Confirming structures seen in SMILE UV image by ground-based optical data

ESA-China joint mission SMILE (Solar wind Magnetosphere Ionosphere Link Explorer), to be launched in 2025, measures Earth´s global responses to solar wind and geomagnetic variations using combination of imaging and in-situ measurements during its 3-year nominal mission time after 2-months commissioning.

Although the budget is much less than Cluster, its unique orbit and instrumentation (particularly soft X ray and UV imagers), and  its close collaboration with ground-based observations allows unique science, stressing on* What are the fundamental modes of the dayside solar wind-magnetosphere interaction?* What defines the substorm cycle?* How do CME-driven storms arise, and what is their relationship to substorms?IRF will provide the 3D distribution of auroral emission reconstructed from ALIS_4D, that other similar systems cannot provide the same spatial and temporal resolutions.

Together with data from other instruments in Kiruna (all-sky camera, magnetometer etc), complement of SMILE optical data by IRF data will be unique and important, such as spatial resolution (150 km for SMILE UV image whereas 1 km for 3D reconstructed emission) and emission altitude for different wavelength (428 nm, 558 nm, 630 nm).

The above information is inevitable in judging the types of the aurora (e.g., diffuse aurora vs. discrete aurora) and aurora activity (e.g., quiet arc, substorm expansion, westward traveling bulge, omega band, pulsating aurora).

Although IRF´s long-time monitoring data itself is open to everybody, correct interpretation of the data (e.g., spatial resolution and possible bifurcation of the observed aurora) requires expert knowledge to reconstruct the image and interpret the results. Therefore extra support (extra processing of the data) by the ground-based team is inevitable.

However, the existing routine for such 3D reconstruction require considerable manual intervention and expert skills, causing it to be time consuming.

Therefore, it is difficult to respond to all the requests that are excepted from the SMILE team in complementing the SMILE UV image.

To improve this, we propose to work on the following tasks.(1) We develop more efficient routine for 3D reconstruction, which is divided into two parts: (1a) automated pipeline  to prepare the raw image ready for 3D reconstruction (e.g., noise removal), and (1b) manual reconstruction routine that is more user-friendly to a wider group of scientists.  (2) To make this routine effective, we also develop an automated evaluation system of the raw images that are taken by all-sky camera and ALIS_4D stations.

Fortunately, we have two types automated evaluation scheme that are succnotssfully running for the all-sky camera images: morphology evaluation and intensity evaluation. We plan to (2a) combine these evaluation schemes and (2b) further apply the combined scheme to the raw ALIS_4D images.

Here, unlike the all-sky camera, ALIS_4D provides absolute column emission measurements for different wavelength.(3) We actually provide the 3D reconstructed auroral emissions on the request basis from the SMIILE team.  (4) To make our 3D reconstructed auroral emissions and their interpretations most reliable, we make comparison between our optical data (all-sky images or 3D reconstructed aurora) and satellite images for many samples of different types of aurora.

Used satellites are (4a)  three active satellites that have the same imagers: NASA´s NSPP and NOAA´s JSPP-1 and JSPP-2, and (4b) SMILE.Considering the commission period and processing time of the initial UV data, the automated scheme should ideally be ready by 2026, while classification (validation) scheme should be ready 2027 for actual validation that lasts until 2028.