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On the use of Numerical Weather Models to Predict Neutral-Atmosphere Delays

On the use of Numerical Weather Models to Predict Neutral-Atmosphere Delays. Felipe G. Nievinski. The curse of tropospheric delay in GPS positioning. One of main error sources in medium- to long-range kinematic applications. Estimation more challenging than in static app.

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On the use of Numerical Weather Models to Predict Neutral-Atmosphere Delays

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  1. On the use of Numerical Weather Models to Predict Neutral-Atmosphere Delays Felipe G. Nievinski

  2. The curse of tropospheric delay in GPS positioning • One of main error sources in medium- to long-range kinematic applications. • Estimation more challenging than in static app. • Due to, e.g., time-varying height. • A better a priori prediction would be valuable. • Whether estimating or only correcting for tropospheric delay.

  3. Numerical Weather Models: a better picture of today’s weather? • Typical tropospheric delay prediction models: (i) Climatological models (ii) Surface-measured pressure, temperature, humidity • NWM aims at representing (i) The daily weather (ii) The entire 3-dimensional weather field. Northern half of 3D refractivity (unitless) field on Aug 16, 2004, 22:45 UTC (vertical scale 100x)

  4. Methods • 1. How to predict delays with NWM • 2. How to test if the delays are not wrong • 3. How to assess whether the delays improve GPS applications

  5. Numerical integration: Coordinate conversion: Interpolation: Refractivity calculation: Predicting delays with NWM

  6. Tropospheric corrections: NWM–radiosonde discrepancy Total (cm) Hydro- static (cm) Non- hydro- static (cm)

  7. GPS positioning • Two scenarios for kinematic processing: • Moving rover: on board ferry boat • Stationary rover: one of two base stations • In each scenario, test and reference solutions:

  8. Impact assessment • 3 tropospheric prediction models assessed: • NWM • UNB3m • Saastamoinen with standard weather parameters • uncorrected observations (no model) • Criteria: • Discrepancy in rover position between test and reference solutions • RMS of observation residuals

  9. Stationary rover:test–reference discrepancy

  10. Saint John Digby Moving rover: discarding unreliable epochs

  11. Moving rover (1): test–reference discrepancy

  12. Moving rover (2): test–reference discrepancy

  13. Conclusions and future work • NWM has only marginal improvement on that particular 70 km baseline. • Validation: vertical coordinates in NWM • Study how it is handled in data assimilation • Test it with GPS-equipped radiosondes • Impact assessment: varying-length baselines • Kinematic processing at stationary rover • From 100 to 1,000 km

  14. Publications • Paper at ION AM 2005 in Boston, MA • Poster at AGU Joint Assembly in Washington, DC • Paper at ION GNSS 2006 in Fort Worth, TX

  15. Thanks!Questions? Felipe G. Nievinski

  16. satellite receiver Neutral-Atmosphere Delays • GPS signals are refracted in the Earth’s neutral atmosphere. • Hence timings (rangings) are delayed (increased). • ~ 2.5 m at zenith direction, ~ 25 m at 5º elevation angle (for a station on the geoid)

  17. Tropospheric corrections: NWM self-discrepancy NWM Ray-trace vs NWM Saastamoinen Hydro- static (cm) NWM Ray-trace vs Radiosonde ray-trace Hydro- static (cm)

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