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

The common practice of using 30-year sub-samples of climatological data for describing past, present and future conditions has been widely applied, in many cases without considering the properties of the time series analyzed. This paper shows that this practice can lead to an inefficient use of the information contained in the data and to an inaccurate characterization of present, and especially future, climatological conditions because parameters are time and sub-sample size dependent. Furthermore, this approach can lead to the detection of spurious changes in distribution parameters. The time series analysis of observed monthly temperature in Veracruz, México, is used to illustrate the fact that these techniques permit to make a better description of the mean and variability of the series, which in turn allows (depending on the class of process) to restrain uncertainty of forecasts, and therefore provides a better estimation of present and future risk of observing values outside a given coping range. Results presented in this paper show that, although a significant trend is found in the temperatures, giving possible evidence of observed climate change in the region, there is no evidence to support changes in the variability of the series and therefore there is neither observed evidence to support that monthly temperature variability will increase (or decrease) in the future. That is, if climate change is already occurring, it has manifested itself as a change-in-the-mean of these processes and has not affected other moments of their distributions (homogeneous non-stationary processes). The Magicc-Scengen, a software useful for constructing climate change scenarios, uses 20-year sub-samples to estimate future climate variability. For comparison purposes, possible future probability density functions are constructed following two different approaches: one, using solely the Magicc-Scengen output, and another one using a combination of this information and the time series analysis. It is shown that sub-sample estimations can lead to an inaccurate estimation of the potential impacts of present climate variability and of climate change scenarios in terms of the probabilities of obtaining values outside a given coping range.  

Study of diurnal and seasonal variation of atmospheric trace gases is essential to understand our atmosphere. For this, daily zenith-sky scattered light observations have been made by UV-visible spectrometer during the period 2000-2003. Slant column densities (SCD) from morning (solar zenith angle SZA = 90º) to evening (SZA = 90º) were retrieved to see the diurnal variation of NO2, O3, H2O and O4. For the study of seasonal behavior of NO2 and O3, vertical column densities (VCD) were retrieved during the above period. For the whole period, NO2 and O3 VCD are found in a positive correlation of r = 0.72 for the morning data and r = 0.79 for the evening data. Satellites borne observations are compared with the spectroscopic observations, which are found in good correlation. It is seen that highest NO2 and O3 VCD are found in summer months (May and June) and lowest in winter months (December and January). Evening NO2 VCD are found higher compared to morning. There is found an interesting seasonal change that at Pune (18º32´ N, 73º51´ E), the evening-to-morning (PM/AM) ratios of NO2 as well as temperature maximum/minimum ratios are higher in winter months and lower in summer months during the above period. In winter months NO2 PM/AM ratio goes up to 3.8 and in summer months lowest ratio is 1.25. During the day, N2O5 can be photolyzed to regenerate NO2, which reflects in the evening hours. In the winter, nights are longest; therefore, during night NO2 to N2O5 conversion is more, hence in the morning NO2 value will be less that leads to high PM/AM ratio. O3 PM/AM ratio is slightly higher in winter months compared to summer months.

In this paper the urban heat islands (UHI), both atmospheric and surface, and their relationship with the land use in the city of Mexicali, Baja California, México, were examined by means of direct in situ measurements of air temperature, and the use of NOAA´s AVHRR and Ladsat thermal satellite images. The results show the development of a nocturnal urban heat island, whose highest mean value was recorded in autumn (4.5 ºC), however during the day-time, in any season of the year, this situation is reversed and the city becomes a cold urban island. The existence of a surface urban heat island (SUHI) could be proved when the city was compared with nearby surroundings. Within the city, important thermal contrasts can be seen as a topographic map, and then can be related to different urban land use. The discussion is focused to the relationship that exists between the canopy air temperature, the surface temperature, and the atmospheric energy balance near the ground.

The descriptive study related to the evolution of O3, NO, NO2, CO, SO2, CH4, NMHC and PM10 concentrations in downtown Sfax showed, during the period October 1996-June 1997, that the city is significantly influenced by many sources and meteorological factors. The diurnal average concentrations of these species let appear at times some peculiarities due to the population local customs and also to particular meteorological conditions associated with predominant strong cyclonic situations (cut-off lows). Based on NO and CH4, two species selected respectively as local and synoptic tracers, this descriptive study which is refined by a principal component analysis showed, out from these particular meteorological conditions, three components of the atmospheric pollution: a first component formed by CH4 and in less degree NMHC showing the impact of synoptic sources, a second component containing NO, NO2, CO, SO2 and in less degree PM10 and NMHC displaying the impact of local sources (vehicle and industrial sources), and finally a third component constituted by O3 and in less degree PM10 presenting the impact of regional sources. Under the above quoted cyclonic situations, the distribution of such components was shown considerably modified.

Applying principal component analysis (PCA), we determined climate zones in a topographic gradient in the central-northeastern part of México. We employed nearly 30 years of monthly temperature and precipitation data at 173 meteorological stations. The climate classification was carried out applying the Köppen system modified for the conditions of México. PCA indicates a regionalization in agreement with topographic characteristics and vegetation. We describe the different bioclimatic zones, associated with typical vegetation, for each climate using geographical information systems (GIS).

