1. Expert Meeting on Improving Space Weather Forecasting in the Next Decade 10 -11 February 2014 United Nations, Vienna, Austria Dr. Keith Groves Boston College, Chestnut Hill, MA USA keith.groves@bc.edu Space Weather and the Role of ISWI in the Development of the SCINDA Sensor Network

2. Outline Motivation: Impacts on Space-based RF Systems SCINDA Sensors and Model The Role of the ISWI in the Development of SCINDA Scientific Context and Need 2 Lessons Learned by an Instrument Provider Summary From C. Mitchell, Univ of Bath Equatorial scintillation affects a large region encompassing many developing countries

3. Motivation Dual Frequency GPS Positioning Errors Scintillation causes rapid fluctuations in GPS position fix Typical night from solar maximum at Ascension Island Scintillation causes rapid fluctuations in GPS position fix Typical night from solar maximum at Ascension Island 3

4. SCINTILLATION NETWORK DECISION AID (SCINDA) 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 A regional nowcasting system to support research and users of space-based communication and navigation systems

5. Primary SCINDA GPS Sensor GPS Antenna GPS Receiver PRN 7 Scintillated GPS Signal 5

6. SCINDA Model VHF Groves, K.M., et al., Equatorial scintillation and systems support, Radio Sci., 32, 2047, 1997. Scintillation data collected in near real-time from global SCINDA network S 4 and ionospheric drift Smoothed data passed through Discrete Bubble Model (DSBMOD) Observed structures propagated with observed drift and decayed with empirical algorithm SCINDA Model Product Ascension Island, Nov. 2011 UHF S4 L-Band S4 Drift UHF S4 6

7. Data-Driven Scintillation Map Ionospheric Specification SCINDA User Product Example for 250MHz Watch Areas Scintillation Warning Areas UHF Scintillation 7

8. Typical Hardware Configuration cable out to antennas Shared Monitor VHF Computer GPS Computer VHF Receiver Internet / Local Network GPS Receiver KVM Switch Keyboard GPS Antenna West ReceiverEast Receiver 50-150 meters 2 meters RG9913 Coaxial Cable (180 meters max.) Magnetic E-W Baseline VHF (250 MHz) Receiver Chain and Data Acquisition System Antenna Layout Receivers Set-Up

9. SCINDA Sensor Locations Kirtland Villegas Roatan Bogota, Apiay Piura Ancon Antofagasta Santarem, Parintins Sao LuisIquitos Cuiaba Cachoeira Paulista Corrientes Cape Verde Butare Dakar Helwan Qatar Akure, Lagos, Ile-Ife, Ilorin, Nsukka, Yaounde, Sao Tome & Principe Brazzaville, Kinshasa Bahir Dar Djibouti Kampala, Maseno Nairobi Zanzibar East Timor Diego Garcia Rajkot Tirunelveli Calcutta Chiang Mai Bangkok Singapore Taipei Seoul Kwajalein Baguio Manila Christmas Island (AUS) Seychelles Christmas Island Haystack NC A&T Dayton Dourados Wahiawa Davao Guam Darwin Bahrain Addis Ababa Kisangani Ascension Island Abidjan Tefe Leoncito Santa Marta Puerto Maldonado Alta Floresta Santa Maria Boa Vista Belo Horizonte Brasilia Imperatriz Natal Petrolina Ilheus Hermanus 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 SCINDA = SCIntillation Network Decision Aid 9

10. 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

11. 2009 – Livingston, Zambia 116 delegates from 27 nations including 79 representing 19 African countries SCINDA/IHY Workshops: How we got here today ZAMBIA 2007 – Addis Ababa, Ethiopia ~50 participants from 12 nations at 2007 IHY in Ethiopia 2006 – Sal, Cape Verde 20 participants representing 7 nations 2010 – Nairobi, Kenya; Bahir Dar, Ethopia; Cairo, Egypt* * The beginning of ISWI 11

12. Science Issues Global Distribution of Irregularities 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 Satellite observations show that Africa and South America are active nearly year-round; activity peaks in these sectors 12

13. Longitudinal Variability Examine 250 MHz scintillation observations from three separate longitude sectors in 2011 13

14. Extreme Day-to-Day Variability ? 14 Occurrence dominated by seasonal factors Increase in solar flux evident in last quarter of the year Cuiaba, Brazil VHF 2011

15. Scintillation “Variability” in Cuiaba, Brazil 15 Variability is mostly seasonal, not daily Forecasting challenge akin to predicting seasonal transitions, e.g., monsoons in India Let’s check some other sites Probability of S4 > 0.6 for ≥ 1 hour

16. Scintillation Occurrence in W. Africa 16 Response looks pretty similar to Cuiaba Wet and Dry seasons Cape Verde VHF 2011

17. Probability of S4 > 0.3 Probability of S4 > 0.6 Cape Verde, West Africa 17 Occurrence suggests dominant mechanism(s); not dependent on GWs, tides, phase of the moon, nighttime ionization rate, etc.

18. Scintillation Occurrence in E. Africa 18 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 Nairobi, Kenya, VHF 2011

19. Probability of S4 > 0.3 Probability of S4 > 0.6 Nairobi, Kenya Variability 19 Variability exists throughout the year, even during the period of increased solar flux in the last quarter of 2011

20. Kwajalein Scintillation 20 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 Kwajalein Atoll VHF 2011

21. Probability of S4 > 0.3 Probability of S4 > 0.6 Kwajalein Variability 21

22. Christmas Island 22 Overall pattern similar to Kwajalein Decrease in severity may be magnetic latitude effect (1° vs 4°) Christmas Island, Kiribati VHF 2011

23. Christmas Island Variability 23 Probability of S4 > 0.3 Probability of S4 > 0.6 Highly variable Severity further decreased, probably due to mag lat effects

24. 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) 24 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

25. Is it all about “B”? If seeds and tropospheric forcing are not critical, what’s left? Consider equation for RTI linear growth rate 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 25

26. Key Elements for Developing a Successful Sensor Network in Remote Locations Develop robust low cost sensor 26 Identify responsible site hosts and support sensor deployment Conduct educational workshops and training for sensor and related science 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 90% below the surface P.S. And don’t be easily discouraged Lessons Learned

27. Summary SCINDA addresses space weather phenomena that affect low- latitudes and are typically not associated with impulsive solar events—the dynamics are dominated by internal ionosphere- thermosphere 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

28. Way Ahead Programmatically speaking, SCINDA is presently at a cross- roads 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 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