Atmósfera (Journal)
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Interactive long wave spectrum for the thermo dynamic model
Get PDFSmith's (1969) analytical absorption spectrum of the atmosphere is incorporated in a thermodynamic model. This radiative formulation is applied to the infrared region. It computes separately the absorptivity by carbon dioxide and by water vapor, with a high wave length resolution, as a function of atmospheric pressure, temperature and gas content. The precipitable water or H2O content is computed using Adem's (1967) formula as a function of variables evaluated in the model: the surface temperature, the mid-tropospheric temperature and the horizontal extent of cloudiness. With this approach the model is able to simulate the positive feedback effect by long wave opacity of water vapor; that is to say its greenhouse effect. The computed spectrum for present values of CO2 and H2O concentrations shows good agreement with the estimates of Goody and Robinson (1951), Goody (1954) and Fleagle and Businger (1963)
Analysis of temporal behavior of climate variables using artificial neural networks: an application to mean monthly maximum temperatures on the Spanish Central Plateau
Get PDFA forecasting model for the mean monthly maximum temperatures (TMaxMean) using an artificial neuronal network (ANN) of the multilayer perceptron type (Multilayer Perceptron, MLP) has been developed. This model forecast the TMaxMean variable one month ahead after the last data point of the climate series. The study area considered is the central plateau of the Iberian Peninsula (Castilla y León and Castilla la Mancha). The data series of mean monthly maximum temperature (TMaxMean) were obtained of the observations at the stations of the synoptic and climatological network of the Agencia Estatal de Meteorología (AEMET). The data set is divided into two samples of training and testing. The training data set is used for the model development and the test set is used to evaluate the established model. The parameters of the ANN are fitted experimentally. A supervised training of the MLP ANN is performed. We used a backpropagation (BP) training algorithm with a variable learning rate. After that we evaluated the forecasting skills of the model from the coefficient of determination (R2), the mean square root error (MSE) and the dispersion and sequence graphics of the real and simulated series. The results obtained with the model (indicates a good fit between the real and simulated series) are compared with those obtained with ARIMA models. The results are similar, while the model ANN is able to adjust the extreme values of the real series and certain anomalies, which is not the case with ARIMA models
Net radiation estimation under pasture and forest in Rondônia, Brazil, with TM Landsat 5 images
Get PDFThe main objective of this study is to obtain the spatial distribution of net radiation (RN) in two contrasting vegetation covers (forest and pasture) through the SEBAL algorithm, and to analyze its performance when applied to tropical humid atmospheric conditions. This study was conducted in the state of Rondônia in northwestern Brazil, using four Landsat TM images, as well as, digital elevation model data. The correlation coefficients between estimated (SEBAL) and measured values of RN, and surface albedo are of 0.97 and 0.88, respectively. These results present SEBAL as an important tool to be used in hydrological and environmental studies, and to obtain coherent temporal and spatial variations of surface characteristics, helping in the improvement and validation of model parameterizations. However, the applications of remote sensing techniques in tropical humid climates are difficult, because of the existence of a constant presence of convective clouds
Assessing current and potential rainfed maize suitability under climate change scenarios in México
Get PDFWe conducted an assessment on the capacity to grow maize under rainfed conditions as well as under simulations of climate change scenarios in México. The selected method took into account the most limiting factor from different variables that maize requires to grow. These factors were compared, resulting in potential areas for maize distribution, classified in four different suitability levels: suitable, moderately suitable, limited suitability and not suitable. The emissions scenarios of climate change selected were A2 and B2 by 2050, including the GFDL-CM2.0, UKHADGEM1 and ECHAM5/MPI models. The results indicated that in base scenario, 63.1% of the national surface presents some degree of maize growing suitability. Specifically, 6.2% of the