mean temperatures in PD and LIA periods (i.e., differences PD minus LIA). Forcings involved in PD simulations are indicated in each figure: **a)** all forcings, **b)** only volcanic, **c)** only orbital, **d)** only solar, **e)** only GHG, **f)** only ozone/aerosol, **g)** only land use/land cover. Stippling indicates differences not statistically significant at the 95% level.

769

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773

774

**Fig. 8.** Proxy-based reconstructions of temperature during the MCA, LIA, LM and PD. Unit: °C. **a)** Annual mean temperature in the AP and SPat extracted from reconstruction of Mann et al. (2009). Values are anomalies with respect to the 1961–1990 reference period mean. **b)** Summer mean temperature in SPat extracted from reconstruction of Neukom et al. (2011). Values are anomalies with respect to the 1931–1995 reference period mean. **c)** Annual mean temperature in the AP extracted from reconstructions of Stenni et al. (2017). ECH and NB identify the methodology used in each reconstruction. Values are anomalies with respect to the 1900–1990 reference period mean.

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777

778

779

780

781

782
**Fig. 9.** Proxy-based reconstructions of temperature in the AP and SPat (see sites in Supplementary Material 3). **a)** Reconstructed temperature in the AP. Red points (●) indicate MCA warmer than LIA, blue point (●) indicates MCA colder than LIA, green points (●) indicate MCA similar to or warmer than PD, and orange point (●) indicates MCA warmer than LIA and similar to or warmer than PD. **b)** Reconstructed temperature in SPat. Red points (●) indicate MCA warmer than LIA, blue point (●) indicates MCA colder than PD, black points (●) indicate MCA warmer than LIA and warmer than PD.

**Table 1.** Differences between simulated PD and LM temperatures (PD minus LM), PD and MCA temperatures (PD minus MCA), and PD and LIA temperatures (PD minus LIA). The forcing involved in PD simulations is indicated in the second column. Dot (●) and asterisk (*) indicates difference statistically significant at the 90% and 95% level respectively. Unit: °C.

**Table 2.** Differences between simulated PD temperatures considering each forcing individually and all forcings simultaneously (i.e., differences $PD_{FORCING}$ minus $PD_{FULL}$). The individual forcing is indicated in each column. Asterisk (*) indicates difference statistically significant at the 95% level. Unit: °C.

**Table 3.** Differences between simulated PD and MCA temperatures (PD minus MCA), and PD and LIA temperatures (PD minus LIA) considering all forcings simultaneously (FULL) and the sum of individual forcings (SUM) showed in Table 1 (SUM = VOLC + ORB + SOL + GHG + O3/AER + LAND).

**Table 4.** Temperature differences and trends considering the reconstructions of Mann et al. (2009), Neukom et al. (2011) and Stenni et al. (2017) mentioned in the text. Differences and trends simulated by the model (full-forcing simulation) are indicated in the column on the right of each table. Dot (●) and asterisk (*) indicate values statistically significant at the 90% and 95% level respectively. Units: °C (differences) and °C/decade (trends). NOTE: Summer trends in Table 4c correspond to periods 900-1849 and 1850-1995 due to extension of the time series available from Neukom et al. (2011).
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815

**Supplementary Figure S1.** Meteorological stations used to calculate linear trends in annual mean surface temperature during the last decades of the 20th century over the AP and SPat.

816

817

818

819

820

821

822

823

**Supplementary Table 1.** Linear trends (and uncertainties on the slopes) in annual mean surface temperature for 1968-2005 period in CESM-LME full-forcing simulation and meteorological stations displayed in Supplementary Fig. S1. Trends in the model simulation corresponds to averaged time series of all model grid points within the regions and averaged time series of model data at station locations (these latest values are indicated in parentheses). AP (SPat) indicates the time series of averaged anomalies of the seven (four) stations located in the region AP (SPat). Unit: °C/year.

824

825

826

827

828

829

**Supplementary Figure S2.** Differences between simulated annual mean temperatures in PD considering each individual forcing and all forcings simultaneously (i.e., differences $PD_{FORCING}$ minus $PD_{FULL}$). Individual forcings are indicated in each figure: **a**) only volcanic, **b**) only orbital, **c**) only solar, **d**) only GHG, **e**) only ozone/aerosol, **f**) only land use/land cover. Stippling indicates differences not statistically significant at the 95% level.

