1. ASAP In-Flight Icing Research at NCAR J. Haggerty, F. McDonough, J. Black, S. Landolt, C. Wolff, and S. Mueller In collaboration with: P. Minnis and W. Smith, Jr. NASA Langley Research Center, Hampton, Virginia NASA Applied Sciences Weather Program Review, 18-19 Nov 2008, Boulder, CO

2. Objective Use advanced satellite cloud products to detect areas of supercooled liquid and improve FAA operational icing products Approach Combine satellite products with other data sources using the Current Icing Product (CIP) fuzzy logic scheme

3. Products FAA/NCAR Current Icing Product (CIP) –Uses fuzzy logic methods and decision tree technology to combine data sets –Produces estimates of icing probability, supercooled large droplet (SLD) potential, and icing severity over CONUS NASA LaRC Satellite Cloud Products (“ASAP Products”) –Based on daytime GOES imager data –Available every half hour –Hydrometeor phase, cloud top height, cloud effective temperature, liquid water path, effective radius

4. Model Satellite Surface Obs Radar Pilot Reports NO YES Determine Vertical Cloud Structure and Weather Scenario Match data to each 3-D model grid box Cloudy? ICING PROBABILITY and SLD POTENTIAL FIELDS ICING=0.0 SLD=0.0 Lightning Apply interest maps. Calculate icing probability and potential for supercooled large drop (SLD). Current Icing Product (CIP)

5. FY08 Accomplishments Icing probability estimates now use ASAP products –experimental CIP available at http://www.rap.ucar.edu/icing/cip/gdcp/ http://www.rap.ucar.edu/icing/cip/gdcp/ Improved cloud top height estimates using ASAP products Icing probability comparison: experimental vs. operational CIP Use of ASAP products for icing severity estimates in progress

6. Integration of ASAP Products into CIP Icing Probability Cloud screeningHydrometeor phase Cloud top temperature interest map Cloud effective temperature Hydrometeor phase Cloud top height estimate Cloud top height Cloud effective temperature CIP Function Satellite Product Used

7. GOES IR brightness temperature Model sounding Observed cloud top Height (m) Temperature (K) Cloud Top Height Estimation – Current CIP Scheme CIP cloud top

8. CIP CTZ CloudSat CTZ Terrain Matching CIP to CloudSat

9. CTZ ≤ 3 km 3 km < CTZ ≤ 6 km 6 km 9 km

10. Hybrid Method Blend satellite-derived cloud top height and effective temperature products with model profiles Apply fuzzy logic to incorporate qualitative info about location of cloud tops in a sounding, e.g., RH < 100% Inversion in θ e Presence of wind shear Develop interest maps; combine weighted values to determine cloud top height

11. CIP Method Satellite Method Hybrid Method Errors in Cloud Top Height Estimates (Compared to TOP-REPS) x

12. Cloud Top Height -- 19 January 2005 Operational CIP Method Experimental Hybrid Method 1000 m 3000 m 5000 m

13. Operational CIP Method Experimental Hybrid Method Icing Probability at 3500 m -- 19 January 2005

14. Statistical Validation Operational CIP vs. Experimental CIP Analyze 6 weeks of 2005 winter icing data Compare icing volume and probability of detection (POD) of icing PIREPS

15. Volume Comparison Experimental CIP 8.4% of grid contains icing 83% of the cases had less volume Operational CIP 9.0% of grid contains icing Comparison limited to gridpoints where both versions agreed on cloudy/clear status

16. Probability of Detecting Icing PIREPS Experimental CIP PODy = 74% PODn = 68% Operational CIP PODy = 83% PODn = 58% Need to examine loss of PODy in the experimental version

17. Icing Severity ASAP Products vs. PIREPs LWP/IWP, phase, tau, effective radius Compared to PIREPS for each CIP scenario

18. ASAP Products – CIP Icing Severity Combine the NASA Langley retrievals with other CIP input data sets Appropriately apply fields such as LWP/IWP Scenarios –Liquid Small drop (effective radius) Large drop (effective radius) –Multi Layer –Ice Glaciated Mixed phase

19. Create membership function

20. Example: liquid - small drop Supercool liquid LWP = 300 g/m 2

21. Small drop Example: liquid - small drop

22. Example - cont Liq. Cloud top LWP 300 g/m 2 LWP_map applied to all grid points within cloud layer Model sounding

23. Two layer example LWP_map applied LWP_map not applied Model sounding Liq. Cloud top LWP 300 g/m 2

24. Future Plans Experimental CIP now runs routinely at NCAR; evaluate against operational CIP in winter 2008- 2009 season Integrate ASAP products into icing severity algorithm Investigate use of multi-layer cloud product for improved layer placement in CIP Transition to operations; dependent upon operational availability of ASAP products