Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

Impacts of Changes in Precipitation Amount and Distribution on Water Resources Studied Using a Model Rainwater Harvesting System

Water supply reliability is expected to be affected by both precipitation amount and distribution changes under recent and future climate change. We compare historical (1951‐2010) changes in annual‐mean and annual‐maximum daily precipitation in the global set of station observations from Global Historical Climatology Network and climate models from the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP), and develop the study to 2011‐2099 for model projections under high radiative forcing scenario (RCP8.5). We develop a simple rainwater harvesting system (RWHS) model and drive it with observational and modeled precipitation. We study the changes in mean and maximum precipitation along with changes in the reliability of the model RWHS as tools to assess the impact of changes in precipitation amount and distribution on reliability of precipitation‐fed water supplies. Results show faster increase in observed maximum precipitation (10.14% per K global warming) than mean precipitation (7.64% per K), and increased reliability of the model RWHS driven by observed precipitation by an average of 0.2% per decade. The ISI‐MIP models show even faster increase in maximum precipitation compared to mean precipitation. However, they imply decreases in mean reliability, for an average 0.15% per decade. Compared to observations, climate models underestimate the increasing trends in mean and maximum precipitation and show the opposite direction of change in reliability of a model water supply system.     

Impact of Climate Change on Fish Population Dynamics in the Baltic Sea: A Dynamical Downscaling Investigation

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties.     

煤巷掘进过程中粉尘浓度影响因素分析

为了掌握煤巷掘进过程中粉尘浓度变化的影响因素,根据气固两相流理论,针对矿井掘进工作面的特点,采用计算流体力学的离散相模型（DPM）考察了掘进巷道风速、风筒直径、风筒出风口到掘进工作面距离以及风筒的悬挂高度对粉尘浓度变化的影响。结果发现：当掘进巷道风速为0.25-4 m/s时,提高巷道内的通风风速,可以降低巷道内的粉尘浓度,缩短呼吸性粉尘浓度达到稳定的时间,减小工作面粉尘的危害;有利于通风除尘的风筒相关参数为风筒直径0.4-0.6 m、风筒出风口到掘进工作面距离6-7 m、风筒悬挂高度2.0-2.2 m。     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

Highlights of LNG risk technology

The authors have recently undertaken a major review of LNG consequence modeling, compiling a wide range of historical information with more recent experiments and modeling approaches in a book entitled “LNG Risk-Based Safety: Modeling and Consequence Analysis”. All the main consequence routes were reviewed – discharge, evaporation, pool and jet fire, vapor cloud explosions, rollover, and Rapid Phase Transitions (RPT’s). In the book, experimental data bases are assembled for tests on pool spread and evaporation, burn rates, dispersion, fire and radiation and effects on personnel and structures. The current paper presents selected highlights of interest: lessons learned from historical development and experience, comparison of predictions by various models, varying mechanisms for LNG spread of water, a modeling protocol to enable acceptance of newer models, and unresolved technical issues such as cascading failures, fire engulfment of a carrier, the circumstances for a possible LNG BLEVE, and accelerated evaporation by LNG penetration into water.     

Consistent assessments of pathways toward sustainable development and climate stabilization

Many of the numerous difficult issues facing the world today involve relationships entailing trade‐offs and synergies. This study quantitatively assesses some alternative scenarios using integrated assessment models, and provides several indicators relating to sustainable development and climate change, such as indicators of income (per capita GDP), poverty, water stress, food access, sustainable energy use, energy security, and ocean acidification, with high consistencies among the indicators within a scenario. According to the analyses, economic growth helps improve many of the indicators for sustainable development. On the other hand, climate change will induce some severe impacts such as ocean acidification under a non‐climate intervention scenario (baseline scenario). Deep emission reductions, such as to 2°C above the pre‐industrial level, could cause some sustainable development indicators to worsen. There are complex trade‐offs between climate change mitigation levels and several sustainable development indicators. A delicately balanced approach to economic growth will be necessary for sustainable development and responses to climate change.     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.     

Calculating losses of crops in Denmark caused by high ozone levels

In order to help guide air pollution legislation at the European level, harmful air pollution effects on agriculture crops and the consequent economic implications for policy have been studied for more than a decade. Ozone has been labeled as the most serious of the damaging air pollutants to agriculture, where growth rates and consequently yields are dramatically reduced. Quantifying the effects has formed a key factor in policymaking. Based on the widely held view that AOT40 (Accumulated exposure Over Threshold of 40 ppb) is a good indicator of ozone-induced damage, the Danish Eulerian Model (DEM) was used to compute reduced agriculture yields on a 50 km×50 km grid over Europe. In one set of scenarios, a ten year meteorological time series was combined with realistic emission inventories. In another, various idealized emission reduction scenarios are applied to the same meteorological time series. The results show substantial inter-annual variability in economic losses, due in most part to meteorological conditions which varied much more substantially than the emissions during the same period. It is further shown that, taking all uncertainties into account, estimates of ozone-induced economic losses require that a long meteorological record is included in the analysis, for statistical significance to be improved to acceptable levels for use in policy analysis. In this study, calculations were made for Europe as a whole, though this paper presents results relevant for Denmark.     

Flow Dynamics in Eccentrically Rotating Flasks Used for Dispersant Effectiveness Testing

The evaluation of dispersant effectiveness used for oil spills is commonly done using tests conducted in laboratory flasks. We used a Hot Wire Anemometer (HWA) to characterize mixing dynamics in the Swirling Flask (SF) and the Baffled Flask (BF), the latter is being considered by the EPA to replace the prior to test dispersant effectiveness in the laboratory. Five rotation speeds of the orbital shaker carrying the flasks were considered, Ω = 50, 100, 150, 175 and 200 rpm. The radial and azimuthal water speeds were measured for each Ω. It was found that the flow in the SF is, in general, two-dimensional changing from horizontal at low Ω to axi-symmetric at high Ω. The flow in the BF appeared to be three-dimensional at all rotation speeds. This indicates that the BF is more suitable for representing the (inherently) 3-D flow at sea. In the SF, the speeds and energy dissipation rates ɛ increased gradually as the rotation speed increased. Those in the BF increased sharply at rotation speeds greater than 150 rpm. At 200 rpm, the Kolmogorov scale (i.e., size of smallest eddies) was about 250 and 50 μm in the SF and BF, respectively. Noting that the observed droplet sizes of dispersed oils range from 50 to 400 μm (hence most of it is less than 250 μm), one concludes that the mixing in the SF (even at 200 rpm) is not representative of the vigorous mixing occurring at sea.