A Re-evaluation of Climate Sensitivity

Equilibrium climate sensitivity (ECS) is the change in global mean temperature expected to result from doubling atmospheric CO2 concentration from pre-industrial levels. Extensive research during the past 40 years has not reduced the uncertainty associated with ECS. Sherwood et al. [1] applied Bayesian statistics to evidence from climate-process physics, historical observations and earlier proxies to reduce the range of ECS from 1.5 – 4.5 K to 2.6 – 4.1 K. This paper examines their methods and many of the assumptions they made. It also evaluates two additional periods in the Holocene to show that factors other than CO2 drove recent climate change. It identifies potential systematic errors resulting from adding non-equilibrium short-term adjustments to the radiative forcing of greenhouse gases and from underestimating the effects of solar irradiance, ocean currents and aerosols. These factors have resulted in estimates of the forcing by CO2 that far exceed the apparent effects in paleoclimate data.

(Paleo)climate science for the 21st century

<p>Records of past climate trends, variability, and extremes hold key insights into Earth’s changing climate, yet their full potential will remain untapped without a concerted effort to surmount several critical challenges, some time-sensitive.  In a century defined by accelerating climate change and human disturbance, the climate archive itself is at grave risk given that i) many paleoclimate records end in the late 20<sup>th</sup> century, with no concerted effort to extend them to the present-day, and ii) many paleoclimate archives are disappearing under pressure from climate change and/or human disturbance. Second, many paleoclimate records are comprised of oxygen isotopes, yet the coordinated, multi-scale observational and modeling infrastructures required to unravel the mechanisms governing water isotope variability are as yet underdeveloped. This dramatic oversight exists despite development of technologies that avoid costly analysis via mass spectrometers, and despite the fact that water isotopes may very well be one of the most powerful diagnostic tracers of a changing global water cycle. Lastly, in part owing to the aforementioned deficiencies, paleoclimate data assimilation efforts remain fraught with large uncertainties, despite their promise in constraining many of the most uncertain aspects of future climate impacts, including the evolution of extreme events and hydrological trends and variability. Climate science for the 21<sup>st</sup> century requires deep investments in the full integration of paleoclimate data and approaches into frameworks for climate risk and hazard assessments. In this sense, it is not surprising that paleoclimate scientists have played a key role in the communication of climate change science to decision-makers and the general public alike. Their understanding of the Earth system also equips them to contribute valuable insights to teams comprised of researchers, practitioners, and  decision-makers charged with leveraging science to inform solutions, in service to society. It’s time to recognize that all climate scientists study climate of the past, and all paleoclimate scientists have insights that are relevant to our climate future.</p>

Timescale-dependent stability of surface air temperature and the forced temperature response

<p><span>Earth's climate can be understood as a dynamical system that changes due to external forcing and internal couplings. It can be characterized from the evolution of essential climate variables, such as surface air temperature. Yet, the mechanisms, amplitudes, and spatiotemporal patterns of global and local temperature fluctuations around its mean, called temperature variability, are insufficiently understood. Discrepancies exist between temperature variability from model and paleoclimate data at the temporal scale of years to centuries and at the local scale, both of which are important socio-economic scales for long-term planning.</span> <br><span>Here, we clarify whether global and local temperature signals from the last millennia show a stationary variance on these timescales and thus behave in a stable manner or not. Therefore, we contrast power spectral densities and their scaling behaviors using simulated, observed, and reconstructed temperatures on periods between 10 and 200 years. Despite careful consideration of possible spectral biases, we find that local temperatures from paleoclimate data tend to show unstable behavior, while simulated temperatures almost exclusively show stable behavior. Conversely, the global mean temperature tends to be stable. We explain this by introducing the gain as a powerful tool to analyze the forced temperature response, based on a novel estimate of the joint power spectrum of radiative forcing.</span> <br><span>Our analysis identifies main deficiencies in the properties of temperature variability and offers new insights into the linkage between raditative forcing and temperature response, relevant to the understanding of Earth’s dynamics and the assessment of climate risks.</span></p>

Improving Access to Paleoclimate Data

Paleoclimate databases are powerful tools for improving climate models. The recent work of speleothem researchers offers lessons on creating a lasting database and fostering the needed mindset.

Climate model teleconnection patterns govern the Niño 3.4 response to early 19th century volcanism in coral-based data assimilation reconstructions

Scientific understanding of low-frequency tropical Pacific variability, especially responses to perturbations in radiative forcing, suffers from short observational records, sparse proxy networks, and bias in model simulations. Here, we combine the strengths of proxies and models through coral-based paleoclimate data assimilation. We combine coral archives (δ18O, Sr/Ca) with the dynamics, spatial teleconnections, and intervariable relationships of the CMIP5/PMIP3 Past1000 experiments using the Last Millennium Reanalysis data assimilation framework. This analysis creates skillful reconstructions of tropical Pacific temperatures over the observational era. However, during the period of intense volcanism in the early 19th century, southwestern Pacific corals produce El Niño Southern Oscillation (ENSO) reconstructions that are of opposite sign from those from eastern Pacific corals and tree ring records. We systematically evaluate the source of this discrepancy using 1) single-proxy experiments, 2) varied proxy system models (PSMs), and 3) diverse covariance patterns from the Past1000 simulations. We find that individual proxy records and coral PSMs do not significantly contribute to the discrepancy. However, following major eruptions, the southwestern Pacific corals locally record more persistent cold anomalies than found in the Past1000 experiments and canonical ENSO teleconnections to the southwest Pacific strongly control the reconstruction response. Furthermore, using covariance patterns independent of ENSO yield reconstructions consistent with coral archives across the Pacific. These results show that model bias can strongly affect how proxy information is processed in paleoclimate data assimilation. As we illustrate here, model bias influences the magnitude and persistence of the response of the tropical Pacific to volcanic eruptions.