General Plan

  1. Team introduction

  2. Learning to use the tools (Wiki, Python and Eclipse, Subversion, Madrigal)

  3. Learning about the ionosphere, incoherent scatter radar, GPS, and scientific databases. The REU lecture series will give a starting point. You can also explore the links on our Space Science Resources page - in particular, pay attention to the links in the first paragraph.

  4. An old but straightforward tutorial page on incoherent scatter radar measurements from the EISCAT Scientific Association is available.

  5. An entertaining way to get a very broad introduction is to view Episode 1 of our Space Weather FX video podcast series.

  6. Although an overview description is not available, there is information on the Poker Flat, Alaska phased array radar, one of the data sources for this project.

Project Rules

  1. The project will be documented in the Millstone Science wiki.

  2. OpenOffice will be used when an office suite is necessary. (e.g. OpenDraw for planning drawings)

  3. Software will be written following our python software conventions.

  4. All project designs, software, and documents outside the wiki will be revision controlled using Subversion.

  5. The official IDE will be Eclipse.

Science Project 1: Heavy Ion Outflows at Mid-Latitudes

With the tools at your disposal, we can attack our first science question. A hot topic in mid and high latitude ionospheric physics right now is the nature of processes which couple the ionosphere and the overlying magnetosphere (a region of the atmosphere farther out, controlled by Earth's magnetic field). One of the events seen during disturbed periods when coupling processes are especially strong is the presence of strong upward flows of oxygen ions (O+) at mid-latitudes during dusk. These outflows are driven by a strong electric field imposed by the magnetosphere on the ionosphere, or in another view by electric currents flowing along magnetic field lines between the ionosphere and magnetosphere.

The outflowing O+ ions have to end up somewhere, and they do in fact end up in orbits pretty far from the planet, where they can have a significant impact on the energetics and electrodynamics of that region of the outer atmosphere during geomagnetic storms. They have been spotted on other satellites, but only recently has it become clear that the O+ ions are unmistakably generated by ionospheric outflows - once again, a case of everything being coupled to everything else.

Heavy ion outflows from the ionosphere have been studied in a couple specific cases, but the Millstone Hill incoherent scatter radar database contains a great deal of zenith pointing (i.e. vertical) data which, during dusk times, may have observed these outflows. In fact, there may be enough data to make some statistically significant statements about the plasma conditions which characterize these outflows. Then again, there may not be. We'd like to find out. The results would in fact have implications for modelers of magnetosphere-ionosphere coupling, which does tie in directly to the high latitude investigations we'd like to do with the Poker Flat ISR and other supporting instruments.

So the task is to survey all Millstone Hill incoherent scatter radar data in the database, looking for ion outflow events in zenith measurements. We can do this by filtering the data to meet the following criteria:

  • UTC between 17 and 22 hours

  • elevation > 85 degrees

  • velocity >= 100 m/s for at least three points which further have altitudes > 200 km

Try writing a filtering program which goes through all Millstone ISR experiments and finds records meeting these criteria. For the records you find, have the program make a simple "value vs altitude" four panel plot for the following quantities:

  • log electron density NEL

  • line of sight ion velocity VO

  • electron temperature TE and ion temperature TI (both on the same plot)

  • upward flux, defined as NE times VO

We can then look at things and decide how good the statistics are, as well as whether our filters need to be tightened or refined. Make sure to label each plot with the UTC start and stop time of the record. Bill Rideout has made these individual record plots before and might be able to provide some sample code to make that task easier.

You will find that you have to fix the axes for the value axis as outliers can make autoscaling difficult. A useful set of ranges to start with:

  • NEL: 9.5 to 12

  • VO: -200 to 200

  • TE, TI: 500 to 4000

  • flux: NE*VO using the numbers above

After this is done, it would then also be useful to further sort the outflow events found into the following categories:

  • flux below 1E13 / m^2 s

  • flux between 1E13 / m^2 s and 1E14

  • flux between 1E14 / m^2 s and 1E15

and determine within each bin the distribution of events according to

  • UTC, say in 30 minute bins

  • geomagnetic disturbances, according to the KP parameter (Planetary K index)

There are a few practical details to this which will become apparent as you work through it, but we'll tackle those as they arise, and make changes based on the results.

Science Project 2: Sub-Auroral Polarization Stream (SAPS) Characteristics

Another related project is characterizing aspects of the ionosphere in regions where fast sunward flow occurs during moderate geomagnetic disturbances (Kp=3 and up), driven by magnetosphere-ionosphere coupling. This is the Sub-Auroral Polarization Stream (SAPS) which gets a great deal of attention.

John Foster and Hien Vo used hand inspection of all Millstone Hill azimuth scan (i.e. low elevation / wide coverage) data to identify the location and strength of the SAPS velocity field. We'd like to use their identifications to pull out further information on the ionosphere in these areas. The first task is to assimilate John's database into something workable from python. The database is now in three ASCII files on jupiter, and these along with a readme file and John's JGR paper in PDF form are in my home directory at

  • /home/jupiter/pje/science/saps_scan_database

I would suggest that we start with the following:

  • By combining the allscan_data and the scanmarkers_data information, see if it is possible to go into Madrigal and pull out data corresponding to an azimuth scan which John has identified. Hopefully, there is enough unique information here to do this.

  • If you can do the above, try to recreate Figure 3 of Foster and Vo (2002).

  • Using python, examine a few of the scans which John has identified in scaninfosummary_data information and see if you agree with his conclusions about the "aplat" and "Vlos" values in that data set.

Approximate Timeline

  • June 2, 2008 : Students Arrive

  • June 3, 2008 : First Team Meeting

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