European Space Weather Week – ESWW#14 Northern scintillations characteristics and impact on SBAS behavior: EGNOS case R. Chaggara(*), C. Paparini (*), U. Ngayap(**), B. Duparc(*), S.M. Radicella(***), L. Ciraolo(***) (*) European Satellite Services Provider (ESSP-SAS) (**) ABBIA GNSS Technologies (***)ICT4D Laboratory / International Center for Theoretical Physics (ICTP) European Space Weather Week – ESWW#14 27th November – 1st December 2017 Ostend, Belgium 30/11/2017 ESSP-MEMO-20929

Table of Contents Introduction Space Weather and EGNOS RIMS behaviour and Space Weather AATR: time and space correlation analysis Final considerations 30/11/2017

Ionospheric activity at different latitudes North (~above 60N) impact of geomagnetic activity Auroral scintillations Middle latitudes (30-60N) South (~below 35N) Higher values of TEC/high TEC gradients Equatorial scintillations 30/11/2017

Space weather and EGNOS performance (1) Impact on the availability of GPS/GEO measurements and data Impact on ground station measurements quality and validity (Typ. Scintillations) Triggering of barriers and consistency checks 30/11/2017

Space weather and EGNOS performance (2) Northern Scintillation is the phenomena that impacts EGNOS performance the most (in terms of occurrences) Main observation consists on the loss of GPS L2 signal on many high latitude ground stations. The lack of observable deprives the processing facility from the computation of the ionosphere delay with consequence on both ionosphere and satellite monitoring. IGP monitoring is more concerned than SV monitoring which is only (slightly)impacted during severe episodes. Increased phase noise (C/No) that will lead to increased noise in the results. 30/11/2017

Space weather and EGNOS performance (3) SBAS has to remain safe under disturbed ionosphere conditions: Needs for barriers at different system levels. 30/11/2017

Northern latitudes stations reception quality is mainly affected during high geomagnetic activity: increased L2 signal loss Relationship between geomagnetic activity and the average rate of L2 losses for some northern stations located above 69°N (Svalbard, Jan Mayen, Kirkenes and Tromsoe) since 2014 30/11/2017

In-house ionosphere parameters computations Slant TEC (Total Electron Content) can be computed from the integral path of the Ne  (Electron density - electrons/m3), and S is the distance along the propagation path (m). Extracted from RIMS stations (TEC Cal. Technique) measure of the slant TEC in the ionosphere along the propagation direction of the beam. 𝑇𝐸𝐶= 𝑧 𝑁𝑒 𝑑𝑠 (TECU) 𝑇𝐸𝐶= 1 40.3 ( 𝑓1 𝑓2 𝑓1 −𝑓2 ) (P2-P1) ROT (Rate of change of TEC) and ROTI (ROT index) 𝑅𝑂𝑇= 𝑆𝑇𝐸𝐶(𝑘+1)−𝑆𝑇𝐸𝐶(𝑘) 𝑡𝑖𝑚𝑒(𝑘+1)− 𝑡𝑖𝑚𝑒(𝑘) 𝑅𝑂𝑇𝐼= < 𝑅𝑂𝑇 2 >− <𝑅𝑂𝑇> 2 Ref. X. Pi, A. J. Mannucci, U.J. Lindqdwister, C.M. Ho, “Monitoring of Global Ionospheric Irregularities using the worldwide GPS,” Geophysical Research Letters, 24, (18), 2283-2286. Doi/10.1029/97GL022732007. 𝐴𝐴𝑆𝑅𝑖= ∆𝑆𝑇𝐸𝐶 ∆𝑡 AATRi = ∆𝑆𝑇𝐸𝐶 (𝑀 𝜀 ) 2 ∆𝑡 = 𝐴𝐴𝑆𝑅𝑖 (𝑀 𝜀 ) 2 AATR = 1 𝑁 𝐴𝐴𝑇𝑅𝑖 2 Calculated AATR (Arc-Along TEC Rate) Ref. J.M. Juan, J. Sanz, M. Hernandez-Pajares, R. Prieto and S. Schlueter. “New Indicator for Definition of Ionospheric Operational Conditions”. SBAS IONO Working Group. Bath (UK), July 2013. 30/11/2017

AATR/L2 Loss probability evolution Tromso Station 2014 AATR/L2 Loss probability evolution Tromso Station for February/March 2014 30/11/2017

