1. SMAP OSWV Product Potential for the OSWV Gap Augmentation SMAP Ocean Surface Wind Vector CalVal Team Simon Yueh and Alex Fore (JPL) Don Boucher and Josh Park (Aerospace), Steve Swadley, Tanya Maurer, Kim Richardson (NRL) Gene Poe, Al Uliana (NRL/SAIC)

2. The DoD Ocean Surface Wind Vector Gap Significant near-term capability gap with respect to the collection of ocean surface vector winds (OSVW) data (Ref. JROCM-091-12, 15 June 2012) Operational gap is driven by the fact that WindSat is 3 times beyond design life No US based near-term operational material solutions are planned for fielding an OSWV capable solution in time to avoid a gap (FY15- FY18) Compact Ocean Wind Vector Radiometer (COWVR) is currently being designed and built by JPL as a Technology Demonstration Recently launched SMAP has the potential to provide OSWVs in near real-time DoD is extremely interested in this capability and is investigating feasibility

3. Applications of Near Real-time OSWVs DoD considered OSWVs and Tropical Cyclone Intensity (TCI) as CAT A high priority GAPS that require a materiel solution for the Weather Satellite Follow-On (WSF) Space-based OSWVs provide nearly all of the winds used by the Joint Typhoon Warning Center (JTWC) Space-based OSWVs provide a valuable input data source for Numerical Weather Prediction (NWP) Models Timeliness of the OSWV is critical for DoD applications Typical Data Latency requirements are 1-3 hours after initial time of observation for Operational users in support of DoD and NOAA NHC SMAP OSWV have the potential of providing winds in the higher wind speed regimes and are less subject to rain contamination suffered by other space based sensor systems using higher MW frequencies SMAP OSWVs could also help better delineate the various TC Wind Radii due to the lesser rain contamination effects

4. Typhoon Wind Radii Multi-Platform TC Surface Wind Analysis http://rammb.cira.colostate.edu/products/tc_realtime/about.asp 35, 50 and 65 kt Wind Radii, 0.1° Res20, 35, 50 and 65 kt Wind Radii, 0.5° Res These wind radii plots are generated using the following input data

5. Summary: Potential Benefits of Near Real-time SMAP OSWVs SMAP OSWVs are currently being developed, tested and validated Initial results show great promise for the high wind speed regimes with rain contamination effects small at L-band This capability can provide enhanced benefit for the DoD CAT A GAPs: OSWV and Tropical Cyclone Intensity (TCI) Key for Operational DoD and NOAA users is to provide the SMAP OSWVs in near real-time

6. Preliminary SMAP OSWV Image provided by Simon Yueh and Alex Fore (JPL)

7. Backup slides

8. Importance of Spaceborne MW Sensors in Nowcasting Applications MW Imagery Provides Invaluable Assets to Nowcasting Applications Small, intense eye with secondary eyewall developing. Small inner eye just visible, while secondary eyewall the main feature as reduced resolution. JDH Inner eye not viewable, secondary eyewall difficult to full identify. JDH TMI SSM/I AMSU-B

9. Importance of Spaceborne MW Sensors in Nowcasting Applications MW Imagery Provides Invaluable Assets to Nowcasting Applications 39 Hr Eyewall Evolution (Nuri): IR (MTSAT) vs Passive Microwave 08-18 0750Z08-18 2053Z08-19 1539Z08-19 2305Z F-14 TMIF-15 8-18 0730Z 8-18 2020Z8-19 1530Z8-19 2257Z MTSAT MW Detects eye formation 24 hours earlier Eyewall in MW Imagery Eyewall in IR Imagery

10. Importance of Spaceborne MW Sensors in Nowcasting Applications MW Imagery Resolution Advancement Providing Better Tools for Nowcasting Applications AMSR-2 36.5 GHz H-pol Typhoon Krosa 02 Nov 2013

11. Importance of Spaceborne MW Sensors in Nowcasting Applications MW Imagery Resolution Advancement Providing Better Tools for Nowcasting Applications AMSR-2 89.0 GHz H-pol Typhoon Krosa 02 Nov 2013

12. Importance of Spaceborne MW Sensors in Nowcasting Applications MW Imagery Resolution Advancement Providing Better Tools for Nowcasting Applications AMSR-2 36.5 GHz H-pol AMSR-2 89.0 GHz H-pol Typhoon Krosa 01 Nov 2013

13. Preliminary SSMIS OSWV Results and The Importance of Quality Control Wind Direction Scatter Density Plots In order to overcome the weaknesses and limitations of the current OSWV Algorithm, Quality Control (QC) procedures need to be developed and implemented. Limit the Direction Departure to |∆ Dir| < 90° Limit β < 2, < sqrt(2) or < 1 F18 All Wind Speeds

14. Preliminary SSMIS OSWV Results and The Importance of Quality Control Wind Direction Scatter Density Plots Typically, OSWV performance studies limit the wind speeds to greater than an arbitrary chosen threshold value (Wentz, 2005), as well as excluding large direction departures: |∆ Dir| < 90° (see RSS backup slide) WS > 1 WS > 3 WS > 5WS > 7 F18

15. Preliminary SSMIS OSWV Results and The Importance of Quality Control Sample Wind Vector Plot No QC

16. Preliminary SSMIS OSWV Results and The Importance of Quality Control Sample Wind Vector Plot with QC

17. Preliminary Performance Comparisons with ECMWF and other OSWV Sensors NAVGEM vs. SSMIS OSWSECMWF vs. SSMIS OSWS DTG: 2013102206 SSMIS Ocean Surface Winds Speed vs. NWP

18. Preliminary Performance Comparisons with ECMWF and other OSWV Sensors NAVGEM vs. SSMIS OSW DirectionECMWF vs. SSMIS OSW Direction DTG: 2013102206 SSMIS OSWV QC Parameters: β < 1 and Wind Speed Thresholds

19. ECMWF vs. OSCAT OSWS and OSWV ECMWF 10 m Wind Directions Bilinear Interpolation to OSCAT Scene Locations ECMWF vs. OSCAT OSWS ECMWF vs. OSCAT OSWD

20. ECMWF vs. WindSat 6.8 GHz OSWS and OSWV ECMWF vs. WindSat OSWS at 6.8 GHz Scene Locations ECMWF 10 m Wind Directions Bilinear Interpolation to WindSat 6.8 GHz Scene Locations |∆ Dir| < 90° WindSat produces an OSWV product at 6.8, 18 and 37 GHz scene locations

21. ECMWF vs. WindSat 37 GHz OSWS and OSWV ECMWF vs. WindSat OSWS at 37 GHz Scene Locations ECMWF 10 m Wind Directions Bilinear Interpolation to WindSat 37 GHz Scene Locations |∆ Dir| < 90°

22. ECMWF vs. WindSat 6.8 GHz OSW Direction Wind Speed Effects on the Wind Direction Accuracy ECMWF 10 m vs. WindSat 6.8 GHz Direction, QC: No Rain and |∆ Dir| < 90° WS > 3 WS > 5 WS > 7

23. ESA/SMOS Brightness Temperatures

24. NRL SMOS/Experimental Rain Accumulations