Subsoil zoning of Mexico City using qualitative relationships between soil strength and electrical resistivity

Summary The seismic events occurring on 19 and 20 September 1985, whose epicentre was located in the coastal region of Michoacan, Mexico, produced tremendous damage in Mexico City. As a result of these losses the civil authorities of the city decided to study and evaluate the mechanical characteristics of the subsoil. To achieve this, it was necessary to drill several boreholes to obtain needed geophysical and geotechnical information. The geophysical method of electrical resistivity was the most appropriate to the research. This method enabled us to understand the structure and soil characteristics of the Mexican Valley.     

Space/time tectono-sedimentary evolution of the Umbria-Romagna-Marche Miocene Basin (Northern Apennines, Italy): a foredeep model

The space/time evolution of the Umbria-Romagna-Marche domains of the northern Apennine Miocene foredeep is proposed. In this period, the turbidite siliciclastic sedimentation is represented mainly by the Miocene Marnoso-Arenacea Formation, which generally ends with mainly marly deposits. From the internal Apennine sectors (Umbria-Romagna domain) to the external Adriatic Margin (Marche domain) the siliciclastic succession overlies hemipelagic marly deposits (Schlier Formation). The whole depositional area can be considered as a single wide basin with depocenter or main sedimentation areas progressively migrating eastwards. This basin is characterized by some morphological highs which did not constitute real dams for the sedimentary flows (turbidity currents). Multiple feeding (arkose, litharenites, calcarenites) from different sources is related to palaeogeographical and palaeotectonic reorganization of the most internal, previously deformed, Apennine areas. The activation of the foredeep stage is marked by the beginning of the siliciclastic sedimentation (Late Burdigalian in the most internal sector). This sedimentation ends in the most external sector in the Early Messinian, pointing to a depositional cycle of about 9?C10?Ma. The diachronism of the base of the siliciclastic deposition proves to be almost 5?Ma. The syn-depositional compressional deformation, which shows a marked diachronism, affected the internal area of the foredeep in the Early-Middle Serravallian, and progressively migrated up to Late Miocene, involving more and more external sectors. The deformed siliciclastic sedimentary wedge constitutes an orogenic pile incorporated in the Apennine Chain, represented by different tectonic elements superimposed by means of NE-vergent thrusts. The main stratigraphic and tectonic events of the Toscana-Romagna-Marche Apennines are presented in a general framework, resulting also in a terminological revision.     

Analysis of climatic trends in data from the agrometeorological station of Bologna-Cadriano, Italy (1952–2007)

Agriculture is highly exposed to climate change, as farming activities directly depend on climatic conditions. Knowledge of the extent of such change and of related phenomena will help to answer the questions posed by society about adaptation strategies. The global situation is well described by the Fourth IPCC assessment report (IPCC 2007), but local studies are important to understand the impact and the priorities to adopt in adaptation strategies. In this study a historical set of meteorological data, collected during the period 1952–2007 at the University of Bologna (Italy) agrometeorological station, was analysed. Several indexes, such as Frost Severity Index, number of hot days, number of rainy days, etc., were calculated, and their trends in time were analysed. The results show a scenario of increasing temperatures and evapotranspiration, a decrease in rainy days and a deepening of the watertable. The effect of these changes on agriculture will be a decrease in water availability, an increase in heat stress in plants and an increase in drought risk.     

Regional climate change experiments over southern South America. I: present climate

We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables, such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures. Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however, the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer. Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation, we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from the A2 and B2 forcing scenarios which are being reported in a separate study.     

Nonparametric analysis of high wind speed data

In this paper, nonparametric curve estimation methods are applied to analyze time series of wind speeds, focusing on the extreme events exceeding a chosen threshold. Classical parametric statistical approaches in this context consist in fitting a generalized Pareto distribution (GPD) to the tail of the empirical cumulative distribution, using maximum likelihood or the method of the moments to estimate the parameters of this distribution. Additionally, confidence intervals are usually computed to assess the uncertainty of the estimates. Nonparametric methods to estimate directly some quantities of interest, such as the probability of exceedance, the quantiles or return levels, or the return periods, are proposed. Moreover, bootstrap techniques are used to develop pointwise and simultaneous confidence intervals for these functions. The proposed models are applied to wind speed data in the Gulf Coast of US, comparing the results with those using the GPD approach, by means of a split-sample test. Results show that nonparametric methods are competitive with respect to the standard GPD approximations. The study is completed generating synthetic data sets and comparing the behavior of the parametric and the nonparametric estimates in this framework.     

