The winds of young Solar-type stars in the Hyades

Stellar winds govern the spin-down of Solar-type stars as they age, and play an important role in determining planetary habitability, as powerful winds can lead to atmospheric erosion. We calculate 3D stellar wind models for five young Solar-type stars in the Hyades cluster, using TOUPIES survey stellar magnetograms and state-of-the-art Alfvén wave-driven wind modelling. The stars have the same 0.6 Gyr age and similar fundamental parameters, and we account for the uncertainty in and underestimation of absolute field strength inherent in Zeeman-Doppler imaging by adopting both unscaled and scaled (by a factor of five) field strengths. For the unscaled fields, the resulting stellar wind mass-loss is 2-4 times greater and the angular momentum loss 2-10 times greater than for the Sun today, with the scaled results correspondingly greater. We compare our results with a range published of wind models and for the Alfvén wave-driven modelling see evidence of mass-loss saturation at ${\sim 10} \dot{M}_{\odot }$

The winds of young Solar-type stars in Coma Berenices and Hercules-Lyra

We present wind models of 10 young Solar-type stars in the Hercules-Lyra association and the Coma Berenices cluster aged around ∼0.26 and ∼0.58 Gyr, respectively. Combined with five previously modelled stars in the Hyades cluster, aged ∼0.63 Gyr, we obtain a large atlas of 15 observationally based wind models. We find varied geometries, multi-armed structures in the equatorial plane, and a greater spread in quantities such as the angular momentum loss. In our models, we infer variation of a factor of ∼6 in wind angular momentum loss J˙ and a factor of ∼2 in wind mass-loss M˙ based on magnetic field geometry differences when adjusting for the unsigned surface magnetic flux. We observe a large variation factor of ∼4 in wind pressure for an Earth-like planet; we attribute this to variations in the ‘magnetic inclination’ of the magnetic dipole axis with respect to the stellar axis of rotation. Within our models, we observe a tight correlation between unsigned open magnetic flux and angular momentum loss. To account for possible underreporting of the observed magnetic field strength we investigate a second series of wind models where the magnetic field has been scaled by a factor of 5. This gives M˙∝B0.4 and J˙∝B1.0 as a result of pure magnetic scaling

Mass Transfer by Stellar Wind

I review the process of mass transfer in a binary system through a stellar wind, with an emphasis on systems containing a red giant. I show how wind accretion in a binary system is different from the usually assumed Bondi-Hoyle approximation, first as far as the flow's structure is concerned, but most importantly, also for the mass accretion and specific angular momentum loss. This has important implications on the evolution of the orbital parameters. I also discuss the impact of wind accretion, on the chemical pollution and change in spin of the accreting star. The last section deals with observations and covers systems that most likely went through wind mass transfer: barium and related stars, symbiotic stars and central stars of planetary nebulae (CSPN). The most recent observations of cool CSPN progenitors of barium stars, as well as of carbon-rich post-common envelope systems, are providing unique constraints on the mass transfer processes.Comment: Chapter 7, in Ecology of Blue Straggler Stars, H.M.J. Boffin, G. Carraro & G. Beccari (Eds), Astrophysics and Space Science Library, Springe

The sub-seasonal to seasonal prediction (S2S) project database

A database containing sub-seasonal to seasonal forecasts from 11 operational centres is available to the research community and will help advance our understanding of the sub-seasonal to seasonal time range. Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the sub-seasonal to seasonal time range, a sub-seasonal prediction (S2S) research project has been established by the World Weather Research Program/World Climate Research Program. A main deliverable of this project is the establishment of an extensive database, containing sub-seasonal (up to 60 days) forecasts, 3-weeks behind real-time, and reforecasts from 11 operational centers, modelled in part on the THORPEX Interactive Grand Global Ensemble (TIGGE) database for medium range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the sub-seasonal to seasonal time range that has been considered for a long time as a “desert of predictability”. In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of sub-seasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models underestimate significantly the amplitude of the Madden Julian Oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database represents also an important tool for case studies of extreme events. For instance, a multi-model combination of S2S models displays higher probability of a landfall over Vanuatu islands 2 to 3 weeks before tropical cyclone Pam devastated the islands in March 2015

cohesion and conflict in transnational merchant families

How do people negotiate the diversity of positionalities within kin groups? Through a diachronic approach, I investigate how Ali and Jalal, two merchants with Azeri and Gilaki ethnic identifications who came to Hamburg in the 1930s, mobilized kin to generate capital along the lines of generation, gender, and age. The reader simultaneously learns about the local history of Iranian immigration. Building on literature about historical merchant networks, the social organization of the Iranian marketplace (bazaar), the anthropology of kinship and transnational families, I question the social cohesion on which Aihwa Ong's study of flexible capital creation relies. The material suggests that the experience of family relations influences agents' positioning in the local Iranian social field

Simulation of maximum surface air temperature over India using the UK met office global seasonal (GloSea) model

A comparative study was performed to evaluate the performance of the UK Met Office’s Global Seasonal (GloSea) prediction General Circulation Model (GCM) for the forecast of maximum surface air temperature (Tmax) over the Indian region using the model generated hindcast of 15-members ensemble for 16 years (1987–2002). Each hindcast starts from 1st January and extends for a period of six months in each year. The model hindcast Tmax is compared with Tmax obtained from verification analysis during the hot weather season on monthly and seasonal scales from March to June. The monthly and seasonal model hindcast climatology of Tmax from 240 members during March to June and the corresponding observed climatology show highly significant (above 99.9% level) correlation coefficients (CC) although the hindcast Tmax is over-estimated (warm bias) over most parts of the Indian region. At the station level over New Delhi, although the forecast error (forecast-observed) at the monthly scale gradually increases from March to June, the forecast error at the seasonal scale during March to May (MAM) is found to be just 1.67 °C. The GloSea model also simulates well Tmax anomalies on monthly and seasonal scales during March to June with the lower Root Mean Square Error (RMSE) of bias corrected forecast (less than 1.2 °C), which is much less than the corresponding RMSE of climatology (reference) forecast. The anomaly CCs (ACCs) over the station in New Delhi are also highly significant (above 95% level) on monthly to seasonal time scales from March to June, except for April. The skill of the GloSea model for the seasonal forecast of Tmax as measured from the ACC map and the bias corrected RMSE map is reasonably good during MAM and April to June (AMJ) with higher ACC (significant at 95% level) and lower RMSE (less than 1.5 °C) found over many parts of the Indian regions

Explaining and predicting earth system change: a world climate research programme call to action

The World Climate Research Programme (WCRP) envisions a world “that uses sound, relevant, and timely climate science to ensure a more resilient present and sustainable future for humankind.” This bold vision requires the climate science community to provide actionable scientific information that meets the evolving needs of societies all over the world. To realize its vision, WCRP has created five Lighthouse Activities to generate international commitment and support to tackle some of the most pressing challenges in climate science today. The overarching goal of the Lighthouse Activity on Explaining and Predicting Earth System Change is to develop an integrated capability to understand, attribute, and predict annual to decadal changes in the Earth system, including capabilities for early warning of potential high impact changes and events. This article provides an overview of both the scientific challenges that must be addressed, and the research and other activities required to achieve this goal. The work is organized in three thematic areas: (i) monitoring and modeling Earth system change; (ii) integrated attribution, prediction and projection; and (iii) assessment of current and future hazards. Also discussed are the benefits that the new capability will deliver. These include improved capabilities for early warning of impactful changes in the Earth system, more reliable assessments of meteorological hazard risks, and quantitative attribution statements to support the Global Annual to Decadal Climate Update and State of the Climate reports issued by the World Meteorological Organization