Model/Technique Registration (*=required):
Information about your group/project:
Solar activity monitoring and forcasting
Name(s) and e-mail (s) (please list primary contact first)*:
Martina Exnerova, martina.exnerova@asu.cas.cz
Associated Institution/Project name/Group name*:
Solar Department, Astronomical Institute of the Czech Academy of Sciences
(AI CAS), Solar Patrol Service (SPS)
Website url(s):
http://www.asu.cas.cz/~sunwatch/
Logo(s):
attachement – AI CAS, SPS
Information about your method:
human forecast
Forecasting method name*:
purely human - experienced observer
Shorthand unique identifier for your method (methodname_version, e.g.
ASSA_1, ASAP_201201):
SPS
Short description*:
Daily flare forecast for active regions are based on our own data sources
(sunspot drawings) and are weather dependent. Daily full disk forecast are
based on sunspot drawings and satellite data, they are not weather dependent.
Weekly flare forecast is issued on each Thursday and is not in probability format
(i. e. percentage). It declares the range or count of how many flares of each level
(C/M/X/P) can be expected for next 7 days.
Further Model Details:
(1)* Please specify if the forecast is human generated, human generated but
model-based, model-based, or other.
Human generated.
(2)* Does your flare prediction method forecast “M1.0-9.9” or “M and
above”? Would it be difficult for you to adapt your method from one to another?
Which forecast binning method do you prefer?
Only „M and above“ method!
(3)* How do you specify active regions in your model? Do you relate their
location to other schemes such as NOAA or Catania? If so, what is your criteria
to relate them?
We use McIntosh classification and numbering according to NOAA. For flare
forecast we come out from McIntosh classification but include also the
evolution of active regions and experience of qualified human observer.
(4)* Uncertainties given as an upper and lower bound is an optional field.
Does your model provide uncertainties for the forecasted probability?
We do not provide any uncertanties for the flare forecast.
If yes, what percentiles do you use to determine your upper and lower bound?
If you are using the XML format, multiple percentiles of the probability density
distribution can be specified.
(5)* For each forecast, what prediction window(s) does your method use?
E.g. Does your method predict for the next 24 hours, 48, and 72 hours or the
next 24 hours, 24-48 hours, 48-72 hours? (This information is useful for
displaying only comparable methods together).
24 hours and 7 days
(6)* For how many degrees from disk center is your full disk forecast valid
for? E.g. 60 degrees; or 90 degrees (valid for entire disk).
The entire disk.
(7)* Calibration levels are optional fields. Do you have calibration for the
probabilities from your model? E.g. is a 40% forecast a “high” probability for
your method?
Precentual range 0 %, 1 %, …,99%, 100%, where values 0% and 100% are only limit
values.