1. Exploring Application of Radio Occultation Data in Improving Analyses of T and Q in Radiosonde Sparse Regions Using WRF Ensemble Data Assimilation System
H. Liu, J. Anderson, B. Kuo, C. Snyder, A. Caya
NCAR/IMAGe/COSMIC/MMM

2. Motivation • Over oceans, radiosondes are sparse.
• Current NCEP and ECMWF global analyses of T and Q rely heavily on satellite radiances and winds.

3. Motivation (cont.)
• Significant areas of cloud-cover may exist over oceans, e.g., in case of tropical cyclones and hurricanes. Radiances are not yet routinely used in cloud-covered areas.
• In such cases, satellite winds are the major data resource and NCEP and ECMWF analyses of T and Q may have large uncertainty.
• Initialization of landing cyclones and hurricane forecasts from such analyses may also have large uncertainty.
• Study of the weather and climate over oceans (e.g., ITCZ and MJO) also needs more reliable analyses of T and Q.

4. Radio Occultation (RO) Refractivity
• Have T and Q information with high vertical resolution.
• Its observation operators are simple and accurate.
• Has good coverage over oceans and not affected by clouds.
RO data have potential to improve analyses of T & Q over oceans.

5. Our Goal Application of RO data to improve:
 Analyses of T and Q over oceans
 Initialization (large-scale) for cyclone and hurricane forecast
 Initialization for tropical cyclone genesis forecast
In this preliminary study:
We explore impact of current experimental (CHAMP) RO refractivity data on improving analyses of T and Q in the presence of only satellite winds over the Continental US domain.

6. Experimental Design • EXP 1: Assimilate satellite cloud winds only.
(Simulate cloudy situations over oceans)
 EXP 2: Assimilate satellite cloud winds + RO refractivity
Radiances are not included and this may serve as an upper bound on the impact of RO data.
• A total of ~500 RO refractivity profiles during Jan 1-31, 2003 are assimilated.
• Impact of RO data on 50km resolution WRF analyses is examined.
• Analyses are verified to the ~100 co-located (< 200km and +/- 3 hours) radiosonde profiles, which are withheld from the assimilations.

7. Why use the WRF Ensemble System?
• Advanced (non-local) RO observation operators can be easily implemented (requiring only forward models). This is especially important for the tropics.
• Time varying forecast error correlation of T and Q is included in the assimilation of RO data and this may significantly improve retrieval of T and Q from RO refractivity/bending angle.

8. Radiosondes used for Verification
(Jan 1-31, 2003)

9. Impact of RO Refractivity
(T analysis mean & RMS error, entire domain)

10. Impact of RO Refractivity
(Q analysis mean and RMS error, entire domain)

11. Impact of RO Refractivity
(T analysis mean & RMS error, hPa )

12. Impact of RO Refractivity
(Q analysis mean & RMS error, hPa)

13. Conclusion
The preliminary results suggest that RO data may have the potential to significantly improve the analyses of T and Q over oceans, especially in cloudy situation.
Study to provide high resolution (30km or better) tropical analyses of T and Q using satellite winds and RO refractivity is underway.
P.S. WRF ensemble data assimilation system is available to the public on