DOI: 10.57760/sciencedb.space.02978
title: Solar Activity AI Forecaster Database
title: Solar Activity AI Forecaster Database

description: SA-AI Forecaster Dataset Structure==================================Data used in SA-AI Forecaster modeling is stored in the "dataset" folder, which consists of four subfolders: - "Observation_image"- "SPNet_data"- "IATools_data"- "FPNet_data"1. Observation_image--------------------Observational image data (JPG format) used in modeling, categorized into:• Magnetograms: Solar photospheric magnetic field observations - SDO_HMI - SOHO_MDI - ASO-S_FMG• Coronal EUV images: Solar coronal atmospheric observations - SDO_AIA - SOHO_EIT - GOES-16_SUVI (Images of different wavelengths stored in separate subfolders)• Hα: Solar chromospheric Hα observations - BBSO - KSO - HSOS2. SPNet_data-------------Files for SPNet module input/output:• Labeling_data: Manually annotated ground truth• output_data: Module recognition outputBoth contain three feature subfolders: - AR (Active Region) - CH (Coronal Hole) - FL (Filament)3. IATools_data---------------TXT output from IATools module (Jan 2023 - May 2024):• AR_parameters: Active Region parameters - Daily_flare_events: Identified/located flare events - flare_index: Calculated flare indices - parameters: Other AR parameters• CH_parameters: Coronal Hole parameters• FL_parameters: Filament parameters4. FPNet_data-------------Training/testing data for FPNet module:• F10.7_index: Daily solar radio flux observations• FPNet-independent_data: Data from SWPC daily reports ▪ flare_index: Flare indices (Formula 1) ▪ label_M_class: M-class+ flare labels (24hr forecast) ▪ mag_type: Mount Wilson magnetic classification ▪ AR_parameters: Active region parameters (R-value, location, etc.)• Output: The output of the FPNet and FPNet* ▪ Full-disk_FPNet-independent: Full-disk forecasting result of FPNet* ▪ AR_FPNet-independent: AR forecasting result of FPNet* ▪ Full-disk_FPNet: Full-disk forecasting result of FPNet ▪ AR_FPNet: AR forecasting result of FPNetThe data used in the SA-AI forecaster modeling process is stored in the dataset folder, which consists of four subfolders: "Observation_image", "SPNet_data", "IATools_data", and "FPNet_data"."Observation_image" contains observational image data in JPG format used for modeling, categorized into three types: "magnetograms", "Coronal EUV images", and "Hα". The "magnetograms" subfolder stores solar photospheric magnetic field observation images from different sources: "SDO-HMI", "SOHO-MDI", and "ASO-S-FMG". The "Coronal EUV images" subfolder contains solar coronal atmospheric observation images from various sources: "SDO-AIA", "SOHO-EIT", and "GOES-16-SUVI", with images of different wavelengths stored in separate subfolders. The "Hα" subfolder preserves solar chromospheric Hα observation images from different institutions: "BBSO", "KSO", and "HSOS".The "SPNet_data" folder contains input and output files for building the SPNet module, with two subfolders: manually annotated ground truth data "Labeling data" and module recognition output data "output_data". Each subfolder is further divided into three feature-based subfolders: "AR", "CH", and "FL".The "IATools_data" folder stores output data (TXT format) from the IATools module between January 2023 and May 2024. The "AR_parameters" subfolder contains three subfolders: daily identified and located flare events "Daily_flare_events", flare indices calculated using formulas "flare_index", and other AR parameters "parameters". The "CH_parameters" and "FL_parameters" subfolders store CH and FL parameters respectively.The "FPNet_data" folder contains training and testing data for building the FPNet module. It includes "F10.7_index" (daily F10.7 index observation data required for modeling), "FPNet_data" (data obtained from daily reports provided by SWPC for building the flare prediction module FPNet), and "Output"(forecasting results of the FPNet and FPNet*). The "FPNet_data*" contains four subfolders: "flare_index" (flare indices calculated using formula 1 based on SWPC event list), "label_M_class" (M-class flare eruption labels for the next 24 hours derived from SWPC event lists), "mag_type" (AR Mount Wilson magnetic classifications obtained from SWPC solar active region summaries), and "AR_parameters" (AR parameters including R-values and locations, obtained from SWPC and manual annotations). The "Output" contains four files in .xlsx format, which are forecasting results of the FPNet and FPNet* on the full-disk and AR, respectively.