The principal area of tropical cyclogenesis in the tropical eastern Pacific Ocean is offshore in the Gulf of Tehuantepec, between 8 and 15º N, and most of these cyclones move towards the west and northwest during their initial phase. Historical analysis of tropical cyclone data in the Northeastern (NE) Pacific over the last 38 years (from 1966 to 2004) shows a mean of 16.3 tropical cyclones per year, consisting of 8.8 hurricanes and 7.4 tropical storms. The analysis shows great geographical variability of cyclone tracks, and that there were a considerable number of hurricane strikes along the Mexican coast. About 50% of the tropical cyclones formed turned north to northeast. It was rare that any passed further north than 30º N in latitude because of the cold California Current. Hurricane tracks that affected the NE Pacific may be separated into 5 groups. We compared the historical record of the sea surface temperature (SST), related with the El Niño events with a data set of tropical cyclones, including frequency, intensity, trajectory, and duration. Although the statistical dependence between the frequencies of tropical cyclones of the most abundant categories, 1 and 2, over this region and SST data was not convincing, the percentage of high intensity hurricanes and hurricanes with a long life-time (greater than 12 days) was more during El Niño years than in non-El Niño years.

In this article, some results of numerical prediction of binary tropical cyclones (or binary systems) paths are presented. The analyzed systems were produced between 1984 and 2005, southward of 20º North latitude on northeastern Pacific Ocean adjacent to México. In this zone, it is common that tropical cyclones be accompanied by cloud clusters or another tropical cyclone that might be a mesoscale convective system, (MCS), a tropical depression, a tropical storm or a hurricane, establishing an interaction that is able to affect their typical tracks. When simulating a binary system in this work, the ability of the model to predict the path of this kind of tropical cyclones was improved. In all cases, western coast of México was affected by this kind of systems.

We study here the evolution of the ozone hole size (OHS) with the aim of contributing to understand the long term evolution and the origin of the discrepancies between modeled and observed size. Using the September, October and November monthly average data of the OHS, for the years 1982-2003, we separate the series into two components: a linear and a residual one. The residual OHS components for October-November, shows a tendency to decrease after 1997, whereas the residual component of September does not show a clear decrease. The OHS during September evolve different, in relation to the other months. Therefore, the earlier results for the OHS analysis obtained with an annual approach may be refined.

An one-dimensional atmospheric second order closure model, coupled to an oceanic mixed layer model, is used to investigate the short term variation of the atmospheric and oceanic boundary layers in the coastal upwelling area of Cabo Frio, Brazil (23º S, 42º08’ W). The numerical simulations were carried out to evaluate the impact caused by the thermal contrast between atmosphere and ocean on the vertical extent and other properties of both atmospheric and oceanic boundary layers. The numerical simulations were designed taking as reference the observations carried out during the passage of a cold front that disrupted the upwelling regime in Cabo Frio in July of 1992. The simulations indicated that in 10 hours the mechanical mixing, sustained by a constant background flow of 10 m s-1, increases the atmospheric boundary layer in 214 m when the atmosphere is initially 2 K warmer than the ocean (positive thermal contrast observed during upwelling regime). For an atmosphere initially -2 K colder than the ocean (negative thermal contrast observed during passage of the cold front), the incipient thermal convection intensifies the mechanical mixing increasing the vertical extent of the atmospheric boundary layer in 360 m. The vertical evolution of the atmospheric boundary layer is consistent with the observations carried out in Cabo Frío during upwelling condition. When the upwelling is disrupted, the discrepancy between the simulated and observed atmospheric boundary layer heights in Cabo Frío during July of 1992 increases considerably. During the period of 10 hours, the simulated oceanic mixed layer deepens 2 m and 5.4 m for positive and negative thermal contrasts of 2 K and -2 K, respectively. In the latter case, the larger vertical extent of the oceanic mixed layer is due to the presence of thermal convection in the atmospheric boundary layer, which in turn is associated to the absence of upwelling caused by the passage of cold fronts in Cabo Frío.

In regions of complex relief and scarce meteorological information it becomes difficult to implement techniques and models of numerical interpolation to elaborate reliable maps of climatic variables essential for the study of natural resources using the new tools of the geographic information systems. This paper presents a method for estimating annual and monthly mean values of temperature and precipitation, taking elements from simple interpolation methods and complementing them with some characteristics of more sophisticated methods. To determine temperature, simple linear regression equations were generated associating temperature with altitude of weather stations in the study region, which had been previously subdivided in accordance with humidity conditions and then applying such equations to the area’s digital elevation model to obtain temperatures. The estimation of precipitation was based on the graphic method through the analysis of the meteorological systems that affect the regions of the study area throughout the year and considering the influence of mountain ridges on the movement of prevailing winds. Weather stations with data in nearby regions were analyzed according to their position in the landscape, exposure to humid winds, and false color associated with vegetation types. Weather station sites were used to reference the amount of rainfall; interpolation was attained using analogies with satellite images of false color to which a model of digital elevation was incorporated to find similar conditions within the study area.