830

831

832

**Supplementary Material 3.** Site number, site name and archive type of paleorecords mentioned in Section 4.

833

834
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Study area. a) Continental regions referred as the Antarctic Peninsula (AP) and southern Patagonia (SPat) are delimited by green squares. Acronyms identify South Pacific Ocean (SPO), South Atlantic Ocean (SAO), Drake Passage (Dp), Scotia Sea (Sco), Bellingshausen Sea (Bel), and Weddell Sea (Wed). Red (blue) contour shows the annual average ice extent for 1979–2005 in CESM-LME full-forcing simulation (observed NOAA/NSIDC data; https://nsidc.org/data/G02202) plotted as the 15% ice concentration limit. b) Observed 0.25-degree latitude-longitude resolution topography (http://research.jisao.washington.edu/data_sets/elevation) in the AP and SPat. Unit: meters. c) Modeled and observed 1979–2005 annual mean sea level pressure. Red (blue) contours correspond to 986 hPa, 996 hPa and 1006 hPa in CESM-LME full-forcing simulation (ERA5 reanalysis).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Differences of annual mean temperature in the CESM-LME full-forcing simulations. a) MCA minus LM. b) MCA minus LIA. c) LIA minus LM. Differences are significant at 95% level in all grid points.</figcaption></figure>
a) Trend 850–1849

<figure><img src="image_6.png" /></figure>

b) Trend 1850–2005

<figure><img src="image_7.png" /></figure>

c) Difference PD – LM

<figure><img src="image_8.png" /></figure>

**Fig. 3.** a) Linear trends in annual mean surface temperature from the full-forcing simulation for 850-1849 period. Trends are significant at 95% level in all grid points. b) As a) but for 1850-2005 period. Color scale is different to that of a) because trends in 850-1849 are markedly lower than those of 1850-2005. c) Differences between annual mean surface temperatures from the full-forcing simulation in PD and LM periods (i.e., differences PD minus LM). Stippling indicates differences not statistically significant at the 95% level.
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

**Fig. 4.** Mean temperature in the AP and SPat during the MCA, LIA, L19C, E20C and each PD experiment (see details in the text). Red points (●) indicate MCA; blue points (●) indicate LIA; white points (o) indicate LM; black points (●) indicate L19C, E20C and PD of full-forcing simulation; green points (●) indicate PD of each single natural forcing; grey points (●) indicate PD of each single anthropogenic forcing. Horizontal black lines indicate the limits $M_{MCA} \pm 2\sigma_{MCA}$ being $M_{MCA}$ and $\sigma_{MCA}$ the statistics mean and standard deviation of decadal mean temperature in the MCA period of the full-forcing simulation. Unit: °C.
<figure><img src="image_11.png" /><figcaption>**Fig. 5.** Differences between simulated annual mean temperatures in PD and MCA periods (i.e., differences PD minus MCA). Forcings involved in PD simulations are indicated in each figure: **a)** all forcings, **b)** only volcanic, **c)** only orbital, **d)** only solar, **e)** only GHG, **f)** only ozone/aerosol, **g)** only land use/land cover. Stippling indicates differences not statistically significant at the 95% level.</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>**Fig. 6.** Linear trends in annual mean surface temperature for 1850-2005 period. Forcings involved in the simulation are indicated in each figure: **a)** all forcings, **b)** only volcanic, **c)** only orbital, **d)** only solar, **e)** only GHG, **f)** only ozone/aerosol, **g)** only land use/land cover. Stippling indicates trends not statistically significant at the 95% level.</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>**Fig. 7.** Differences between simulated annual mean temperatures in PD and LIA periods (i.e., differences PD minus LIA). Forcings involved in PD simulations are indicated in each figure: **a)** all forcings, **b)** only volcanic, **c)** only orbital, **d)** only solar, **e)** only GHG, **f)** only ozone/aerosol, **g)** only land use/land cover. Stippling indicates differences not statistically significant at the 95% level.</figcaption></figure>
<figure><img src="image_14.png" /><figcaption>**Fig. 8.** Proxy-based reconstructions of temperature during the MCA, LIA, LM and PD. Unit: °C. **a)** Annual mean temperature in the AP and SPat extracted from reconstruction of Mann et al. (2009). Values are anomalies with respect to the 1961–1990 reference period mean. **b)** Summer mean temperature in SPat extracted from reconstruction of Neukom et al. (2011). Values are anomalies with respect to the 1931–1995 reference period mean. **c)** Annual mean temperature in the AP extracted from reconstructions of Stenni et al. (2017). ECH and NB identify the methodology used in each reconstruction. Values are anomalies with respect to the 1900–1990 reference period mean.</figcaption></figure>
a

