Moisture recycling in the Iberian Peninsula from a regional climate simulation: spatiotemporal analysis and impact on the precipitation regime

The contribution of the evapotranspiration from a certain region to the precipitation over the same area is referred to as water recycling. In this paper, we explore the spatiotemporal links between the recycling mechanism and the Iberian rainfall regime. We use a 9 km resolution Weather Research and Forecasting simulation of 18 years (1990-2007) to compute local and regional recycling ratios over Iberia, at the monthly scale, through both an analytical and a numerical recycling model. In contrast to coastal areas, the interior of Iberia experiences a relative maximum of precipitation in spring, suggesting a prominent role of land-atmosphere interactions on the inland precipitation regime during this period of the year. Local recycling ratios are the highest in spring and early summer, coinciding with those areas where this spring peak of rainfall represents the absolute maximum in the annual cycle. This confirms that recycling processes are crucial to explain the Iberian spring precipitation, particularly over the eastern and northeastern sectors. Average monthly recycling values range from 0.04 in December to 0.14 in June according to the numerical model and from 0.03 in December to 0.07 in May according to the analytical procedure. Our analysis shows that the highest values of recycling are limited by the coexistence of two necessary mechanisms: (1) the availability of sufficient soil moisture and (2) the occurrence of appropriate synoptic configurations favoring the development of convective regimes. The analyzed surplus of rainfall in spring has a critical impact on agriculture over large semiarid regions of the interior of Iberia.

Maximum-revenue tariff under Bertrand duopoly with unknown costs

This paper considers an international trade under Bertrand model with differentiated products and with unknown production costs. The home government imposes a specific import tariff per unit of imports from the foreign firm. We prove that this tariff is decreasing in the expected production costs of the foreign firm and increasing in the production costs of the home firm. Furthermore, it is increasing in the degree of product substitutability. We also show that an increase in the tariff results in both firms increasing their prices, an increase in both expected sales and expected profits for the home firm, and a decrease in both expected sales and expected profits for the foreign firm.

Maximum-revenue tariff with different roles in a price-setting competition

Published also at Lecture Notes in Engineering and Computer Science

Maximum level and time to peak of dam-break waves on mobile horizontal bed

Journal of Hydraulic Engineering, Vol. 135, No. 11, November 1, 2009

IgG recognizing 21-24 kDa and 30-33 kDa tachyzoite antigens show maximum avidity maturation during natural and accidental human toxoplasmosis

We describe the avidity maturation of IgGs in human toxoplasmosis using sequential serum samples from accidental and natural infections. In accidental cases, avidity increased continuously throughout infection while naturally infected patients showed a different profile. Twenty-five percent of sera from chronic patients having specific IgM positive results could be appropriately classified using exclusively the avidity test data. To take advantage of the potentiality of this technique, antigens recognized by IgG showing steeper avidity maturation were identified using immunoblot with KSCN elution. Two clusters of antigens, in the ranges of 21-24 kDa and 30-33 kDa, were identified as the ones that fulfill the aforementioned avidity characteristics.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Maximum likelihood detection for OFDM signals with strong nonlinear distortion effects

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Relationship between rainfall and temperature: observations on the cases of visceral leishmaniasis in São Luis Island, State of Maranhão, Brazil

INTRODUCTION: Visceral leishmaniasis is a serious public health problem that requires global control strategies, especially with respect to factors that may intervene in reducing the incidence of endemicity. In this work, rainfall density and temperature were correlated with the incidence of human cases in an area endemic for leishmaniasis in São Luis do Maranhão, Northeastern Brazil. METHODS: Notification of human cases by the National Health Foundation/Regional Coordination of Maranhão (FUNASA/COREMA) from 2002 to 2010 was used. Ecological data (mean temperature and rainfall density) were provided by the Meteorological Office of State. RESULTS: A significant association was verified between the number of VL cases and rainfall rate but not in the analysis concerning mean temperatures. CONCLUSIONS: These data suggest that the control actions in visceral leishmaniasis should be performed during rainy season in the State of Maranhão, which is in the first half of the year.

Schistosomiasis mansoni in urban Northeast Brazil: influence of rainfall regime on the population dynamics of Biomphalaria sp.

Introduction Our objective was to evaluate the influence of rainfall regime on the population dynamics of Biomphalaria in a potential urban focus of schistosomiasis in Aracaju, Brazil, during 2009-2010. Methods Snails were collected monthly and were counted, measured and identified; the level of infection and fecal contamination at the sampling sites was determined; rainfall data were obtained. Results High levels of fecal contamination were observed, and the abundance of Biomphalaria glabrata increased during the rainy and post-rainy seasons. The snails' size was variable, and infected snails were identified independently of rainfall. Conclusions These results provide evidence of anthropogenic and climate interference in an urban focus of schistosomiasis in the Aracaju metropolitan area.

