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Improving the NOAA Joint global OSSE System for Lidar data impact evaluation

Improving the NOAA Joint global OSSE System for Lidar data impact evaluation. Yuanfu Xie 1 , Yu Zhang 1 Zoltan Toth 1 , and Bob Atlas 2. Global Systems Division. 1 Forecast Applications Branch 2 AOML. Outline. Review the joint global OSSE system; Some regional OSSE effort;

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Improving the NOAA Joint global OSSE System for Lidar data impact evaluation

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  1. Improving the NOAA Joint global OSSE System for Lidar data impact evaluation Yuanfu Xie1, Yu Zhang1 Zoltan Toth1, and Bob Atlas2 Global Systems Division 1Forecast Applications Branch 2AOML

  2. Outline • Review the joint global OSSE system; • Some regional OSSE effort; • Development of a new regional nature run; • Improvement for global OSSE system; • Future work

  3. Joint Global OSSE system • The OSSE system is based on the NCEP operational system, GFS and GSI (3DVAR); • Nature Run (“truth”) is from ECMWF’s 13 month free forecast (May 1, 2005 to June 31, 2006) at T511 and 91 levels; • Synthetic observations: • Conventional observation data (NCEP); • Satellite radiance data (NCEP and NASA GMAO); • UAS and WISDOM data (ESRL). • Calibration through data denial (ESRL).

  4. Joint Global OSSE Applications • UAS OSSE (ESRL): a report of data impact; • WISDOM OSSE (ESRL): some results but further improvement needed with targeting obs schemes; • Wind lidar OSSE (NCEP and JCSDA): presented in May LWG • Atmospheric river OSSE: planning.

  5. WISDOM OSSE 110 WISDOM launch sites; every 30 min: 21312 data

  6. Impact of WISDOM on Track The impact of WISDOM data on hurricane track forecast at different forecast time

  7. Issues for Lidar OSSE • T511 resolution of NR may need upgrade • Higher resolution ECMWF nature run; • FIM or other global model forecast for a new NR; • The current data assimilation system needs upgrade • Hybrid GSI for taking advantage of flow dependency; • Other fine scale data assimilation with hotstart capability; • Existing ensemble forecast cannot be used for hybrid data assimilation or targeting observation.

  8. Acknowledgment: Riishojgaard et al: May LWG meeting 500hPa HGT anomaly correlation coefficients (T382) NH SH 1.8% 1.2% Impact of DWL observations is larger at the higher resolution (T382), even though skill of control is higher Lidar Working Group, Miami, May 1-2 2012

  9. Regional OSSEs To address the resolution issue, one solution is regional • AOML and UM have developed a regional NR for hurricane applications embedded in the global OSSE; • ESRL is studying a new nature run approach for regional OSSEs • Fine scale NWP model forecasts nudged towards large scale analysis; • All existing ensemble forecasts can be used for targeting or hybrid data assimilation.

  10. Nudged Nature Run towards Global Analysis • Initial/Boundary • GFS 0.5 degree analysis data • Run time • From 11th Mar. to 18th Mar. • grid points: 402×468 • Domain • D3, but the resolution is 3km

  11. Nudging effectsupper level

  12. Improving Global OSSE for Lidar • Upgrade the nature runs to finer resolution as discussed above; • Upgrade the data assimilation system from GSI to GSI hybrid system • The hybrid can take flow dependent covariance to improve lidar data impact; • Ensemble forecasts are needed for the current nature run. • Upgrade GFS to higher resolution with fine NRs.

  13. Acknowledgment: Daryl T. Kleist at NCEP Single 850mb Tv observation (1K O-F, 1K error)

  14. Future Works • Develop a comprehensive Lidar OSSE plan with this Lidar Working Group; • Adapt the hybrid GSI data assimilation system into the current global OSSE system; • Develop new and fine resolution OSSE nature runs; • Calibrate improved global and new regional OSSEs.

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