<figure><img src="image_15.png" /></figure>

b

<figure><img src="image_16.png" /><figcaption>**Fig. 9.** Proxy-based reconstructions of temperature in the AP and SPat (see sites in Supplementary Material 3). **a)** Reconstructed temperature in the AP. Red points (●) indicate MCA warmer than LIA, blue point (●) indicates MCA colder than LIA, green points (■) indicate MCA similar to or warmer than PD, and orange point (●) indicates MCA warmer than LIA and similar to or warmer than PD. **b)** Reconstructed temperature in SPat. Red points (●) indicate MCA warmer than LIA, blue point (●) indicates MCA colder than PD, black points (●) indicate MCA warmer than LIA and warmer than PD.</figcaption></figure>
a) PD – LM

<table><thead><tr><th></th><th>FULL</th><th>VOLC</th><th>ORB</th><th>SOL</th><th>GHG</th><th>O3/AER</th><th>LAND</th></tr></thead><tbody><tr><th>AP</th><td>1.03 *</td><td>-0.19 *</td><td>0.19 *</td><td>0.12 •</td><td>1.98 *</td><td>-0.69 *</td><td>-0.33 *</td></tr><tr><th>SPat</th><td>0.46 *</td><td>-0.15 *</td><td>0.04</td><td>0.08 *</td><td>0.86 *</td><td>-0.25 *</td><td>-0.05 •</td></tr></tbody></table>

b) PD – MCA

<table><thead><tr><th></th><th>FULL</th><th>VOLC</th><th>ORB</th><th>SOL</th><th>GHG</th><th>O3/AER</th><th>LAND</th></tr></thead><tbody><tr><th>AP</th><td>0.85 *</td><td>-0.37 *</td><td>0.01</td><td>-0.06</td><td>1.80 *</td><td>-0.87 *</td><td>-0.51 *</td></tr><tr><th>SPat</th><td>0.40 *</td><td>-0.21 *</td><td>-0.03</td><td>0.02</td><td>0.80 *</td><td>-0.31 *</td><td>-0.11 *</td></tr></tbody></table>

c) PD – LIA

<table><thead><tr><th></th><th>FULL</th><th>VOLC</th><th>ORB</th><th>SOL</th><th>GHG</th><th>O3/AER</th><th>LAND</th></tr></thead><tbody><tr><th>AP</th><td>1.19 *</td><td>-0.03</td><td>0.35 *</td><td>0.28 *</td><td>2.14 *</td><td>-0.53 *</td><td>-0.17 *</td></tr><tr><th>SPat</th><td>0.51 *</td><td>-0.10 *</td><td>0.08 *</td><td>0.13 *</td><td>0.91 *</td><td>-0.20 *</td><td>0.0</td></tr></tbody></table>

**Table 1.** Differences between simulated PD and LM temperatures (PD minus LM), PD and MCA temperatures (PD minus MCA), and PD and LIA temperatures (PD minus LIA). The forcing involved in PD simulations is indicated in the second column. Dot (●) and asterisk (*) indicates difference statistically significant at the 90% and 95% level respectively. Unit: °C.
<table><thead><tr><th></th><th>VOLC</th><th>ORB</th><th>SOL</th><th>GHG</th><th>O3/AER</th><th>LAND</th></tr></thead><tbody><tr><th>AP</th><td>-1.22 *</td><td>-0.84 *</td><td>-0.91 *</td><td>0.95 *</td><td>-1.72 *</td><td>-1.36 *</td></tr><tr><th>SPat</th><td>-0.61 *</td><td>-0.43 *</td><td>-0.38 *</td><td>0.40 *</td><td>-0.71 *</td><td>-0.51 *</td></tr></tbody></table>

**Table 2.** Differences between simulated PD temperatures considering each forcing individually and all forcings simultaneously (i.e., differences $PD_{FORCING}$ minus $PD_{FULL}$). The individual forcing is indicated in each column. Asterisk (*) indicates difference statistically significant at the 95% level. Unit: °C.

<table><thead><tr><th rowspan="2">region</th><th colspan="2">PD - MCA</th><th colspan="2">PD - LIA</th></tr><tr><th>FULL</th><th>SUM</th><th>FULL</th><th>SUM</th></tr></thead><tbody><tr><th>AP</th><td>0.85</td><td>0.00</td><td>1.19</td><td>2.04</td></tr><tr><th>SPat</th><td>0.40</td><td>0.16</td><td>0.51</td><td>0.82</td></tr></tbody></table>

**Table 3.** Differences between simulated PD and MCA temperatures (PD minus MCA), and PD and LIA temperatures (PD minus LIA) considering all forcings simultaneously (FULL) and the sum of individual forcings (SUM) showed in Table 1 ($SUM = VOLC + ORB + SOL + GHG + O3/AER + LAND$).
a) AP / ANNUAL

