On the Impact of Anthropogenic Heat Fluxes on the Urban Boundary Layer: A Two-Dimensional Numerical Study

The heat generated in buildings and the manner in which this heat is exchanged with the ambient environment can play an important role in urban climate. Recent studies have shown that anthropogenic heat from air-conditioning facilities can increase the exterior ambient temperature and should be taken into account for a more complete urban heat island (UHI) mitigation study. For this purpose, the first part of the present work is focused on the coupling of a new building energy model (BEM) and an urban canopy parameterisation (UCP). The new scheme is implemented in a finite volume mesoscale model (MM) and tested in a two-dimensional (2D) configuration of a city over flat terrain. A sensitivity study is performed with respect to different parameters in order to test the simulation system and enhance the understanding of the possible impacts of the BEM on the exterior microclimate.     

A new Building Energy Model coupled with an Urban Canopy Parameterization for urban climate simulations—part II. Validation with one dimension off-line simulations

Recent studies show that the fluxes exchanged between buildings and the atmosphere play an important role in the urban climate. These fluxes are taken into account in mesoscale models considering new and more complex Urban Canopy Parameterizations (UCP). A standard methodology to test an UCP is to use one-dimensional (1D) off-line simulations. In this contribution, an UCP with and without a Building Energy Model (BEM) is run 1D off-line and the results are compared against the experimental data obtained in the BUBBLE measuring campaign over Basel (Switzerland) in 2002. The advantage of BEM is that it computes the evolution of the indoor building temperature as a function of energy production and consumption in the building, the radiation coming through the windows, and the fluxes of heat exchanged through the walls and roofs as well as the impact of the air conditioning system. This evaluation exercise is particularly significant since, for the period simulated, indoor temperatures were recorded. Different statistical parameters have been calculated over the entire simulated episode in order to compare the two versions of the UCP against measurements. In conclusion, with this work, we want to study the effect of BEM on the different turbulent fluxes and exploit the new possibilities that the UCP–BEM offers us, like the impact of the air conditioning systems and the evaluation of their energy consumption.     

Global and hemispheric temperatures revisited

To characterize observed global and hemispheric temperatures, previous studies have proposed two types of data-generating processes, namely, random walk and trend-stationary, offering contrasting views regarding how the climate system works. Here we present an analysis of the time series properties of global and hemispheric temperatures using modern econometric techniques. Results show that: The temperature series can be better described as trend-stationary processes with a one-time permanent shock which cannot be interpreted as part of the natural variability; climate change has affected the mean of the processes but not their variability; it has manifested in two stages in global and Northern Hemisphere temperatures during the last century, while a second stage is yet possible in the Southern Hemisphere; in terms of Article 2 of the Framework Convention on Climate Change it can be argued that significant (dangerous) anthropogenic interference with the climate system has already occurred.     

Physical modeling and visualization of soil liquefaction under high confining stress

The mechanisms of seismically-induced liquefaction of granular soils under high confining stresses are still not fully understood. Evaluation of these mechanisms is generally based on extrapolation of observed behavior at shallow depths. Three centrifuge model tests were conducted at RPI‘s experimental facility to investigate the effects of confining stresses on the dynamic response of a deep horizontal deposit of saturated sand. Liquefaction was observed at high confining stresses in each of the tests. A system identification procedure was used to estimate the associated shear strain and stress time histories. These histories revealed a response marked by shear strength degradation and dilative patterns. The recorded accelerations and pore pressures were employed to generate visual animations of the models. These visualizations revealed a liquefaction front traveling downward and leading to large shear strains and isolation of upper soil layers.     

