Investigation Vapor Weather using Gigahertz Frequencies up to 100 GHz

Abstract

Atmospheric modeling that is based on weather parameters requires highly accurate prediction as it influences different wide life aspects. Human begins; animal and agriculture are all affected directly by the weather. Recently, in via global crisis COVID 19 pandemic, the atmospheric parameter plays a vital role through air type which could spread the infection, while social distancing compulsory to achieve the prevention. Moreover, the researchers still working hard to eliminate the weather negative impact via investigate climate kinds and provide a scientific contribution in various life fields. One of the significant weather parameters is vapor, which is extremely important to the entire earth's surface in different forms such as evaporation, condensation, and the greenhouse effect, besides, the various massive sectors such as meteorological, manufacturing, and telecommunication.  In this work, we demonstrate the vapor climate in millimeter-wave frequencies to investigate the upcoming new bandwidth demand in specific weather conditions. The work utilized the curve fitting technique to model the data and select the appropriate model among the three, Exponential, Power, and Fourier. The fitting result shows that the Fourier in high term and coefficients is a satisfactory model for vapor climate, while the complicated calculations considered a drawback of the model when consider reaching 100GHz, and will extend the methodology to other models utilizing real data analysis to obtain comprehensive contributable results, which indeed could assist to enhance services in climate modeling and leads to giving accurate prediction in vital sectors.