MS Atmospheric Science thesis defense of Ruby Navarro: Comparison of MO foF2 observations with IRI-2016 model for Solar Cycle 21
The Department of Physics cordially invites you to an Atmospheric Science Thesis Defense:
Ionosonde foF2 observations at Manila Observatory, Philippines for Solar Cycle 21: Comparison with IRI-2016 Model
- MS Atmospheric Science Candidate: Ruby Jane Navarro
- Date and Time: 08 April 2019, 3:30-5:30 p.m.
- Venue: Heyden Hall, Manila Observatory
- Thesis Adviser: Dr. Quirino Sugon Jr
- Thesis Panelists: Mr. Clint Dominic Bennett, Dr. Maria Obiminda Cambaliza, and Dr. James Bernard Simpas
Abstract.We studied the historical data for the critical frequency foF2 of the F2 ionospheric layer from an ionosonde at Manila Observatory (MO) in the Philippines (14.7N, 121.1E) for the years 1976 – 1986, a period covering the entire solar cycle 21. A solar cycle is measured by the Wolf’s number, which depends on the number of sunspots. More sunspots correspond to high solar activity, resulting to more molecules ionized in the upper atmosphere, which range from 60 to 1,000 km. The ionosphere has different layers—D, E, F1, and F2–but the layer most responsive to solar activity is the F2 layer. To monitor the F2 layer, an ionosonde sends radio waves from 2 to 30 MHz upwards to the ionosphere. The speed of these radio waves depend on the density of electrons and the wave frequency. The critical frequency foF2 is the maximum frequency that can be reflected by the ionosphere, neglecting the effect of geomagnetic field, i.e., when a radio wave frequency exceeds this value, it may no longer return to the Earth.
In our work, we compared the observed ionospheric values of MO with those of the International Reference Ionosphere 2016 model (IRI-2016) to determine if the model can accurately predict the observed values or whether the model needs to be updated to accommodate the MO data, which consists of monthly median hourly values of foF2. The IRI- 2016 model was run using the geographic location and temporal resolution of MO data, with the following optional input parameters: geomagnetic storm model turned off and the URSI coefficient set for Ne F-peak. The method of statistical moments was implemented in order to obtain characteristics of observed and model comparison values, such as average, root mean square error, skewness and kurtosis. Analysis showed that the foF2 values derived from the MO- IRI 2016 hourly linear calibration curve (MOIRI) fit well with the observed data for the given geographical time and location, as compared to the values obtained by the basic IRI-2016 model run
