# Hunga Tonga Volcanic Eruption & Earth's Ionosphere¶

This research project was undertaken to fulfill requirements for 'Project 1' of City College of San Francisco's MATH 108 Fundamentals of Data Science course.

## Introduction to Earth's Ionosphere¶

Earth's atmosphere is composed of several layers, each with different physical properties. The ionosphere is region of the atmosphere containing several sub-layers of electrically charged (ionized) gas particles. Depending on the density and energy of these gas particles, radio frequency (RF) traveling through these layers can be absorbed, reflected back to earth, or lost to space.

Sub-layers tend to follow diurnal (day/night) patterns, with E & F being persistent, and D, F1 & F2 emerging only during the day.

## Measuring the Ionosphere¶

Methods of measuring the properties (sounding) the ionosphere range from active radar-like radio frequency probes to passive GPS satellite signal observation. Ionosonde is the term used for active radio frequency probes.

Ionosonde data can be represented visually in the form of an ionogram. Ionograms typically include data such as the Frequency of F2, Frequency of E, Total Electron Content, et al.

An international consortium of research institutions runs several ionospheric sounding stations around the planet. These stations probe the ionosphere periodically through the day, year round. This data is used to predict ionospheric conditions that may effect long range radio transmission, satellite signal reception, and global navigation satellite positioning.

• Pictured: Global Ionosphere Radio Observatory (GIRO) Digisonde sites.
• Source: GIRO https://giro.uml.edu/

Heliophysics has the strongest influence on ionospheric conditions, including day/night, solar wind, sun cycles, sun spots, coronal mass ejections (CMEs), et al. Earth weather & geophysics also influence the ionosphere, including weather & storms, tsunamis & earthquakes.

## Project Description¶

• Question: Given the effect of other Earth geophysics on the ionosphere, and our ability to measure ionospheric conditions with some periodicity, can we measure the effects of a volcanic eruption on the ionosphere?

This project aims to use the global ionospheric surveillance network dataset to determine if the Hunga Tonga volcanic eruption in January 2022 had a measurable effect on the ionosphere.

### Variables¶

Variables & measurements we intend to measure include:

• Frequency of F2 (foF2): The highest frequency of radio signal (RF) that would be reflected back to Earth by the F2 layer of the ionosphere. Measured in MHz.
• Total Electron Content (TEC): The total number of electrons present along a path between a radio transmitter and receiver. Measured in 10^16 electrons/m² = 1 TECU

### Limitations¶

Potential limitations to the data used in this project include:

1. The number of stations within range of the volcano. More stations would allow more granular readings.
2. Periodicity is not guaranteed. Ionosonde readings do not appear to be syncronized, and some periods are missing completely.

### Future Considerations¶

• WSPR Data
• CWOP Data
• Space Weather Data

### Errata / N.B.¶

This project originally used raw MIDS data from NOAA, but switched over to use FastChar data from GIRO. Consider all MIDS-related functions DEPRECATED in favor of FastChar.

### Sources¶

The data used in this project comes from these sources:

Ionosonde MIDS & FastChar:

• Reinisch, B. W., and I. A. Galkin, Global ionospheric radio observatory (GIRO), Earth, Planets, and Space, 63, 377-381, doi:10.5047/eps.2011.03.001, 2011.
• http://spase.info/SMWG/Observatory/GIRO
• "This paper uses ionospheric data from the USAF NEXION Digisonde network, the NEXION Program Manager is Annette Parsons"

### Other Notes¶

"A large eruption commenced on 15 January 2022 at 04:20 local time, sending clouds of ash 20 km (12 mi) into the atmosphere."

https://volcano.si.edu/ShowReport.cfm?doi=10.5479/si.GVP.WVAR20220112-243040

https://cimss.ssec.wisc.edu/satellite-blog/archives/44214

https://en.wikipedia.org/wiki/2022_Hunga_Tonga_eruption_and_tsunami

https://appliedsciences.nasa.gov/our-impact/news/tonga-eruption-sent-ripples-through-earths-ionosphere

Look at Guam barometric pressure data to see when pressure wave hit:

https://www.ndbc.noaa.gov/station_history.php?station=aprp7

## The 'Code'¶

### Data Science!¶

#### Focus Data¶

We're going to focus our investigation on the station at Guam.

## Visualize Ionosonde Data¶

### Zoomed-out view¶

For our zoomed-out view we'll look at data for the entire month of January. Red dot represents the eruption.

#### Scatter: foF2 & TEC¶

We'll look at two values from the ionosonde, the foF2 and the total electron content (TEC). There is an association between these two values - that is: As the TEC increases so does the foF2.

#### Line: TEC¶

The plot below shows TEC measurements for all of January, which seem to follow some diurnal patterns, climaxing during the day and dropping at night.

### Zoomed-in View¶

To 'zoom-in' we're going to take a snapshot of our data within the day of the eruption.

#### Line: TEC¶

This plot shows the typical diurnal pattern of daytime peak and nightime low, but with a considerable spike shortly after the eruption.

#### Line: foF2¶

Similar to the TEC pattern plotted above, the foF2 plot shows usual diurnal pattern, with a notable peak-trough-peak shortly after the eruption, followed by another peak later in the day.

#### Histogram: foF2¶

This histogram of foF2 shows us the distribution of foF2 readings throughout our snapshot period, with two prominent areas around 2.5 and 10.75 MHz.