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

NICT ionospheric observation network

SEALION

Poster: P-36

Domestic

network

HF Transequatorial Propagation (HF-TEP) Experiments

[Maruyama and Kawamura, AG, 2006]

plasma bubble

Eastward drift

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.]

GEONET GNSS Receivers operated by GSI, Japan

GNSS total electron content observation

TEC ROTI Loss-of-lock on GPS

~1300 stations

Plasma buble

Quasi-realtime

1-2 hours

200 stations

Realtime

< 10 minRegional and Global GNSS-TEC observations based on GTEX format and international data sharing.

Poster: P-32

Future plan: data assimilationGAIA and regional high-resolution modelRegional and global ionospehric observations

Expanding observation area

Data Assimilation

Difficult to detect iono. disturbances over the ocean

Ionospheric disturbances can be detected even over the ocean.

• Replacing domestic ionosondes(10C → VIPIR2）

• New ionospheric storm scales based on long-term 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

Some of recent progress

• Ionosonde observations in Japan started in 1937.

• Routine observations has been operated since 1957.

• 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 manually-scaled ionospheric parameters are derived with several minutes and a few months delay, respectively.

Domestic ionosonde observations

• 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

Replacing domestic ionosondes

10C

Tx/Rx

VIPIR2

Tx

Rx

Major Improvements

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 60-1500km 60-1500km

Intensity resolution 8 bit 16 bit

Observing intervalRoutine: 15 minutes Special: 1 min

Routine: 15 minutes Special: TBD

Sweeping time ~15 sec ~15 sec

Pulse repeating rate 50, 100 Hz 50-100 Hz (<250 Hz)

Tx 1 ch 1 ch

Rx 2 ch 8 ch

Ionosonde specification (for Japanese Routine Observation)

Current status and future plan• Comparing ionograms between 10C and VIPIR2 for calibration.

• Routine observations by VIPIR2 will start in 2017.

• Improving ionogram autoscaling method.

10C VIPIR2

Ionogram autoscaling method

Raw imageNoise reduction by

Wavelet transform

and 2D low-pass

filter

Detect traces

and remove

multi-hop echoes

Choose most

probable traces

Estimate ionospheric

parameters

Check parameters if

they are reasonable or

not

Current status and future plan

• Bistatic observations between NICT (Japan) and KSWC (Korea) using VIPIR2 are planed.

Oblique ionogram

Vertical ionogram

A new ionospheric storm scale: I-scale

Ionospheric storms have no clear definition.

Ionospheric parameters largely depend on local time, season, and latitude.

It is necessary to investigate the ionospheric parameters statistically in order to define an universal ionospheric scale.

TEC in the Japanese sectorduring the St Patrick’s day storm

Observation median of 27 days

Positive storm Negative storm

Ionospheric activity index (AI) is used to describe ionospheric state [e.g. Bremer et al., 2006].

AI=

15-minute TEC for 18 years from 1997 to 2014 (TECobs).

Data set and methodology【Data Set】

【Methodology】

The reference value, TECref is defined as a median of TECobs at the same local time and latitude in the past 27 days.

Distribution of AI is investigated to determine an ionospheric storm scale.

TECobs-TECref

TECref

AI

Nu

mb

er

of

Sam

ple

s

σ=0.21

Distribution of AI(29oＮ, May-Jul, 20JST)

4 (samples/hour) x 90 (days) x 18 (years) =6480 samples

Distribution of 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

Nu

mb

er

of

Sam

ple

s σ=0.21 σ=0.34 σ=0.26

(a) May-Jul, 20JST (b) Feb-Apr, 20JST (c) Feb-Apr, 12JST

69% 53% 62%

Distribution of AI (29oＮ)

AI AI

(a) May-Jul, 20JST (b) Feb-Apr, 20JST (c) Feb-Apr, 12JST

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.

Normalized AI

Nu

mb

er

of

sam

ple

s 71%72% 76%

Normalized AI Normalized AI

A new ionospheric scale: I-scale

Normalized AI( all season, all LT at 37oN)

Nu

mb

er

of

sam

ple

s

Positive storm scaleIP1: 1σ~3σIP2: 3σ~5σIP3: 5σ>

Negative storm scaleIN1: -1σ~-2σIN2: -2σ~-3σIN3: -3σ<

IN1

(2242)

IN2

(170)

IN3

(4)

IP1

(2840)

IP2

(175)

IP3

(17)

Occurrence rates（every 15min）（%）

I-scale（Number of events with a

duration of 2h or more)

I-scale does not depend on season/LT/latitude.

I0

List of top IP3 events

Date Normalized AIAI

[%]Duration

[hour]K

indexDST

2004.11. 8 (11JST) 39.9 884 21 7 -374

2004.11.10 (19JST) 21.5 483 8 7 -263

2006.12.15 (10JST) 15.3 316 12 7 -157

2000. 2.12 (19JST) 11.0 315 10 6 -101

2003. 10.31 (21JST) 10.2 186 4 7 -356

1999.10.22 (13JST) 9.13 179 7 7 -223

1998. 9.26 ( 6JST) 8.02 151 2 7 -190

2015. 1 .7 (19JST) 7.88 173 6 6 -93

AGU storm

Halloween storm

The extreme IP3 event

TECobs reached ten times larger than TECref.

The extremely enhanced TEC would be caused by storm-induced plasma stream (SIPS) [Maruyama et al., 2013].

St. Patrick’s event

N2 ScaleNormalized AI=-2.7, AI=-65%The 7th negative storm since 1997

P2 ScaleNormalized AI=3.2, AI=105%

The 191th positive storm since 1997.

Normalized AI (all season, all LT @37oN)

Nu

mb

er

of

Sm

ap

les

N1

N2

N3

P1 P2 P3

Positive storm Negative storm

Forecast model of TEC over Japan using a machine learning technique

・

・

・・

・

・

・

・

・

Ａ00

Ａ20

B77

Input OutputHidden May 24-25, 2014

Local Mean Time

Geogra

. Lat.

2D TEC map against latitude and local mean time, which is represented by 36 coefficients of the surface harmonics function.

7000-day data from 1997年 were used

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

2016

------ Observation ------ Q-model

2016--- Observation --- Q-model --- D-modelQuiet Model

Disturbed Model

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 2017. Bistaticobservations 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.