Local Rainfall Variability - A Potential Bias for Bioecological Studies in the Central Amazon

Rainfall data registered betwe en 1910 and 1979 at Manaus confirm the existence of a dry season between June and November (monthly rainfall: 42-162mm) and a rainy season from December until May (monthly rainfall: 211-300mm). Annual precipitation amounted to 2105mm with about 75% of the rainfall recorded during the rainy season. Rainfall data collected over 12 months at eigth stations in the vicinity of and at Manaus are compared. Annual precipitation was lower in Inundation Regions (1150-2150mm) compared with Dryland Regions (2400-2550mm). Considerable differences are found in rainfall patterns (intensity, frequency and time of rainfall). This is also truefor neighbouring stations, even if data of a 11-year record period are compared. Thus, it is highly recommended that preciptation data for bioecological studies be collected at the study site.

On the influences of the El Niño, La niña and Atlantic Dipole Paterni on the Amazonian Rainfall during 1960-1998

The influence of the large-scale climatic variability dominant modes in the Pacific and in the Atlantic on Amazonian rainfall is investigated. The composite technique of the Amazon precipitation anomalies is used in this work. The basis years for these composites arc those in the period 1960-1998 with occurrences of extremes in the Southern Oscillation (El Niño or La Niña) and the north/south warm (or cold) sea surface temperature (SST) anomalies dipole pattern in the tropical Atlantic. Warm (cold) dipole means positive (negative) anomalies in the tropical North Atlantic and negative (positive) anomalies in the tropical South Atlantic. Austral summer and autumn composites for extremes in the Southern Oscillation (El Niño or La Niña) and independently for north/south dipole pattern (warm or cold) of the SST anomalies in the tropical Atlantic present values (magnitude and sign) consistent with those found in previous works on the relationship between Amazon rainfall variations and the SST anomalies in the tropical Pacific and Atlantic. However, austral summer and autumn composites for the years with simultaneous occurrences of El Niño and warm north/south dipole of the SST anomalies in the tropical Atlantic show negative precipitation anomalies extending eastward over the center-eastern Amazon. This result indicates the important role played by the tropical Atlantic in the Amazon anomalous rainfall distribution.

Microphysical evidence of the transition between predominant convective/stratiform rainfall associated with the intraseasonal oscillation in the Southwest Amazon

The distinction between convective and stratiform precipitation profiles around various precipitating systems existent in tropical regions is very important to the global atmospheric circulation, which is extremely sensitive to vertical latent heat distribution. In South America, the convective activity responds to the Intraseasonal Oscillation (IOS). This paper analyzes a disdrometer and a radar profiler data, installed in the Ji-Paraná airport, RO, Brazil, for the field experiment WETAMC/LBA & TRMM/LBA, during January and February of 1999. The microphysical analysis of wind regimes associated with IOS showed a large difference in type, size and microphysical processes of hydrometeor growth in each wind regime: easterly regimes had more turbulence and consequently convective precipitation formation, and westerly regimes had a more stratiform precipitation formation.

The drought of the century in the Amazon Basin: an analysis of the regional variation of rainfall in South America in 1926

The most severe drought in tropical South America during the 20th century occurred in 1926. This extreme El Nino year is further documented anecdotally, in an update of the river stage observations at Manaus, and in annual rainfall records. The annual rainfall anomaly is an east-west dipole over tropical South America, with drought to the west over the Amazon basin whose discharge is documented at Manaus, and with a surplus to the east and including the Nordeste region of Brazil. Speculations about a role for aerosol in aggravating the drought are discussed.

Global warming in Amazonia: impacts and Mitigation

Global warming has potentially catastrophic impacts in Amazonia, while at the same time maintenance of the Amazon forest offers one of the most valuable and cost-effective options for mitigating climate change. We know that the El Niño phenomenon, caused by temperature oscillations of surface water in the Pacific, has serious impacts in Amazonia, causing droughts and forest fires (as in 1997-1998). Temperature oscillations in the Atlantic also provoke severe droughts (as in 2005). We also know that Amazonian trees die both from fires and from water stress under hot, dry conditions. In addition, water recycled through the forest provides rainfall that maintains climatic conditions appropriate for tropical forest, especially in the dry season. What we need to know quickly, through intensified research, includes progress in representing El Niño and the Atlantic oscillations in climatic models, representation of biotic feedbacks in models used for decision-making about global warming, and narrowing the range of estimating climate sensitivity to reduce uncertainty about the probability of very severe impacts. Items that need to be negotiated include the definition of "dangerous" climate change, with the corresponding maximum levels of greenhouse gases in the atmosphere. Mitigation of global warming must include maintaining the Amazon forest, which has benefits for combating global warming from two separate roles: cutting the flow the emissions of carbon each year from the rapid pace of deforestation, and avoiding emission of the stock of carbon in the remaining forest that can be released by various ways, including climate change itself. Barriers to rewarding forest maintenance include the need for financial rewards for both of these roles. Other needs are for continued reduction of uncertainty regarding emissions and deforestation processes, as well as agreement on the basis of carbon accounting. As one of the countries most subject to impacts of climate change, Brazil must assume the leadership in fighting global warming.