Multidecadal hydroclimate variability has been expressed as “megadroughts” (dry periods more severe and prolonged than observed over the twentieth century) and corresponding “megapluvial” wet periods in many regions around the world. The risk of such events is strongly affected by modes of coupled atmosphere–ocean variability and by external impacts on climate. Accurately assessing the mechanisms for these interactions is difficult, since it requires large ensembles of millennial simulations as well as long proxy time series. Here, the Community Earth System Model (CESM) Last Millennium Ensemble is used to examine statistical associations among megaevents, coupled climate modes, and forcing from major volcanic eruptions. El Niño–Southern Oscillation (ENSO) strongly affects hydroclimate extremes: larger ENSO amplitude reduces megadrought risk and persistence in the southwestern United States, the Sahel, monsoon Asia, and Australia, with corresponding increases in Mexico and the Amazon. The Atlantic multidecadal oscillation (AMO) also alters megadrought risk, primarily in the Caribbean and the Amazon. Volcanic influences are felt primarily through enhancing AMO amplitude, as well as alterations in the structure of both ENSO and AMO teleconnections, which lead to differing manifestations of megadrought. These results indicate that characterizing hydroclimate variability requires an improved understanding of both volcanic climate impacts and variations in ENSO/AMO teleconnections.

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The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial) variability in the climate system. Since this lowfrequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long term, high-magnitude variability under greenhouse forcing (??). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper

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Accurate assessments of future climate impacts require realistic simulation of interannual-century-scale temperature and precipitation variability. Here, well-constrained paleoclimate data and the latest generation of Earth system model data are used to evaluate the magnitude and spatial consistency of climate variance distributions across interannual to centennial frequencies. It is found that temperature variance generally increases with time scale in patterns that are spatially consistent among models, especially over the mid-and high-latitude oceans. However, precipitation is similar to white noise across much of the globe. When Earth system model variance is compared to variance generated by simple autocorrelation, it is found that tropical temperature variability in Earth system models is difficult to distinguish from variability generated by simple autocorrelation. By contrast, both forced and unforced Earth system models produce variability distinct from a simple autoregressive process over most high-latitude oceans. This new analysis of tropical paleoclimate records suggests that low-frequency variance dominates the temperature spectrum across the tropical Pacific and Indian Oceans, but in many Earth system models, interannual variance dominates the simulated central and eastern tropical Pacific temperature spectrum, regardless of forcing. Tropical Pacific model spectra are compared to spectra from the instrumental record, but the short instrumental record likely cannot provide accurate multidecadal-centennial-scale variance estimates. In the coming decades, both forced and natural patterns of decade-century-scale variability will determine climaterelated risks. Underestimating low-frequency temperature and precipitation variability may significantly alter our understanding of the projections of these climate impacts.

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Deep (> 5 m) sheeting fractures in the Navajo sandstone are evident at numerous sites in southern Utah and derive from tectonic stresses. Strong diurnal thermal cycles are, however, the likely triggers for shallow (< 0.3 m) sheeting fractures. Data from subsurface thermal sensors reveal that large temperature differences between sensors at 2 and 15 cm depth on clear summer afternoons are as great as those that trigger sheeting fractures in exposed California granite. Extensive polygonal patterns in the Navajo sandstone are composed of surface-perpendicular fractures and were produced by contractile stresses. Numerous studies have shown that porewater diminishes the tensile strength of sandstone. Based on our thermal records, we propose that cooling during monsoonal rainstorms triggers polygonal fracturing of temporarily weakened rock. On steep outcrops, polygonal patterns are rectilinear and orthogonal, with T-vertices. Lower-angle slopes host hexagonal patterns (defined by the dominance of Y-vertices). Intermediate patterns with rectangles and hexagons of similar scale are common. We posit that outcropping fractures are 1 digitalcommons.unl.edu

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