Search

In this study, we propose a methodology for training a deep learning model using historical time series data to predict current values. Using 11,942 past meteorological observations collected over a specific period from the Osan weather station in Gyeonggi-do, we predicted the atmospheric radio refractivity at the current time. As a result of predicting the atmospheric radio refractivity at 00Z on August 4, 2023, and August 5, 2023, at the Osan weather station in Gyeonggi-do, the average MAPE(mean absolute percentage error) and ARIMA(autoregressive integrated moving average) of the proposed model were 2.75 % and 7.61 %, respectively. [ABSTRACT FROM AUTHOR]

In this study, we propose a model for predicting atmospheric refractivity using meteorological data and deep learning. The purpose of this study is to compare the prediction accuracy of traditional interpolation methods and the proposed model, verify whether the deep learning model trained on meteorological data can provide values closer to the true values, and thus demonstrate the potential for utilizing deep learning in predicting atmospheric refractivity. [ABSTRACT FROM AUTHOR]

The quality of services provided via Inter-Terrestrial radio communication links such as GSM networks, Wide Area Network (WAN), Radio and TV broadcasts is largely influenced by some meteorological parameters such as temperature, pressure and humidity. Proper knowledge of these parameters, specifically at microwave antenna heights (about 70m) is important in order to maintain an effective line-of-sight (LOS) link even during the worst weather conditions. The geoclimatic factor is an important quantity that must be considered in the design of terrestrial links for effective wireless communication. This work utilized satellite data from the European Center for Medium-Range Weather Forecasts (ECMWF) to compute the point refractivity gradient and geoclimatic factor for Yenagoa and its environs. The research was necessitated by the paucity of research on this subject matter for Yenegoa. The results of the research show that point refractivity gradient and geoclimatic factor in the study area vary with season. The average point refractivity gradient and geoclimatic factor at 70 m above the ground level are:136.433 N-unit/Km and 6.638633E-05 respectively. This implies that radiowaves propagating in this region at the said altitude is most likely to be super refractive in both rain and clear air atmospheric conditions. Rain or worst condition refers to the period when atmospheric components such as hydrometeor, lithometeor, aerosol have significant effects on propagated radio signals. Clear-air conditions means when maximum possible signal is received such that the most threatening atmospheric components (rain drops) have negligible effects on propagated signal. The results will be useful for radio engineers in the design and configuration of inter-terrestrial microwave links in Yenagoa and Its environs for optimum quality of service. [ABSTRACT FROM AUTHOR]

Dynamic refractive environments within the marine atmospheric boundary layer (MABL) pose difficulties in the prediction of X‐band radar wave propagation due to natural phenomena such as evaporation ducts (ED). This study utilizes a unique data set collected during the Coupled Air‐Sea Processes and Electromagnetic Ducting Research (CASPER)‐East field campaign, including multiple refractivity estimation methods and twelve point‐to‐point (PTP) electromagnetic datasets, to assess the efficacy of PTP inversion techniques for remote sensing of atmospheric refractivity within the MABL. Comparison of refractivity between the inverse and other refractivity methods show reasonable evaporation duct height estimates by the inversion, and inverse‐based propagation predictions are also shown to be more accurate than propagation based on other refractivity prediction methods: numerical weather prediction, theory, and in situ atmospheric measurements. These results propose the effectiveness of a PTP metaheuristic radar inversion to remotely sense refractive environments from radar propagation measurements in stable and unstable atmospheric conditions. Plain Language Summary: Continually varying atmospheric properties in the marine environment, especially at altitudes within 100 m of the surface, cause radar waves to deviate from expected patterns resulting in positioning uncertainties and other adverse effects. Measurements and mathematical models are commonly implemented to understand atmospheric structure, where data from these models or measurements are used within radar simulations to evaluate the impact of such conditions on radar. This study demonstrates the application of a technique that models the atmosphere in a reverse manner‐determining the atmospheric structure based on radar wave propagation measurements that are impacted by this structure. The radar measurements used in this study were collected in conjunction with measured and modeled atmospheric data, which are used to verify the results of the reverse methodology, a unique data set for this application. We find that remote sensing of the atmosphere based on propagation measurements generates adequate representation of the atmospheric structure. The highlighted technique also most accurately predicts the propagation measurements as compared to more common atmospheric measurement and modeling techniques. Thus, this method of determining atmospheric conditions shows merit for sensing of the environment in order to enable corrections of a radar system, paving the way for improvements in associated technologies. Key Points: Inversion employing a genetic algorithm solves for refractivity from point‐to‐point radar propagation measurements in a marine environmentInversion results scrutinized by comparison with other refractivity sources: numerical weather prediction, theory, and in situ measurementsInversion solutions adequately remotely sense atmospheric refractivity in unstable and stable atmospheric regimes [ABSTRACT FROM AUTHOR]

Surface radio refractive gradient and k-factor are very imperative in observing propagation conditions, designing and planning of microwave communication links in the lower part of the atmospheric boundary layer. The measurement of weather variables (air temperature, atmospheric pressure, relative humidity and wind speed) were conducted in this study at the School of Science, Emmanuel Alayande College of Education, Oyo (7.83°N, 3.95°E), Oyo State, Nigeria. The research was carried out for a period of one year (January to December, 2020) using self-designed cost effective portable weather monitoring systems. The systems were sited from the ground to a height of 200 m on a 220 m Nigeria Television Authority (NTA) UHF channel 37 tower at Oke-Apitipiti in Oyo Town of Oyo State. The calculated daily and monthly averages data are employed to investigate the vertical surface radio refractivity and its refractivity gradient. The highest value of -1.093E+26 N-units/km was recorded in January, while the month of July experienced the least of about -9.305E+19 N-units/km. The months of January–July verified sub-refractive conditions with propagation conditions having varying degree of occurrence. On the other hand, super-refraction and ducting were recorded mostly between August–December from the study. The results also find applicability in radio engineering for refining VHF/UHF terrestrial links based on clear-air considerations which will support operational planning of terrestrial radio networks in Oyo, South Western Nigeria. [ABSTRACT FROM AUTHOR]