Early detection of large eruptions at Piton de La Fournaise volcano (La Réunion Island): Contribution of a distant tiltmeter station

We report a compilation of data recorded at a distant tiltmeter station (RER) during recent episodes of dyke emplacement and eruption (2003–2007) at Piton de La Fournaise volcano (La Réunion Island). This sensitive station provides useful information for evaluating the extent of deformation. Distinct responses of this station were recorded based on the eruption type. Dykes feeding summit eruptions did not significantly influence the RER tiltmeter signals, whereas dykes feeding large distal eruptions (with vents located more than 4 km from the summit) generated up to 1.4 μrad of tilt, an amplitude 2 to 4 times greater than for proximal eruptions (0.3–0.7 μrad) on the flanks of the summit cone. The distinct tilt amplitude is directly linked to the location, depth, and volume of the dyke. Comparison with summit tiltmeters reveals that up to one-third to half of the RER tilt signal associated to dyke propagation is recorded when the dyke is still below the summit crater. Thus, before large distal eruptions, more than 0.5 μrad of tilt is recorded in less than 20 min when the dyke is below the summit crater (i.e. a few minutes/hours before the beginning of the eruption). We can thus propose for the RER station a threshold value of 0.5 μrad which, when reached as a dyke rises beneath the summit crater, suggests a high likelihood of a large distal eruption. The distant RER tiltmeter station thus appears to be a powerful tool for forecasting the type of eruption that is likely to occur, and can contribute to the early detection of large distal eruptions at Piton de La Fournaise, which are the most dangerous to inhabitants. For volcano monitoring, installation of high precision distant tiltmeters along the lower slopes of a volcano may provide warnings of large eruptions with enough lead time to allow for short-term hazards mitigation efforts.     

A reassessment of late glacial – Holocene diatom oxygen isotope record from Lake Baikal using a geochemical mass‐balance approach

We present a new palaeoenvironmental record of hydrological variability in Lake Baikal, based on re‐modelled δ¹⁸O_diatom values of diatom silica (δ¹⁸O_modelled), where the residual contaminants are identified and compensated for using electron optical imaging and whole‐sample geochemistry. δ¹⁸O_modelled interpretations are based on the balance between rivers with high δ¹⁸O values and rivers with low δ¹⁸O values. Isotopic variability is related to latitudinal differences in precipitation which feed these rivers. The δ¹⁸O_modelled record suggests that rather moist conditions prevailed in the Lake Baikal region during the latter stages of the Younger Dryas. Throughout the Holocene, episodes of low δ¹⁸O_modelled values are, in general, in good agreement with increases in percentage haematite‐stained grains in North Atlantic sediments (indicative of ice‐rafted debris events). Rivers with southerly catchments dominate fluvial input especially between c. 3.3 and 2 cal ka BP, concurrent with high precipitation in the Lake Baikal region. Copyright © 2011 John Wiley & Sons, Ltd.     

Public perception of climate change and disaster preparedness: Evidence from the Philippines

The Philippines is highly susceptible to both geophysical and climate-related disasters. This article explores Filipinos knowledge and perception of climate change and their association with what action Filipinos take to prepare for rapid onset natural hazards such as typhoons. Data for this study were collected from a nationally representative random survey of 5,184 adults conducted between March and April of 2017. Filipinos self-report relatively low levels of knowledge of climate change and cited increased temperatures, shifts in seasons, and heavier rains as the most likely consequences. Levels of disaster preparedness in the Philippines differ widely by region. Although most Filipinos perceive that natural hazards are a risk to them, only a third of Filipinos undertake measures to prepare for disasters. Filipinos who perceive climate-related changes directly impacting their households report taking greater action to prepare for disasters. Filipinos who believe they have been directly impacted by climate-related changes are also more likely to prepare for disasters, take planning actions, and undertake material actions to prepare, such as dwelling improvements. Other factors associated with disaster preparedness include gender, membership in an association, wealth, risk perception, and prior exposure to and losses due to disasters. The findings imply that, while posing different challenges and requiring different responses, adaptation to climate change and disaster preparedness are inherently associated and potentially mutually reinforcing. Policies and programs would arguably benefit from a more unified intervention framework that links climate change adaptation and disaster preparedness.     

