Space Weather and the Role of ISWI in the
Development of the SCINDA Sensor Network
Dr. Keith Groves
Boston College, Chestnut Hill, MA USA
keith.groves@bc.edu
Expert Meeting on Improving Space Weather Forecasting in the Next Decade
10 -11 February 2014
United Nations, Vienna, Austria
Outline
• Motivation: Impacts on
Space-based RF Systems
From C. Mitchell, Univ of Bath
• SCINDA Sensors and
Model
• The Role of the ISWI in the
Development of SCINDA
• Scientific Context and
Need
• Lessons Learned by an Instrument Provider
• Summary
Equatorial scintillation affects a large region
encompassing many developing countries
2
Motivation
Dual Frequency GPS Positioning Errors
Scintillation causes rapid fluctuations in GPS position fix
Typical night from solar maximum at Ascension Island
3
SCINTILLATION NETWORK DECISION AID
(SCINDA)
A regional nowcasting system to support
research and users of space-based
communication and navigation systems
• Ground-based sensor network
− Passive UHF / L-band /GPS
scintillation receivers
− Measures scintillation intensity,
eastward drift velocity, and TEC
− Automated real-time data
retrieval via internet
• Data supports research and
space weather users
− Understand on-set, evolution and
dynamics of large-scale
ionospheric disturbances
− Empirical model provides
simplified visualizations of
scintillation regions in real-time
Primary SCINDA GPS Sensor
GPS Antenna
GPS Receiver
Scintillated GPS Signal
PRN 7
5
SCINDA Model Product
VHF
Ascension Island, Nov. 2011
SCINDA Model
•
Scintillation data collected in near
real-time from global SCINDA
network
UHF S4
•
S4 and ionospheric drift
L-Band S4
•
Smoothed data passed through
Discrete Bubble Model (DSBMOD)
•
Observed structures propagated
with observed drift and decayed
with empirical algorithm
UHF S4
Drift
Groves, K.M., et al., Equatorial scintillation and
systems support, Radio Sci., 32, 2047, 1997.
6
Data-Driven Scintillation Map
Ionospheric Specification
SCINDA User Product Example for 250MHz
Scintillation
Warning Areas
Watch Areas
UHF Scintillation
7
Typical Hardware Configuration
Antenna Layout
50-150 meters
75 – 150 meters
2 meters
West Receiver
2 meters
East Receiver
Magnetic E-W Baseline
Shared
Monitor
Figure1. SCINDA VHF Antenna Set-Up
RG9913 Coaxial Cable
(180 meters max.)
cable out to
antennas
VHF Receiver
KVM
Switch GPS
Keyboard
Receiver
GPS
Antenna
Internet /
Local
Network
VHF (250 MHz) Receiver Chain and
Data Acquisition System
Figure 2. SCINDA VHF (250 MHz) Receiver Chain and Data Acquisition
System
VHF
Computer
GPS
Computer
Receivers Set-Up
SCINDA Sensor Locations
SCINDA = SCIntillation Network Decision Aid
• Approximately 75 low latitude sites
– Including about two dozen from Low Latitude Ionsopheric Sensor Network (LISN)
• Several mid-to-high latitude sites for research purposes
Akure, Lagos, Ile-Ife,
Ilorin, Nsukka, Yaounde,
Sao Tome & Principe
Kirtland
Dayton
Haystack
Seoul
NC A&T
Helwan
Bahrain
Qatar
Wahiawa
Roatan
Christmas Island
Cape Verde
Santa Marta
Bogota,
Apiay
Boa Vista
Iquitos
Piura
Imperatriz
Alta Floresta
Ancon
Dakar
Santarem,
Parintins
Sao Luis
Tefe
Abidjan
Kisangani
Rajkot
Addis Ababa
Natal
Brazzaville,
Petrolina Ascension IslandKinshasa
Ilheus
Taipei
Chiang Mai
Bangkok
Djibouti
Tirunelveli
Nairobi
Puerto Maldonado
Antofagasta
ZanzibarSeychelles Diego Garcia
Baguio
Manila
Guam
Kwajalein
Davao
Singapore
East Timor
Christmas Island
(AUS)
Darwin
Brasilia
Cuiaba
Leoncito
Bahir Dar
Calcutta
Belo Horizonte
Cachoeira Paulista
Villegas
Dourados
Santa Maria
Hermanus
Kampala,
Maseno
Butare
Corrientes
9
The Role of IHY/ISWI in SCINDA Expansion
• After 2003 the SCINDA team recognized that the lack of data
from Africa created a serious gap in our knowledge of global
low-latitude scintillation—SCINDA needed Africa
• Attended the UAE Workshop in 2005 at the invitation of Joe
Davila and made first contact with potential site hosts
• A series of workshops and exchanges followed rapidly under
the auspices of the IHY and ISWI programs; ~20 new sites
were established in a 5 year period
• The timing and opportunities afforded by the IHY/ISWI program
contributed substantially to the success of the SCINDA
program in fielding sensors and maintaining community
10
SCINDA/IHY Workshops:
How we got here today
2006 – Sal, Cape Verde
• 20 participants representing 7 nations
2007 – Addis Ababa, Ethiopia
• ~50 participants from 12 nations
at 2007 IHY in Ethiopia
2009 – Livingston, Zambia
• 116 delegates from 27 nations
including 79 representing 19
African countries
2010 – Nairobi, Kenya; Bahir Dar,
Ethopia; Cairo, Egypt*
* The beginning of ISWI
ZAMBIA
11
Science Issues
Global Distribution of Irregularities
Satellite observations show that
Africa and South America are
active nearly year-round; activity
peaks in these sectors
• We need ground-based
observations to understand more
detail about scintillation
characteristics and irregularities
• From scintillation sensors we find
that Africa (and Pacific) exhibit
significant variability relative to the
American sector
• The question is Why?
Adapted from S.Y. Su, 2005
12
Longitudinal Variability
Examine 250 MHz scintillation observations from three
separate longitude sectors in 2011
13
Extreme Day-to-Day Variability ?
Cuiaba, Brazil VHF 2011
• Occurrence dominated by seasonal factors
• Increase in solar flux evident in last quarter of the year
14
Scintillation “Variability” in Cuiaba, Brazil
Probability of S4 > 0.6 for ≥ 1 hour
• Variability is mostly
seasonal, not daily
• Forecasting challenge
akin to predicting
seasonal transitions,
e.g., monsoons in
India
• Let’s check some
other sites
15
Scintillation Occurrence in W. Africa
Cape Verde VHF 2011
• Response looks pretty similar to Cuiaba
• Wet and Dry seasons
16
Cape Verde, West Africa
Probability of S4 > 0.3
Probability of S4 > 0.6
• Occurrence suggests dominant mechanism(s); not dependent on
GWs, tides, phase of the moon, nighttime ionization rate, etc.
17
Scintillation Occurrence in E. Africa
Nairobi, Kenya, VHF 2011
• Region shows a lot of activity, much of it severe
• Fundametal shift in local time of onset during June/July
• Data appears to show more variability than American sector
18
Nairobi, Kenya Variability
Probability of S4 > 0.3
Probability of S4 > 0.6
• Variability exists throughout the year, even during the period of
increased solar flux in the last quarter of 2011
19
Kwajalein Scintillation
Kwajalein Atoll VHF 2011
• Variability exists throughout the year, but average severity is
markedly less than in Nairobi
• Part of the difference in severity may be attributable to mag lat
20
Kwajalein Variability
Probability of S4 > 0.3
Probability of S4 > 0.6
21
Christmas Island
Christmas Island, Kiribati VHF 2011
• Overall pattern similar to Kwajalein
• Decrease in severity may be magnetic latitude effect (1° vs 4°)
22
Christmas Island Variability
Probability of S4 > 0.3
Probability of S4 > 0.6
• Highly variable
• Severity further decreased, probably due to mag lat effects
23
Factors Contributing to Spread F
What about “seeds”?
• Region of low variability characterized by significant (> ~5°)
westward declination and relatively low B-field strength
• Variability usually associated with “seeds” (e.g., gravity waves)
x Gravity wave activity cannot be a critical factor (no rationale for
differences in AGW activity across such a range of longitudes/land
mass/ocean environments)
x Non-migrating tides (i.e., classic 4-cell pattern) cannot be a critical
factor since low variability region encompasses both maxima and
minima
x Large-scale tropospheric systems, such as the inter-tropical
convergence zone (ITCZ) cannot be factors since the low-variability
region encompasses a range of +/- latitudes
24
Is it all about “B”?
• If seeds and tropospheric forcing are not critical, what’s left?
• Consider equation for RTI linear growth rate

