Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

The two sophisticated applied multivariate techniques, ‘Principal Component Analysis’ and ‘Two-group Linear Discriminant Analysis’ have been applied in the present work to analyze the pre-monsoon weather in Calcutta (India) and hence to forecast the pre-monsoon thunderstorms there. The work has been performed in the following two stages: i) Analysis with 20 thermodynamic and dynamic parameters derived from daily radiosonde data in Calcutta; ii) Analysis with 10 newly formed parameters which are actually the first 10 principal components formed with the 20 original parameters. The study indicates that an index known as ‘Linear Discriminant Function’ (LDF) may be constructed to predict the pre-monsoon weather in Calcutta. Not only that, the study also reveals that if the dimensionalities of the data matrices are reduced, then the accuracy of the results may improve.

Nonlinear dynamical systems (systems of 1st order ordinary differential equations) capable of generating chaos are analytically nonintegrable. Despite of this fact, analytical tools can be used to extract useful information. In this paper the original Lorenz system and its modifications are reduced to single oscillatory type integral-differential equations with delayed argument. This yields to appearance of an ‘‘endogenous’’ term interpreted as memory for the past. Moreover, the equations are valid far from the initial instant (theoretically at t→∞), when the system eventually evolves on its attractor set. This corresponds to the numerical solutions when an appropriate initial part of the iterates is usually discarded to eliminate the transients. Besides, the form of the equations allows statistical treatment.

This note contains an investigation of the inertial motion on the sphere including all the terms of the Coriolis forces. The velocity vector has a zonal, a meridional and a height components. The time dependence of these components are calculated by a solution of the three velocity equations containing only the Coriolis’ terms, and the three-dimensional position vector is then calculated from the velocity vector. The results depend on the latitude of the starting position. For most starting positions it is a good approximation to consider the latitude as a constant, because the results show that the south-north variations are quite small for reasonable values of the initial velocity vector which may be considered as the a-geostrophic wind and thus quite small. These remarks will be considered in detail in the paper. For each case the initial velocity vector (uo, vo, wo) and the starting position (xo, yo, zo) are given. However, due to the nature of the Coriolis terms it is seen that the vertical component (wo) cannot be given an arbitrary value since it is related to the other two components. The first step is to determine the time variations of the three velocity components, whereafter the trajectory of the three dimensional motion is determined.

During the years between 1967 and 1994 the trimestral abundance of the yellowfin tuna fish (Thunnus albacares), expressed as the number of individuals per group age and cohort, for the Eastern Pacific Ocean (EPO), was used to calculate the biomass of this species per trimester. This information was obtained from the Inter-American Tropical Tuna Commission publications (ITTC). Graphic methods were applied to this data (crude data, phase space, subseries per trimester as well as annual averages) in order to identify the behavior of the dynamics of this variable; this data was correlated with information on the presence of El Niño Southern Oscillation (ENSO) for the same period. The analysis suggests that the presence of strong ENSO events correlate with the decline of tuna fish biomass, which is followed by a rapid increase of this variable in a 3:1 time ratio; this means that it takes three times as long for the biomass to decrease than it does to recover and return to similar or higher values. After the ENSO-tuna fish biomass relations were established, two types of models were adjusted to the tuna fish biomass information: neuronal network and ARIMA. Both models described adequately the tuna fish biomass dynamics; however, the ARIMA model also permitted an adequate prediction of the behavior of ENSO variable, emphasizing that this model correctly predicted the presence of 1997 ENSO.  

During the second semester of 1997 the project “Utilización de pronósticos climáticos para actividades agrícolas en Tlaxcala” was instrumented with the purpose of aiding decision making in agricultural activities in the estate of Tlaxcala, México. The main objective of the project was to characterize extreme values of precipitation associated with El Niño/ La Niña events, to produce useful forecasts for decision-making. This was achieved through close contacts with the farmers whose specific needs were taken into account to the extent possible. In a sense such forecasts became “forecasts watched over by producers”. The method of ensemble of analogs was applied to historical data. The evaluation of annual and monthly forecasts is presented here. The results show that knowledge about the regional climate has been gained as it is reflected by the skill of the method to forecast. The forecast for the region, for the year 2003 is analyzed in terms of the precipitation anomalies.  

