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Using EOP and Space Weather Data for Satellite Operations

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Presentation on theme: "Using EOP and Space Weather Data for Satellite Operations"— Presentation transcript:

1 Using EOP and Space Weather Data for Satellite Operations
David A. Vallado and T. S. Kelso Analytical Graphics Inc. Center for Space Standards and Innovation Paper USR S7.3, Presented at the 6th US Russian Space Surveillance Workshop, St. Petersburg, Russia, August 22-26, 2005

2 Outline Introduction Analysis STK Files Summary Definitions Problem
Objectives Motivation Analysis EOP Space Weather STK Files Summary

3 Definitions Earth Orientation Parameters (EOP) Space Weather Data
Assist transformation between Celestial and Terrestrial Coordinate Frames Celestial – GCRF (generic ECI) Terrestrial – ITRF (generic ECEF) UT1, LOD, xp, yp, AT Space Weather Data Incoming solar radiation effects the atmosphere Geomagnetic kp, ap Eight 3-hourly and daily averages Solar radiation F10.7 Daily values Affects upper atmospheric temperature and density Large factor in determining atmospheric drag effect on satellite orbits

4 Problem EOP and space weather data needed to support tasks
Mission Design Fuel budgets Lifetime maneuver / orbit box planning Real-time Operations Few days into the future Mission planning a few months ahead Anomaly resolution a few months in the past Available data is “chaotic” at best Mix of predicted and observed values Post processing data often takes a month or more No synchronized update schedule for all parameters Need seamless file of data to accomplish each mission task

5 Objectives Analyze currently available data
Recommend best option for splicing data Discuss setup of data files Available on CelesTrak website STK compatible

6 Summary of EOP Data Files
IERS EOPC04.62-now (DUT1, xp, yp,, LOD, , , X, Y) 1962 00:00 USNO Finals.daily, Finals2000a.daily (DUT1, xp, yp,, , , X, Y) -3 months + 90 days USNO Finals.all, Finals2000a.all (DUT1, xp, yp) 1973 + 1 year NGA EOPPyddd.txt (DUT1, xp, yp) 00:00 Sunday 23:59 Saturday 14:28 PAST Current Time, T FUTURE

7 Summary of Space Weather Data Files
00:00 -1 month 00:00 1 month Current Year 00:00 yyyy.vm (daily F10.7, daily and 3 hrly kp, ap) Quar_dgd.txt (3 hrly kp, daily ap) Quar_dsd.txt (daily F10.7) - 3 months 45df.txt (daily F10.7, ap) + 45 days Predict.txt (monthly F10.7) - 6 months + 6 year 14:28 PAST FUTURE Current Time, T

8 I. EOP Data

9 Analyses Series are recomputed Comparisons Useful IERS USNO
Twice weekly Some smoothing due to use of Vondrak algorithm Removes high-frequency noise USNO Weekly ? Comparisons Useful Within Organizations Bulletin A and B ,  X , Y Between Organizations USNO, IERS, NGA Note that axes scales and units are not constant

10 Analysis USNO Bltn A and Bltn B values Reasonably consistent , 
Bull B values only from Jan 1, 1989 Reasonably consistent Bltn B dpsi some anomalies Sep 1999

11 Analysis USNO Bltn A and Bltn B values Values before 1990
X , Y Values from 1973 Values before 1990 Additional variations Bltn B some anomalies Sep-Oct 1999

12 Comparisons Between Organizations
USNO (Bltn A and Bltn B) and IERS (EOPC04) Before 1984 Larger variations FK5 instituted Before 1997 Smaller variations Update to Equation of the equinoxes Note last few values See next slide

13 Comparisons (Cont) Between Organizations
USNO (Bltn A and Bltn B) and IERS (EOPC04) Last few days appear to differ (IERS and USNO) On Feb 22 for xp IERS USNO On May 5 for xp IERS USNO IERS Delta = USNO delta =

14 Comparisons (FK5 Corrections)
Between Organizations USNO (Bltn A and Bltn B) and IERS (EOPC04) Data availability Bltn B values only after Jan 1, 1989 Each appear to have noise

15 Comparisons (IAU 2000 Corrections)
Between Organizations USNO (Bltn A and Bltn B) and IERS (EOPC04) Data availability EOPCO4 Values after Jan 1, 1984 Bltn B appears to better follow EOPC04

