Hotspots and a clumpy disc: variability of brown dwarfs and stars in the young σ Ori cluster

The properties of accretion discs around stars and brown dwarfs in the σ Ori cluster (age 3 Myr) are studied based on near-infrared (IR) time series photometry supported by mid-IR spectral energy distributions (SEDs). We monitor ∼30 young low-mass sources over eight nights in the J and K band using the duPont telescope at Las Campanas. We find three objects showing variability with J -band amplitudes  ≥0.5 mag  ; five additional objects exhibit low-level variations. All three highly variable sources have been previously identified as highly variable; thus, we establish the long-term nature of their flux changes. The light curves contain periodic components with time-scales of  ∼0.5–8 d  , but have additional irregular variations superimposed – the characteristic behaviour for classical T Tauri stars. Based on the colour variability, we conclude that hotspots are the dominant cause of variations in two objects (#19 and #33), including one likely brown dwarf, with spot temperatures in the range of 6000–7000 K. For the third one (#2), a brown dwarf or very low-mass star, inhomogeneities at the inner edge of the disc are the likely origin of variability. Based on mid-IR data from Spitzer , we confirm that the three highly variable sources are surrounded by circum-(sub)-stellar discs. They show typical SEDs for T Tauri-like objects. Using SED models, we infer an enhanced scaleheight in the disc for the object #2, which favours the detection of disc inhomogeneities in light curves and is thus consistent with the information from variability. In the σ Ori cluster, about every fifth accreting low-mass object shows persistent high-level photometric variability. We demonstrate that estimates for fundamental parameters in such objects can be significantly improved by determining the extent and origin of the variations.     

Using micro-catchment experiments for multi-local scale modelling of nature-based solutions

The Q-natural flood management project has co-developed with the Environment Agency 18 monitored micro-catchments (~1 km²) in Cumbria, UK installing calibrated flumes aimed at quantifying the potential shift in observed flows resulting from a range of nature-based-solutions installed by local organizations. The small-scale reduces the influence of variability characterizing larger catchments that would otherwise mask any such shifts, which we attempt to relate to a shift in model parameters. This paper demonstrates an approach to applying donor-parameter-shifts obtained from modelling two of the paired micro-catchments to a much larger scale, in order to understand the potential for improved distributed modelling of nature-based solutions in the form of additional tree-planting. The models include a rainfall-runoff model, Dynamic Topmodel, and a 2D hydrodynamic model, JFlow, permitting analysis of changes in hillslope processes and channel hydrodynamics resulting from a range of distributed measures designed to emulate natural hydrological processes that evaporate, store or infiltrate flows. We report on attempts to detect shift in hydrological response using one of the paired-micro-catchment moorland versus forestry sites in Lorton using Dynamic Topmodel. A donor-parameter-shift approach is used in a hypothetical experiment to represent new woodland in a much larger catchment, although testing all combinations of spatial planting strategies, responses to multiple-extremes, failure-modes and changes to synchronization becomes intractable to support good decision making. We argue that the problem can be re-framed to use donor-parameter-shifts at multi-local-scale catchments above communities known to be at risk, commensurate with most of the evidence of NbS impacts being effective at the small scale (ca. 10 km²). This might lead to more effective modelling to help catchment managers prioritize those communities-at-risk where there is more evidence that NbS might be effective.     

Intensity and Magnetic Field Distribution of Sunspots

We study the relationship between the brightness (I) and magnetic field (B) distributions of sunspots using 272 samples observed at the San Fernando Observatory and the National Solar Observatory, Kitt Peak, whose characteristics varied widely. We find that the I – B relationship has a quadratic form for the spots with magnetic field less than about 2000 G. The slope of the linear part of the I – B curve varies by about a factor of three for different types of spots. In general the slope increases as the spot approaches disk center. The I – B slope does not have a clear dependency on the spot size but the lower limit appears to increase as a function of the ratio of umbra and penumbra area. The I – B slope changes as a function of age of the sunspots. We discuss various sunspot models using these results.     

The formation of the Oort cloud in open cluster environments

We study the influence of an open cluster environment on the formation and current structure of the Oort cloud. To do this, we have run 19 different simulations of the formation of the Oort cloud for 4.5 Gyrs. In each simulation, the Solar System spends its first 100 Myrs in a different open cluster environment before transitioning to its current field environment. We find that, compared to forming in the field environment, the inner Oort cloud is preferentially loaded with comets while the Sun resides in the open cluster and that most of this material remains locked in the interior of the cloud for the next 4.4 Gyrs. In addition, the outer Oort cloud trapping efficiencies we observe in our simulations are lower than previous formation models by about a factor of 2, possibly implying an even more massive early planetesimal disk. Furthermore, some of our simulations reproduce the orbits of observed extended scattered disk objects, which may serve as an observational constraint on the Sun's early environment. Depending on the particular open cluster environment, the properties of the inner Oort cloud and extended scattered disk can vary widely. On the other hand, the outer portions of the Oort cloud in each of our simulations are all similar.     

