The Potential of Galileo Inter-Satellite Ranging for Tropospheric Monitoring

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Johannes Böhm 1, Michel Tossaint 3 1 Department of Geodesy and Geoinformation, TU Wien, Austria, 2

1 The Potential of Galileo Inter-Satellite Ranging for Tropospheric Monitoring Gregor Möller 1, Fabian Hinterberger 1, Robert Weber 1, Philipp Berglez 2, Lakshmi Privy Sevuga Vijayakumara 2, Janina Boisits 1, Johannes Böhm 1, Michel Tossaint 3 1 Department of Geodesy and Geoinformation, TU Wien, Austria, 2 TeleConsult Austria GmbH, Graz, Austria, ³ ESA / ESTEC, Noordwijk, The Netherlands ESTEC, Noordwijk, 21 st of February, 2017

2 Overview 1. Galileo constellation (MEOs, IGSOs and satellites on transfer) 2. Transit events when ISR signals enter the neutral atmosphere 3. Impact case study (without/with simulated ISR) 4. Requirements / Conclusions 2

3 Constellation 1. MEO satellites We have simulated three different Galileo MEO constellations (24, 27 and 30/3/1 ) for one year (2014) Precise orbits files were used to compute the Keplerian elements for satellite E19 (IOV-3) over the whole period 2014 Then the Keplerian elements of the other MEO satellites were computed wrt. satellite E19 Lagrange interpolation was applied to the ECEF coordinates to increase the sampling rate to 1 sec 3

4 Constellation 2. MEO spare Simulation of one additional MEO spare satellite in order to complement the 24/3/1 constellation and to install a permanent link in the same orbital plane. 4

5 Constellation 3. IGSO satellites Four elliptical inclined geosynchronous orbits (IGSO) were simulated with two ground tracks and two satellites per ground track centered at 10 W and 10 E for the period 2014, assuming stable nodes for the entire period. 5

6 Constellation 4. Satellite in transfer orbit Simulation of a satellite in transfer orbit from LEO to MEO in 395 days by series of circular orbits with trusts perpendicular to the satellite position vector (satellite raised to MEO orbit). Injection inclination 56 Injection altitude 1000 km Thrusts 54e-6 m/s^2 Ω drift

7 Transit events Definition of a transit event An event is detected when the path of the ISR signal approximates the Earth closer than 40 km (neutral atmosphere). One event is counted as long as the ISR signal remains in the atmosphere (0 km < Mc < 40 km). 7

MEO satellites 4 different types of transit events per satellite Duration: sec - min Path geometry

8 Transit events MEO-MEO (24/3/1 constellation ) Satellites in plane 1: E01, E04, E07, plane 2: E02, E05, E08, plane 3: E03, E06, E09, Graphic shows the number of the transit events per year between MEO satellites 4 different types of transit events per satellite Duration: sec - min Path geometry for all MEO satellite pairs Period: 5 th Jan 2014 Covered region: 10 to 50 lat band in both hemispheres 8

9 Transit events MEO-IGSO Number of the transit events per year between 24 MEO and 4 IGSO satellites Events change permanently, drift westwards Duration: in 90% sec - min Path geometry for all MEO/IGSO satellite pairs Period: GPSweek 1774 Covered region: globally (east and west of the ground track) 9

Screening of a defined atmospheric layer The transit events for the MEO/MEOspare satellite

10 Transit events MEO-MEOspare Transit event for the MEO/MEOspare satellite pair in the same orbital plane = permanent event Period: 4 th May 2014 Region: -50 to 50 lat band Option: Screening of a defined atmospheric layer The transit events for the MEO/MEOspare satellite pairs in different orbital planes Period: 4 th May 2014 Covered region: 3 bands between -50 and 50 lat 10

11 Transit events Transfer MEO Events per week between MEO satellites and a satellite in transit (GPSweek 1796) 11

12 Neutral atmosphere Expected ISR events over Europe (global), May 2014 MEO-MEO MEO-IGSO MEO-MEOspare Obs. type # Events per day ø Event duration Repeat cycle Vertical range MEO-MEO (~ 320) ~ 16 sec, no bend. 5 days 0 40 km MEO-IGSO (~ 110) sec min 5 days 0 40 km MEO-MEOspare continuously 10 days specific layer 12

13 Neutral atmosphere Special investigation: ISR MEO/MEO events at 4 May 2014 Voxel resolution: 1 x 1 horizontal 10 vertical layers blue: traversed parts of the neutral atmosphere 13

