Holocene tephra horizons at Klocka Bog,west‐central Sweden: aspects of reproducibility in subarctic peat deposits

This paper presents one of the most extensive Holocene tephra records found to date in Scandinavia. Microtephra horizons originating from Icelandic eruptions were recorded in two ca. 2 m thick peat profiles at Klocka Bog in west‐central Sweden. Five of the microtephra horizons were geochemically correlated to the Askja‐1875, Hekla‐3, Kebister, Hekla‐4 and Lairg A tephras respectively. Radiocarbon‐based dating of these tephras broadly agree with previously published ages from Iceland, Sweden, Germany and the British Isles. The identification of the Lairg A tephra demonstrates a more widespread distribution than previously thought, extending the usefulness of Icelandic Holocene tephrochronology further north into west‐central Scandinavia. Long‐lasting snow cover and seasonal wind distribution in the lower stratosphere are suggested as factors that may be responsible for fragmentary tephra deposition patterns in peat deposits of subarctic Scandinavia. Copyright © 2004 John Wiley & Sons, Ltd.     

Nonlinear wave propagation along a magnetic flux tube

The weakly nonlinear wave propagation of a slow sausage surface wave traveling along a magnetized slab with a thin nonuniform boundary layer is considered. The ideal incompressible MHD equations are used and the nonlinearities are assumed to be due to second harmonic generation. A nonlinear dispersion relation and the related nonlinear Schrödinger equation is derived. The existence of a continuous thin interface leads to sharply peaked field amplitudes due to resonant interaction with local Alfvén waves. It is shown that the nonlinear effects from processes within the thin layer are much more important than those from the main slab. Furthermore, the nonlinear interaction with local Alfvén waves yields a nonlinear damping rate of the wave that is much larger than the linear damping rate when the transition layer is sufficiently thin.     

Improving the performance of genetic algorithms for land-use allocation problems

Multi-objective optimization can be used to solve land-use allocation problems involving multiple conflicting objectives. In this paper, we show how genetic algorithms can be improved in order to effectively and efficiently solve multi-objective land-use allocation problems. Our focus lies on improving crossover and mutation operators of the genetic algorithms. We tested a range of different approaches either based on the literature or proposed for the first time. We applied them to a land-use allocation problem in Switzerland including two conflicting objectives: ensuring compact urban development and reducing the loss of agricultural productivity. We compared all approaches by calculating hypervolumes and by analysing the spread of the produced non-dominated fronts. Our results suggest that a combination of different mutation operators, of which at least one includes spatial heuristics, can help to find well-distributed fronts of non-dominated solutions. The tested modified crossover operators did not significantly improve the results. These findings provide a benchmark for multi-objective optimization of land-use allocation problems with promising prospectives for solving complex spatial planning problems.     

Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15

Total uncertainty in greenhouse gas (GHG) emissions changes over time due to “learning” and structural changes in GHG emissions. Understanding the uncertainty in GHG emissions over time is very important to better communicate uncertainty and to improve the setting of emission targets in the future. This is a diagnostic study divided into two parts. The first part analyses the historical change in the total uncertainty of CO₂ emissions from stationary sources that the member states estimate annually in their national inventory reports. The second part presents examples of changes in total uncertainty due to structural changes in GHG emissions considering the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) emissions scenarios that are consistent with the EU’s “20-20-20” targets. The estimates of total uncertainty for the year 2020 are made under assumptions that relative uncertainties of GHG emissions by sector do not change in time, and with possible future uncertainty reductions for non-CO₂ emissions, which are characterized by high relative uncertainty. This diagnostic exercise shows that a driving factor of change in total uncertainty is increased knowledge of inventory processes in the past and prospective future. However, for individual countries and longer periods, structural changes in emissions could significantly influence the total uncertainty in relative terms.     

Uncertainty in an emissions-constrained world

Our study focuses on uncertainty in greenhouse gas (GHG) emissions from anthropogenic sources, including land use and land-use change activities. We aim to understand the relevance of diagnostic (retrospective) and prognostic (prospective) uncertainty in an emissions-temperature setting that seeks to constrain global warming and to link uncertainty consistently across temporal scales. We discuss diagnostic and prognostic uncertainty in a systems setting that allows any country to understand its national and near-term mitigation and adaptation efforts in a globally consistent and long-term context. Cumulative emissions are not only constrained and globally binding but exhibit quantitative uncertainty; and whether or not compliance with an agreed temperature target will be achieved is also uncertain. To facilitate discussions, we focus on two countries, the USA and China. While our study addresses whether or not future increase in global temperature can be kept below 2, 3, or 4 °C targets, its primary aim is to use those targets to demonstrate the relevance of both diagnostic and prognostic uncertainty. We show how to combine diagnostic and prognostic uncertainty to take more educated (precautionary) decisions for reducing emissions toward an agreed temperature target; and how to perceive combined diagnostic and prognostic uncertainty-related risk. Diagnostic uncertainty is the uncertainty contained in inventoried emission estimates and relates to the risk that true GHG emissions are greater than inventoried emission estimates reported in a specified year; prognostic uncertainty refers to cumulative emissions between a start year and a future target year, and relates to the risk that an agreed temperature target is exceeded.     

