Application of the Bagged Trees Technique on Retrieving the Nighttime Ionospheric Peak Density From OI‐135.6 nm Airglow

Abstract

Abstract The NASA global‐scale observations of the limb and disk (GOLD) mission is a measurement opportunity to scan the far ultraviolet airglow at ∼134–162 nm over the American Hemisphere since October 2018. The FORMOSAT‐7/COSMIC‐2 (F7/C2) satellite mission has provided thousands of daily radio occultation soundings in the low‐ and mid‐latitude regions since July 2019. The nighttime OI–135.6 nm emission is mainly through radiative recombination, and the radiance is used to derive the peak electron density. Comparison with corresponding F7/C2 observations demonstrates good correlation in low‐latitudes, while is overestimated near mid‐latitudes in winter, induced by the photoelectrons emanating from magnetically conjugate Hemisphere. The machine learning technique Bagged Trees is implemented to develop an intensity to peak density model training from GOLD and F7/C2 observations. The validation demonstrates that Bagged Trees peak‐density has less influence from conjugate photoelectrons and indicates the power of machine learning techniques for geophysics data processing.

Keywords

• machine learning
• OI‐135.6 nm airglow
• GOLD
• FORMOSAT‐7/COSMIC‐2
• radio occultation