SOLAR MAGNETOGRAM SYNTHESIS A Vital Component in Space Weather Forecasting

1. Peter MacNeice (NASA/GSFC) Joel Allred (Drexel Univ.) Kevin Olson (Drexel Univ.) Sandro Taktakishvilli (NPP) Marlo Maddox (NASA/GSFC) AISRP Workshop – May 5-7, 2008 Peter.J.MacNeice@nasa.gov SOLAR MAGNETOGRAM SYNTHESISA Vital Component in Space Weather Forecasting I am going to tell you about a project we have just begun to build a tool to synthesize solar magnetograms. This is a vital, and so far, neglected part of the infra-structure required for space weather forecasting. I have a number of collaborators listed here. While I get to stand up here and collect the glory, most of the work is being done at Drexel by Joel Allred and Kevin Olson, who is in fact giving the next talk . Yesterday when I counted the slides I had prepared, I realised I had way too many for 15 minutes, so naturally, I solved the problem by adding one more. So in case I don’t finish, here is my talk distilled to one slide.I am going to tell you about a project we have just begun to build a tool to synthesize solar magnetograms. This is a vital, and so far, neglected part of the infra-structure required for space weather forecasting. I have a number of collaborators listed here. While I get to stand up here and collect the glory, most of the work is being done at Drexel by Joel Allred and Kevin Olson, who is in fact giving the next talk . Yesterday when I counted the slides I had prepared, I realised I had way too many for 15 minutes, so naturally, I solved the problem by adding one more. So in case I don’t finish, here is my talk distilled to one slide.

2. My Talk in One Slide Space Weather is hot! Forecasting model chains start with solar magnetograms New generation of models will demand much more from the magnetogram data No single magnetogram source can satisfy them Need to synthesize magnetograms from multiple sources ! Who is going to create the infra-structure for this ? Modelers ? Observatories ? No ! - We will ! Developing GUI driven CAD-like tool First check arrived two weeks ago. ….. That then is my talk. The rest is just the details, and the most important of which is that the first check arrived two weeks ago, so technically ours may be the youngest of all the projects being presented here. ….. That then is my talk. The rest is just the details, and the most important of which is that the first check arrived two weeks ago, so technically ours may be the youngest of all the projects being presented here.

3. Space Weather Primer Sun is the source of all transients driving space weather Most severe cases - Highly stressed coronal magnetic fields relax explosively – Flares/Coronal mass ejection The sun is the source of all transients driving space weather. It spits out a bunch of stuff on different timescales, some of which leave us with some hope of forecasting their arrival. These hazards have real societal consequences.The sun is the source of all transients driving space weather. It spits out a bunch of stuff on different timescales, some of which leave us with some hope of forecasting their arrival. These hazards have real societal consequences.

4. Societal Impact of Space Weather Power Grid failures Blackouts (eg Quebec, Mar 13 1989) long term, if high voltage transformers damaged Satellite failures (and over long term, reduced lifetimes) Communication and GPS blackouts Particle hazards to astronauts and polar flight passengers The produce induced currents in long power transmission lines which can lead to widespread system failures. They compromise satellite functions and lead to earlier reentry tmes, they cause communication and GPS blackouts and produce radiation hazards for astronauts.The produce induced currents in long power transmission lines which can lead to widespread system failures. They compromise satellite functions and lead to earlier reentry tmes, they cause communication and GPS blackouts and produce radiation hazards for astronauts.

5. Space Weather Primer (contd) Worst Case Scenario – Carrington event, Sept 1,1859 Aurora in Havana No solar event of comparable magnitude in the technological era, by factor of 4 ! Ice core records suggest one ‘Carrington like’ event or bigger impacts Earth every 500 years.

6. Space Weather Primer (contd) Carrington Event, Sept 1,1859 Telegraph Disruption Observations made at Pittsburgh, Pa., communicated by E.W. CULGAN, Telegraph manager. “During the Aurora of Aug. 28th the intensity of the current evolved from it varied very much, being at times no stronger than an ordinary battery, and then suddenly changing the poles of the magnets it would sweep through them, charging them to their utmost capacity, and compelling a cessation of work while it continued. On the morning of Sept. 2nd, at my request the Philadelphia operator detached his battery, mine being already off. We then worked with each other at intervals as long as the auroral current continued, which varied from thirty to ninety seconds. During these working intervals we exchanged messages with much satisfaction, and we worked more steadily when the batteries were off than when they were attached. On the night of Aug. 28th the batteries were attached, and on breaking the circuit there were seen not only sparks (that do not appear in the normal condition of a working line) but at intervals regular streams of fire, which, had they been permitted to last more than an instant, would certainly have fused the platinum points of the key, and the helices became so hot that the hand could not be kept on them. These effects could not have been produced by the batteries.” Boteler(2006) Estimates ~$70 billion impact on satellite industry (Odenwald et al 2006) - (equiv 6 months in Iraq, or, quarterly profits for the 3 biggest oil companies, or 1 Bill Gates) more than 80 satellites would be disabled Approx 100 LEO would reenter prematurely

