The Influence of Recurrent Modes of Climate Variability on the Occurrence of Winter and Summer Extreme Temperatures over North America

The influence of the Pacific–North American (PNA) pattern, the northern annular mode (NAM), and the El Ni~no–Southern Oscillation (ENSO) on extreme temperature days and months over North America is examined. Associations between extreme temperature days and months are strongest with the PNA and NAM andweaker for ENSO. In general, the associationwith extremes tends to be stronger onmonthly than daily time scales and for winter as compared to summer. Extreme temperatures are associated with the PNAandNAMin the vicinity of the centers of action of these circulation patterns; however, many extremes also occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however, many of these smaller-scale events are concurrent with amplified PNA or NAMpatterns. Associations are weaker in summer when other physicalmechanisms affecting the surface energy balance, such as anomalous soilmoisture content, also influence the occurrence of extreme temperatures

Model evidence for a seasonal bias in Antarctic ice cores

Much of the global annual mean temperature change over Quaternary glacial cycles can be attributed to slow ice sheet and greenhouse gas feedbacks, but analysis of the short-term response to orbital forcings has the potential to reveal key relationships in the climate system. In particular, obliquity and precession both produce highly seasonal temperature responses at high latitudes. Here, idealized single-forcing model experiments are used to quantify Earth’s response to obliquity, precession, CO2, and ice sheets, and a linear reconstruction methodology is used to compare these responses to long proxy records around the globe. This comparison reveals mismatches between the annual mean response to obliquity and precession in models versus the signals within Antarctic ice cores. Weighting the model-based reconstruction toward austral winter or spring reduces these discrepancies, providing evidence for a seasonal bias in ice cores

The Apical Complex Couples Cell Fate and Cell Survival to Cerebral Cortical Development

Cortical development depends upon tightly controlled cell fate and cell survival decisions that generate a functional neuronal population, but the coordination of these two processes is poorly understood. Here we show that conditional removal of a key apical complex protein, Pals1, causes premature withdrawal from the cell cycle, inducing excessive generation of early-born postmitotic neurons followed by surprisingly massive and rapid cell death, leading to the abrogation of virtually the entire cortical structure. Pals1 loss shows exquisite dosage sensitivity, so that heterozygote mutants show an intermediate phenotype on cell fate and cell death. Loss of Pals1 blocks essential cell survival signals, including the mammalian target of rapamycin (mTOR) pathway, while mTORC1 activation partially rescues Pals1 deficiency. These data highlight unexpected roles of the apical complex protein Pals1 in cell survival through interactions with mTOR signaling

Comparison between Observed and Model-Simulated Atmospheric CirculationPatterns Associated with Extreme Temperature Days over North AmericaUsing CMIP5 Historical Simulations

Circulation patterns associated with extreme temperature days over North America, as simulated by a suite of climate models, are compared with those obtained from observations. The authors analyze 17 coupled atmosphere–ocean general circulation models contributing to the fifth phase of the Coupled Model Intercomparison Project. Circulation patterns are defined as composites of anomalies in sea level pressure and 500-hPa geopotential height concurrent with days in the tails of temperature distribution. Several metrics used to systematically describe circulation patterns associated with extreme temperature days are applied to both the observed and model-simulated data. Additionally, self-organizing maps are employed as a means of comparing observed and model-simulated circulation patterns across the North American domain. In general, the multimodel ensemble resembles the observed patterns well, especially in areas removed from complex geographic features (e.g., mountains and coastlines). Individual model results vary; however, the majority of models capture the major features observed. The multimodel ensemble captures several key features, including regional variations in the strength and orientation of atmospheric circulation patterns associated with extreme temperatures, both near the surface and aloft, as well as variations with latitude and season. The results from this work suggest that these models can be used to comprehensively examine the role that changes in atmospheric circulation will play in projected changes in temperature extremes because of future anthropogenic climate warming

On the Use of Cloud Forcing to Estimate Cloud Feedback

Uncertainty in cloud feedback is the leading cause of discrepancy in model predictions of climate change. The use of observed or model-simulated radiative fluxes to diagnose the effect of clouds on climate sensitivity requires an accurate understanding of the distinction between a change in cloud radiative forcing and a cloud feedback. This study compares simulations from different versions of the GFDL Atmospheric Model 2 (AM2) that have widely varying strengths of cloud feedback to illustrate the differences between the two and highlight the potential for changes in cloud radiative forcing to be misinterpreted