Morning Lectures
Topics to cover:
ISR theory (Phil/Josh/others? Don Farley?)
Signal Extraction/Processing/Fitting at AMISR (Mike Nicolls)
Madrigal (Bill Rideout/Anthea Coster)
Radar Design/Signal Propagation
Experiment design: tradeoffs in fidelity, parameter observability, etc. which impact the final science available with the experiment
How to spot an outlier: with UAF staff help (who should be contacted early in the process anyhow), training yourself to see things which don't look quite right:
impossible temperature ratios
negative composition fractions
etc.
Notes:
Don Farley has been invited to help with ISR theory - waiting on his response.
Signal extraction/processing/fitting needs to have the right amount of technical detail. UAF facility people will be taking care of the true gritty details of fitting so this shouldn't be a lecture to produce radar technique experts. We need informed data consumers.
Phil confesses that I don't know what is meant by Signal Propagation. Also, radar and experiment design are other danger areas where we could veer off into transmitter design or other things which would be of interest only to EE students. How did the PARS summer school handle this balance between instrument design theory and science with the final reduced parameters? (NB: the PARS 2006 material is available.)
Afternoon Hands-On Sessions
Homework Assignments (sic): Staged hands-on activities to lead students through
Proposing an AMISR experiment
Scheduling and executing experiments
Scientifically analyzing the resulting data
Potential groupings for student activities - reduces teacher-to-student ratios:
ELIZABETH NOTE: Don't we have 4 afternoons to work with? Friday afternoon will be time for presentations. It seems like we need one more activity. Perhaps we rotate through these activities on M-W and then on Thursday the groups have time to process their data and prepare presentations?
Using Madrigal practically and productively
Easy ways to import Madrigal data into your favorite working language
Contextual parameters (geophysical and geomagnetic indices, IRI model, magnetic coordinates, etc.) available within Madrigal
Millstone ISR tour
Single antenna / transmitter system design
Live radar demonstration
Comparison of single antenna ISR with phased array AMISR
Planning an AMISR experiment, selecting modes, and requesting final data
How to select the right mode
How to schedule
Rules of the road for data access?
Typical data availability times?
Items needed from the AMISR technical team:
Reduced list of three or four experiment choices for student experiments, with a one-page style sheet available for each with the following:
Mode name
Parameters measured
Relative parameter accuracy in standard analysis mode
Altitude resolution
Time resolution
Spatial coverage
Times available for student experiments
Schedule deadlines for student experiments
Data delivery details
will realtime analysis be different than batch (Phil imagines it will), leading to different relative parameter accuracies and other tradeoffs? Accordingly, what will the student need to know about quick look vs. later detailed analysis?
What turnaround for realtime analysis?
What turnaround for batch analysis? Will this happen before the workshop ends?
More afternoon hands-on notes:
What should the followup be with students on their designed experiments? More long-distance help will clearly be needed to get students through to using the data in their science experiments.
Careful grouping of students is the only way Phil can see that we can cycle all students through experiment requests, which means they need to be grouped by common science topic.
ELIZABETH: How many actual experiments did we have proposed? Anthea and I discussed making it really simple and just assigning a science problem to each group. Then they have to think about how to use the radar to solve the problem and get the proper data requested. This week is not really for PhD research - it's to learn the basics of performing an ISR experiment and so it's okay for the science reasons to be "artificial" and hand-picked.
Can we really do this practically?
If not, what is the alternate model we should operate under?
If we run out of time, what will the followup be to ensure all students get a chance to design and execute an experiment?
NOTES FROM CEDAR SUMMER SCHOOL DINNER MEETING
Tentative schedule of events:
Monday AM lecture: ISR theory and basic ionospheric physics (and history of ISR by Behnke?)
Monday PM: tour facility and introduction to Madrigal (alternating/rotating)
Tuesday AM lecture: ISR theory, basic ionospheric physics and some analysis/fitting
Tuesday PM: design and submit their PFISR experiments
Wednesday AM lecture: analysis and fitting
Wednesday PM: retrieve their data and analyze it
Thursday AM lecture: science and AMISR
Thursday PM: prepare their presentations
Friday AM: present their projects and evaluate the workshop
Student organization: 20 students will be divided into 2 or 3 groups for the tour. These will be the same groups that will work together on their PFISR projects.
Lecturers / staff:
Phil Erickson
Bill Rideout
Anthea Coster
Anja Strømme
Elizabeth Kendall
Josh Semeter [exact commitment TBD]
Mike Nicolls [provides material to Phil - CEDAR tutorial plus a little supplemental]
Rich Behnke: 10-15 min talk on personal ISR history
John Holt: helps with afternoon data reduction/interpretation
(It was discussed that keeping the number of lecturers to a minimum may make a more cohesive program.)
PFISR experiments: Each groups of students will design their experiment, submit it, retrieve their data from Madrigal, analyze it and present their results. Longpulse (LP) and alernating code (AC) will be the transmitted pulse scheme. The students will have the option of choosing the beam positions. Some obvious experiment goals are:
vector velocity vs altitude
vector velocity vs latitude
Ne vs latitude
They will submit their experiment via Todd's webpage and it will run during Tuesday night. Their runs will be processed and loaded into Madrigal in time for the Wednesday afternoon session.
Items to incorporate into the lectures:
levels of data (raw, fitted, resolved, etc.)
scale heights
time scales
resolution trade-offs
pitfalls
outliers, out-liers, out-lyers, out-liars, outright liars, big fat liars
error bars
assumptions