Simulating a Dual Technology DWL at 833km

1. Simulating a Dual Technology DWL at 833km G. D. Emmitt and S. A. Wood, SWA M. J. Kavaya, NASA/LaRC B.Gentry, NASA/GSFC Working Group on Space-based Lidar Winds June 28- July 1, 2005 Welches, Oregon

2. Proposed NPOESS DWL MissionConcept • Acquire useful data • Demonstrate instrument architecture • Hybrid DWL • Direct detection for molecular backscatter • Coherent detection for aerosol backscatter • NASA SHADOE scanner • 2 tracks, biperspective • 3 m/s wind accuracy • 0-20 km altitude • Adaptive targeting • < 100% duty cycle to maintain NPOESS P3I margins • Select high impact targets • Hurricanes/typhoons (DoD, DOC) • Air quality “episodes” (DoD, DOC) • Mid and high latitude cyclones (DoD, DOC) • Civilian and military aircraft operations (DoD, DOT) • Stratospheric/Tropospheric Exchange (NASA, DoD, IPO)

3. The Hybrid DWL Approach • First proposed in 1995 as WOS/H (Wind Observing Satellite/Hybrid) • Capitalize on the strengths of both technologies • Coherent detection for probing lower troposphere with high velocity accuracy below clouds and in regions of enhanced aerosols • Direct detection for broad coverage of the mid/upper troposphere (+ stratosphere) with modest accuracy • Lower total mission costs by reducing investment in “very big” individual lidars; sharing a launch; sharing a platform; sharing pointing control, data collection, mission management and science team, etc.

4. The hybrid approach will provide full tropospheric wind observations sooner, with much of the accuracy, resolution and coverage needed by tomorrows global and regional models The direct detection molecular DWL sub-system would, in its first mission, provide useful wind observations in cloud free regions of the mid/upper troposphere and lower stratosphere The coherent DWL sub-system would immediately meet the science and operational IORD requirements throughout the troposphere in regions of high aerosol backscatter (dust layers, clouds, PBL aerosols) Science Synergies for the Hybrid DWL Approach

5. NPOESS Hybrid DWL

6. Uses two lidar subsystems One direct detection, the other coherent Subsystems have complementary measurement properties Direct detection subsystem Detects doppler shift from atmospheric molecules Operates everywhere, 0 to 20 km altitude Provide useful wind observations in cloud free regions Coherent DWL subsystem Meets requirements in regions of high aerosol backscatter (dust layers, clouds, PBL aerosols) The Hybrid Instrument

7. The Adaptive Targeting Mission • Adaptive targeting of tropospheric wind profiles for high impact weather situations • Hurricanes/typhoons (Navy) • Air quality “episodes” (Army) • Mid and high latitude cyclones (DoD) • Civilian and military aircraft operations (DoD) • Stratospheric/Tropospheric Exchange (USAF) • Coherent detection sub-system (wedge scanner or HOE) • 100% duty cycle • Lower tropospheric and enhanced aerosol/cloud winds • CMV height assignment • Reduce DAS observation error by ~2-3 m/s • Depth of PBL • Initial Condition Adaptive Targeting (ICAT) for managing direct detection • Direct detection (molecular) sub-system (using HOE) • 10-15% duty cycle (aperiodic, i.e. adaptively targeted) • Cloud free mid-upper tropospheric/ lower stratospheric winds

8. Primary Targets for Hybrid/AT* • Significant Shear regions • Requires contiguous observations in the vertical. Thus both direct and coherent detection technologies are needed. • Divergent regions • Requires some cross track coverage. Identified by NCEP adaptive targeting scheme(s) • Partly cloudy regions • Requires measurement accuracy weakly dependent upon shot integration (i.e., coherent detection). • Tropics • Tropical cyclones (in particular, hurricanes & typhoons). Requires penetration of high clouds and partly cloudy scenes. *AT: Adaptive Targeting

9. Locations for current wind profiles from rawinsondes

10. Coherent sub-system coverage Global coverage of lower tropospheric wind profiles, clouds and elevated aerosol layers using 100% duty cycle of coherent subsystem.

11. Direct sub-system coverage Full tropospheric/lower stratospheric wind soundings, 10% duty cycle with direct detection subsystem combined with coherent detection coverage of lower troposphere

12. Example Adaptive Targeting coverage

13. Example of AT coverage with CONUS interests only Red: direct detection coverage; Blue: coherent detection coverage

14. Example of vertical AT coverage With background aerosol distribution Red: < 4 m/s error Blue: < 1.5 m/s error With convectively pumped aerosol distribution

15. Adaptive Targeting OSSE(performed at NASA/GSFC) 1999

16. Forecast impact of 10% duty cycle AT

17. Current wind profiles for NWP P3I coherent 100% duty Blue indicates percent of 300 x 300 km areas not sampled by observing system P3I direct 10% duty Full potential for an NPOESS orbit

18. Evaluation of adaptive targeting of DWL observations • IPO-funded studies at NOAA/NCEP and NASA/GSFC show adaptive targeting (10-15% duty cycles) products can rival 100% duty cycle • IPO and THORPEX funded OSSEs at NCEP and GSFC • Quantify AT impacts • Evaluate methods of identifying targets • Field programs (NASA’s CAMEX and NOAA’s WSR) demonstrated the value of adaptive targeting • Many military needs would be met with targeted wind observations. * OSSE: Observing System Simulation Experiment

19. Backup slides

20. IPO funded Hybrid feasibility study • 1999-2001 Developed “reference systems” which could be used in trade studies. • Defined a common data product as target • Scaled each technology to obtain the same data product. (yielded very large systems) • Defined a hybrid system that would yield the same data products; in some respects better.

21. Potential Impact of new space-based observations on Hurricane Track Prediction Based on OSSEs at NASA Laboratory for Atmospheres Tracks Green: actual track Red: forecast beginning 63 hours before landfall with current data Blue: improved forecast for same time period with simulated wind lidar Lidar in this one case Reduces landfall prediction error by 66% DWLs greatly improve hurricane track predictions

22. DWLs greatly improve hurricane track predictions Potential Impact of new space-based observations on Hurricane Track Prediction Based on OSSEs at NASA Laboratory for Atmospheres • Tracks • Green: actual track • Red: forecast • Blue: improved forecast for same time period with simulated wind lidar • Lidar in this one case • Indicates the hurricane will make landfall