1. Recent developments for a forward operator for GPS RO Lidia Cucurull NOAA GPS RO Program Scientist NOAA/NWS/NCEP/EMC NCU, Taiwan, 16 August 2010 1

2. n Introduction n 3-term Refractivity expression n Bending angle n Effects of including compressibility factors (Yu-Chun Chen) n Summary and future work Outline 2

3. Radio Occultation concept LEO Occulting GPS Ionosphere Neutral atmosphere Earth Raw measurement: change of the delay (phase) of the signal path between the GPS and LEO during the occultation. (It includes the effect of the atmosphere) GPS transmits at two different frequencies: ~1.6 GHz (L1) and ~1.3 GHz (L2). n An occultation occurs when a GPS (GNSS) satellite rises or sets across the limb wrt to a LEO satellite n A ray passing through the atmosphere is refracted due to the vertical gradient of refractivity (density) n During an occultation (~ 3min) the ray path slices through the atmosphere 3

4. s 1, s 2,  1,  2  N T, P w, P Raw measurements of phase of the two signals (L1 and L2) Bending angles of L1 and L2 (neutral) bending angle Refractivity Ionospheric correction Abel transfrom Hydrostatic equilibrium, eq of state, apriori information Clocks correction, orbits determination, geometric delay choice of ‘observations’ Atmospheric products 4

5. Choice of observation operators Complexity L1, L2 phase L1, L2 bending angle Neutral atmosphere bending angle (ray-tracing) Linearized nonlocal observation operator (distribution around TP) Local refractivity, Local bending angle (single value at TP) Retrieved T, q, and P Not practical Not good enough Possible choices 5

6. Introduction n At microwave wavelengths (GPS), the dependence of N on atmospheric variables can be expressed as: Hydrostatic balance P is the total pressure (mb) T is the temperature (K) Scattering terms W w and W i are the liquid water and ice content (gr/m 3 ) Moisture P w is the water vapor pressure (mb) Ionosphere f is the frequency (Hz) n e electron density(m -3 ) – important in the troposphere for T> 240K –can contribute up to 30% of the total N in the tropical LT. –can dominate the bending in the LT. Contributions from liquid water & ice to N are very small and the scattering terms can be neglected RO technology is almost insensitive to clouds. 6

7. Forward Model for refractivity n (1) Geometric height of observation is converted to geopotential height. n (2) Observation is located between two model levels. n (3) Model variables of pressure, (virtual) temperature and specific humidity are interpolated to observation location. n (4) Model refractivity is computed from the interpolated values. n The assimilation algorithm produces increments of –surface pressure –water vapor of levels surrounding the observation –(virtual) temperature of levels surrounding the observation and all levels below the observation (ie. an observation is allowed to modify its position in the vertical) n Each observation is treated independently and we account for the drift of the tangent point within a profile 7

8. k1 k1-1 surface k2 k1-2 obs

9. Pre-operational implementation run n PRYnc (assimilation of operational obs ), n PRYc (PRYnc + COSMIC refractivity) n We assimilated around 1,000 COSMIC profiles per day Anomaly correlation as a function of forecast day (geopotential height) rms error (wind) 9

10. Dashed lines: PRYnc Solid lines: PRYc (with COSMIC) Red: 6-hour forecast Black: analysis Pre-operational implementation run (cont’d) 10

11. n More accurate forward operator for refractivity –Three term expression –Analysis of different sets of refractive indexes n Update of the quality control procedures –More observations (in particular in tropical latitudes) n Optimal observation error characterization (Desroziers 2005) –Smoother normalized differences –No empirical tuning n Changes resulted in an improvement in model skill in SH (mass fields) and reduction of the low- and high-level tropical wind errors n These changes were implemented operationally at NCEP in Dec 2009 n Detailed description of the changes and results can be found in Cucurull 2010, WAF, 25,2,769-787 Improved algorithms for N

12. 3-term Forward Operator for refractivity n (1) Geometric height of observation is converted to geopotential height. n (2) Observation is located between two model levels. n (3) Model variables of pressure, (virtual) temperature and specific humidity are interpolated to observation location. n (4) Model refractivity is computed from the interpolated values. n The assimilation algorithm produces increments of –surface pressure –water vapor of levels surrounding the observation –(virtual) temperature of levels surrounding the observation and all levels below the observation (ie. an observation is allowed to modify its position in the vertical) n Each observation is treated independently and we account for the drift of the tangent point within a profile 12

13. 13

14. original (ops) QC & errormodified QC & error (O-B)/O_err Errors too small Many more Observations !! Very few observations NH TR SH

15. Impact with COSMIC n AC scores (the higher the better) as a function of the forecast day for the 500 mb gph in Southern Hemisphere n 40-day experiments: –expx (NO COSMIC) –cnt (old RO assimilation code - with COSMIC) –exp (ops –- with COSMIC) COSMIC provides 8 hours of gain in model forecast skill starting at day 4 !!! Cucurull 2010 (WAF)

16. Forward Model for bending angle n Make-up of the integral: –Change of variable to avoid the singularity –Choose an equally spaced grid to evaluate the integral by applying the trapezoid rule 16

17. n Compute model geopotential heights and refractivities at the location of the observation n Convert geopotential heights to geometric heights n Add radius of curvature to the geometric heights to get the radius: r n Convert refractivity to index of refraction: n n Get refractional radius (x=nr) and dln(n)/dx at model levels and evaluate them in the new grid. We make use of the smoothed Lagrange-polynomial interpolators to assure the continuity of the FM wrt perturbations in model variables. n Evaluate the integral in the new grid. n Each observation is treated independently and we account for the drift of the tangent point within a profile Forward Model for bending angle (cont’d) 17

18. QC 18 NH TR SH NH TR SH

19. QC (model level) 19 NH TR SH NH TR SH

20. N vs BA (single case, T62L64) 20 N BA

21. 21 N BA

22. 22 N BA

23. Assimilation algorithm 23 0:gps 82761 9.1646957113037395E+04 1.107 0:gps 83635 5.1683558671757288E+04 0.618 0:gps 83705 5.1001526772670179E+04 0.609 0:gps 49970 7.7231250467998078E+04 1.546 0:gps 50934 2.8707346020729292E+04 0.564 0:gps 51138 2.7751283896612065E+04 0.543 Counts J J/counts N BA

24. Experiments setup Case: 2010/02/01 12Z CTRL : no compressibility factor, old coefficient for N EXP0 : Compressibility Factor + old coefficient for N EXP1 : Compressibility Factor + Rueger’s Coefficient for N EXP2 : (Compressibility Factor + Rueger’s Coefficient for N) for GPS only EXP0 V.S. CTRL EXP1 V.S. CTRL Northern Hemisphere Yu-Chun Chen

25. CTRL anl V.S. EXP1 anl CTRL anl V.S. EXP2 anl

26. EXP1 anl V.S. EXP2 anl Small differences 0.3%~0.7%

27. Summary n NCEP’s operational assimilation algorithm for GPS RO makes use of a three-term forward operator for refractivity n Current work focuses on the use of a (local) bending angle operator n Compressibility factors will be further evaluated and tested in a future parallel run n Future work should address the horizontal gradients of refractivity (non-local operators) 27