AATR/L2 Loss probability evolution Tromso Station 2014 AATR/L2 Loss probability evolution Tromso Station for October/November 2014 30/11/2017

2015 AATR indicator evolution TRO - 15th/16th/17th/18th/19th/20th/21st/22nd/23rd March 2015 17/03/2015 19/03/2015 18/03/2015 30/11/2017

AATR indicator evolution on 17th March 2015 RIMS LYR/KIR/TRO/EGI/RKK 30/11/2017

Space weather vs EGNOS performance Typical impact on APV-1 Availability (St. Patrick Storm March 2015) March 16 2015 March 15 2015 March 17 2015 March 18 2015 30/11/2017

Tromso Station on 17th March 2015 C/No time evolution Tromso Station on 17th March 2015 TRO - PRN 14 TRO - PRN 20 TRO - PRN 31 30/11/2017

Ground stations behavior analysis High correlation between AATR parameters and RIMS L2 tracking capability has been observed Other factors such as C/N0 drive the risk of loosing the signal tracking (mainly L2 signal). AATR between 0.8 and 1 could be considered as harmful to ground station tracking performance. 30/11/2017

AATR correlation analysis (1) For some stations, it has been observed that individual AATR evolution exhibits large day to day variation (regardless the level of SW disturbance) Auto-Correlation based analysis provide more refined characterization of the experienced ionosphere conditions. 30/11/2017

AATR correlation analysis The goal is to characterize the AATR behavior in terms of auto-correlation to better understand the ionosphere variability. Different ground stations has been investigated to reflect the latitude dependency The auto-correlation is computed over 24 hours as the following 𝑅(𝑘)= 1 𝑁 𝑛=1 𝑁 𝐴𝐴𝑇𝑅 𝑛 . 𝐴𝐴𝑇𝑅(𝑛+𝑘) 𝑅 𝑁 (𝑘)= 𝑅(𝑘) ⁡𝑚𝑎𝑥 (𝑅) 𝑅 𝑁 stands for the Normalized Auto correlation AATR function computed each 30 seconds N reflects the number of AATR samples over 24h =2880 samples AATR values for two days are used to produce the daily auto-correlation 30/11/2017

AATR correlation analysis The shape of the auto correlation function shows high consistency for Toulouse station (AATR derived mainly by sun exposure) Situation changes dramatically with Tromsoe station (the AATR shows quite unpredictable behavior) 30/11/2017

AATR correlation analysis (2) Average 24 hours autocorrelation was computed over one year (2014) data for four stations Toulouse (43N, 1 E) Gavle (60N, 17 E) The 95% and 5% envelopes provide indication on the autocorrelation discrepancy Results for High latitude suggests high discrepancy with Flat (near-zero) average auto correlation High latitudes AATR shows higher variability than for mid-latitudes Time of day dependency is more pronounced for mid-latitude stations Tromsoe(69N, 18 E) Longyearbyen (78N, 15 E) 30/11/2017

AATR correlation analysis (3) Time period over which the AATR auto correlation level remains higher than 0.8 (and 0.5) with 95% confidence has been estimated Station Correlation above 0.8 Correlation above 0.5 Toulouse 41 minutes 1 hour and 25 minutes Gavle 26 minutes 50 minutes Tromsoe Longyearbyen 21 minutes 30/11/2017

AATR correlation analysis (4) Cross-correlation between different stations has been also computed (on month data) Mid-Latitude stations shows quite moderate to high cross-correlation Extreme north station (LYR 79N) exhibits low cross-correlation with other stations. 30/11/2017

Final considerations Insight on EGNOS ground station response to northern scintillations has been discussed. Northern stations are the most impacted with disturbance observed out of the Solar cycle episode. High correlation between AATR parameters and RIMS L2 tracking capability has been observed. Based on correlation analysis; it is confirmed that the ionosphere conditions show in general high time and space variability over high latitudes (above ~65N). This study confirms that ionosphere prediction over these locations is much more complex than from mid-latitudes. NO integrity issue either on pseudorange or in the user domains have been observed nor reported for all the events. 30/11/2017

thank you! www.essp-sas.eu claudia.paparini@essp-sas.eu http://egnos-user-support.essp-sas.eu egnos-helpdesk@essp-sas.eu +34 911 236 555 (H24/7) 30/11/2017