The Upper Oligocene of Antigua: the volcanic to limestone transition in a limestone Caribbee

Antigua is a small island at the northern end of the Lesser Antilles chain. Its geology is largely limited to the Upper Oligocene and it records with unusual fidelity the transition from island arc volcanism to quiescence and limestone deposition. Despite the apparent limitation of a rock record confined to a short stratigraphical interval, Antigua has a geodiversity that ranges from thick andesites through silicified logs and freshwater snails in cherts to limestones that include both shallow and deeper water facies, and fine karstic features.     

Adaptation and poverty reduction in Mozambique: an opportunity for developing countries to lead§

Climate change disproportionately impacts the world’s poorest countries. A recent World Bank report highlighted that over 100 million people are at risk of falling into extreme poverty as a result of climate change. There is currently a lack of information about how to simultaneously address climate change and poverty. Climate change challenges provide an opportunity for those impacted most to come up with new and innovative technologies and solutions. This article uses an example from Mozambique where local and international partners are working side-by-side, to show how developing countries can simultaneously address climate change and poverty reduction using an ecosystem-based adaptation approach. Using ecosystem-based adaptation, a technique that uses the natural environment to help societies adapt to climate change, developing countries can lead the way to improve climate adaptation globally. This paradigm shift would help developing countries become leaders in ecosystem-based adaptation and green infrastructure techniques and has implications for climate policy worldwide.

POLICY RELEVANCE

The Paris Agreement resulting from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of Parties (COP 21) in December 2015 was rightly lauded for its global commitment to cut greenhouse gas emissions. However, COP 21 was also historic because of its call for non-party stakeholders to address climate change, inclusion of a global goal of ‘enhancing adaptive capacity, strengthening resilience and reducing vulnerability’, and the United States’ commitment of $800 million to adaptation funding. The combination of recognizing the need for new stakeholders to commit to climate change adaptation, the large impact climate change will have on the developing world, and providing access to funds for climate change adaptation creates a unique opportunity for developing countries to pave the way in adaptation policies in practices. Currently, developing countries are creating National Adaptation Plans (NAPs) for the UNFCCC. Through including a strong component of ecosystem-based adaptation in NAPs, developing countries can shape their countries’ policies, improve local institutions and governments, and facilitate a new generation of innovative leaders. Lessons learned in places like Mozambique can help lead the way in other regions facing similar climatic risks.     

Optimal Processing of Marine High-Resolution Seismic Reflection (Chirp) Data

Chirp frequency-modulated (FM) systems offer deterministic, repeatable source-signatures for high-resolution, normal incidence marine seismic reflection data acquisition. An optimal processing sequence for uncorrelated Chirp data is presented to demonstrate the applicability of some conventional seismic reflection algorithms to high-resolution data sets, and to emphasise the importance of a known source-signature. An improvement of greater than 60dB in the signal- to-noise ratio is realised from correlating the FM reflection data with the transmitted pulse. Interpretability of ringy deconvolved data is enhanced by the calculation of instantaneous amplitudes. The signal-to-noise ratio and lateral reflector continuity are both improved by the application of predictive filters whose effectiveness are aided by the repeatability of the Chirp source.     

Intercomparison of multiple statistical downscaling methods: multi-criteria model selection for South Korea

A number of statistical downscaling methodologies have been introduced to bridge the gap in scale between outputs of climate models and climate information needed to assess potential impacts at local and regional scales. Four statistical downscaling methods [bias-correction/spatial disaggregation (BCSD), bias-correction/constructed analogue (BCCA), multivariate adaptive constructed analogs (MACA), and bias-correction/climate imprint (BCCI)] are applied to downscale the latest climate forecast system reanalysis (CFSR) data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. All methods are calibrated with observational station data for 19 years from 1973 to 1991 and validated for the more recent 19-year period from 1992 to 2010. We construct a comprehensive suite of performance metrics to inter-compare methods, which is comprised of five criteria related to time-series, distribution, multi-day persistence, extremes, and spatial structure. Based on the performance metrics, we employ technique for order of preference by similarity to ideal solution (TOPSIS) and apply 10,000 different weighting combinations to the criteria of performance metrics to identify a robust statistical downscaling method and important criteria. The results show that MACA and BCSD have comparable skill in the time-series related criterion and BCSD outperforms other methods in distribution and extremes related criteria. In addition, MACA and BCCA, which incorporate spatial patterns, show higher skill in the multi-day persistence criterion for temperature, while BCSD shows the highest skill for precipitation. For the spatial structure related criterion, BCCA and MACA outperformed BCSD and BCCI. From the TOPSIS analysis, we found that MACA is the most robust method for all variables in South Korea, and BCCA and BCSD are the second for temperature and precipitation, respectively. We also found that the contribution of the multi-day persistence and spatial structure related criteria are crucial to ranking the skill of statistical downscaling methods.