Relevance of warm air intrusions for Arctic satellite sea ice concentration time series

Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature-induced snow metamorphism and ice crust formations, e.g., after melt–refreeze events. Common microwave radiometer satellite sea ice concentration retrievals are based on empirical models using the snow-covered sea ice emissivity and thus can be influenced by strong warm air intrusions. Here, we carry out a long-term study analyzing 41 years of winter sea ice concentration observations from different algorithms to investigate the impact of warm air intrusions on the retrieved ice concentration. Our results show that three out of four algorithms underestimate the sea ice concentration during (and up to 10 d after) warm air intrusions which increase the 2 m air temperature (daily maximum) above − 5 ∘C. This can lead to sea ice area underestimations in the order of 104 to 105 km2. If the 2 m temperature during the warm air intrusions crosses − 2 ∘C, all algorithms are impacted. Our analysis shows that the strength of these strong warm air intrusions increased in recent years, especially in April. With a further climate change, such warm air intrusions are expected to occur more frequently and earlier in the season, and their influence on sea ice climate data records will become more important.</p

Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean–sea ice modelling system

The accuracy of the initial state is very important for the quality of a forecast, and data assimilation is crucial for obtaining the best-possible initial state. For many years, sea-ice concentration was the only parameter used for assimilation into numerical sea-ice models. Sea-ice concentration can easily be observed by satellites, and satellite observations provide a full Arctic coverage. During the last decade, an increasing number of sea-ice related variables have become available, which include sea-ice thickness and snow depth, which are both important parameters in the numerical sea-ice models. In the present study, a coupled ocean–sea-ice model is used to assess the assimilation impact of sea-ice thickness and snow depth on the model. The model system with the assimilation of these parameters is verified by comparison with a system assimilating only ice concentration and a system having no assimilation. The observations assimilated are sea ice concentration from the Ocean and Sea Ice Satellite Application Facility, thin sea ice from the European Space Agency's (ESA) Soil Moisture and Ocean Salinity mission, thick sea ice from ESA's CryoSat-2 satellite, and a new snow-depth product derived from the National Space Agency's Advanced Microwave Scanning Radiometer (AMSR-E/AMSR-2) satellites. The model results are verified by comparing assimilated observations and independent observations of ice concentration from AMSR-E/AMSR-2, and ice thickness and snow depth from the IceBridge campaign. It is found that the assimilation of ice thickness strongly improves ice concentration, ice thickness and snow depth, while the snow observations have a smaller but still positive short-term effect on snow depth and sea-ice concentration. In our study, the seasonal forecast showed that assimilating snow depth led to a less accurate long-term estimation of sea-ice extent compared to the other assimilation systems. The other three gave similar results. The improvements due to assimilation were found to last for at least 3–4 months, but possibly even longer.</p

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March-April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial-temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations

Predictors of binge drinking in adolescents: ultimate and distal factors - a representative study

<p>Abstract</p> <p>Background</p> <p>As epidemiological surveys have shown, binge drinking is a constant and wide-spread problem behavior in adolescents. It is not rare to find that more than half of all adolescents engage in this behavior when assessing only the last 4 weeks of time independent of the urbanity of the region they live in. There have been several reviews on predictors of substance consumption in adolescents in general, but there has been less high quality research on predictors of binge drinking, and most studies have not been theoretically based. The current study aimed to analyze the ultimate and distal factors predicting substance consumption according to Petraitis' theory of triadic influence. We assessed the predictive value of these factors with respect to binge drinking in German adolescents, including the identification of influence direction.</p> <p>Methods</p> <p>In the years 2007/2008, a representative written survey of N = 44,610 students in the 9^thgrade of different school types in Germany was carried out (net sample). The return rate of questionnaires was 88% regarding all students whose teachers or school directors had agreed to participate in the study. In this survey, prevalence of binge drinking was investigated as well as potential predictors from the social/interpersonal, the attitudinal/environmental, and the intrapersonal fields (3 factors of Petraitis). In a multivariate logistic regression analysis, these variables were included after testing for multicollinearity in order to assess their ability to predict binge drinking.</p> <p>Results</p> <p>Prevalence of binge drinking in the last 30 days was 52.3% for the surveyed adolescents with a higher prevalence for boys (56.9%) than for girls (47.5%). The two most influential factors found to protect against binge drinking with <it>p </it>< .001 were low economic status and importance of religion. The four most relevant risk factors for binge drinking (<it>p </it>< .001) were life-time prevalence of school absenteeism/truancy, academic failure, suicidal thoughts, and violence at school in the form of aggressive behavior of teachers. The model of Petraitis was partly confirmed for Binge Drinking in German adolescents and the direction of influence factors was clarified.</p> <p>Conclusions</p> <p>Whereas some of the risk and protective factors for binge drinking are not surprising since they are known for substance abuse in general, there are two points that could be targeted in interventions that do not focus on adolescents alone: (a) training teachers in positive, reassuring behavior and constructive criticism and (b) a focus on high risk adolescents either because they have a lack of coping strategies when in a negative mood or because of their low academic achievement in combination with absenteeism from school.</p

Demographic, Psychological, and Social Characteristics of Self-Identified Lesbian, Gay, and Bisexual Adults in a US Probability Sample

Using data from a US national probability sample of self-identified lesbian, gay, and bisexual adults (N = 662), this article reports population parameter estimates for a variety of demographic, psychological, and social variables. Special emphasis is given to information with relevance to public policy and law. Compared with the US adult population, respondents were younger, more highly educated, and less likely to be non-Hispanic White, but differences were observed between gender and sexual orientation groups on all of these variables. Overall, respondents tended to be politically liberal, not highly religious, and supportive of marriage equality for same-sex couples. Women were more likely than men to be in a committed relationship. Virtually all coupled gay men and lesbians had a same-sex partner, whereas the vast majority of coupled bisexuals were in a heterosexual relationship. Compared with bisexuals, gay men and lesbians reported stronger commitment to a sexual-minority identity, greater community identification and involvement, and more extensive disclosure of their sexual orientation to others. Most respondents reported experiencing little or no choice about their sexual orientation. The importance of distinguishing among lesbians, gay men, bisexual women, and bisexual men in behavioral and social research is discussed

Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project has been established in 2016. It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, ship-borne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data