16 Coefficient Approach NGA provides coefficients
Continuous representation of UT1, xp, yp Lacks LOD, , , X , Y Generally smaller order effects Long-term behavior of EOP coefficients xp, yp reasonable to use past the end of a data file UT1 not recommended past about a month

17 Comparisons – Long Term
EOPC04 to NGA Coefficients One year different epochs are shown Notice variability Runoff for UT1, xp Current week is valid (highlighted) Note 0.04 s ≈ 280m at 7 km/s

18 EOP – How to Splice Together
EOPC04 Use 62-now file Up to current day Recomputed frequently USNO Predicted Bulletin A Use .daily file Daily values (t-3 months to t+3 months) Updated daily Use .all file 1 year predictions Data availability Use last known file of each if any are not available Values are “acceptable” for short periods of time (~week)

19 II. Space Weather Data

20 Space Weather Tracked for many years Older data
Data to the 1930s Older data Has numerous missing dates Physically a zero means little here! Corrected in our files Quality flag set to 4 as an indicator Includes seasonal/solar cycle variations Observed and adjusted to 1.0 AU values DRAO and Lenhart values Atmospheric models use both

21 Sensitivity Results Atmospheric Drag (see Vallado AAS 05-199)
Large variations Changing the atmospheric model Changing how the input data is interpreted F10.7 at 2000 UTC Last 81-day average F10.7 vs. the central 81-day average Using step functions for the atmospheric parameters vs interpolation Many others Point to take away: km ephemeris differences are possible Unable to determine if from data interpretation or model differences

22 Space Weather – Predictions
Lots of Variability Constant F10.7 Not very accurate Never use 0.0! Schatten Varies with each solar cycle Polynomial Trend (Vallado 2004, 535) Matches several solar cycles F10.7 = *COS{ t – 0.35*SIN(π t )} t is the number of days from Jan 1, 1981

23 Historical and Polynomial Trend

24 Schatten Predictions

25 Statistics Comparisons
Combined Results Avg Deviation Standard Deviation Ctr 81-day – Daily F10.7 15.00 21.99 Last 81-day – Daily F10.7 17.17 24.92 Trend 81-day – Daily F10.7 20.79 29.88 Monthly Trend – Monthly F10.7 15.33 21.85 Individual Results Variability ‘same’ between 81-day averages and daily values Monthly trend and monthly averages Predicted (3-day, 45-day and 2 year) solar flux values

26 Observed / Adjusted values

27 kp – ap Conversions Rigorously defined
1940 – Chapman and Bartels – Geomagnetism Discrete values Values exist that are not in the discrete values Finding 3-hourly ap values for the last month Finding kp values from predicted ap values Some Interpolation clearly required Approaches Linear Interpolation Iteration Spline

28 Comparison of Conversions
Techniques – Interpolate, Iterate, Splines Between approaches (left) To exact values (right)

29 III. File Setup

30 File Setup Proceeding can be complex and time consuming
CSSI (Dr. Kelso) has done the work for you! Files updated every 3 hours STK compatible Naming indicates start date Schedule EOP and Space weather files ready today Operational in next STK release

31 Additional Information
Common changes for both files All ASCII text Start dates can be set to a time before the current date Naming convention permits quick determination Set an end date Observed and predicted sections consistent Spacing minimized (file size) Maintain free-field read capability Indicate number of data points

32 Additional Information
Specifics EOP Add day, month, year to data Switch to predominantly IERS EOP-C04 data from USNO Bltn A data Data now available from 1962 instead of 1973 Removed data for errors in xp, yp, and UT1 Added LOD, ,  Added AT, X, Y into one file Last values set to zero Include automatic leap second introduction Space Weather Data from 1957 to date (more is possible) Added centered 81 day in addition to last 81 day average values, observed and adjusted Spliced past, current, and predicted data New structure for predicted data Monthly and Daily sections Trend values for long term prediction possible

33 Conclusions EOP and Space Weather data Not high visibility
However, large variations in numerical results Ap/kp conversion Recommend using Cubic Spline approach Predicted solar flux values Polynomial trend available for long term use Reasonable statistics to existing Schatten files Your single source for consolidated values available:

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