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Motivation

Exploring application of radio occultation data in improving analyses of T and Q in traditionally data void regions using WRF/DART H. Liu, J. Anderson, B. Kuo, C. Snyder, A. Caya NCAR. Motivation.

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Motivation

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  1. Exploring application of radio occultation data in improving analyses of T and Q in traditionally data void regions using WRF/DART H. Liu, J. Anderson, B. Kuo, C. Snyder, A. Caya NCAR

  2. Motivation Over remote oceans (e.g., Tropical and North Pacific) and polar regions, there is a lack of traditional high quality observations.

  3. Motivation (cont.) • The current analyses of T and Q over the traditionally data void regions heavily rely on satellite radiances and in cloudy situations where satellite radiances are difficult to use. • In such cases, satellite wind is the major data resource and the analyses may be generally questionable. • The large uncertainty of the analyses makes initialization of forecasts including cyclones and hurricanes difficulty. Study of the weather and climate related to these regions also suffers from the large uncertainty of the analyses. • So, there is a significant need to improve the analyses.

  4. New Radio Occultation measurements atmosphere Radio ray GPS receiver on Low Earth Orbit (LEO) satellites GPS satellite • A new type of observation is being developed using radio occultation technique. • The radio rays are bent due to refractivity of the atmosphere. • The bending angles of the rays and retrieved refractivity contain T and Q information.

  5. New GPS radio occultation (RO) data Unique features: • RO data is not affected by clouds and precipitation. • Under geometric approximation, calculation of the RO bending and refractivity is relative easy and actually, no bias correction needed for the data ( required for radiances). Current experimental CHAMP and SAC-C RO data: ~ 300 profiles globally per day Upcoming COSMIC and EQUARS RO data: ~ 4000 profiles globally per day

  6. New GPS radio occultation data Good coverage over oceans and polar regions

  7. Previous impact studies of RO data • RO data have been assimilated into ECMWF and NCEP operational global variational data assimilation systems together with all other observations (Healy et al., 2005, Zou et al, 2004). • However, examination of the impact of RO data on analyses were limited to co-located radiosondes’ locations and some positive impact was found. • Over radiosonde void regions, impact of RO data still needs to be demonstrated. Actually, larger impact of RO data may be expected because the forecasts over the radiosonde void regions have larger uncertainty.

  8. Our work • Our goal is to explore application of RO data in improving current analyses of T and Q over the radiosonde void regions. • In this study, we will examine impact of the experimental CHAMP RO data on improving the regional analyses of T and Q in the presence of only satellite wind observations, which is the major data source in cloudy situations, using the WRF/DART over Continental US (CONUS) domain.

  9. Why using ensemble approach? • Our recent study (Liu et al., 2006) suggest that inclusion of time-varying forecast error correlation of T with Q with ensemble approach may significant improve retrieval of T and Q from RO data (which is function of both T and Q). • However, in variational approach, inclusion of the error correlation of Q with T has not been successful yet (e.g., Berre, 2001). Only time-averaged forecast error variances of T and Q are used to retrieve T and Q from RO data.

  10. Experimental design • Two assimilation experiments are done: EXP 1: Assimilate only satellite wind observations EXP 2: Assimilate satellite wind + RO refractivity • 50km resolution of WRF model is used to assimilated the RO data. • Analyses of T and Q are verified to co-located (< 200km and +/- 3 hours) radiosonde observations. • Jan 1-31, 2003 is examined. • 20 members are used.

  11. CHAMP RO profiles’ locations (Jan 1-31, 2003)

  12. Radiosondes used for verification (Jan 1-31, 2003)

  13. Impact of RO refractivity (T analysis fits to radiosondes averaged over the domain)

  14. Impact of RO refractivity (Q analysis fits to radiosondes averaged over the domain)

  15. Impact of RO refractivity (T analysis fits to radiosondes averaged between 600 and 800 hPa )

  16. Impact of CHAMP RO refractivity (Q fits to radiosondes averaged 600 - 800 hPa)

  17. Conclusion The results suggest that RO data may significantly improve analyses of T and Q in the troposphere over the radiosonde void regions, especially in cloudy situations.

  18. Future work Next, we will explore application of the upcoming UCAR/COSMIC and EQUARS RO data in improving regional analyses of T and Q over tropical oceans and polar regions. Upon successful, we may provide better quality analyses of T and Q for hurricane forecasts and promote study of weather and climate related to the tropics and polar regions.

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