Shallow frontal deformation related to active continental subduction: structure and recent stresses in the westernmost Betic Cordillera

The westernmost Betic Cordillera front is located along the arcuate alpine belt formed by the interaction of the Eurasian‐African plate boundary and the Alboran continental domain in between. Although classical geological data suggest that the western Cordillera front is inactive, recent GPS data show a westward–north‐westward motion of up to 3.4 mm a^?1 with respect to the foreland. In addition, the increasing thickness of Guadalquivir sedimentary infill towards the Cordillera, and the rectilinear character of the front formed by soft sediments, suggest that the Cordillera is still active. Large ENE–WSW‐oriented open folds detected in the field, seismic reflection profiles and new audiomagnetotellurics data are consistent with active deformation. Fracture analysis in Quaternary deposits evidences recent NW–SE horizontal compression. The GPS motion and maximum stress orientation may be due to north‐westward tectonic collision of the westernmost Betic Cordillera, accommodated at depth by active continental subduction of the Iberian lithosphere.     

Relationship between wind power production and North Atlantic atmospheric circulation over the northeastern Iberian Peninsula

The wind power generated during winter months 1999–2003 at several wind farms in the northeastern Iberian Peninsula is investigated through the application of a statistical downscaling. This allows for an improved understanding of the wind power variability and its relationship to the large scale atmospheric circulation. It is found that 97 % of the variability of this non-climatic variable is connected to changes in the atmospheric circulation. The methodological uncertainty associated with multiple configurations of the statistical downscaling method replicates well the observed variability of the wind power, an indication of the robustness of the methodology to changes in the model set up. In addition, the use of the statistical model is extended out of the observational period providing an estimation of the long-term variability of wind power throughout the twentieth century. The extended wind power reconstruction shows large inter-annual and multidecadal variability. Alternative approaches to calibrate the empirical downscaling model using actual wind power observations have also been investigated. They involve the estimation of wind power changes from downscaled wind values and make use of several transfer functions based on the linearity between wind and wind energy. The performance of the latter approaches is similar to the direct downscaling of wind power and may allow wind power production estimations even in the absence of historical wind turbine records. These results can be of great interest for deriving medium/long term impact-oriented energy assessments, especially when wind power observations are missing as well as in the context of climate change scenarios.     

Improving the Wishart Synthetic Aperture Radar image classifications through Deterministic Simulated Annealing

This paper proposes the use of Deterministic Simulated Annealing (DSA) for Synthetic Aperture Radar (SAR) image classification for cluster refinement. We use the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution that is then supplied to the DSA optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The improvement is verified by computing a cluster separability coefficient. During the DSA optimization process, for each iteration and for each pixel, two consistency coefficients are computed taking into account two kinds of relations between the pixel under consideration and its neighbors. Based on these coefficients and on the information coming from the pixel itself, it is re-classified. Several experiments are carried out to verify that the proposed approach outperforms the Wishart strategy. We try to improve the classification results by considering the spatial influences received by a pixel through its neighbors. Finally, a link about the contribution of DSA to thematic mapping is also established.     

Generalized extreme wind speed distributions in South America over the Atlantic Ocean region

Statistical analysis of extreme values is applied to wind data from National Centers for Environmental Prediction and National Center for Atmospheric Research reanalysis grid points over the ocean region bounded at 23°S and 40°W and 42°W towards the south and southeastern Brazilian coast. The period of analysis goes from 1975 to 2006. The generalized extreme value and generalized Pareto distributions are employed for annual and daily maxima, respectively. The Pareto?CPoisson point process characterization is also used to analyze peaks over threshold. Return levels for 10, 25, 50, and 100?years are calculated at each grid point. However, most of the reanalysis data fall within 1?C10-year return periods, suggesting that hazardous wind speed with low probability (return periods of 50?C100) have rarely measured in this period. Wide confidence intervals on these levels show that there is not enough information to make predictions with any degree of certainty to return periods over 100?years. Low extremal index (??) values are found for excess wind speeds over a high threshold, indicating the occurrence of consecutively high peaks. In order to obtain realistic uncertainty information concerning inferences associated with threshold excesses, a declustering method is performed, which separates the excesses into clusters, thereby rendering the extreme values more independent.