Coordination Group for Meteorological Satellites - CGMS
NICT's space weather
activities based on spacebased observations
Presented to CGMS-44 Space Weather Task Team session, agenda item
SWTT/4
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Overview - NICT's space weather activities based on space-based observations
1.
2.
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4.
5.
Introduction
Data Reception from Space Weather Monitoring Spacecraft
Monitoring High Energy Particle Environment in Geospace
Prediction of High Energy Electron Flux Environment
Recommendation
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Coordination Group for Meteorological Satellites - CGMS
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Data Reception from Space Weather
Monitoring Spacecraft
STEREO
Real-time space weather data is used for daily forecaster’s briefing
and empirical model of Dst index and relativistic electron flux.
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Kodama(DRTS) / ERG Project
Kodama
Energization and Radiation in Geospace
(ERG)
The satellite will be launched in FY2016.
Real-time space weather data from ERG
satellite will be provided.
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Energetic particle monitoring over Japan
by the Japan meteorological satellite, Himawari-8
 Instrument: SEDA（Space Environment Data Acquisition monitor）
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Purposes: house-keeping and failure analysis
Launch: 2014/10/07，Himawari-9 Launch; 2016 (plan)
Longitude: ~140 deg.
SEDA data is available from Nov. 03, 2014
Near-real time SEDA data is archived at NICT.
electron sensors
Electrons: 8 ch. (8 series plate)
proton sensors
Protons: 8 ch. (8 sensors)
Electrons: 0.2 MeV ~ 5 MeV
Protons: 15 MeV ~ 100 MeV
Electron sensor: ± 78.3°
Proton sensor: ± 39.35°
Time resolution: 10 s
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Himawari-8/SEDA quick-look &
databese
In Preparation
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3-Dimensional Geospace Monitoring Network
Himawari-8/SEDA data as
a source of global space
environment monitoring
around GEO, We wish to
share space environment
data obtained from other
meteorlorogical satellites.
Kodama(DRTS)
(JAXA)
Japanese GEO Satellites
are operated in this area.
GOES 13
(NOAA)
Van Allen Probes
(NASA)
GOES 15
(NOAA)
AC Mag.
HF radar
DC Mag.
ERG(JAXA)
(plan:FY2016)
Himawari-8 (JMA）
Himawari-9 (plan:2016)
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Time series prediction result of GEO MeV flux
by AR model + Kalman filter
Observation
↓
Regression order
ー 28 hours
↑
Prediction
Inputs
ー Solar wind velocity
ー Solar wind pressure
ー Dst index
↑
Margin for
prediction error
↑
40-h
ahead
#Coefficient matrix A is
estimated by the least
square method
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Outer radiation belt prediction model
The model successfully predicts the timing and location of the flux maximum as
much as 2 days in advance and that the electron flux decreases faster with time at
higher L values, both model features consistent with the actually observed behavior.
Input
Prediction
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Radiation Belt Electron Forecast Web
http://seg-web.nict.go.jp/radi/en/
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Recommendations for consideration
by CGMS SWTT
• Sharing of space-based space weather
observation data from meteorological
satellites and anomaly information of these
satellites.
• Standardization of space weather data and its
processing (including calibration method) is
also important issue to be discussed.
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Inter-calibration
0.1-0.2MeV
0.35-0.6MeV
13UT
• Particle data obtained from
each satellite should be
compared during the same
drift shell (L*).
• What magnetospheric
model should we use?
• How do we interpolate the
differential flux of specific
energy for comparison?
0.2MeV
13UT
0.45MeV
23UT
23UT
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This assumption
may not be good.
Diff. Flux more
than 2 MeV
significantly
decrease.
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