national surface indicated suitable conditions, while 25.1 and 31.6% had moderated and limited conditions, respectively. According to the climate change models, we were able to determine the full suitability level is also the most vulnerable one and as a consequence, this will also be the most aggravated one by decreasing its surface 3% according with UKHadley B2 and up to 4.3% in accordance with ECHAM5/MPI A2. This will make the limited suitability classification the one with the largest national territory, as much as 33.4%, according to ECHAM5/MPI A2 and up to 43.8% reflected by the GFDL-CM2.0 A2 model. The ECHAM5/MPI model indicates the most adverse conditions for maize growth, while GFDL model represents the less aggravating. All this clearly reflects that the natural conditions given for maize growing will become more restrictive, making it critical to implement environmental adapting measures.Se evaluó la aptitud que bajo condiciones de temporal se tiene en México para el cultivo del maíz, así como bajo simulaciones de escenarios de cambio climático. El método aplicado consideró el factor más limitante a partir de diferentes variables que el maíz requiere para poder desarrollarse. Se compararon los factores y se obtuvieron zonas potenciales de distribución para el maíz, categorizadas en cuatro niveles de aptitud: apto, moderadamente apto, marginalmente apto y no apto. Los escenarios de emisiones de cambio climático aplicados fueron A2 y B2 para el horizonte de tiempo 2050, tanto para los modelos GFDL-CM2.0, UKHADGEM1 y ECHAM5/MPI. Los resultados muestran para el escenario base que un 63.1% de la superficie nacional presenta algún grado de aptitud para el cultivo del maíz. Específicamente, un 6.2% de la superficie nacional presenta condiciones aptas mientras que en 25.1 y 31.6% hay condiciones moderadas y marginales, respectivamente. De acuerdo a los modelos de cambio climático aplicados, se encontró que la categoría apto es la más vulnerable y será la más afectada al disminuir su superficie desde un 3% de acuerdo con UKHadley B2 y hasta un 4.3% de acuerdo con ECHAM5/MPI A2. La categoría marginalmente apto será la que más superficie nacional ocupe, desde un 33.4% según ECHAM5/MPI A2 y hasta un 43.8% de acuerdo con el modelo GFDL-CM2.0 A2. El modelo ECHAM5/MPI es el que señala las condiciones más adversas para el cultivo mientras que el modelo GFDL es el menos agresivo. Lo anterior denota que las condiciones naturales en el país para el cultivo de maíz serán más restrictivas, por lo que es urgente la aplicación de medidas de adaptación
Simulated dynamics of net primary productivity (NPP) for outdoor livestock feeding coefficients driven by climate change scenarios in México
Get PDFIn this paper the concept of Net Primary Productivity (NPP) is used as a way to estimate the capacity of the ecosystem to produce dry matter which may be available for livestock to meet the forage requirements. The method allows the simulation of the possible impact on NPP and dry matter (DM), under climate change conditions observable for the country in a given time horizon. The concept was also used for current coefficients of rangeland and under current climate change scenarios, thus allowing to observe possible changes on the required surface for a sustainable cattle nutrition. It was found that México has NPP values ranging from 0 to 50 000 kgDM / ha / year. Dry matter is in the range that goes from 0 to 25 000 kgDM / ha / year. The coefficients of rangeland for the current scenario do not change significantly compared to those presented by COTECOCA, the official body determining such values. The states that present a greater impact due to current conditions under climate change scenarios were Baja California, Baja California Sur, Coahuila, Colima, Jalisco, Nuevo León, Puebla, Querétaro, San Luis Potosí, Sonora, Tamaulipas, Veracruz and Yucatán; this group will also have changes in its coefficients of rangeland in the future. Considering all of the above we discuss the implications that can be observed and we analyze the alternatives proposed by the federal government for the country’s livestock sector.En este trabajo se aplicó el concepto de productividad primaria neta (NPP, por sus siglas en inglés) como una forma de estimar la capacidad que tienen los ecosistemas de producir materia seca (DM, por sus siglas en inglés) que puede estar disponible para que el ganado cubra sus requerimientos de forraje. El método permite simular bajo condiciones de cambio climático el impacto posible que sobre la NPP y la materia seca se podrán observar para el país a un horizonte de tiempo dado. El concepto además fue aplicado