7. Current ‘Forecasting Models’ Typical model chain model coronal field Coronal solution sets inner boundary to heliospheric model CCMC has 4 model chains (WSA, WSA/ENLIL, CORHEL, SWMF SC/IH) Principal role – to model ambient corona and heliosphere Only beginning to dabble in transients

8. SWMF – SC/IH (Univ. Mich)

9. WSA/ENLIL

10. ENLIL-WSA Fieldline Tracing

11. Advances in Space Weather Models Current Generation: use ‘static’ synoptic magnetograms at 1o resolution create ambient corona and heliosphere solutions Next Generation: will benefit from much better data sources, model algorithms computer hardware will create time dependent coronal models will use time dependent vector magnetogram data at 0.05o resolution the model’s physics, not the data, will define the resolution.

12. Next Generation Space Weather Models Coronal models will be Global Time dependent 3D MHD with adaptive mesh refinement Driven by observed surface flows Models will need to support both forecasting and research Function with latest data and archived data regardless of data limitations Models will define spatial resolution and cadence of magnetogram data at inner boundary eg global vector fields with maximum resolution of ~ 1”, cadence of 1 second

13. Magnetogram Problems Magnetogram source limitations include Cadence and duty cycle Resolution Field of view Quality, particularly horizontal components of vector data Systematic errors associated with line fittings No coverage of far side Very poor polar fields No single source provides enough coverage ! eg SDO – 1” resolution data Limited FOV Vector data every 10 minutes Full Disk Line of Sight data every 10 minutes Full disk vector data every 6 hours

14. A Hypothetical Modeling Challenge Active Region evolution Model Suppose we need a model for slow evolution of Active Region A There is a second active region B on disk Synoptic vector magnetogram data is available from Kitt Peak along with individual vector magnetograms taken 3 times per day. However data for region B is poorly sampled due to instrument problems. Marshall Vector Magnetogram has data for B but at different times and resolution than Kitt Peak. Also have LOS magnetograms at selected times from Kitt Peak, Mt Wilson and MDI.

15. Modeler Requirements

16. Tool Requirements Ability to interpolate in space (on a sphere) and in time Ability to handle many file formats Data – usually fits, sometimes ascii Model – customized at whim of developer Graphics – IDL, TecPlot, OpenDx etc

17. MAGIC Design Modular design – 6 components GUI (Python/TkL) A magnetogram database manager (MySQL) VSO interaction ? Lightweight magnetogram processing layer, executing interactive single line calls to Kameleon functions and simple canned Python routines for frequently used processing tasks (eg monopole subtraction) A third-party program execution interface Small suite of basic visualization tools (IDL and OpenDx) A command recorder function to facilitate batch processing. Open Source Linux Application

18. Typical Basic Use User requests a menu of all available data for time frame from database User selects their preferred data for each time User imports their model surface grids for all required times MAGIC does default (x,t) interpolation for each dataset to the appropriate grid User calls basic composition function for first grid - at prompt they input requested dataset weights or weighting rule MAGIC returns a composed surface vector field with a set of default images (Br, B?, B?, J) MAGIC asks if this synthesized magnetogram is acceptable No - go back and rework Yes - move on to next grid MAGIC reads in second grid Etc MAGIC outputs synthesized magnetograms in KAMELEON format files

19. MAGIC Design Backbone already in hand in CCMC’s Kameleon Tool. KAMELEON (Maddox) two components, a file formater and an interpolator handles many file formats handles many model coordinate systems has both spatial and temporal interpolation functions portable – an interactive interface and a callable library (from C, Fortran and IDL).

20. STATUS First funds only arrived in last few weeks Initial focus on defining a generic magnetogram format inside Kameleon Kameleon can now read, reformat, and interpolate on LOS data from Kitt Peak, Mt Wilson, SOHO/MDI vector data from Kitt Peak and Marshall Vector Magnetograph. Have begun initial GUI construction Added first python processing widget – a monopole removal function Added graphics calls to compare initial data, interpolated data and data after processing.

21. Importing and Converting Datafiles

22. Processing Data

23. Summary Developing a magnetogram synthesis tool using KAMELEON as the low-level manager of the data structures, I/O interfaces and basic interpolation layer Upon this foundation we add two processing layers (lightweight and heavyweight) Have added ability to ingest and interpolate most current magnetogram files Have begun building GUI and lightweight processing layer Have begun developing visualization tools to display different stages of data processing.

24. Modeler Requirements

25. ENLIL Heliosphere Model (Odstrcil) 3D MHD equations solved from 21.5rs to 2 AU Input at rotating inner boundary MHD parameters Output Magnetic field Velocity Density Temperature Two operating modes Ambient solution CME modeling using Cone model approximation