Geodesy and Meteorology: Serendipity, Synergy and Reciprocity

1. Geodesy and Meteorology: Serendipity, Synergy and Reciprocity Seth I. Gutman NOAA Earth System Research Laboratory Boulder, Colorado USA Workshop on Applications of GPS/GNSS in NOAA Thursday October 25, 2007

2. Serendipity • When we think of serendipity, we usually think of unsought-after but highly beneficial consequences of an action. • Sometimes discoveries that are thought to be serendipitous are actually the result of experience and good observation. • As the saying goes, “Fortune favors the prepared mind.“ • Clearly this was the case for Archimedes. • And so I believe it is with the contributions of Geodesy to Meteorology and visa versa. Archimedes of Syracuse and Buoyancy.

3. One Person’s Noise is Another Person’s Signal • It’s fair to say that when GPS was designed and developed by the U.S. military, the use of GNSS for atmospheric remote sensing was probably the last thing on their minds. • It’s also reasonable to assume that the techniques developed by geodesists to (1) estimate atmospherically induced signal delays as nuisance parameters in the calculation of antenna position, and (2) remove them to improve survey accuracy, were not developed to improve weather forecasts. • So the recognition that ground based (Bevis et al. 1992) and space-based (Yuan et al. 1993) GNSS observations could be used for atmospheric remote sensing with applications in operational weather forecasting, climate monitoring and atmospheric research can rightly be called serendipitous.

4. Mapping Function ~1/sin(a) sz sj si ~5km a h~500 hPa ~22 km a FOV GNSS Observations in Meteorology In both cases, the fundamental measurement is Surface Based Geometry N(s) the refractivity of the atmosphere along the path of the radio signal N(s) = 106 (n(s)-1). Space Based Geometry S(t) S(t+60s) Hurricane Ivan Illustration above courtesy of T. Yunk, NASA JPL.

5. Overview of GPS Meteorology • GPS Signal in Troposphere • Refractivity associated with changes in T,P,WV in neutral atmosphere. • Signal delays are unrelated to frequency below 30 GHz. • Delays must be modeled using assumptions about the structure and length-scale variability of these parameters. • GPS Signal in Ionosphere • Refractivity associated with changes in electron plasma density or TEC between 50 and 400 km AGL. • Signal delays in dispersive media are inversely proportional to frequency. • Ionospheric delays are estimated (or removed) using dual frequency receivers.

6. Zenith Tropospheric Delay Estimation • When we process GPS data, we first form an “ionospheric free” carrier phase solution by combining L1 & L2, and then form a “double-difference” (DD) to remove receiver and satellite clock biases. • We start with two assumptions: the radio-refractive properties of the neutral atmosphere are primarily elevation dependant and the total neutral signal delay has only a wet and dry component. • The GPS signal delay along a single slant path, T(), is modeled in terms of an unknown “zenith delay” and known elevation angle-dependent mapping functions, mD() and mW(). • Since there are usually 6-10 satellites at different elevations in view at all times, solutions for the zenith delay (and its spatial gradients) are over-determined and can be estimated with high accuracy.

7. Ground-Based PW Accuracy 2004 NSA Arctic Winter Radiometric Experiment at Pt. Barrow, AK All weather operability Measurements agree to within ~0.75 mm. 1mm

8. Why This Is Important • Conventional ground and space-based moisture sensing systems cannot (by themselves) capture the temporal & spatial variability of water vapor with the accuracy and resolution needed to improve weather forecast skill (in the short term) or monitor climate change (in the long term). • Water vapor measurements derived from space geodetic observations provide us with a new & totally independent way of making long and short-term moisture measurements, and for calibrating/validating other water vapor measurements: • with high accuracy; • under all weather conditions; • tied to SI standards; • without the need for external calibration.

9. Why This Is Important • Water vapor is one of the most important components of the Earth’s atmosphere. • It is the source of clouds and precipitation, and an ingredient in most major weather events. • PW moves rapidly through the atmosphere, redistributing energy (latent heat) through evaporation and condensation. • One of the most valuable attributes of GPS is its ability to provide accurate signal delay estimates under all weather conditions, including thick cloud cover and precipitation.

10. Why This Is Important • Water vapor also plays a critical role in the global climate system: • It is by far the most plentiful greenhouse gas; • It absorbs and radiates energy from the sun; • It affects the formation of clouds and aerosols and the chemistry of the lower atmosphere; • Understanding & monitoring the quantity and distribution of PW, and the effects it has on atmospheric radiation and circulation, is vital to the diagnosis and prognosis of long-term changes in climate.

11. Where Are We Now • GPS observations at about 360 sites over CONUS: • are now assimilated into two operational weather models running at NCEP/EMC; • significantly improve moisture and precipitation forecasts; • are routinely used by forecasters to provide situational awareness under rapidly changing weather conditions; • are used to quality control radiosondes, still the backbone of the global upper-air observing system; • are used by researchers to verify satellite moisture observations and develop techniques to improve satellite TPW measurements.

