Spaceborne Doppler Wind Lidars - Scientific motivation and impact studies for ADM/Aeolus

1. Spaceborne Doppler Wind Lidars-Scientific motivation and impact studies for ADM/Aeolus Erland Källén with help from David Tan, Carla Cardinali, Paul Berrisford ECMWF Wind Lidar working group February 2010

2. Outline • ADM/Aeolus • Scientific motivation • Present observing system • Forecast error Sensitivity to Observations • Re-analysis uncertainties • ADM/Aeolus impact study • Conclusions Wind Lidar working group February 2010

3. Atmospheric Dynamics Mission ADM/Aeolus Wind Lidar working group February 2010

4. ADM-Aeolus • Doppler Lidar • Aerosol and molecular scattering • Intermittent pulses • Only one wind component • Dawn-dusk polar orbit • Measurement error < 2 m/s [H]LOS Wind Lidar working group February 2010

5. ADM/Aeolus Wind Lidar working group February 2010

6. Main scientific objectives of ADM/Aeolus • Improve representation of wind field in atmospheric analyses • Tropics: Wind field governs dynamics • Mid-latitudes: Intense storm developments and meso-scale circulation systems • Numerical weather prediction • Climate sensitivity Wind Lidar working group February 2010

7. Additional objectives • Aerosol information • Cloud properties Wind Lidar working group February 2010

8. Outline • ADM/Aeolus • Scientific motivation • Present observing system • Forecast error Sensitivity to Observations • Re-analysis uncertainties • ADM/Aeolus impact study • Conclusions Wind Lidar working group February 2010

9. Present observing system • Radiosondes • Pilot balloons and profilers • Buoys • Satellites • Aircraft data Wind Lidar working group February 2010

10. Radiosondes1 Nov 2004, ECMWFTotal: 590 Wind Lidar working group February 2010

11. Satellite polar orbiting1 Nov 2004, ECMWF Total: 247309 Wind Lidar working group February 2010

12. Aircraft data1 Nov 2004, ECMWF Total 26219 Wind Lidar working group February 2010

13. Outline • ADM/Aeolus • Scientific motivation • Present observing system • Forecast error Sensitivity to Observations • Re-analysis uncertainties • ADM/Aeolus impact study • Conclusions Wind Lidar working group February 2010

14. Forecast error J (“dry energy norm” ps, T, u, v) Forecast error sensitivity to the analysis xa: → (y: observations) Forecast error Sensitivity to Observations Rabier F, et al. 1996. Analysis solution: → The tool provides the Forecast Error Contribution for each assimilated observation, which can be accumulated by observation type, subtype, variable or level Compute the δJ: Wind Lidar working group February 2010

15. 24 H Forecast Error Contribution of GOS Wind Lidar working group February 2010

16. Mass versus Wind contributions Wind Lidar working group February 2010

17. Outline • ADM/Aeolus • Scientific motivation • Present observing system • Forecast error Sensitivity to Observations • Re-analysis uncertainties • ADM/Aeolus impact study • Conclusions Wind Lidar working group February 2010

18. Re-analyses of zonal winds NCEP ERA-15 Difference NCEP/ERA-15 Kistler et al., 2001 Wind Lidar working group February 2010

19. ERA-InterimZonal mean wind 1989-2001 >15 <-10 >30 m/s >25 30 Wind Lidar working group February 2010

20. Difference ERA-Interim vs. ERA-40 Zonal mean wind 1989-2001 >2 <-4 m/s Wind Lidar working group February 2010

21. Outline • ADM/Aeolus • Scientific motivation • Present observing system • Forecast error Sensitivity to Observations • Re-analysis uncertainties • ADM/Aeolus impact study • Conclusions Wind Lidar working group February 2010

22. Assimilation study for ADM/Aeolus • Assimilation ensembles for data impact assessment • Use ensemble spread as proxy for short-range forecast errors (background errors) • By extension, good data reduce ensemble spread • DWL impact • Radiosonde/profiler impact - provides calibration • Tan et al., QJRMS 133:381-390 (2007) Wind Lidar working group February 2010

23. OSE Reference Observations NWP-System Verification Result Assimilation/ forecast Compare to reference Impact assessment Real atmosphere Assimilation/ forecast Compare to reference Assimilation Ensemble Reference Ensemble Observations NWP-System An & Fc Diagnostics Result Assimilation/ forecast Ensemble spread Calibrate Ref. run Assimilation/ forecast Ensemble spread Impact assessment Assimilation/ forecast Ensemble spread Wind Lidar working group February 2010

24. Data impact on ensemble forecasts - zonal wind spread at 500 hPa • Radiosondes and wind profilers over Japan, Australia, N.Amer, Europe • DWL over oceans & tropics Control Sondes ADM-Aeolus Wind Lidar working group February 2010

25. Control Data impact on ensemble forecasts - zonal wind spread at 200 hPa • Radiosondes and wind profilers over Japan, Australia, N.Amer, Europe • DWL over oceans and tropics Sondes ADM-Aeolus Wind Lidar working group February 2010

26. Conclusions • Wind data is lacking in present global observing system • Tropical analyses suffer • Climate system re-analyses uncertain in tropics, polar areas and stratosphere • ADM/Aeolus will provide vertical wind profiles with global coverage Wind Lidar working group February 2010

27. Thank you for your attention– questions? Wind Lidar working group February 2010