Multifractal detrended fluctuation analysis of temperature in Spain (1960–2019)

Datos de investigación disponibles en: http://www.aemet.es/es/datos_abiertos/AEMET_OpenDataIn the last decades, an ever-growing number of studies are focusing on the extreme weather conditions related to the climate change. Some of them are based on multifractal approaches, such as the Multifractal Detrended Fluctuation Analysis (MF-DFA), which has been used in this work. Daily diurnal temperature range (DTR), maximum, minimum and mean temperature from five coastal and five mainland stations in Spain have been analyzed. For comparison, two periods of 30 years have been considered: 1960–1989 and 1990–2019. By using the MF-DFA method, generalized Hurst exponents and multifractal spectra have been obtained. Outcomes corroborate that all these temperature variables have multifractal nature and show changes in multifractal properties between both periods. Also, Hurst exponents values indicate that all time series exhibit long-range correlations and a stationary behavior. Coastal locations exhibit in general wider spectra for minimum and mean temperature than for maximum and DTR, in both periods. On the contrary, the mainland ones do not show this pattern. Also, width from multifractal spectra of these two variables (minimum and mean temperature) is shortened in the last period in almost every case. To authors’ mind, changes in multifractal features might be related to the climate change experienced in the studied region. Furthermore, reduction of spectra width for minimum and mean temperature implies a decrease of the complexity of these temperature variables between both studied periods. Finally, the wider spectra found in coastal stations might be useful as a discriminator element to improve climate models

Application of Fractals and Complex Networks of meteorological variables in the description of climate change

El cambio climático está provocando distintos efectos según la región del planeta que se trate. Para estudiar estos cambios, se analizan largas series de registros de variables meteorológicas, como la temperatura o la precipitación, a través de modelos y técnicas predictivas. Estos están basados principalmente en bases de datos que se apoyan en análisis estadísticos e ignoran ciertas propiedades no lineales y multifractales de las series temporales implicadas. Esta tesis se presenta como compendio de tres trabajos publicados en revistas indexadas en Journal Citation Reports. En ella se busca encontrar posibles patrones espaciales y temporales en las propiedades de las series y mejorar la descripción de la temperatura del aire en superficie y la precipitación. Para este propósito, se utilizan los análisis multifractal y de redes complejas. Para el primer análisis, se aplica el método de Análisis Multifractal de Fluctuación sin Tendencia (MF-DFA, por sus siglas en inglés), mientras que para el segundo se usa la técnica del Grafo de Visibilidad Horizontal (HVG). Este permite transformar las series temporales en redes complejas que heredan las propiedades de las series originales. Las estaciones meteorológicas analizadas se distribuyen a lo largo del territorio peninsular español y abarcan un mismo periodo de 60 años: 1960-2019. En el primer trabajo, se lleva a cabo el análisis multifractal de las series de temperatura máxima, mínima, media y rango térmico diario (DTR, por sus siglas en inglés) en los subperiodos 1960-1989 y 1990-2019. Tras aplicar el método MF-DFA, se observa que las series son multifractales. Las temperaturas mínima y media experimentan una reducción del grado de multifractalidad en el último periodo en la mayoría de las estaciones. Además, muestran un mayor grado de multifractalidad en las estaciones costeras. En el segundo trabajo, se usa el método HVG para analizar las series anuales de temperatura media diaria que se estudiaron en el primero. Los resultados indican que las estructuras de las redes complejas y sus propiedades no parecen estar afectadas por el ascenso de las temperaturas derivado de las condiciones climáticas globales y son similares para las diferentes localizaciones consideradas. Finalmente, en el tercer trabajo, se usa de nuevo el método MF-DFA en series de precipitación. Como resultado, se observa que la precipitación presenta un carácter multifractal más complejo que el de la temperatura, con al menos tres regímenes de escala distintos para las pequeñas fluctuaciones de estas señales. A escalas pequeñas, la precipitación diaria tiene una gran persistencia y la magnitud de las correlaciones sigue el gradiente espacial de la precipitación anual característico de la Península Ibérica. Estas correlaciones se reducen de manera uniforme en el segundo periodo. Los principales cambios observados a grandes escalas comprenden un aumento en la complejidad de las pequeñas fluctuaciones y una disminución de las singularidades de las series en la zona oriental de la Península.Climate change is causing different effects depending on the region of the planet concerned. To study these changes, long record series of meteorological variables, such as temperature or precipitation, are analyzed by means of models and predictive techniques. These are mainly based in data bases which are supported by statistical analysis and ignore some nonlinear and multifractal properties of the time series involved. This thesis is presented as a compendium of three works published in journals indexed in Journal Citation Reports. It aims to find possible spatial and temporal patterns in the properties of series and to improve the description of the air surface temperatura and the precipitation. For that purpose, multifractal and complex networks analysis are used. For the first analysis, the Multifractal Detrended Fluctuation Analysis (MF-DFA) is applied, while for the second one the Horizontal Visibility Graph (HVG) technique is employed. This allows to transform time series into complex networks which inherit the features of the original series. The analyzed meteorological stations are distributed over the Spanish peninsular territory and span the same 60-year period: 1960-2019. In the first work, the multifractal analysis of the series of maximum, minimum, mean temperature, and diurnal temperature range (DTR) is carried out in the subperiods 1960-1989 and 1990-2019. After the MF-DFA method is applied, it is observed that the time series are multifractal. Minimum and mean temperatures experience a reduction of the degree of multifractality in the last period in most stations. Furthermore, they show a higher degree of multifractality in the coastal stations. In the second work, the HVG method is used on the annual series of daily mean temperature which were studied in the first one. Outcomes denote that the complex network structures and their properties seem not to be affected by the rise of temperatures derived from the global climatic conditions and they are similar for the different locations considered. Finally, in the third work, the MF-DFA method is used again on precipitation series. As a result, it is observed that the precipitation exhibits a more complex multifractal character than the temperature, with at least three different scaling regions for the small fluctuations of these signals. At small scales, daily precipitation has a high persistence, and the magnitude of correlations follows the characteristic spatial gradient of annual precipitation in the Iberian Peninsula. These correlations are reduced uniformly in the second period. The main changes observed at large scales include a rise in the complexity of small fluctuations and a decrease of singularities of series in the eastern part of the Peninsula

