Surface and Tropospheric Response of North Atlantic Summer Climate from Paleoclimate Simulations of the Past Millennium
We investigate the effects of solar forcing on the North Atlantic (NA) summer climate, in climate simulations with Earth System Models (ESMs), over the preindustrial past millennium (AD 850–1849). We use one simulation and a four-member ensemble performed with the MPI-ESM-P and CESM-LME models, respectively, forced only by low-scaling variations in Total Solar Irradiance (TSI). We apply linear methods (correlation and regression) and composite analysis to estimate the NA surface and tropospheric climatic responses to decadal solar variability. Linear methods in the CESM ensemble indicate a weak summer response in sea-level pressure (SLP) and 500-hPa geopotential height to TSI, with decreased values over Greenland and increased values over the NA subtropics. Composite analysis indicates that, during high-TSI periods, SLP decreases over eastern Canada and the geopotential height at 500-hPa increases over the subtropical NA. The possible summer response of SSTs is overlapped by model internal variability. Therefore, for low-scaling TSI changes, state-of-the-art ESMs disagree on the NA surface climatic effect of solar forcing indicated by proxy-based studies during the preindustrial millennium. The analysis of control simulations indicates that, in all climatic variables studied, spurious patterns of apparent solar response may arise from the analysis of single model simulations. Keywords: TSI; solar forcing; last millennium; paleoclimate simulations; CESM-LME; North Atlantic; surface climatic response
Changes in the climate system may be a result of internal climate variability or external influences that may be either anthropogenic or natural (i.e., orbital, solar, or volcanic forcing). The human influence on global temperature since the start of the industrial era (after AD 1850) has very likely exceeded the impact of natural forcings . However, during the pre-industrial era, externally driven climate change at decadal-to-multidecadal time scales is considered to be forced primarily by variation in solar output and by volcanic eruptions [2,3,4]. In contrast to volcanic forcing, solar forcing may cause long-term (decadal mean) continental and regional climate changes that are greater than unforced (internal) variability .The Sun’s climatic impact arises from changes in its total solar irradiance (TSI), spectral solar irradiance (SSI) and energetic particle precipitation (EPP) [6,7,8,9,10]. Recently, more efforts were placed on the representation of variations in SSI and EPP in climate model simulations, with new recommendations regarding the magnitude of SSI variations used to force state of the art global climate models. The SSI uncertainty and the possible impacts of the higher SSI variations are discussed extensively in Matthes et al. . In the current study, we are interested in the climatic impact of TSI variations during the preindustrial last millennium (AD 850–1849), as TSI is used as proxy for identifying the effect of solar variability in paleoclimate proxy data. The effect of TSI changes on the climate of the past millennium was identified by early works in the context of the historical Maunder Minimum (AD 1675–1715)  and confirmed by more recent studies investigating climate changes during periods of solar maxima and minima [13,14,15,16]. In the early 2000s it was generally accepted that a long-term change in solar activity between the mean solar output during the Maunder Minimum (decline in solar activity) and the present-day climate, a period with presumably higher solar output, was about 0.3% . However, the amplitude of these TSI changes was subsequently revised and reduced to a value of approximately 0.1% [18,19]. This new scaling was applied to the models participating in the 5th phase of the Coupled Model Intercomparison Project—CMIP5 [20,21]. Even though this change in the TSI scaling has implications for our understanding of the effects of changes in solar output on climate, a quantitative assessment of this effect has not yet been made. We use simulations forced with the latest estimations of the solar amplitude and investigate how these TSI variations are reflected in the North Atlantic (NA) climate of model simulations in the preindustrial last millennium. We focus on the NA, where ocean-atmosphere interactions crucially affect the climate of North America and Europe [22,23,24], and on the summer season, as it is more relevant for comparison to studies using proxy data. Biological proxies, such as trees and bivalve shells, tend to reflect the growing season more strongly. The variability in their growth increment widths is related to environmental conditions and their growth is biased towards summer [25,26]. Investigating the Sun-climate relationship prior to industrial times is important for the comparison between climate models and proxy records and for disentangling anthropogenic climate change from natural variations . Modeling and proxy-based studies have so far disagreed on the importance of TSI forcing on driving variations in global annual mean surface temperatures [28,29,30], but they agree on larger regional effects of TSI forcing [31,32,33]. Nevertheless, these effects might be too large to be attributed to direct solar heating, and positive feedbacks have been invoked , particularly in regions that usually are cloud covered [35,36,37]. Regarding the NA region, some authors have claimed the detection of influence of solar forcing in marine proxies over the past millennium for Sea Surface Temperatures (SSTs) in centennial and multi-decadal time scales [33,38,39]. Jiang et al.  used regression analysis and paleoclimate proxy data, and identified a positive correlation between SSTs and solar forcing for the region of the North Icelandic shelf. Further, these authors used composite analysis and found that surface temperatures north of Iceland increase for stronger solar forcing. In order to investigate whether such signals occur in model simulations, we make use of linear regression and composite analysis, and investigate the spatial climatic changes that are solely induced by changes in solar activity, during the summer seasons of AD 850–1849, over the North Atlantic. For this goal, we use solar-only forced CMIP5-type simulations available for the Max Planck Institute Earth System Model (MPI-ESM) and the Community Earth System Model (CESM). These simulations employ reduced long-term solar amplitudes, smaller than that used in simulations carried out one or two decades ago, and implement solar activity changes for different wavelength bands. The use of only-solar forced simulations is important for having a clearer solar forcing signal, as solar forcing effects might be concealed by the larger effect of volcanic eruptions, for example, in periods when TSI minima coincided with volcanic eruptions during the last millennium. For this reason, the use of linear regression might not be appropriate for detecting the signal of solar forcing . Moreover, the CESM output includes an ensemble of solar-only forced experiments. That is important in order to quantify the magnitude of model internal variability and the magnitude of the TSI effects on the modeled climate.Other studies also used simulations with current estimations of long-term solar amplitudes and investigated the sun-climate relationship, but they investigated the winter season in the recent historical period and used fully forced experiments [41,42,43,44]. Our analysis focuses on summer season and the preindustrial period, therefore being more relevant to model-proxy comparisons. Moreover, the use of only-solar forced experiments during the preindustrial era automatically excludes possible influences from volcanic eruptions and anthropogenic forcing. Therefore, the investigation of the pure impact of changes in solar activity on the simulated climate is more robust. Another aspect of the paper is that our analysis includes different techniques for signal identification. Therefore, our results might help to disentangle potential solar-only induced changes from those of the fully forced runs, focusing spatially on the effect of model internal variability.
The full article appeared on the Atmosphere website at https://www.mdpi.com/2073-4433/12/5/568/htm]]>