Meteorological Temperature and Humidity Prediction from Fourier-Statistical Analysis of Hourly Data

Abstract

The temperature readings for all the 365 days and the 24 hours may be fitted through a 3 × 3 matrix (the so-called T-matrix). The mean square deviation between this fit and the actual meteorological measurements is smaller than three degrees Celsius. Four entries of this (nonsymmetric) matrix may be fixed by other means, leaving only five independent components. However, the same method applied to the humidity measurements produces a larger mean square deviation. A strong stochastical connection is found between the T-temperature matrix and the U-humidity matrix. The computer program, in C, may be used to adjust a (2M + 1) × (2m + 1) matrix simply by changing the arguments at the command line and has been tested with m and M ranging from zero to 11 (eleven) (more than 24 readings per day are necessary for larger values of m). The physical meaning of these constants is given only in the case m = M = 1. Our results have also been connected to fundamental cosmological properties: Earth’s orbit, the ecliptic angle, and the latitude of Querétaro (or whatever geographical location is chosen). A separate program calculates the angular position of the Sun as measured in the sky of Querétaro, to determine the length of the day or the mean value of the solar cosine. This work introduces several new variables which happen to be stochastically connected.

ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements

“…Recently, the world has generated electric power from wind turbines, but the airflow control strategy for wind turbines has uncertainty. However, with the developments in meteorological temperature and humidity predictions from Fourier-statistical analysis of hourly data, which guarantees its operation [34][35][36], the temperature readings for all the 365 days and the 24 h may provide a strong stochastical connection to the classic strategy. Likewise, the neural network models were able to perform cold wind control [37][38][39].…”

Hydrodynamic Performance of a Pitching Float Wave Energy Converter

“…As fossil energy reserves continue to shrink and environmental problems become more prominent, countries around the world increasingly favor clean energy sourced from the Earth's cycles. For example, the world has generated electric power from wind turbines with uncertainty on airflow control, most recently, using a classic strategy of Fourier-statistical analysis of hourly data, which guarantees the continuous operation [1][2][3]. Furthermore, suitable neural network models were able to perform predictions [4][5][6].…”

The Use of Artificial Neural Networks for Forecasting of Air Temperature inside a Heated Foil Tunnel

“…An example would be monitoring and forecasting climate conditions. Scientific studies have shown that, for opencast agriculture, Fourier analysis of hourly data demonstrates that the atmospheric pressure intervened in the occurrence of rainfall on semi-arid regions [13][14][15][16]. The production management in greenhouse systems demands decision-making over several timescales.…”