Influence of radiative forcing factors on ground–air temperature coupling during the last millennium: implications for borehole climatology

Past climate variations may be uncovered via reconstruction methods that use proxy data as predictors. Among them, borehole reconstruction is a well-established technique to recover the long-term past surface air temperature (SAT) evolution. It is based on the assumption that SAT changes are strongly coupled to ground surface temperature (GST) changes and transferred to the subsurface by thermal conduction. We evaluate the SAT–GST coupling during the last millennium (LM) using simulations from the Community Earth System Model LM Ensemble (CESM-LME). The validity of such a premise is explored by analyzing the structure of the SAT–GST covariance during the LM and also by investigating the evolution of the long-term SAT–GST relationship. The multiple and single-forcing simulations in the CESM-LME are used to analyze the SAT–GST relationship within different regions and spatial scales and to derive the influence of the different forcing factors on producing feedback mechanisms that alter the energy balance at the surface. The results indicate that SAT–GST coupling is strong at global and above multi-decadal timescales in CESM-LME, although a relatively small variation in the long-term SAT–GST relationship is also represented. However, at a global scale such variation does not significantly impact the SAT–GST coupling, at local to regional scales this relationship experiences considerable long-term changes mostly after the end of the 19th century. Land use land cover changes are the main driver for locally and regionally decoupling SAT and GST, as they modify the land surface properties such as albedo, surface roughness and hydrology, which in turn modifies the energy fluxes at the surface. Snow cover feedbacks due to the influence of other external forcing are also important for corrupting the long-term SAT–GST coupling. Our findings suggest that such local and regional SAT–GST decoupling processes may represent a source of bias for SAT reconstructions from borehole measurement, since the thermal signature imprinted in the subsurface over the affected regions is not fully representative of the long-term SAT variations.Ministerio de Industria, Comercio y Competitividad (FPI grant no. BES-2015-075019)Versión del editor3,50

Internal and external variability in regional simulations of the Iberian Peninsula climate over the last millennium

In this study we analyse the role of internal variability in regional climate simulations through a comparison of two regional paleoclimate simulations for the last millennium. They share the same external forcings and model configuration, differing only in the initial condition used to run the driving global model simulation. A comparison of these simulations allows us to study the role of internal variability in climate models at regional scales, and how it affects the long-term evolution of climate variables such as temperature and precipitation. The results indicate that, although temperature is homogeneously sensitive to the effect of external forcings, the evolution of precipitation is more strongly governed by random unpredictable internal dynamics. There are, however, some areas where the role of internal variability is lower than expected, allowing precipitation to respond to the external forcings. In this respect, we explore the underlying physical mechanisms responsible for it. This study identifies areas, depending on the season, in which a direct comparison between model simulations of precipitation and climate reconstructions would be meaningful, but also other areas where good agreement between them should not be expected even if both are perfect

Climate field reconstruction uncertainty arising from multivariate and nonlinear properties of predictors

Climate field reconstructions (CFRs) of the global annual surface air temperature (SAT) field and associated global area-weighted mean annual temperature (GMAT) are derived in a collection of pseudoproxy experiments for the past millennium. Pseudoproxies are modeled from temperature (T), precipitation (P), T + P, and VS-Lite (VSL), a nonlinear and multivariate proxy system model for tree ring widths. Spatial patterns of reconstruction skill and spectral bias for the T + P and VSL-derived CFRs are similar to those previously shown using temperature-only pseudoproxies but demonstrate overall degraded skill and spectral bias for SAT reconstruction. Analysis of GMAT spectra nevertheless suggests that the true GMAT frequency spectrum is resolved by those pseudoproxies (T, T + P, and VSL) that contain some temperature information. The results suggest that mixed temperature and moisture-responding paleoclimate data may produce actual GMAT reconstructions with skill, error, and spectral characteristics like those expected from univariate and linear temperature responders, but spatially resolved CFR results should be analyzed cautiousl

European summer temperatures since Roman times

The spatial context is critical when assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding frequency and severity in the long-term perspective. Recent initiatives have expanded the number of high-quality proxy-records and developed new reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and the possibility of evaluating climate models on policy-relevant, spatio-temporal scales. We provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer temperature fields back to 755 CE based on a Bayesian hierarchical modelling (BHM), together with estimates of the European mean temperature variation since 138 BCE based on Composite-plus-Scaling. Our reconstructions compare well with independent instrumental and proxy-based temperature estimates, but suggest a larger amplitude in summer temperature variability than previously reported. Temperature differences between the medieval period, the recent period and Little Ice Age are larger in reconstructions than simulations. This may indicate either inflated variability of the reconstructions, a lack of sensitivity to external forcing on sub-hemispheric scales in the climate models and/or an underestimation of internal variability on centennial and longer time scales including the representation of internal feedback mechanisms

The PMIP4 contribution to CMIP6 – Part 3: the Last Millennium, Scientific Objective and Experimental Design for the PMIP4 past1000 simulations

The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial timescales. This paper describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents orbital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data)