12. What’s Missing?

13. Synergy • Synergy comes from the Greek word meaning “working together.” • Let’s look at some current models for the synergy between Geodesy and Meteorology. NOAA CORS Network IGS Tracking Network Permanent Stations in Europe

14. Another Example • Astronomical observations, especially at infrared and submillimeter wavelengths, are heavily impacted by the amount of PW in the column of air above the telescope. • To mitigate this, observatories are usually located in high, dry places or in outer space. • Because the transparency of the atmosphere is inversely proportional to IPW, astronomers routinely apply corrections based on this quantity. • Knowledge of the amount of IPW usually comes from MWR’s operating at 183 GHz.

15. Synergy • A well calibrated MWR can provide the most precise measurements of IPW for astronomical and other applications, but… • all amplitude-based measurements (including MWR) depend on the quality of the instrument calibration. • Another way to make the same measurement (but with different physics) is to measure GNSS signal delays. • The accuracy of GNSS IPW retrievals under clear sky conditions are comparable to MWR estimates, but their precision is usually a little lower. • The strong-points of using GNSS receivers for many applications especially in remote areas are 1) self calibration, 2) all-weather operability, 3) high reliability, and 4) comparatively low cost.

16. Tying Things Together • Infrared and submillimeter observatories are located at high elevations. • The PW that negatively impacts these observations resides in the middle-upper troposphere. • How moisture changes in the middle-upper troposphere in response to global warming is one of the most important and challenging questions we face. • We could use MWR’s to provide this information, but frequent recalibration is required to provide the long-term accuracy needed to detect climate-related changes. • Or we could use GNSS receivers which require no external calibration and who’s accuracy improves rather than degrades with time.

17. MKEA MLO1 360 m Monitoring PW At High Elevations MLO1 - MKEA x = 32.0 km z = 0.360 km

18. MLO1 MKEA MLO1 - MKEA Diurnal PW Cycle at Mauna Loa & Mauna Kea Observatories Period of comparisons Computed from all GPS observations at MLO and MKEA between 2004-2007

19. MLO1 MKEA MLO1 - MKEA PW Differences at MLO1 & MKEA Change in interval PW from GPS obs between 2004 - 2007 = 4.3 mm/decade using data collected each day between 08 - 18 UTC Water Vapor is the Primary Greenhouse Gas T.R. Karl and K.E. Turnbeth: Science 5 December 2003: Vol. 302. no. 5651, pp. 1719 – 1723 DOI: 10.1126/science.1090228

20. Reciprocity • Reciprocity is a joint, shared or common relationship of mutual dependence, action or influence. • We have seen how Meteorology has benefited from space geodetic observations. • How has Geodesy benefited from Meteorology? • Development and refinement of mapping functions: • models of neutral atmospheric propagation delay as a function of elevation; • derived from surface observations; • derived from UA observations; • derived from numerical weather models.

21. Reciprocity • Detection and reduction of systematic errors in the estimation of ZTD: • by comparing GNSS-derived IPW with radiosonde and MWR observations • minimized with processing protocols using NMF and IGS phase center models that allow networks to incorporate data from more than one antenna type. • Development of ultra rapid and hourly orbits: • needed to provide PW estimates in NRT to weather forecasters and modelers. • Development of the sliding window data processing technique: • allow DD technique to estimate ZTD or monitor site stability in NRT.

22. Reciprocity • If GNSS-derived ZTD estimates improve NWP accuracy, can estimates of ZTD derived from atmospheric models improve geodetic accuracy? • This question has been investigated independently by several investigators, including: • P. Alves, Y.W. Ahn, J. Liu, and G. Lachapelle at U. Calgary; • S. Bisnath and D. Dodd at U. Southern Miss; • B. Remondi and M. Albright at XYZ’s of GPS; • F. Nievinski and M. Santos at U. New Brunswick; • Y. Bock and P. Fang at SOPAC.

23. Impact of NWP on Geodesy • The use of “physically-based” models such as NOAATrop adds value over “deterministic” tropospheric delay models such as Saastamoinen, Hopfield and UNB3. • Depending on the processing approach and local conditions, improvements in positioning accuracy range from 10%-40%, mostly in elevation. • Results from all investigators are reasonably consistent. • NOAATrop model effectively reduces the correlation between zenith delay, multipath, and vertical position at all time scales, but impact diminishes with time. • Greatest impact is always during active weather.

24. Impact of NWP on Geodesy • Atmospheric models such as those used by NOAA for operational weather forecasting contain all of the mass and momentum information needed to describe and predict the refractivity of the troposphere. • Thanks to the GPS, the systematic errors in models associated with wet refractivity have been reduced by almost 50%

25. GNSS Opportunities for NOAA • In collaboration with international partners: • Expand NRT global GNSS observations: • in poorly observed regions of the planet • in areas prone to natural disasters. • Merge global GNSS networks to achieve onshore global coverage for GEOSS. • Expected results: • Improved air, sea and land transportation safety • Improved global weather prediction • Improved climate monitoring • Improved monitoring of sea level • Real-time monitoring of active faults, volcanoes and other geological hazards • Improved lead time for tsunami warnings • More effective use of satellite data through global calibration and validation.

26. DMSP SSM/I 2 satellite composite GPS-IPW NOAA AMSU 3 satellite composite Images courtesy of J. Forsythe @cira.colostate.edu

27. Thanks for your Attention! Any Questions?