$refractivities [Wickert, 2002, GFZ] b) Process delays in a tomography$

14 Neutral atmosphere Processing strategy a) Convert delays into a profile of bending angles (radio occultation) Result: Vertical profiles of refractivities [Wickert, 2002, GFZ] b) Process delays in a tomography approach Result: Refractivity fields N N= f(pressure, temperature, water vapour) 14

15 Neutral atmosphere GNSS tomography Atmospheric structure (voxels) 1.0 x 1.0 spatial resolution 10 equidistant height layers (h = 0-40 km) Least Squares Adjustment (SVD) N = ( A ( A T T P A) P A) + + A T = V / S U P STD STD slant tropospheric delays [mm] A design matrix with ray paths [km] N refractivity field [ppm] P observation weights S diagonal matrix of eigenvectors (EV) Background dataset Slant Tropospheric Delays (STD) from 71 European GNSS sites 15

$5 a) a priori model (standard atmosphere) b) STDs derived from ground based GPS+GLO observations (background dataset) c) simulated ISR delays Output: improved refractivity fields with and$

16 Neutral atmosphere GNSS tomography Input: N [ppm] derived from STDs + ISR delays, lat:41.5, lon:20.5 a) a priori model (standard atmosphere) b) STDs derived from ground based GPS+GLO observations (background dataset) c) simulated ISR delays Output: improved refractivity fields with and without ISR delays Validation: comparisons with a) operational ECMWF analysis data and b) GNSS ZTDs 16

$MEO/MEO event ORID ISR provides precise vertical infomation about refractivity variations -> reduces refractivity bias (wrt.$

17 Neutral atmosphere GNSS tomography a) Validation with ECMWF data dn [ppm] (STD only) dn [ppm] (STD+ISR) ORID, 7 May 2014, 18 UTC Center points of MEO/MEO event ORID ISR provides precise vertical infomation about refractivity variations -> reduces refractivity bias (wrt. operational ECMWF data) 17

$Neutral atmosphere GNSS tomography b) Validation with GNSS ZTDs Vertical integration through the refractivity fields:$

18 Neutral atmosphere GNSS tomography b) Validation with GNSS ZTDs Vertical integration through the refractivity fields: PENC, 5 May 2014, 18 UTC MEO/MEOspare event ISR helps to stabilise the tomography solution and to reduce the ZTD error 18

19 ISR Requirements ISR requires cross-plane ranging (except for MEO-MEOspare) atmospheric losses in the ISR frequency range do not harm signal reception ISR delays and the reference ranges are quantified with adequate accuracy. The current goal for G2G satellite position quality is +/- 12 cm (reference range) ionospheric effect is mitigated (by models or dual frequency observations) S/C-band K-band 19

20 Conclusions If requirements can be fulfilled ISR provides: ~320 atmospheric MEO-MEO profiles/day in medium latitude bands IGSO-MEO ISRs allow to penetrate the atmosphere at all latitude bands; with obervation periods up to several minutes MEO-MEO spare constellations are able to monitor the atmosphere permanently between 50 S and 50 N ISR is adequate for long term analysis (e.g. to study recent changes in tropopause height) Combination with other observations (STD, RO) in a tomography approach allows to compute refractivity fields for a wider area (rather than vertical profiles) 20

21 References Use of Inter-Satellite Ranging for Troposphere Tomography and Ionosphere Monitoring, R. Weber, G. Möller, F. Hinterberger, P. Berglez, L. P. Sevuga Vijayakumar, S. Hinteregger, J. Böhm, ISR-Atmosphere final report, GNSS Evolutions Scientific and Innovative Technology Research, Announcement of Opportunity AO/2-1610/14/NL/CVG, July 2016, 209 pages G. Möller, F. Hinterberger, A. Hofmeister, R. Weber, M. Tossaint, The potential of Galileo Inter- Satellite Ranging for Atmospheric Research, 5th International Galileo Science Colloquium, October 2015 Thank you for your attention! Contact: Gregor Möller 21

We have processed RO data for climate research and for validation of weather data since 1995 as illustrated in Figure 1.

We have processed RO data for climate research and for validation of weather data since 1995 as illustrated in Figure 1. Real-time Analysis of COSMIC Data Christian Rocken, Doug Hunt, Bill Schreiner University Corporation for Atmospheric Research (UCAR) COSMIC Project Office Boulder, CO Abstract UCAR has analyzed GPS radio