Atmospheric and Terrestrial Water Balances of Labrador's Churchill River Basin,as Simulated by the North American Regional Climate Change Assessment Program

In an effort to understand the sources of uncertainty and the physical consistency of climate models from the North American Regional Climate Change Assessment Program (NARCCAP), an ensemble of general circulation models (GCMs) and regional climate models (RCMs) was used to explore climatological water balances for the Churchill River basin in Labrador, Canada. This study quantifies mean atmospheric and terrestrial water balance residuals, as well as their annual cycles. Mean annual atmospheric water balances had consistently higher residuals than the terrestrial water balances due, in part, to the influences of sampling of instantaneous variables and the interpolation of atmospheric data to published pressure levels. Atmospheric and terrestrial water balance residuals for each ensemble member were found to be consistent between base and future periods, implying that they are systemic and not climate dependent. With regard to the annual cycle, no pattern was found across time periods or ensemble members to indicate whether the monthly terrestrial or atmospheric root mean square residual was highest. Because of the interdependence of hydrological cycle components, the complexity of climate models and the variety of methods and processes used by different ensemble members, it was impossible to isolate all causes of the water balance residuals. That being said, the residuals created by interpolating a model's native vertical resolution onto NARCCAP's published pressure levels and the subsequent vertical interpolation were quantified and several other sources were explored. In general, residuals were found to be predominantly functions of the RCM choice (as opposed to the GCM choice) and their respective modelling processes, parameterization schemes, and post-processing.     

Investigation of the impact in variation of secondary radioclimatic variables on microwave at the lower atmosphere

The work discusses the effect in the variations of secondary radioclimatic parameters in Nsukka, Nigeria. The data collected from the measured atmospheric profile using two automatic wireless weather stations for 3 years were used to estimate the propagation condition, geoclimatic factor, and effective earth radius. The result shows that, the calculated median value of k-factor is 1.595, with an absolute span of 0.26 of the standard value of k-factor 1.333 owing to the increase in relative humidity during the rainy seasons and intensive temperature inversion in the morning and early afternoon periods of December due to the dry harmattan for the season. Also, from the result super-refraction propagation condition was observed for about 7 months of a year, while ducting condition dominates the remaining 5 months in the region. The regression analysis of k-factor as a function of ground refractivity showed that the pair is strongly correlated (0.9996). These results have not been obtained in the region and it will help in planning of radio wave line-of-sight for better signal reception.     

Drivers of change in Brazil’s carbon dioxide emissions

Brazil’s economic development has been underpinned by a diverse and – in a global comparison – unusual set of energy carriers, notably hydroelectricity and ethanol from sugar cane. Its energy mix makes Brazil one of the least energy-related carbon-intensive economies worldwide. Given that the country is fast becoming one of the world’s economic powerhouses, decision-makers need to understand the drivers underlying past and current carbon dioxide emissions trends. We therefore investigate a) which key long-term drivers have led to Brazil’s unique emissions profile, and b) the implications of these drivers for Brazil’s national policies. We show that Brazil’s emissions are growing mainly due to increasing individual standards of living, exports and population size, and that this growth is so far unchallenged by technological and structural improvements toward lower emissions intensities and more efficient production structures. As these trends are likely to continue amidst growing international pressure on key economies to reduce their carbon emissions, a decoupling of drivers from emissions is needed to simultaneously meet development and environmental goals.     

Be exposure dating of river terraces at the southern mountain front of the Dzungarian Alatau (SE Kazakhstan) reveals rate of thrust faulting over the past ~ 400 ka

The mountain belts of the Dzungarian Alatau (SE Kazakhstan) and the Tien Shan are part of the actively deforming India–Asia collision zone but how the strain is partitioned on individual faults remains poorly known. Here we use terrace mapping, topographic profiling, and ¹⁰Be exposure dating to constrain the slip rate of the 160-km-long Usek thrust fault, which defines the southern front of the Dzungarian Alatau. In the eastern part of the fault, where the Usek River has formed five terraces (T₁–T₅), the Usek thrust fault has vertically displaced terrace T₄ by 132 ± 10 m. At two sites on T₄, exposure dating of boulders, amalgamated quartz pebbles, and sand from a depth profile yielded ¹⁰Be ages of 366 ± 60 ka and 360 ^+ 77/_− 48 ka (both calculated for an erosion rate of 0.5 mm/ka). Combined with the vertical offset and a 45–70° dip of the Usek fault, these age constraints result in vertical and horizontal slip rates of ~ 0.4 and ~ 0.25 mm/a, respectively. These rates are below the current resolution of GPS measurements and highlight the importance of determining slip rates for individual faults by dating deformed landforms to resolve the pattern of strain distribution across intracontinental mountain belts.     

Assessing response behaviour of debris-flows affected communities in Kaohsiung,Taiwan

During Typhoon Morakot which hit Taiwan from 6 to 9 August, 2009, Kaohsiung City was highly affected by devastating debris-flows and flooding. Recorded casualties were 699 deaths and 1,766 damaged homes, mostly in the mountainous areas of Kaohsiung City. Due to a largely malfunctioning or absent early-warning system, residents in those mountainous villages were required to rely on individual- and/or community-based capacities to evacuate and respond to debris-flow-related disasters. Hence, this study investigates the response behaviour of selected debris-flow-affected communities in Kaohsiung City, based on a preparedness awareness action and affect model. Key results from the survey highlight that only 13.8 % of the households received formal (institutional) early warning, whereas 86.2 % households had to rely on their intrinsic senses and indigenous knowledge to recognise the onset of debris-flows in their villages during Typhoon Morakot. Among those households who did not receive formal early warning, 10 % of the households received previous disaster education, 17 % had previous disaster experience, and 73 % did have neither disaster education nor disaster experience. Furthermore, households with disaster education were among those who were best prepared and knew best how to evacuate and respond to debris-flow-related disasters followed by households with disaster experiences. Finally, findings from the survey and selected key informants’ interviews identified that the response behaviour of communities ought to be enhanced through the following measures: conduction of hydro-meteorological-related disaster education, improved participatory risk communication and enhanced recognition of communities as vital actors during a disaster to provide local knowledge and support to relief operations.