Investigating a Hierarchy of Eulerian Closure Models for Scalar Transfer Inside Forested Canopies

Modelling the transfer of heat, water vapour, and CO₂ between the biosphere and the atmosphere is made difficult by the complex two-way interaction between leaves and their immediate microclimate. When simulating scalar sources and sinks inside canopies on seasonal, inter-annual, or forest development time scales, the so-called well-mixed assumption (WMA) of mean concentration (i.e. vertically constant inside the canopy but dynamically evolving in time) is often employed. The WMA eliminates the need to model how vegetation alters its immediate microclimate, which necessitates formulations that utilize turbulent transport theories. Here, two inter-related questions pertinent to the WMA for modelling scalar sources, sinks, and fluxes at seasonal to inter-annual time scales are explored: (1) if the WMA is to be replaced so as to resolve this two-way interaction, how detailed must the turbulent transport model be? And (2) what are the added predictive skills gained by resolving the two-way interaction vis-à-vis other uncertainties such as seasonal variations in physiological parameters. These two questions are addressed by simulating multi-year mean scalar concentration and eddy-covariance scalar flux measurements collected in a Loblolly pine (P. taeda L.) plantation near Durham, North Carolina, U.S.A. using turbulent transport models ranging from K-theory (or first-order closure) to third-order closure schemes. The multi-layer model calculations with these closure schemes were contrasted with model calculations employing the WMA. These comparisons suggested that (i) among the three scalars, sensible heat flux predictions are most biased with respect to eddy-covariance measurements when using the WMA, (ii) first-order closure schemes are sufficient to reproduce the seasonal to inter-annual variations in scalar fluxes provided the canonical length scale of turbulence is properly specified, (iii) second-order closure models best agree with measured mean scalar concentration (and temperature) profiles inside the canopy as well as scalar fluxes above the canopy, (iv) there are no clear gains in predictive skills when using third-order closure schemes over their second-order closure counterparts. At inter-annual time scales, biases in modelled scalar fluxes incurred by using the WMA exceed those incurred when correcting for the seasonal amplitude in the maximum carboxylation capacity (V _{cmax, 25}) provided its mean value is unbiased. The role of local thermal stratification inside the canopy and possible computational simplifications in decoupling scalar transfer from the generation of the flow statistics are also discussed.

“The tree, tilting its leaves to capture bullets of light; inhaling, exhaling; its many thousand stomata breathing, creating the air”. Ruth Stone, 2002, In the Next Galaxy

     

Quantifying Organization of Atmospheric Turbulent Eddy Motion Using Nonlinear Time Series Analysis

Using three methods from nonlinear dynamics, we contrast the level of organization inthe vertical wind velocity (w) time series collected in the atmospheric surface layer(ASL) and the canopy sublayer (CSL) for a wide range of atmospheric stability ()conditions. The nonlinear methods applied include a modified Shannon entropy, waveletthresholding, and mutual information content. Time series measurements collected overa pine forest, a hardwood forest, a grass-covered forest clearing, and a bare soil, desertsurface were used for this purpose. The results from applying all three nonlinear timeseries measures suggest that w in the CSL is more organized than that in the ASL, and that as the flows in both layers evolve from near-neutral to near-convective conditions, the level of organization increases. Furthermore, we found that the degree of organization in w associated with changes in is more significant than the transition from CSL to ASL.     

Analysis of uncertainties in future climate projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5 models

This paper identifies two sources of uncertainties in model projections of temperature and precipitation: internal and inter-model variability. Eight models of WCRP-CMIP3 and WCRP-CMIP5 were compared to identify improvements in the reliability of projections from new generation models. While no significant differences are observed between both datasets, some improvements were found in the new generation models. For example, in summer CMIP5 inter-model variability of temperature was lower over northeastern Argentina, Paraguay and northern Brazil, in the last decades of the 21st century. Reliability of temperature projections from both sets of models is high, with signal to noise ratio greater than 1 over most of the study region. Although no major differences were observed in both precipitation datasets, CMIP5 inter-model variability was lower over northern and eastern Brazil in summer (especially at the end of the 21st century). Reliability of precipitation projections was low in both datasets. However, the signal to noise ratio in new generation models was close to 1, and even greater than 1 over eastern Argentina, Uruguay and southern Brazil in some seasons.