Recent progress of NICT ionospheric observations in Japan

Transcription

1 Recent progress of NICT ionospheric observations in Japan T. Tsugawa, M. Nishioka, H. Kato, H. Jin, and M. Ishii National Institute of Information and Communications Technology (NICT), Japan

2 NICT ionospheric observation network Domestic network SEALION Poster: P-36

3 HF Transequatorial Propagation (HF-TEP) Experiments Eastward drift plasma bubble [Maruyama and Kawamura, AG, 2006] Poster: P-35,36 Illustration of how TEP propagation with multiple side-reflection because of tilted reflector and eastward-drifting upwelling. [Tsunoda et al., JGR, in press.]

4 GNSS total electron content observation GEONET GNSS Receivers operated by GSI, Japan TEC ROTI Loss-of-lock on GPS Quasirealtime ~1300 stations 1-2 hours Plasma buble Realtime 200 stations < 10 min Regional and Global GNSS-TEC observations based on GTEX format and international data sharing. Poster: P-32

5 Future plan: data assimilation Regional and global ionospehric observations GAIA and regional high-resolution model Expanding observation area Data Assimilation Difficult to detect iono. disturbances over the ocean Ionospheric disturbances can be detected even over the ocean.

6 Some of recent progress Replacing domestic ionosondes (10C VIPIR2) New ionospheric storm scales based on longterm ionospheric data for real-time warning system. Forecast model of TEC over Japan using a machine learning technique. Poster: P-30 GNSS-TEC exchange format (GTEX) has been included in ITU-R SG 3 Databanks. Poster: P-32

7 Domestic ionosonde observations Ionosonde observations in Japan started in Routine observations has been operated since Near real-time observations at four ionosondes in Japan (Wakkanai, Kokubunji, Yamagawa, Okinawa) and one ionosonde in Syowa base, Antarctica. Observations routinely every 15 min (up to 1 min in special observations). Automatically- and manuallyscaled ionospheric parameters are derived with several minutes and a few months delay, respectively.

8 Replacing domestic ionosondes 10C VIPIR2 Tx Tx/Rx Rx Major Improvements Digital signal processing for precise mixing and filtering 8ch Rx antenna array for O-X mode separation in ionogram 16 bit sampling for greater dynamic range Lower power consumption

9 Ionosonde specification (for Japanese Routine Observation) 10C VIPIR2 Method Single pulse Single pulse Observation mode Vertical/oblique Vertical/oblique Ave./Peak Tx power 80W / 10kW 32W / 4kW Frequency rage 1-30 MHz 1-30 MHz Observing height km km Intensity resolution 8 bit 16 bit Observing interval Routine: 15 minutes Special: 1 min Sweeping time ~15 sec ~15 sec Routine: 15 minutes Special: TBD Pulse repeating rate 50, 100 Hz Hz (<250 Hz) Tx 1 ch 1 ch Rx 2 ch 8 ch

10 Current status and future plan Comparing ionograms between 10C and VIPIR2 for calibration. Routine observations by VIPIR2 will start in Improving ionogram autoscaling method. 10C VIPIR2 Raw image Noise reduction by Wavelet transform and 2D low-pass filter Detect traces and remove multi-hop echoes Choose most probable traces Check parameters if they are reasonable or not Estimate ionospheric parameters Ionogram autoscaling method

11 Current status and future plan Bistatic observations between NICT (Japan) and KSWC (Korea) using VIPIR2 are planed. Oblique ionogram Vertical ionogram

12 A new ionospheric storm scale: I-scale TEC in the Japanese sector during the St Patrick s day storm Observation median of 27 days Ionospheric storms have no clear definition. Ionospheric parameters largely depend on local time, season, and latitude. Positive storm Negative storm It is necessary to investigate the ionospheric parameters statistically in order to define an universal ionospheric scale.