sobre los coeficientes de agostadero actuales y bajo escenarios de cambio climático, permitiendo observar los posibles cambios en superficie requerida para la alimentación sostenible del ganado. Así, se encontró que en México se tienen valores de la NPP que van desde 0 y hasta 50 000 kgDM/ha/año. La DM, por su parte, se encuentra en el rango que va de 0 hasta 25 000 kgDM/ha/año. Los coeficientes de agostadero para el escenario actual no cambian considerablemente con relación a los presentados por COTECOCA, el organismo oficial encargado de su determinación. Bajo los escenarios de cambio climático se encontró que los estados de Baja California, Baja California Sur, Coahuila, Colima, Jalisco, Nuevo León, Puebla, Querétaro, San Luis Potosí, Sonora, Tamaulipas, Veracruz y Yucatán podrán ser los más impactados por posibles cambios en las condiciones actuales y verán modificados sus coeficientes de agostadero en el futuro. A partir de lo anterior se discuten las implicaciones que se podrán observar y se analizan las alternativas propuestas por el gobierno federal para el sector ganadero del país
Vulnerability of water resources to climate change scenarios. Impacts on the irrigation districts in the Guayalejo-Tamesí river basin, Tamaulipas, México
Get PDFThis paper presents an assessment of the impacts of climate change induced water availability variations on the irrigation districts in the Guayalejo-Tamesí River Basin in Tamaulipas, México. A model was developed using WEAP (Water Evaluation and Planning) to describe the vulnerability of the water resources in the case study river basin, taking into account the effects that climate change can have on water availability in the municipal, industrial, and agricultural sectors. The parameter to assess the extent to which the area is vulnerable to climate change was the Precipitation/Temperature relationship, or Lang Index. The latest version of the climate change program MAGICC/ScenGen was used, considering the MPIECH-5, GFDL2.0, and UKHADCM3 models for the A2 and B2 greenhouse gas emissions scenarios. The results indicate that climate change scenarios have the most negative impact on water availability in the agricultural sector. In addition, an analysis of the results suggests that water concessions, irrigation districts and hydraulic infrastructure in the river basin need to be reconsidered and updated to assure water availability to all its users.En este artículo se describe la metodología aplicada para la modelación de la disponibilidad del agua en la cuenca del Río Guayalejo-Tamesí, en el sur de Tamaulipas, México, tomando en cuenta los efectos que el cambio climático puede tener sobre la disponibilidad del agua en los sectores municipal, industrial y agrícola. Los resultados obtenidos indicaron que el sector agrícola es el más afectado; por lo que, los resultados que se describen en este artículo hacen especial énfasis en el sector agrícola. La relación Precipitación/Temperatura o Índice de Lang fue el parámetro que se utilizó para determinar la vulnerabilidad del área de estudio ante el cambio climático. Se aplicó la nueva versión del programa MAGICC/ScenGen considerando los modelos MPIECH-5, GFDL2.0 y UKHADCM3, para los escenarios de emisiones A2 y B2
Evaluative testing of a prototype barometer
Get PDFThe authors present the evaluative testing of a portable prototype of digital electronic barometer (UBII001). The prototype was developed in Venezuela although it includes low-cost multinational parts. The six year evaluation included response stability against atmospheric pressure variations. The UBII001 successfully passed a 550-1100 hPa test in the pressurization chamber of the Fondo de Metrología Legal (SENCAMER, Venezuela) and its responses remained within an acceptable ±0.1 hPa stability variation range. The prototype reached an absolute ±0.078 hPa exactitude better than that of ±0.1 hPa required by the World Meteorological Organization (WMO) and the International Civil Aviation Organization (ICAO) regulations for surface stations and airports. The information gathered here through the merging of measurement details with prototype characteristics represents a proven and replicable alternative of barometric development
Winter aerosol and trace gas characteristics over a high-altitude station in the Western Ghats, India