Estimation of bit error rate in 2×2 and 4×4 multi-input multi-output-orthogonal frequency division multiplexing systems

Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with multiple input antennas and multiple output antennas in dynamic environments face the challenge of channel estimation. To overcome this challenge and to improve the performance and signal-to-noise ratio, in this paper we used the Kalman filter for the correct estimation of the signal in dynamic environments. To obtain the original signal at the receiver end bit error rate factor plays a major role. If the signal to noise ratio is high and the bit error rate is low then signal strength is high, the signal received at the receiver end is almost similar to the ith transmitted signal. The dynamic tracking characteristic of Kalman filter is used to establish a dynamic space-time codeword and a collection of orthogonal pilot sequences to prevent interference among transmissions in this paper. Using the simulation, the Kalman filter method can be compared to the other channel estimation method presented in this paper that can track time-varying channels rapidly

Sesión 495, Ordinaria Modalidad Virtual. Vigésimo Cuarto Consejo Académico, 12 de julio de 2022

1 archivo PDF (305 páginas) + 1 archivo zipLista de asistencia. -- Orden del Día. -- Acta de la Sesión 495 Ordinaria. -- Acuerdos de la Sesión 495 Ordinaria. -- Acta de la Sesión 494. -- Jurados Diploma a la Investigación 2021. -- Renuncias Comisiones Dictaminadoras Divisionales (Dr. Ernesto Rodrigo Vázquez Cerón, Mtro. Fabricio Vanden Broeck y Dr. León Tomás Ejea Mendoza). -- Dictamen creación de Área Mecánica -- Dictamen Premio a las Áreas 2022 -- Escrito DCSH.AZC.336.22 Dictamen C. Docencia Consejo Divisional CSH. -- Escrito suscrito por el Dr. Saúl Jerónimo Romero con fecha 11 de julio de 2022 y anexos. -- Escrito con fecha 12 de julio de 2022 firmado por un grupo del sector estudiantil relativo a la petición de un diálogo público con el Rector de la Unidad Azcapotzalco