description: SA-AI Forecaster Dataset Structure==================================Data used in SA-AI Forecaster modeling is stored in the "dataset" folder, which consists of four subfolders: - "Observation_image"- "SPNet_data"- "IATools_data"- "FPNet_data"1. Observation_image--------------------Observational image data (JPG format) used in modeling, categorized into:• Magnetograms: Solar photospheric magnetic field observations - SDO_HMI - SOHO_MDI - ASO-S_FMG• Coronal EUV images: Solar coronal atmospheric observations - SDO_AIA - SOHO_EIT - GOES-16_SUVI (Images of different wavelengths stored in separate subfolders)• Hα: Solar chromospheric Hα observations - BBSO - KSO - HSOS2. SPNet_data-------------Files for SPNet module input/output:• Labeling_data: Manually annotated ground truth• output_data: Module recognition outputBoth contain three feature subfolders: - AR (Active Region) - CH (Coronal Hole) - FL (Filament)3. IATools_data---------------TXT output from IATools module (Jan 2023 - May 2024):• AR_parameters: Active Region parameters - Daily_flare_events: Identified/located flare events - flare_index: Calculated flare indices - parameters: Other AR parameters• CH_parameters: Coronal Hole parameters• FL_parameters: Filament parameters4. FPNet_data-------------Training/testing data for FPNet module:• F10.7_index: Daily solar radio flux observations• FPNet-independent_data: Data from SWPC daily reports ▪ flare_index: Flare indices (Formula 1) ▪ label_M_class: M-class+ flare labels (24hr forecast) ▪ mag_type: Mount Wilson magnetic classification ▪ AR_parameters: Active region parameters (R-value, location, etc.)• Output: The output of the FPNet and FPNet* ▪ Full-disk_FPNet-independent: Full-disk forecasting result of FPNet* ▪ AR_FPNet-independent: AR forecasting result of FPNet* ▪ Full-disk_FPNet: Full-disk forecasting result of FPNet ▪ AR_FPNet: AR forecasting result of FPNetThe data used in the SA-AI forecaster modeling process is stored in the dataset folder, which consists of four subfolders: "Observation_image", "SPNet_data", "IATools_data", and "FPNet_data"."Observation_image" contains observational image data in JPG format used for modeling, categorized into three types: "magnetograms", "Coronal EUV images", and "Hα". The "magnetograms" subfolder stores solar photospheric magnetic field observation images from different sources: "SDO-HMI", "SOHO-MDI", and "ASO-S-FMG". The "Coronal EUV images" subfolder contains solar coronal atmospheric observation images from various sources: "SDO-AIA", "SOHO-EIT", and "GOES-16-SUVI", with images of different wavelengths stored in separate subfolders. The "Hα" subfolder preserves solar chromospheric Hα observation images from different institutions: "BBSO", "KSO", and "HSOS".The "SPNet_data" folder contains input and output files for building the SPNet module, with two subfolders: manually annotated ground truth data "Labeling data" and module recognition output data "output_data". Each subfolder is further divided into three feature-based subfolders: "AR", "CH", and "FL".The "IATools_data" folder stores output data (TXT format) from the IATools module between January 2023 and May 2024. The "AR_parameters" subfolder contains three subfolders: daily identified and located flare events "Daily_flare_events", flare indices calculated using formulas "flare_index", and other AR parameters "parameters". The "CH_parameters" and "FL_parameters" subfolders store CH and FL parameters respectively.The "FPNet_data" folder contains training and testing data for building the FPNet module. It includes "F10.7_index" (daily F10.7 index observation data required for modeling), "FPNet_data" (data obtained from daily reports provided by SWPC for building the flare prediction module FPNet), and "Output"(forecasting results of the FPNet and FPNet*). The "FPNet_data*" contains four subfolders: "flare_index" (flare indices calculated using formula 1 based on SWPC event list), "label_M_class" (M-class flare eruption labels for the next 24 hours derived from SWPC event lists), "mag_type" (AR Mount Wilson magnetic classifications obtained from SWPC solar active region summaries), and "AR_parameters" (AR parameters including R-values and locations, obtained from SWPC and manual annotations). The "Output" contains four files in .xlsx format, which are forecasting results of the FPNet and FPNet* on the full-disk and AR, respectively.