Melt-induced speed-up of Greenland ice sheet offset by efficient subglacial drainage

Fluctuations in surface melting are known to affect the speed of glaciers and ice sheets, but their impact on the Greenland ice sheet in a warming climate remains uncertain. Although some studies suggest that greater melting produces greater ice-sheet acceleration, others have identified a long-term decrease in Greenland's flow despite increased melting. Here we use satellite observations of ice motion recorded in a land-terminating sector of southwest Greenland to investigate the manner in which ice flow develops during years of markedly different melting. Although peak rates of ice speed-up are positively correlated with the degree of melting, mean summer flow rates are not, because glacier slowdown occurs, on average, when a critical run-off threshold of about 1.4?centimetres a day is exceeded. In contrast to the first half of summer, when flow is similar in all years, speed-up during the latter half is 62?±?16 per cent less in warmer years. Consequently, in warmer years, the period of fast ice flow is three times shorter and, overall, summer ice flow is slower. This behaviour is at odds with that expected from basal lubrication alone. Instead, it mirrors that of mountain glaciers, where melt-induced acceleration of flow ceases during years of high melting once subglacial drainage becomes efficient. A model of ice-sheet flow that captures switching between cavity and channel drainage modes is consistent with the run-off threshold, fast-flow periods, and later-summer speeds we have observed. Simulations of the Greenland ice-sheet flow under climate warming scenarios should account for the dynamic evolution of subglacial drainage; a simple model of basal lubrication alone misses key aspects of the ice sheet's response to climate warming.     

Extended megadroughts in the southwestern United States during Pleistocene interglacials

The potential for increased drought frequency and severity linked to anthropogenic climate change in the semi-arid regions of the southwestern United States (US) is a serious concern. Multi-year droughts during the instrumental period and decadal-length droughts of the past two millennia were shorter and climatically different from the future permanent, 'dust-bowl-like' megadrought conditions, lasting decades to a century, that are predicted as a consequence of warming. So far, it has been unclear whether or not such megadroughts occurred in the southwestern US, and, if so, with what regularity and intensity. Here we show that periods of aridity lasting centuries to millennia occurred in the southwestern US during mid-Pleistocene interglacials. Using molecular palaeotemperature proxies to reconstruct the mean annual temperature (MAT) in mid-Pleistocene lacustrine sediment from the Valles Caldera, New Mexico, we found that the driest conditions occurred during the warmest phases of interglacials, when the MAT was comparable to or higher than the modern MAT. A collapse of drought-tolerant C(4) plant communities during these warm, dry intervals indicates a significant reduction in summer precipitation, possibly in response to a poleward migration of the subtropical dry zone. Three MAT cycles ～2?°C in amplitude occurred within Marine Isotope Stage (MIS) 11 and seem to correspond to the muted precessional cycles within this interglacial. In comparison with MIS 11, MIS 13 experienced higher precessional-cycle amplitudes, larger variations in MAT (4-6?°C) and a longer period of extended warmth, suggesting that local insolation variations were important to interglacial climatic variability in the southwestern US. Comparison of the early MIS 11 climate record with the Holocene record shows many similarities and implies that, in the absence of anthropogenic forcing, the region should be entering a cooler and wetter phase.     

Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?

We study the performance of recently developed linear regression models for interval data when it comes to forecasting the uncertainty surrounding future stock returns. These interval data models use easy‐to‐compute daily return intervals during the modeling, estimation and forecasting stage. They have to stand up to comparable point‐data models of the well‐known capital asset pricing model type—which employ single daily returns based on successive closing prices and might allow for GARCH effects—in a comprehensive out‐of‐sample forecasting competition. The latter comprises roughly 1000 daily observations on all 30 stocks that constitute the DAX, Germany's main stock index, for a period covering both the calm market phase before and the more turbulent times during the recent financial crisis. The interval data models clearly outperform simple random walk benchmarks as well as the point‐data competitors in the great majority of cases. This result does not only hold when one‐day‐ahead forecasts of the conditional variance are considered, but is even more evident when the focus is on forecasting the width or the exact location of the next day's return interval. Regression models based on interval arithmetic thus prove to be a promising alternative to established point‐data volatility forecasting tools. Copyright ©2015 John Wiley & Sons, Ltd.     

ANG mutations segregate with familial and 'sporadic' amyotrophic lateral sclerosis

We recently identified angiogenin (ANG) as a candidate susceptibility gene for amyotrophic lateral sclerosis (ALS), a neurodegenerative disorder characterized by adult-onset loss of motor neurons. We now report the finding of seven missense mutations in 15 individuals, of whom four had familial ALS and 11 apparently 'sporadic' ALS. Our findings provide further evidence that variations in hypoxia-inducible genes have an important role in motor neuron degeneration.     

Male-pattern baldness susceptibility locus at 20p11

We conducted a genome-wide association study for androgenic alopecia in 1,125 men and identified a newly associated locus at chromosome 20p11.22, confirmed in three independent cohorts (n = 1,650; OR = 1.60, P = 1.1 x 10(-14) for rs1160312). The one man in seven who harbors risk alleles at both 20p11.22 and AR (encoding the androgen receptor) has a sevenfold-increased odds of androgenic alopecia (OR = 7.12, P = 3.7 x 10(-15)).