Watts N, Amann M, Ayeb-Karlsson S, et al. The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health. Lancet 2018; 391: 581–630—In this Review (published online first on Oct 30, 2017), Jonathan Chambers, Ian Hamilton, Robert Lowe, and Steve Pye's affiliation has been corrected to UCL Energy Institute, London, UK; Fereidoon Owfi and Mahnaz Rabbaniha's affiliation has been corrected to Iranian Fisheries Science Research Institute, AREEO, Tehran, Iran; Meisam Tabatabaei's affiliation has been corrected to Biofuel Research Team, Agricultural Biotechnology Research Institute of Iran, AREEO, Karaj, Iran; and Ali Mohammad Latifi's affiliation has been corrected to Applied Biotechnology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran. In figures 31, 33, and 34, the formatting of the currency in the y-axis title has been corrected to US$2016. In figure 36, the y-axis title has been corrected to “Fossil fuel consumption subsidies (US$2016 billion)”. In figure 37, RGGI has been explained in the figure legend and an asterisk symbol has been removed from the figure. In Table 2, CO2 has been spelled out as carbon dioxide. These corrections have been made to the online version as of Nov 23, 2017, and the printed Review is correct.

The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health (vol 391, pg 540, 2017)

Abstract Current approaches to the detection and attribution of an anthropogenic influence on climate involve quantifying the level of agreement between model-predicted patterns of externally forced change and observed changes in the recent climate record. Analyses of uncertainty rely on simulated variability from a climate model. Any numerical representation of the climate is likely to display too little variance on small spatial scales, leading to a risk of spurious detection results. The risk is particularly severe if the detection strategy involves optimisation of signal-to-noise because unrealistic aspects of model variability may automatically be given high weight through the optimisation. The solution is to confine attention to aspects of the model and of the real climate system in which the model simulation of internal climate variability is adequate, or, more accurately, cannot be shown to be deficient. We propose a simple consistency check based on standard linear regression which can be applied to both the space-time and frequency domain approaches to optimal detection and demonstrate the application of this check to the problem of detection and attribution of anthropogenic signals in the radiosonde-based record of recent trends in atmospheric vertical temperature structure. The influence of anthropogenic greenhouse gases can be detected at a high confidence level in this diagnostic, while the combined influence of anthropogenic sulphates and stratospheric ozone depletion is less clearly evident. Assuming the time-scales of the model response are correct, and neglecting the possibility of non-linear feedbacks, the amplitude of the observed signal suggests a climate sensitivity range of 1.2–3.4 K, although the upper end of this range may be underestimated by up to 25% due to uncertainty in model-predicted response patterns.

Checking for model consistency in optimal fingerprinting

Earth’s climate history is often understood by breaking it down into constituent climatic epochs1. Over the Common Era (the past 2,000 years) these epochs, such as the Little Ice Age2–4, have been characterized as having occurred at the same time across extensive spatial scales5. Although the rapid global warming seen in observations over the past 150 years does show nearly global coherence6, the spatiotemporal coherence of climate epochs earlier in the Common Era has yet to be robustly tested. Here we use global palaeoclimate reconstructions for the past 2,000 years, and find no evidence for preindustrial globally coherent cold and warm epochs. In particular, we find that the coldest epoch of the last millennium—the putative Little Ice Age—is most likely to have experienced the coldest temperatures during the fifteenth century in the central and eastern Pacific Ocean, during the seventeenth century in northwestern Europe and southeastern North America, and during the mid-nineteenth century over most of the remaining regions. Furthermore, the spatial coherence that does exist over the preindustrial Common Era is consistent with the spatial coherence of stochastic climatic variability. This lack of spatiotemporal coherence indicates that preindustrial forcing was not sufficient to produce globally synchronous extreme temperatures at multidecadal and centennial timescales. By contrast, we find that the warmest period of the past two millennia occurred during the twentieth century for more than 98 per cent of the globe. This provides strong evidence that anthropogenic global warming is not only unparalleled in terms of absolute temperatures5, but also unprecedented in spatial consistency within the context of the past 2,000 years.