Rapid Analysis of 1,4‐Dioxane in Groundwater by Frozen Micro‐Extraction with Gas Chromatography/Mass Spectrometry

An innovative micro‐extraction of aqueous samples coupled with gas chromatography/mass spectrometry in selected ion‐monitoring mode (GC/MS‐SIM) was developed to selectively analyze for 1,4‐dioxane with low part‐per‐billion detection sensitivity. Recoveries of 1,4‐dioxane ranged from 93% to 117% for both spiked laboratory reagent water and natural groundwater matrices, the later having elevated organic carbon content (8.34 ± 0.31 mg/L as total organic carbon). We observed that freezing the aqueous sample along with the extraction solvent enhanced the extraction efficiency, minimized physical interferences, and improved sensitivity resulting in a limit of detection for 1,4‐dioxane to approximately 1.6 μg/L. This method substantially reduces the labor, time, reagents and cost, and uses instruments that are commonly found in analytical laboratories. This method requires a relatively small sample volume (200 μL), and can be considered a green analytical method as it minimizes the use of toxic solvents and the associated laboratory wastes.     

Combined model state and parameter estimation with an ensemble Kalman filter in a North Sea station 1-D numerical model

The combined estimation of model state and parameters is investigated by using an ensemble Kalman filter in a 1-D numerical study of the temperature profile at a North Sea station located at 55°30??North and 0°55??East. This simplified model implementation allows to test many configurations for the sampling of the model error for the model state as well as for the parameters. Temperature profiles from thermistor data are assimilated. The influence of a vertically or non-vertically correlated model error is examined through the computation of correlation coefficients, root mean square errors, and model bias. As the CS station is located in the North Sea region stratified in summer, vertically non-correlated model error terms have a slight positive impact on the assimilative runs. The benefit of the combined estimation of the model state and parameters is examined by comparison of a simulation where the model parameters are not adjusted to simulations with the combined estimation of the model state either with one parameter or with a set of parameters related to the surface heat exchange. The optical attenuation coefficient, the sensible, and latent heat exchange coefficients are considered. The best results are obtained when a set of parameters are simultaneously adjusted.     

Location Intelligence: An Innovative Approach to Business Location Decision‐making

As one of the leading ‘world cities’, London is particularly reliant on sources of foreign direct investment (FDI). In the face of increasing global competition and a difficult economic climate, the capital must compete effectively to encourage and support such investors. Through a collaborative study with London's official FDI promotion agency, Think London, the need for a coherent framework for data, methodologies and tools to inform business location decision‐making became apparent. This article discusses the development of a rich environment to explore, compare and rank London's business neighbourhoods. This is achieved through the development and evaluation of a model for location‐based decision support. First, we discuss the development of a geo‐business classification for London which draws upon methods and practices common in geodemographic neighbourhood classification. A geo‐business classification is developed, encapsulating relevant location variables using Principal Components Analysis into a set of composite area profiles. Second, we discuss the implementation of an appropriate Multi‐Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP), enabling the aggregation of the geo‐business classification and decision‐makers' preferences into discrete decision alternatives. Finally, we present the results of the integration of both data and model through the development and evaluation of a web‐based prototype.     

Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i.e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates.     

Analysis of internal solitary waves observed in Davis Strait

Abstract

Current meters and a thermistor chain deployed in the proximity of a drill‐ship over the continental shelf off Baffin Island revealed the presence of large amplitude internal waves. This paper reviews the properties of the internal waves, observed to propagate away from the coast and to coincide with the local low water phase of the tide at the drill‐ship. The observations are considered in terms of internal solitary wave models. A detailed comparison is presented of wave properties with a long‐wave model incorporating continuous stratification and shear.