g
EB


U

n
2
eff
 B


F E
F
 1 N
 N h
• At all seasons, small |B| suggests larger growth rate for an
equivalent |E| (favorable to onset)
– Small |B| implies higher vertical drift which reduces collision frequency and
reinforces high growth rate
• Understanding the longitudinal differences in scintillation activity
may provide important insights into the critical processes
controlling equatorial Spread F occurrence-we need distributed
ground sensors to succeed
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Key Elements for Developing a Successful
Sensor Network in Remote Locations
Lessons Learned
• Develop robust low cost sensor
• Identify responsible site hosts and
support sensor deployment
90% below the surface
• Conduct educational workshops and
training for sensor and related science
P.S. And don’t be easily discouraged
• Operate and maintain site at remote
location; maintenance costs may
include improving infrastructure
(power, network, climate control, etc.)
• Raise funds for all of the above while
receiving spotty data from the majority
of sites
26
Summary
• SCINDA addresses space weather phenomena that affect lowlatitudes and are typically not associated with impulsive solar
events—the dynamics are dominated by internal ionospherethermosphere coupling in the absence of external forcing
• Some longitude sectors exhibit more true variability than others
and understanding this may provide insight into the relative
importance of various processes in the on-set of Spread F
• The expansion of SCINDA and the IHY/ISWI were synergistic
activities that benefited mutually: Scientific necessity drove the
motivation and ISWI provided the opportunity and means
• Developing a sensor network in challenged environments can
be frustrating and requires extensive follow-on support after
the sensor is obtained…but it can be very rewarding!
• Success is an on-going achievement
27
Way Ahead
• Programmatically speaking, SCINDA is presently at a crossroads
• The Air Force Weather
Agency has decided to make
some locations (8-10) fully
operational; these will no
longer be under the purview
of AFRL
• The status and support of the remaining sites is TBD at
present
• Future plans and opportunities are contingent on the
resolution of the these issues, hopefully clarified within the
next 3-6 months
28