/pdf/no-evidence-for-globally-coherent-warm-and-cold-periods-over-4y8dzfr68e.pdf

No evidence for globally coherent warm and cold periods over the preindustrial Common Era

An extensive new multi-proxy database of paleo-temperature time series (Temperature 12k) enables a more robust analysis of global mean surface temperature (GMST) and associated uncertainties than was previously available. We applied five different statistical methods to reconstruct the GMST of the past 12,000 years (Holocene). Each method used different approaches to averaging the globally distributed time series and to characterizing various sources of uncertainty, including proxy temperature, chronology and methodological choices. The results were aggregated to generate a multi-method ensemble of plausible GMST and latitudinal-zone temperature reconstructions with a realistic range of uncertainties. The warmest 200-year-long interval took place around 6500 years ago when GMST was 0.7 °C (0.3, 1.8) warmer than the 19th Century (median, 5th, 95th percentiles). Following the Holocene global thermal maximum, GMST cooled at an average rate −0.08 °C per 1000 years (−0.24, −0.05). The multi-method ensembles and the code used to generate them highlight the utility of the Temperature 12k database, and they are now available for future use by studies aimed at understanding Holocene evolution of the Earth system.

/pdf/holocene-global-mean-surface-temperature-a-multi-method-4we9l61tuq.pdf

Holocene global mean surface temperature, a multi-method reconstruction approach

A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format.

https://biblio.ugent.be/publication/8660486/file/8660487.pdf

A global database of Holocene paleotemperature records

Multi-decadal surface temperature changes may be forced by natural as well as anthropogenic factors, or arise unforced from the climate system. Distinguishing these factors is essential for estimating sensitivity to multiple climatic forcings and the amplitude of the unforced variability. Here we present 2,000-year-long global mean temperature reconstructions using seven different statistical methods that draw from a global collection of temperature-sensitive paleoclimate records. Our reconstructions display synchronous multi-decadal temperature fluctuations, which are coherent with one another and with fully forced CMIP5 millennial model simulations across the Common Era. The most significant attribution of pre-industrial (1300-1800 CE) variability at multi-decadal timescales is to volcanic aerosol forcing. Reconstructions and simulations qualitatively agree on the amplitude of the unforced global mean multi-decadal temperature variability, thereby increasing confidence in future projections of climate change on these timescales. The largest warming trends at timescales of 20 years and longer occur during the second half of the 20th century, highlighting the unusual character of the warming in recent decades.

/pdf/consistent-multi-decadal-variability-in-global-temperature-52898kh0r8.pdf

Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era.

Quantifying past climate variation and attributing its causes improves our understanding of the natural variability of the climate system. Tree-ring-based proxies have provided skillful and...

/pdf/effects-of-memory-biases-on-variability-of-temperature-43g7ftndhg.pdf

Effects of Memory Biases on Variability of Temperature Reconstructions

L. Lucke. was supported by a studentship from the Natural Environment Research Council (NERC) E3 Doctoral training partnership (grant number NE/L002558/1). A. P. Schurer and G.Hegerl. were supported by NERC under the Belmont forum, Grant PacMedy (NE/P006752/1). The authors acknowledge the World Climate Research Program's Working Group on Coupled Modeling, which is responsible for CMIP, and thank all the climate modeling groups for producing and making available their model output. The authors acknowledge the Northern Hemisphere Tree‐Ring Network Development (N‐TREND) and the Past Global Changes (PAGES) project for providing publicly available data.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020GL088776

Orbital Forcing Strongly Influences Seasonal Temperature Trends During the Last Millennium

Abstract. Here we investigate how uncertainties in the solar and volcanic forcing records of the past millennium affect the large-scale temperature response using a two-box impulse response model. We use different published solar forcing records and present a new volcanic forcing ensemble that accounts for random uncertainties in eruption dating and sulfur injection amount. The simulations are compared to proxy reconstructions from PAGES 2k and Northern Hemispheric tree ring data. We find that low solar forcing is most consistent with all the proxy reconstructions, even when accounting
for volcanic uncertainty. We also find that the residuals are in line with CMIP6 control variability at centennial timescales. Volcanic forcing uncertainty induces a significant spread in the temperature response, especially at periods of peak forcing. For individual eruptions and superposed epoch analyses, volcanic uncertainty can strongly affect the agreement with proxy reconstructions and partly explain known proxy–model discrepancies.


Lucie J. Lücke

Papers

Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era.

Effects of Memory Biases on Variability of Temperature Reconstructions

Orbital Forcing Strongly Influences Seasonal Temperature Trends During the Last Millennium

The effect of uncertainties in natural forcing records on simulated temperature during the last millennium