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

Motivation

• Over oceans, radiosondes are sparse.

• Current NCEP and ECMWF global analyses of T and Q rely heavily on satellite radiances and winds.

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.

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.

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.

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.

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.

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

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

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

Impact of RO Refractivity(T analysis mean & RMS error, 600 - 800 hPa )

Impact of RO Refractivity(Q analysis mean & RMS error, 600 - 800 hPa)

Conclusion

The preliminary results suggest that RO data may have The preliminary results suggest that RO data may have the potential to significantly improve the analyses of T the potential to significantly improve the analyses of T and Q over oceans, especially in cloudy situation.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 www.image.ucar.edu/DAReS