Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.

The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here power spectra and power laws (β) are estimated from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). The significance of the estimates of spectral densities and β are tested against the null hypothesis that they reflect solely the effects of local (nonclimate) sources of autocorrelation at the monthly time scale. Although tree-ring-based hydroclimate reconstructions are generally consistent with this null hypothesis, values of β calculated from long moisture-sensitive chronologies (as opposed to reconstructions) and other types of hydroclimate proxies exceed null expectations. Therefore it may be argued that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) are consistent with the null hypothesis and appear unable to generate variance in hydroclimate commensurate with paleoclimate records. Consequently, at decadal-to-multidecadal time scales there is more variability in instrumental and proxy data than in the models, suggesting that the risk of prolonged droughts under climate change may be underestimated by CMIP5 simulations of the future.

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The western United States was affected by several megadroughts during the last 1200 years, most prominently during the Medieval Climate Anomaly (MCA; 800 to 1300 CE). A null hypothesis is developed to test the possibility that, given a sufficiently long period of time, these events are inevitable and occur purely as a consequence of internal climate variability. The null distribution of this hypothesis is populated by a linear inverse model (LIM) constructed from global sea surface temperature anomalies and self-calibrated Palmer drought severity index data for North America. Despite being trained only on seasonal data from the late twentieth century, the LIM produces megadroughts that are comparable in their duration, spatial scale, and magnitude to the most severe events of the last 12 centuries. The null hypothesis therefore cannot be rejected with much confidence when considering these features of megadrought, meaning that similar events are possible today, even without any changes to boundary conditions. In contrast, the observed clustering of megadroughts in the MCA, as well as the change in mean hydroclimate between the MCA and the 1500–2000 period, are more likely to have been caused by either external forcing or by internal climate variability not well sampled during the latter half of the twentieth century. Finally, the results demonstrate that the LIM is a viable tool for determining whether paleoclimate reconstructions events should be ascribed to external forcings or to “out of sample” climate mechanisms, or if they are consistent with the variability observed during the recent period.

The salient feature of the oceanic thermal structure is a remarkably shallow thermocline, especially in the Tropics and subtropics. What factors determine its depth? Theories for the deep thermohaline circulation provide an answer that depends on oceanic diffusivity, but they deny the surface winds an explicit role. Theories for the shallow ventilated thermocline take into account the influence of the wind explicitly, but only if the thermal structure in the absence of any winds, the thermal structure along the eastern boundary, is given. To complete and marry the existing theories for the oceanic thermal structure, this paper invokes the constraint of a balanced heat budget for the ocean. The oceanic heat gain occurs primarily in the upwelling zones of the Tropics and subtropics and depends strongly on oceanic conditions, specifically the depth of the thermocline. The heat gain is large when the thermocline is shallow but is small when the thermocline is deep. The constraint of a balanced heat budget therefore implies that an increase in heat loss in high latitudes can result in a shoaling of the tropical thermocline; a decrease in heat loss can cause a deepening of the thermocline. Calculations with an idealized general circulation model of the ocean confirm these inferences. Arguments based on a balanced heat budget yield an expression for the depth of the thermocline in terms of parameters such as the imposed surface winds, the surface temperature gradient, and the oceanic diffusivity. These arguments in effect bridge the theories for the ventilated thermocline and the thermohaline circulation so that previous scaling arguments are recovered as special cases of a general result.

River flooding is among the most destructive of natural hazards globally, causing widespread loss of life, damage to infrastructure and economic deprivation. Societies are currently under increasing threat from such floods, predominantly from increasing exposure of people and assets in flood‐prone areas, but also as a result of changes in flood magnitude, frequency, and timing. Accurate flood hazard and risk assessment are therefore crucial for the sustainable development of societies worldwide. With a paucity of hydrological measurements, evidence from the field offers the only insight into truly extreme events and their variability in space and time. Historical, botanical, and geological archives have increasingly been recognized as valuable sources of extreme flood event information. These different archives are here reviewed with a particular focus on the recording mechanisms of flood information, the historical development of the methodological approaches and the type of information that those archives can provide. These studies provide a wealthy dataset of hundreds of historical and palaeoflood series, whose analysis reveals a noticeable dominance of records in Europe. After describing the diversity of flood information provided by this dataset, we identify how these records have improved and could further improve flood hazard assessments and, thereby, flood management and mitigation plans. This article is categorized under: Science of Water > Water Extremes Engineering Water > Planning Water Science of Water > Methods

[1] We assess the magnitude of decadal to multidecadal (D2M) variability in Climate Model Intercomparison Project 5 (CMIP5) simulations that will be used to understand, and plan for, climate change as part of the Intergovernmental Panel on Climate Change's 5th Assessment Report. Model performance on D2M timescales is evaluated using metrics designed to characterize the relative and absolute magnitude of variability at these frequencies. In observational data, we find that between 10% and 35% of the total variance occurs on D2M timescales. Regions characterized by the high end of this range include Africa, Australia, western North America, and the Amazon region of South America. In these areas D2M fluctuations are especially prominent and linked to prolonged drought. D2M fluctuations account for considerably less of the total variance (between 5% and 15%) in the CMIP5 archive of historical (1850-2005) simulations. The discrepancy between observation and model based estimates of D2M prominence reflects two features of the CMIP5 archive. First, interannual components of variability are generally too energetic. Second, decadal components are too weak in several key regions. Our findings imply that projections of the future lack sufficient decadal variability, presenting a limited view of prolonged drought and pluvial risk. Citation: Ault, T. R., J. E. Cole, and S. St. George (2012),The amplitude of decadal to multidecadal variability in precipitation simulated by state-of-the-art climate models, Geophys. Res.

We examine how the seasonality of precipitation signals embedded within the North American Drought Atlas varies across the continent. Instrumental records of average summer (JJA) Palmer Drought Severity Index (PDSI) are characterized by major regional differences in the relative importance of precipitation during summer and winter (DJF). The Atlas, which is based on a network of drought-sensitive tree-ring records, is able to reproduce the main geographic patterns of these biases, but tree-ring reconstructions exaggerate the influence of seasonal precipitation anomalies in the southwestern United States and northern Mexico (towards a stronger winter signal) and western Canada (towards a stronger summer signal). Drought reconstructions from the Southwest and Tex-Mex regions are tuned mainly to winter precipitation and display strong teleconnections to both El Niño and La Niña. In contrast, winter precipitation signals are either weak or absent in drought reconstructions from northwestern North America, and tree-ring estimates of PDSI show a much less robust association with the El Niño-Southern Oscillation. Geographical differences in the relative strength of seasonal precipitation signals are likely due to (i) local factors that influence tree growth but are not incorporated into the PDSI algorithm and (ii) real differences in regional climatology. These seasonal biases must be taken into account when comparing drought reconstructions across North America, when comparing tree-ring PDSI to drought records developed from other proxies or when attempting to use the Drought Atlas to link past droughts to potential forcing mechanisms.