1. Quantitative Design: The Right Way to Develop the Composite Observing System A presentation to the GOES R Conference Alexander E. MacDonald NOAA Forecast Systems Lab – Boulder May 11, 2004

2. Quantitative Design: The Right Way to Develop the Composite Observing System Talk Summary 1. Observing subsystems MUST BE TREATED AS PART OF A COMPOSITE SYSTEM – not as stand alone systems. 2. We are now capable of credible simulations: * Continental Scale * Global Scale 3. Quantitative design is the right way to develop the composite observing system.

3. Quantitative Design: The Right Way to Develop the Composite Observing System Talk Summary 1. Observing subsystems MUST BE TREATED AS PART OF A COMPOSITE SYSTEM – not as stand alone systems. 2. We are now capable of credible simulations: * Continental Scale * Global Scale 3. Quantitative design is the right way to develop the composite observing system.

4. Integrated Global Observing The strategic triad of global observing: Satellites – UAVs – Surface

5. Global Hawk could be the Unmanned Aerial Vehicle platform: * Range: 14,000 miles * Speed:350 knots * Altitude:60,000 feet * Payload:1960 lbs * Lease Cost:$ 4 M /plane * Year ops:$ 3 M per plane * ConOP: 2 aircraft, 25% duty cycle * Prime:Northrop AEM in situ System Description:

6. The main idea of the Global Unified Profiling System is to take the most accurate possible profiles from the stratosphere to deep in the ocean over as much of the earth as possible. (Land too!) The profiles should include state (T,p,u,v,q in atmosphere, temperature, current and salinity in the ocean), forcing, and chemistry.

7. Quantitative Design: The Right Way to Develop the Composite Observing System Talk Summary 1. Observing subsystems MUST BE TREATED AS PART OF A COMPOSITE SYSTEM – not as stand alone systems. 2. We are now capable of credible simulations: * Continental Scale * Global Scale 3. Quantitative design is the right way to develop the composite observing system.

8. Results From the FSL Regional Lidar OSSE NOAA/FSL - Steve Weygandt - Stan Benjamin - Steve Koch - Tom Schlatter - Adrian Marroquin - John Smart - Dezso Devenyi NOAA/NWS/NCEP - Michiko Masutani NOAA/ETL - Mike Hardesty -Barry Rye - Aniceto Belmonte - Graham Feingold NCAR - Dale Barker - Qinghong Zhang

9. Relationship between Global and Regional OSSEs Global Nature Run (ECMWF) Global Assimilation Run (GFS) Regional Nature Run (MM5) Regional Assimilation Run (RUC) Global Regional Nature Run Assimilation Run Simulated Observations Boundary Conditions Simulated Observations

10. Lidar Data Coverage Three satellite swaths per 12 h Profiles of two V LOS components at each point 0300 UTC 0130 UTC 0000 UTC 0430 UTC

11. OBSERVATION DATA COUNTS Ob type Variables 12z15z Raob (Z,T,Q,U,V) 3700 0 Prof/VAD (U,V) 26002600 ACARS (T,U,V) 12001300 METAR/Buoy (T,Q,U,V) 16001600 Lidar (Vr) 15001500 Approximate no. of obs data points Lidar adds ~8% more wind obs at raob init times (00z, 12z) Lidar adds ~14% more wind obs at non-raob init times (06z, 18z)

12. Regional OSSE Calibration Does simulated-data impact (OSSE) match real-data impact (OSE) for an existing observation type? Real Data Verify against raobs 4-16 Feb 200115-20 Feb 1993 Simulated Data Verify against nature run Compare real-data and simulated-data ACARS denial

13. ACARS denial yields similar % degradation for real-data and OSSE simulated-data Normalize Errors NEGATIVE VALUE  % degradation POSITIVE VALUE  % improvement CNTL error – EXP error CNTL error Impact of denying ACARS obs on 6-h fcst vector wind RMSE % degradation

14. Lidar obs improve fcst more at non-raob init times Lidar obs improvement greatest aloft 6- hour forecast Non-raob init time (06z,18z) Raob init time (00z,12z) Assimilation of lidar observations (but no lidar obs in boundary conditions) Impact of adding lidar obs on 6-h fcst vector wind RMSE % improvement% degradation

15. The relative impact of the profiler data 3-h Model forecast improvement % improvement due to profiler and ACARS data Profiler/ACARS impact calibrated by difference between 13-day experiments with all data and no observations (lateral boundary conditions only) Fact: Profilers are the best data source for the lower part of the atmosphere within the network.

16. Satellite image taken at 0045 UT, during tornado outbreak. When the profiler data is included, it doubles the “storm energy” that was predicted for the May 3, 1999 Oklahoma tornadoes.

17. Observing System Simulation must be an important part of our efforts to add new observing capabilities on the geostationary satellites.

18. The Potential Impact of Space-based Lidar Winds on Weather Prediction: Update on recent experiments at the NASA DAO Robert Atlas Data Assimilation Office NASA Goddard Space Flight Center

23. Quantitative Design: The Right Way to Develop the Composite Observing System Talk Summary 1. Observing subsystems MUST BE TREATED AS PART OF A COMPOSITE SYSTEM – not as stand alone systems. 2. We are now capable of credible simulations: * Continental Scale * Global Scale 3. Quantitative design is the right way to develop the composite observing system.

24. Important Community Efforts Should Embrace Quantitative Design of Observing Systems: Joint Center for Satellite Data Assimilation NCEP OAR Boulder Labs SSEC NAVY University community International community etc

25. Alexander.E.MacDonald@noaa.gov sandymacd@comcast.net