<table><thead><tr><th></th><th>Mann</th><th>Stenni ECH</th><th>Stenni NB</th><th>model</th></tr></thead><tbody><tr><td>MCA – LIA</td><td><span style="color:blue;">-0.16</span> *</td><td>-0.28</td><td>-0.13</td><td><span style="color:red;">0.34</span> *</td></tr><tr><td>MCA – LM</td><td><span style="color:blue;">-0.07</span> *</td><td>-0.14</td><td>-0.06</td><td><span style="color:red;">0.18</span> *</td></tr><tr><td>LIA – LM</td><td><span style="color:red;">0.09</span> *</td><td>0.15</td><td>0.07</td><td><span style="color:blue;">-0.16</span> *</td></tr><tr><td>PD – MCA</td><td><span style="color:red;">0.73</span> *</td><td><span style="color:red;">1.84</span> *</td><td><span style="color:red;">0.91</span> *</td><td><span style="color:red;">0.85</span> *</td></tr><tr><td>PD – LIA</td><td><span style="color:red;">0.57</span> *</td><td><span style="color:red;">1.56</span> *</td><td><span style="color:red;">0.79</span> *</td><td><span style="color:red;">1.19</span> *</td></tr><tr><td>PD – LM</td><td><span style="color:red;">0.66</span> *</td><td><span style="color:red;">1.70</span> *</td><td><span style="color:red;">0.85</span> *</td><td><span style="color:red;">1.03</span> *</td></tr><tr><td>trend 850-1849</td><td><span style="color:red;">9x10<sup>-4</sup></span> *</td><td>2x10<sup>-3</sup></td><td>1x10<sup>-3</sup></td><td><span style="color:blue;">-5x10<sup>-3</sup></span> *</td></tr><tr><td>trend 1850-2005</td><td><span style="color:red;">0.02</span> *</td><td><span style="color:red;">0.16</span> *</td><td><span style="color:red;">0.07</span> *</td><td><span style="color:red;">0.08</span> *</td></tr></tbody></table>

b) SPat / ANNUAL

<table><thead><tr><th></th><th>Mann</th><th>model</th></tr></thead><tbody><tr><td>MCA – LIA</td><td><span style="color:red;">0.41</span> *</td><td><span style="color:red;">0.11</span> *</td></tr><tr><td>MCA – LM</td><td><span style="color:red;">0.22</span> *</td><td><span style="color:red;">0.06</span> *</td></tr><tr><td>LIA – LM</td><td><span style="color:blue;">-0.20</span> *</td><td><span style="color:blue;">-0.05</span> *</td></tr><tr><td>PD – MCA</td><td><span style="color:red;">0.29</span> *</td><td><span style="color:red;">0.40</span> *</td></tr><tr><td>PD – LIA</td><td><span style="color:red;">0.70</span> *</td><td><span style="color:red;">0.51</span> *</td></tr><tr><td>PD – LM</td><td><span style="color:red;">0.50</span> *</td><td><span style="color:red;">0.46</span> *</td></tr><tr><td>trend 850-1849</td><td><span style="color:blue;">-7x10<sup>-3</sup></span> *</td><td><span style="color:blue;">-2x10<sup>-3</sup></span> *</td></tr><tr><td>trend 1850-2005</td><td><span style="color:red;">0.05</span> *</td><td><span style="color:red;">0.04</span> *</td></tr></tbody></table>

**Table 4.** Temperature differences and trends considering the reconstructions of Mann et al. (2009), Neukom et al. (2011) and Stenni et al. (2017) mentioned in the text. Differences and trends simulated by the model (full-forcing simulation) are indicated in the column on the right of each table. Dot (●) and asterisk (*) indicate values statistically significant at the 90% and 95% level respectively. Units: °C (differences) and °C/decade (trends). NOTE: Summer trends in Table 4c correspond to periods 900-1849 and 1850-1995 due to extension of the time series available from Neukom et al. (2011).
c) SPat / SUMMER

<table><caption>Table 4 (continuation)</caption><thead><tr><th></th><th>Neukom</th><th>model</th></tr></thead><tbody><tr><td>MCA - LIA</td><td>0.10 •</td><td>0.15 *</td></tr><tr><td>MCA - LM</td><td>0.03</td><td>0.08 *</td></tr><tr><td>LIA - LM</td><td>-0.07</td><td>-0.07 *</td></tr><tr><td>PD - MCA</td><td>0.57 *</td><td>0.34 *</td></tr><tr><td>PD - LIA</td><td>0.67 *</td><td>0.49 *</td></tr><tr><td>PD - LM</td><td>0.61 *</td><td>0.42 *</td></tr><tr><td>trend 900-1849</td><td>-1.7x10<sup>-3</sup> •</td><td>-2.2x10<sup>-3</sup> *</td></tr><tr><td>trend 1850-1995</td><td>0.01 *</td><td>0.03 *</td></tr></tbody></table>