Astronomy & Space Sciences
Title : | Development of artificial neural network based predictive model for D-region ionosphere change due to solar flares |
Area of research : | Astronomy & Space Sciences |
Focus area : | Ionospheric Physics |
Principal Investigator : | Dr. Ajeet Kumar Maurya, Babasaheb Bhimrao Ambedkar University, Uttar Pradesh |
Timeline Start Year : | 2023 |
Timeline End Year : | 2026 |
Contact info : | ajeet.iig@gmail.com |
Details
Executive Summary : | The space born and ground based technological systems are highly susceptible to the Sun and its activities. The Solar flares and coronal mass ejections (CMEs) are the two major solar drivers that affect modern technological systems and causing space weather phenomenon. The soft x-rays resulted from Solar flares reaches at earth in almost eight minutes and affect the entire daytime ionosphere that affect the radio wave propagation due to sudden and enormous increase in the ionization. These process results in most serious disruption to the navigation and communication system. The most precise navigation and accurate communication is the need of hour especially in the airplane navigation and financial transactions. Therefore, forecast of exact state of ionization due to a flare is an important step required towards the mitigation of these serious space weather problems. The flares perturbed entire daytime of ionosphere but their effects are very well seen in the D-region of ionosphere. The D-region ranges from 60-90km altitude, is the sandwich region between neutral and ionized part of the atmosphere. The region responsible for HF absorption and radio blackout during solar flare event. The very low frequency (3-30kHz) waves from navigational transmitters almost perfectly reflected from D-region, thus forms a cost effectively tool for continuous monitoring of D-region state of ionization. Thus, in this proposal the aim is to understand various aspects of solar flare effect on the ionosphere. Based on the findings of the rigorous analysis of solar flare effect on the ionosphere by taking into account various parameters, an Artificial Neural Network (ANN) based mathematical model will be developed to nowcast D-region electron density change for a given flare event. The output of such models could be used as input to estimate the error in navigation and communication due to a flare. |
Co-PI: | Dr. Abhirup Datta, Indian Institute Of Technology (IIT) Indore, Madhya Pradesh-453552 |
Total Budget (INR): | 24,05,240 |
Organizations involved