On the Integrability of Limited-Area Numerical Weather Prediction Model ALADIN over Extended Time Periods

This note summarizes results of the first integration of regional numerical weather prediction model ALADIN in a climate mode. The ALADIN model, developed in an international cooperation led by Météo France, is operationally used for weather prediction. The grid step of the model is 12 km; the integration domain covers a major part of Europe. A one-month-long run has been performed with this model on observed boundary conditions (represented by assimilations by the global model ARPEGE). It is demonstrated that no excessive error is generated and accumulated in the model during the integration; hence the model is integrable for extended time periods and may serve a basis for a development towards a regional climate model.     

Evaluating the impact of visualization of wildfire hazard upon decision-making under uncertainty

The paper investigates whether the methods chosen for representing uncertain geographic information aid or impair decision-making in the context of wildfire hazard. Through a series of three human subject experiments, utilizing 180 subjects and employing increasingly difficult tasks, this research evaluates the effect of five different visualizations and a text-based representation on decision-making under uncertainty. Our quantitative experiments focus specifically on the task of decision-making under uncertainty, rather than the task of reading levels of uncertainty from the map. To guard against the potential for generosity and risk seeking in decision-making under uncertainty, the experimental design uses performance-based incentives. The experiments showed that the choice of representation makes little difference to performance in cases where subjects are allowed the time and focus to consider their decisions. However, with the increasing difficulty of time pressure, subjects performed best using a spectral color hue-based representation, rather than more carefully designed cartographic representations. Text-based and simplified boundary encodings were among the worst performers. The results have implications for the performance of decision-making under uncertainty using static maps, especially in the stressful environments surrounding an emergency.     

Embedding reach-scale fluvial dynamics within the CAESAR cellular automaton landscape evolution model

We introduce a new computational model designed to simulate and investigate reach-scale alluvial dynamics within a landscape evolution model. The model is based on the cellular automaton concept, whereby the continued iteration of a series of local process ‘rules’ governs the behaviour of the entire system. The model is a modified version of the CAESAR landscape evolution model, which applies a suite of physically based rules to simulate the entrainment, transport and deposition of sediments. The CAESAR model has been altered to improve the representation of hydraulic and geomorphic processes in an alluvial environment. In-channel and overbank flow, sediment entrainment and deposition, suspended load and bed load transport, lateral erosion and bank failure have all been represented as local cellular automaton rules. Although these rules are relatively simple and straightforward, their combined and repeatedly iterated effect is such that complex, non-linear geomorphological response can be simulated within the model. Examples of such larger-scale, emergent responses include channel incision and aggradation, terrace formation, channel migration and river meandering, formation of meander cutoffs, and transitions between braided and single-thread channel patterns. In the current study, the model is illustrated on a reach of the River Teifi, near Lampeter, Wales, UK.     

Medieval Warming, Little Ice Age, and European impact on the environment during the last millennium in the lower Hudson Valley, New York, USA

Establishing natural climate variability becomes particularly important in large urban areas in anticipation of droughts. We present a well-dated bi-decadal record of vegetation, climate, land use, and fire frequency from a tidal marsh in the Hudson River Estuary. The classic Medieval Warm Period is evident through striking increases in charcoal and Pinus dominance from 800–1300 A.D., paralleling paleorecords southward along the Atlantic seaboard. Higher inputs of inorganic sediment during this interval suggest increased watershed erosion during drought conditions. The presence of the Little Ice Age ensues with increases in Picea and Tsuga, coupled with increasing organic percentages due to cooler, moister conditions. European impact is manifested by a decline in arboreal pollen due to land clearance, increased weedy plant cover (i.e., Ambrosia, Plantago, and Rumex), and an increase in inorganic particles to the watershed.     

The Application of Petroleum Hydrocarbon Fingerprint Characterization in Site Investigation and Remediation

Tremendous resources have been and continue to be spent investigating and remediating petroleum hydrocarbon compounds (PHCs) in soil and ground water. Investigating and planning a remedial strategy for sites affected by PHCs is often a challenging task because of the complex chemical nature of the PHCs. the complex regulatory environment related to PHC cleanup, and the use of analytical methods that provide quantitation but not identification of PHCs. From a technical standpoint, the PHC impacting soil and/or ground water is frequently inadequately characterised, both in identification as well as in is general properties (solubility, toxicity). From a regulatory standpoint, promulgated or recommended total petroleum hydrocarbon (TPH) cleanup levels generally relate to assumed properties of specific unweathered products and are inconsistent among different agencies and regions. This produces a prime situation for unwillingly spending more resources on investigation or remediation than may be necessary, especially when the PHC in the subsurface has different properties from unweathered products such as gasoline or diesel.
Accurately identifying the PHC and its nature, a process known as fingerprint characterization, is critical to the determination of appropriate regulatory goals and design of cost-effective remedial approaches. This paper presents several case studies in which fingerprint characterization made a significant difference in the project outcome. In each instance the nature of the organic material was better understood, the regulatory cleanup levels were negotiated based on the nature of the material, and a remedial approach was implemented that differed significantly from and was generally less costly than what would have been required without fingerprint characterization data.     

A note on frame transformations with applications to geodetic datums

Rigorous equations in compact symbolic matrix notation are introduced to transform coordinates and velocities between ITRF frames and modern GPS-based geocentric geodetic datums. The theory is general but, after neglecting higher than second-order terms, it is shown that the equations revert to the formulation currently applied in most major continental datums. We discuss several examples: the North American Datum of 1983 (NAD83), the European Terrestrial Reference System of 1989 (ETRS89), the Geodetic Datum of Australia of 1994 (GDA94), and the South American Geocentric Reference System (SIRGAS). Electronic Publication     

Surface sediment Chironomidae (Insecta: Diptera) distributions along an ecotonal transect in subarctic Fennoscandia: developing a tool for palaeotemperature reconstructions

We used multivariate statistical techniques to analyse the distributions of surface sediment chironomid assemblages with respect to surface-water temperature, and an additional set of 27 environmental variables, in 30 freshwater lakes of northern Fennoscandia. Our study transect spans boreal coniferous forest to subarctic tundra and includes a steep temperature gradient. Canonical correspondence analysis (CCA) with forward selection and associated Monte Carlo permutation tests revealed that there were statistically significant (P<0.05) relationships between chironomid distributions and two environmental variables, namely lakewater temperature and maximum lake depth. A constrained CCA with temperature as the only predictor variable suggested that the relationship between lakewater temperature and chironomid composition was sufficiently robust for developing a weighted-averaging (WA) based quantitative inference model that will allow palaeotemperature reconstructions using subfossil chironomid remains preserved in lake sediments.