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SW_IBP_CLI_2_
Full product name
Climatological model of ionospheric bubble probability
Description
Climatological model of ionospheric bubble probability based on electron density and magnetic field observations
Data Access
- Files
- HTTPS (Product files): https://swarm-diss.eo.esa.int/#swarm/Level2longterm/IBP
- FTP (Product files): ftp://swarm-diss.eo.esa.int/Level2longterm/IBP
- Web services
Output variables
| Variable | Units | Description | Dim | Type |
|---|---|---|---|---|
| Parameters | - | Bubble Parameters | 1 | CDF_DOUBLE |
| Intensity | - | Periodic Signal Intensity | 1 | CDF_DOUBLE |
| Monthly_LT_Shift | 1 | Density estimations table, 12 month | 12 | CDF_DOUBLE |
| Density_Estimators | 1 | Density estimations table, 12 month | 12 | CDF_DOUBLE |
| Density_Estimator_Lons | degree | Longitudes of density estimations table | 1 | CDF_DOUBLE |
Details
| Product identifier | IBP_CLI_2_ |
|---|---|
| Definition | Climatological model of ionospheric bubble probability |
| Input data | IBIxTMS_2F, EFIx_LP_1B, AUX_F10_2, Bubble detection index of CHAMP vector magnetic field data (similar procedure as for IBIxTMS_2F) |
| Input time span | Model based on magnetic data: Entire Swarm mission + Entire CHAMP mission; Model based on electron density data: Entire Swarm mission |
| Spatial representation | Continuous in geographic longitude at a step size of 1° |
| Time representation | 1 LT hour |
| Units | N/A ([0-1]: probability) |
| Resolution | 0.01 |
| Uncertainty | Refer to Stolle et al. (2024) (An empirical model of the occurrence rate of low latitude post-sunset plasma irregularities derived from CHAMP and Swarm magnetic observations. Space Weather, 10.1029/2023SW003809) |
| Quality indicator | N/A |
| Data volume | Approximately 400 kB per file |
| Data format |
|
| Output data | Probability estimation by longitude, LT, day of year, F10.7 |
| Output time span | N/A |
| Update rate | yearly |
| Latency | < 3 months |
| Notes | The coefficient file, the machine learning model file, the applicable forward modelling code (in Python), and related documentation are available at https://igit.iap-kborn.de/ibp/ibp-model |
Related resources
Software repository for Python package: https://igit.iap-kborn.de/ibp/ibp-model