Observed anomalous atmospheric patterns in summers of unusual Arctic sea ice melt

The Arctic sea ice retreat has accelerated over the last decade. The negative trend is largest in summer, but substantial interannual variability still remains. Here we explore observed atmospheric conditions and feedback mechanisms during summer months of anomalous sea ice melt in the Arctic. Compositing months of anomalous low and high sea ice melt over 1979–2013, we find distinct patterns in atmospheric circulation, precipitation, radiation, and temperature. Compared to summer months of anomalous low sea ice melt, high melt months are characterized by anomalous high sea level pressure in the Arctic (up to 7 hPa), with a corresponding tendency of storms to track on a more zonal path. As a result, the Arctic receives less precipitation overall and 39% less snowfall. This lowers the albedo of the region and reduces the negative feedback the snowfall provides for the sea ice. With an anticyclonic tendency, 12 W/m2 more incoming shortwave radiation reaches the surface in the start of the season. The melting sea ice in turn promotes cloud development in the marginal ice zones and enhances downwelling longwave radiation at the surface toward the end of the season. A positive cloud feedback emerges. In midlatitudes, the more zonally tracking cyclones give stormier, cloudier, wetter, and cooler summers in most of northern Europe and around the Sea of Okhotsk. Farther south, the region from the Mediterranean Sea to East Asia experiences significant surface warming (up to 2.4◦C), possibly linked to changes in the jet stream

Arctic Summer Sea Ice Melt and Related Atmospheric Conditions in Coupled Regional Climate Model Simulations and Observations

Observations from 1979 to 2014 show a positive trend in the summer sea ice melt rate with an acceleration particularly in June and August. This is associated with atmospheric circulation changes such as a tendency toward a dipole pattern in the mean sea level pressure (SLP) trend with an increase over the Arctic Ocean and a decrease over Siberia. Consistent with previous studies, we here show the statistical relationship between the summer sea ice melt rate and SLP and that more than one SLP pattern is associated with anomalously high melt rates. Most high melt rates occur during high pressure over the Arctic Ocean accompanied by low pressure over Siberia, but a strong Beaufort High and advection of warm air associated with a cyclone located over the Taymyr Peninsula can also trigger anomalous high ice melt. We evaluate 10-member ensemble simulations with the coupled atmosphere-ice-ocean Arctic regional climate model HIRHAM-NAOSIM. The simulations have systematically low acceleration of sea ice melt rate in August, related to shortcomings in representing the strengthening pressure gradient from the Barents/Kara Sea toward Northern Greenland in recent decades. In general, the model shows the same classification of SLP patterns related to anomalous melt rates as the observations. However, the evolution of sea ice melt-related cloud-radiation feedback over the summer reveals contrary effects from low-level clouds in the reanalysis and in the simulations

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Evidence for Predictive Skill of High-Latitude Climate Due to Midsummer Sea Ice Extent Anomalies

Previous work has explored the linkages between Arctic sea ice extent (SIE) anomalies at the end of the summer melt season and high-latitude climate. Here we show that Arctic midsummer SIE anomalies provide predictive skill on time scales of similar to 2-3months for high-latitude climate. Midsummers characterized by low SIE are associated with significant positive temperature and easterly wind anomalies throughout the high-latitude troposphere through September and significant positive temperature anomalies at the Arctic surface into October. The inferred predictive skill for autumn climate derives from the persistence of the sea ice field. It is robust throughout the Arctic basin and is supported in climate models from the fifth phase of the Coupled Model Intercomparison Project archive and in prediction experiments from the Arctic Predictability and Prediction on Seasonal to Interannual Time scales project. It is theorized that the predictive skill derives from (1) the anomalous storage of heat in the Arctic Ocean during periods of low summertime SIE and (2) the delayed formation of sea ice during the following autumn months. Plain Language Summary Here we analyze the evidence for predictability of high-latitude climate that derives from Arctic sea ice extent (SIE) anomalies. We demonstrate that the continuous observed lagged correlations between Arctic sea ice anomalies and Arctic/high-latitude climate are most robust in association with midsummer (July) SIE. The linkages between midsummer SIE anomalies and Arctic/high-latitude climate are significant well into autumn and have potential implications for the prediction of high-latitude climate up to 3months in advance. The results have implications for the influence of long-term decreases in summertime sea ice on climate change over the high latitudes

Point mutations and genomic deletions in CCND1 create stable truncated cyclin D1 mRNAs that are associated with increased proliferation rate and shorter survival

A gene expression signature of tumor proliferation rate in mantle cell lymphoma (MCL) is an overriding molecular predictor of the length of survival following diagnosis. Many strongly proliferative MCL tumors have exceptionally high cyclin D1 mRNA levels and preferentially express short cyclin D1 mRNA isoforms. We demonstrate here that these short mRNAs are cyclin D1a isoforms with truncated 3′UTRs, not alternatively spliced cyclin D1b mRNA isoforms. Among 15 MCL tumors with truncated cyclin D1 mRNAs, 7 had genomic deletions in the CCND1 3′UTR region. In 3 others, CCND1 contained point mutations that created premature polyadenylation signals, giving rise to 1.5-kb mRNAs lacking most of the 3′UTR. Both types of genomic alteration created transcripts lacking mRNA destabilization elements present in the wild-type cyclin D1a mRNA. Premature polyadenylation due to a 3′UTR mutation also was present in the Z-138 MCL cell line, which expressed both truncated and full-length cyclin D1a mRNAs. In these cells, the half-life of the short cyclin D1a mRNA was much longer than that of the full-length mRNA. We conclude that alterations of CCND1 3′UTR structure can significantly increase its oncogenic effect and worsen the clinical course of MCL patients

The arctic cloud puzzle: Using ACLOUD/PASCAL multiplatform observations to unravel the role of clouds and aerosol particles in arctic amplification

Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3 project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns