1. Thermospheric density variations due to space weather Tiera Laitinen, Juho Iipponen, Ilja Honkonen, Max van de Kamp, Ari Viljanen, Pekka Janhunen Finnish Meteorological Institute

2. 1.Real-time space weather modelling using the GUMICS global MHD simulation. 2.How space weather expedited GOCE decay Moderate geomagnetic disturbances expedited re-entry by several hours. Changes in decay rate agree with GUMICS simulation. 3.Correlations of magnetic indices with GOCE+ density Time integration of indices enhances results. An empirical proxy correction to NRLMSISE-00 model is being developed. Outline

3. Real-time space weather modelling

4. Global magnetosphere- ionosphere coupling simulation model The only one of its kind in Europe Developed at FMI since 1993 Dozens of scientific publications MHD magnetosphere Electrostatic ionosphere GUMICS

5. GUMICS: M-I-coupling Solar wind J‖J‖ e – prec. Φ Mapped along dipole field lines: B, n, T, v, … Φ, Σ, J, E, e – prec., …

6. A new parallel version of the code Currently under validation and finalisation. Capable of faster than real time running with moderate resolution, ~ 0.5 - 1 RE requires ~ 100 cores. First technical real time operations test was performed during the GOCE case GUMICS-5

7. Chained run system Solar wind propagation from L1 takes ~ 1 h. Allows ~ 20 min prediction time. Initial state from the previous run Latest solar wind from ACE Run extended beyond measured solar wind with constant input New run every 20 min

8. GUMICS results Real-time simulations were done with GUMICS-5. Later the period was simulated with GUMICS-4 with better resolution. Joule heating + electron precipitation. Integral over 24 h (heat accumulation).

9. From Joule heating to air drag

10. A simple model for heat deposition Height [km] Extra heat from SWE Temperature change Quiet time atmospheric profiles from NRLMSISE-00 JH from GUMICS Assume globally even heat distribution Ad hoc heating profile with maximum at 120 km

11. Density increases above ~130 km Atmospheric profiles without and with ionospheric heating. We estimated ~15 % increase at GOCE’s altitude on 30 Oct. Pressure Density Temperature Height [km]

12. Extracting changes in decay rate Nominal decay rate in a time-invariant atmosphere Real decay rate Space weather effect? Decay rate [km/orbit] Nominal density at orbit from NRLMSISE-00 Fit to the real decay rate (get air drag coefficient) Fitted density is the nominal decay rate Calculate difference of real and nominal decay rate

13. Simulation predicts orbit variations

14. Global MHD simulation predicted variations in GOCE decay rate due to space weather. Effect on decay rate about 15 %, with only moderate SWe disturbances, no geomagnetic storms. SWe on 30 Nov. expedited GOCE decay by about 6 h. 7 Nov. another SWe event of similar magnitude. This analysis was done afterwards, but the procedure could be implemented as a forecast routine (with forecast time ~ 20 min). Conclusions on simulations

15. Results from GOCE+ atmospheric density data

16. The decay period exercise incited us to analyse GOCE+ density data from the entire mission. First analysis concentrated on geomagnetic storms with max(AE) > 1000. We identified e.g. TADs and analysed the travel time of disturbances from polar to equatorial region. We found good correlation between magnetic indices and density variations. Currently we are developing an empirical model that corrects NRLMSISE-00 density for geomagnetic activity using AE index. Analysing GOCE+ density

17. Time integration enhances AE index usability GOCE+ density vs. momentary AE GOCE+ density vs. AE time integral

18. Best integral window? AE IMF |B| Window size (h) Max AE

19. MomentaryAvg. int. w.Best int. w.Int. w. length AE0,55 (15)0,83 (12)0,84 (11)21 (12) h ap0,54 (18)0,85 (11)0,86 (9)26 (12) h |B|0,54 (24)0,66 (26)0,76 (21)37 (19) h ε0,27 (15)0,58 (30)0,70 (23)34 (18) h Correlations for proxies AE and ap are equally good proxies. |B| is the best solar wind proxy. Solar wind proxies require longer integration than magnetic indices. Possibility to shorten the integration window from end to increase forecast lead time?

20. Density from GOCE+, MSIS and AE proxy Time Gm. latitude GOCE+ AE proxy MSIS An emperical model based on AE and MSIS is being developed. MSIS underestimates density during geomagnetic storms especially at mid-latitudes.

21. MSIS and AE proxy model performance comparison GOCE+ vs. MSIS relative difference GOCE+ vs. AE proxy relative difference AE increases

22. Using AE index based correction significantly enhances thermosphere model agreement with observations. Thermospheric density correlates best with a time integral over ~24 h of AE or ap index. AE is available in real time. Atmospheric heating could also be derived from a global MHD simulation, as demonstrated by our modelling of GOCE decay. Could be used for prediction. Solar wind data availability limits prediction lead time. Conclusions

23. Tiera.Laitinen@fmi.fi