Get PDFThis paper presents spectral distribution of aerosol optical depth (and derived size distribution), water vapor and ozone in total atmospheric column; in conjunction with particulate mass concentration in the size range from 0.3 to 20 µm and black carbon mass concentration at the surface-level during four different campaigns, conducted in months of December-January-2006-2007 (Campaign I), February-2007 (Campaign II), January-2008 (Campaign III) and November-2008 (Campaign IV) at a high-altitude station, Sinhgad (18º22’N, 73º45’E, 1450 m AMSL) in the Western Ghats of Indian Peninsula. Aerosol optical depth (AOD) measured within the spectral range 440-1020 nm is found lower as compared to that measured over a nearby urban station, Pune; but relatively higher than that over other remote high-altitude stations in India. The columnar Angstrom exponent derived within the 440-870 nm spectral range showed maximum values close to 1 indicating relatively higher contribution from fine-mode particles to aerosol size spectrum. Interestingly, this parameter shows lower values when the total aerosol mass concentration exhibits higher values during afternoon hours. Both columnar water vapor (CWV) and ozone (TCO) exhibit lower values in the morning hours and higher in the afternoon hours. The mass concentration of black carbon shows an association with AOD during the study period over the station. The measured surface aerosol particle number concentrations are used to reconstruct AOD spectra using the Optical Properties of Aerosols and Clouds (OPAC) software package and compared with simultaneously available columnar AOD spectra
A proposal for a vulnerability index for hydroelectricity generation in the face of potential climate change in Colombia
Get PDFThe effect of potential climate change on the relationship water resources/hydropower generation in the Sinú-Caribbean Basin, Colombia, was analyzed. Climatic-hydrological variables that best express the vulnerability (positive or negative changes on water resources and related systems, and not precisely the definition of vulnerability given by the IPCC) of water resources in the region were identified, taking into account the current and projected values for the period of analysis 2010 to 2039. These variables were estimated based on the application of several general circulation models under greenhouse gas emissions scenarios A2. These scenarios were chosen considering that its outputs could provide a better basis to prevent adverse effects. The use of a weighted average scenario was proposed, and a vulnerability index for hydroelectric energy generation was established. In using the weighted average scenario was possible to determine the reduction of 13.3% in water storage volume in the reservoir with respect to the current scenario (year 2005 historic average), and the reduction of 22.8% in water storage volume with respect to the top of conservation storage capacity, and also, the reduction of 16.2% in energy generation with respect to current generation, and the reduction of 29.5% in energy generation with respect to the maximum hydropower generation capacity. The vulnerability index made it possible to determine (according to the models applied) that the hydropower generation system has a 44.4% low degree of vulnerability, a 22.2% medium degree of vulnerability, and a 33.3% high degree of vulnerability. In other words of nine analyzed models, four project a low degree of vulnerability, two medium degree and three a high degree of vulnerability
The life cycle of extreme rainfall events over western Saudi Arabia simulated by a regional climate model: Case study of November 1996
Get PDFA Regional Climate Model (RCM) is employed to simulate and understand the life cycle of the two systems that produced heavy rainfall spells over western Saudi Arabia in November 1996. The first spell of heavy rain occurred from 13 to 20 November, whereas the second occurred from 25 to 27 November 1996. Their spatial patterns are compared with rain-gauge data and also with the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Global Precipitation Climatology Project (GPCP) gridded observations. A series of 144 experiments are conducted for different domain sizes and resolution as well as different boundary forcings and convective parameterization schemes to investigate the optimum combination for the simulation of the two spells. The RCM simulates well the development, the propagation and the lifecycle of the first spell (8-day long) as well as the second spell (3-day long) during November 1996. In particular, the simulation demonstrates how the two systems developed, merged with new cells, reached to maturity, and then decayed, as they moved eastward across the Red Sea, producing rain in the study region. A focus over Jeddah station reveals that the RCM simulated well the peak and amount of rainfall for both spells. However, the first peak is 1-day shifted, whilst the second peak is underestimated