13 Number of Samples Data Set Data set and methodology 15-minute TEC for 18 years from 1997 to 2014 (TEC obs ). Methodology Ionospheric activity index (AI) is used to describe ionospheric state [e.g. Bremer et al., 2006]. Distribution of AI (29 o N, May-Jul, 20JST) σ=0.21 AI= TEC obs -TEC ref TEC ref The reference value, TEC ref is defined as a median of TEC obs at the same local time and latitude in the past 27 days. Distribution of AI is investigated to determine an ionospheric storm scale. AI 4 (samples/hour) x 90 (days) x 18 (years) =6480 samples

14 Number of Samples Distribution of AI Distribution of AI (29 o N) (a) May-Jul, 20JST (b) Feb-Apr, 20JST (c) Feb-Apr, 12JST σ=0.21 σ=0.34 σ= % 53% 62% AI The distribution of AI largely depends on season and local time. standard deviation σ:(a)june solstice<(b)march Equinox (b)night time>(c) Day time Occurrence rates of the situation that AI <0.2 are different among season/local time. It is difficult to use normal AI as an universal ionospheric scale. AI AI

15 Number of samples Normalized AI (a) May-Jul, 20JST (b) Feb-Apr, 20JST (c) Feb-Apr, 12JST 72% 76% 71% Normalized AI Normalized AI Normalized AI The dependence of AI distribution on season/local time /latitude can be mitigated by normalizing AIs by each standard deviation σ. An universal ionospheric scale should be determined using the normalized AI.

16 Number of samples I N 3 (4) A new ionospheric scale: I-scale I N 2 (170) I N 1 (2242) I0 I P 1 (2840) I P 2 (175) I P 3 (17) I-scale (Number of events with a duration of 2h or more) Occurrence rates (every 15min)(%) Positive storm scale I P 1: 1σ~3σ I P 2: 3σ~5σ I P 3: 5σ> Negative storm scale I N 1: -1σ~-2σ I N 2: -2σ~-3σ I N 3: -3σ< Normalized AI( all season, all LT at 37 o N) I-scale does not depend on season/lt/latitude.

17 List of top I P 3 events Date Normalized AI AI [%] Duration [hour] K index DST (11JST) (19JST) (10JST) (19JST) (21JST) (13JST) ( 6JST) (19JST) AGU storm Halloween storm

18 The extreme I P 3 event TEC obs reached ten times larger than TEC ref. The extremely enhanced TEC would be caused by storminduced plasma stream (SIPS) [Maruyama et al., 2013].

19 Number of Smaples St. Patrick s event P2 Scale Normalized AI=3.2, AI=105% The 191th positive storm since N2 Scale Normalized AI=-2.7, AI=-65% The 7 th negative storm since 1997 N3 N2 N1 P1 P2 P3 Positive storm Negative storm Normalized AI (all season, all o N)

20 Geogra. Lat. Forecast model of TEC over Japan using a machine learning technique Data available on realtime bases Quiet model Sun F10.7, SSN MgII Time DOY Iono. Previous-day TEC Disturbed Model Iono. Q-model output SW IMF-Bt Mag. K-index, Dst Input 7000-day data from 1997 年 were used Hidden Quiet Model Output A 00 A Observation Q-model 2D TEC map against latitude and local mean time, which is represented by 36 coefficients of the surface harmonics function. B 77 May 24-25, 2014 Local Mean Time Disturbed Model --- Observation --- Q-model --- D-model 2016

21 Summary Some of recent progress of NICT ionospheric observations were introduced. - Replacing domestic ionosondes (10C VIPIR2) - A new ionospheric storm scale: I-scale - Some new findings by SEALION and HF-TEP P-35, 36 - Forecast model of TEC over Japan P-30 - GNSS-TEC exchange format (GTEX) P-32 We are replacing all the domestic ionosondes with VIPIR2. Their routine observations will start in Bistatic observations between NICT and KSWC using VIPIR2 are planed. A new universal ionospheric storm, I-scale, has been developed based on statistical analysis of 18-year TEC data. It would be needed to investigate a correlation between I- scales and damages for the practical users.