During the last decade of the 20th Century, diverse campaigns for measuring the atmospheric energy balance were performed in downtown México City (School of Mines and Preparatory School No. 7), in the southern suburbs (University Reserve) and in the surrounding rural areas (Plan Texcoco), in addition to a campaign carried out in 1985 in the Tacubaya district, a suburban western peripheral site. The objective was to obtain data for a better understanding of the climatic alterations due to urbanization, particularly to describe the role that the modification of the natural ground cover has played as a result of paving and the construction of urban canyons. In this paper, a review of these campaigns is presented. Energy partitioning in some areas (Tacubaya and Preparatory School No.7) is similar to that observed in urban centers of middle latitudes, whereas the major contrast was observed between Texcoco, with a maximum energy consumption through evaporation, and School of Mines, where the latent heat is as low as in a desert. From the values of the correlations among the different components of energy balance, it may be possible to attempt the modeling of the diverse components of energy balance by means of regression equations starting from the net radiation. Those same coefficients distinguish the type of environment: urban, suburban or rural.

Campo de Gibraltar is a highly industrialized area situated in the South of Spain around Algeciras bay (36º 7’N, 5º27’W). This area has an advantageous situation from a geographical, geological and botanical points of view. However, high wind speeds and a substantial degree of turbulence characterize this area, a situation that contributes to the rapid and wide dispersion of atmospheric pollutants and natural particles that are emitted in the atmosphere. The work described here involved the use of scanning electron microscopy (SEM) and X-ray Dispersive Energy Spectrometry (EDX) to characterize the atmospheric particles (both natural and anthropogenic). The electron microscopy method provides, simultaneously, knowledge about the morphology and the chemical composition of the particles. These are the fundamental parameters that need to be investigated to determine the origin of the particles. A systematic method has been developed that is applicable to the study of particles collected in emission sources, as well as to particles collected in inmission stations. This simple method allows the origin of the particles to be determined. Finally, a general classification of particles has been devised in terms of their physical and chemical characteristics, including morphology, surface characteristics and elementary composition.

Precipitation zone systems exist for México based on seasonality, quantity of precipitation, climates and geographical divisions, but none are convenient for the study of the relation of precipitation with phenomena such as El Niño. An empirical set of seven exclusively Mexican and six shared zones was derived from three series of Standardized Precipitation Index (SPI) images, from 1940 through 1989: a whole-year series (SPI-12) of 582 monthly images, a six month series (SPI-6) of 50 images for winter months (November through April), and a six-month series (SPI-6) of 50 images for summer months (May through October). By examination of principal component and unsupervised classification images, it was found that all three series had similar zones. A set of basic training fields chosen from the principal component images was used to classify all three series. The resulting thirteen zones, presented in this article, were found to be approximately similar, varying principally at zone edges. A set of simple zones defined by just a few vertices can be used for practical operations. In general the SPI zones are homogeneous, with almost no mixture of zones and few outliers of one zone in the area of others. They are compared with a previously published map of climatic regions. Potential applications for SPI zones are discussed.

Autoregressive Integrated Moving Average (ARIMA) models have been devised for long-term monthly series of maximum and minimum temperatures from south-western Spanish observatories. The original series were transformed into stationary ones, and the orders (p, d, q) for each monthly series were obtained. These were validated using series of residuals, and the parameters of the functions were estimated from the monthly stochastic models. The forecasts of change formulated from the ARIMA models suggest that the minimum temperatures in the study area are in a mean warming phase of the order of 0.2 ºC over the next decade. The change in maximum temperatures is not significantly defined. These estimations correspond with those obtained by the authors in earlier studies using other methods, but the level of precision is much higher in this case.

In this work we report measurements of atmospheric pollutants in Puebla City, including those registered during the period characterized by intense volcanic activity from Popocatépetl volcano between December 2000 and January 2001. We used a gaussian air dispersion model to calculate the impact of sulfur compounds from volcanic emissions on the measurements of these compounds in the stations belonging to Puebla City Atmospheric Monitoring Network. The data show that during the analyzed period, this volcanic emissions affected the air quality, increasing the indexes of PM10, CO and sulfur compounds. Also, the results of applying a gaussian air dispersion model to these sulfur compounds explains the measurements from Tecnológico station for days with intense volcanic activity and wind coming from the volcano to Puebla City.