1. Performance characteristics and design trades for an ISS Hybrid Doppler Wind Lidar G. D. Emmitt and S. Wood Simpson Weather Associates Charlottesville, Va ISS Winds Mission Science Workshop Miami, 2011

2. Outline Instrument design issues and data products The DLSM and OSSEs The global coverage The sampling pattern The key atmospheric variable for evaluating the expected performance of a hybrid DWL – Clouds Cloud climatology Cirrus in the tropics – Aerosols Background and enhanced – Wind variability Simulated performance profiles Summary

3. AttributeGoal Vertical depth of regard (km)25 Vertical resolution Tropopause to 25 km Top of BL to tropopause Surface to top of BL 4 2 1 (.25) Horizontal resolution (km)350 (35) # of tracks1 # of perspectives within target volume 2 Horizontal component error (m/s) Above BL Within BL (includes sampling RMSE) < 3 2 (1) Numbers in () are desired Data Goals for Wind Lidar on ISS

4. Instrument Design Issues Vertical coverage in cloudy regions (much of the globe) – Hybrid approach Direct detection molecular for volumes with low aerosol content (mid/upper troposphere and lower stratosphere) Coherent detection for volumes with clouds and sufficient aerosols (dust layers and lower troposphere) – Number of telescopes – Dwell times

5. ISS Wind Lidar Concept Hybrid Doppler Wind Lidar: – Coherent detection (2 um) for aerosol and cloud returns – Direct detection (.355 um) for molecular returns Two fixed telescopes provide forward and aft perspectives Variable dwell times allow a high spatial resolution (~ 28km) for the coherent system while allowing the direct system longer integration (~ 84 km)

6. Instrument parameters used in performance simulations for WISSCRS flown on the ISS *At the fundamental 1.06um for direct detection. The utility wavelength is.355um ** Includes: Pre LRE optics (.48), IF (.7) and LRE throughput (.74) Parameter WISSCRS/ISS Coherent(2um) WISSCRS/ISS Direct (.355um) Orbit altitude (km)350 Orbit inclination (deg)52 Nadir angle (deg)35 Energy/pulse (J)*.25.8 PRF (Hz)10100 Aperture (m).5 EAP.4915.7 # perspectives per cycle22 Optical eff**.51.25 Heterodyne mixing eff.36 Detector eff.8.5 Integration time (sec)12(4,.1)12 Misalignment loss.42 Beam split..48 Filter throughput.17 Edge sensitivity.007 Recycling factor/margin1.6 Conversion eff.45 Wallplug eff *.014.092 Duty cycle (%)100 Power required (Watts)178869 Vertical layer depth (m)1000/500/2502000/1000 Beta(50) backscatter (/m/sr)2.8 x 10-9

7. The DLSM Used since 1988 to simulate DWL performance for OSSEs using inputs from Nature Runs. – Clouds – Subgrid scale wind variability – Aerosol distributions Simulate both direct and coherent detection Stress realistic characterization of random and systematic errors.

8. Doppler Lidar Simulation Model

9. DLSM* simulations for use in OSSEs Emphasis on the tropics. Scaling GWOS down to 350km Uses GWOS instrument performance parameters listed in a prior slide Clouds in T511 Nature Run modified to conform to ISCCP coverage statistics Has been understating very thin to subvisual cirrus effects which would be very positive for coherent detection coverage and slightly negative for direct detection accuracies. * Doppler Lidar Simulation Model

10. ISS Wind Lidar Coverage for three orbits

11. The Sampling Pattern Illuminated volume – Coherent (250m long cylinder, ~ 2m diameter footprint) Spectral domain processing provides information on turbulence intensity, BL depth, precipitation fall velocities – Direct (2000m long, ~ 50m diameter) Accuracy a function of intensity of return, presence of clouds/aerosols could be derived. Sampling pattern, a ground perspective Pattern over a hurricane

12. 4 second dwell pattern for both direct and coherent (fore and aft perspectives)

13. 4 second dwell pattern (fore and aft sampling)

14. Single shot coherent samples (~ 700meter intervals)

16. Clouds and Aerosols

17. 532 nm Total Attenuated Backscatter

18. Seze, Pelon, Flamant, Vaughn, Trepte and Winker

21. Sub-visual Cirrus Until this year, simulations done using the DLSM in support of OSSEs have not included sub-visual cirrus derived from the nature run Recent published studies of very thin and subvisual cirrus have documented a climatology (5 years, in one case) of these upper tropospheric clouds. We have modified the DLSM to generate sub- visual cirrus from the ECMWF T511 Nature Run and are currently assessing the realism of the derivation.

25. Simulated thin and sub-visual cirrus

30. GWOS/ISS Single shot threshold sensitivity

31. Natural Variability of 2  m Backscatter (m sr ) 10 -11 10 -10 10 -9 10 -8 10 -7 10 -6 10 -5 10 -4 10 -3 Land Mid-Upper Troposphere Volcanic Subvisual Cirrus Maritime PBL Continental PBL Ocean Background Enhanced Lower Troposphere Surface GWOS/ISS CALIPSO (derived from 532um) Clouds

32. Simulated WISSCR’s performance using the DLSM with the T511 ECMWF Nature Run

33. Aerosol/cloud subsystem of the Wind Lidar on ISS 20 – 10 N Cirrus returns Opaque clouds Aerosols

34. Aerosol/cloud subsystem of the Wind Lidar on ISS 10 -0 N

35. Aerosol/cloud subsystem of the Wind Lidar on ISS 0 – 10 S

36. Aerosol/cloud subsystem of the Wind Lidar on ISS 10 -20 S

37. Molecular subsystem of the Wind Lidar on ISS 10 – 0 N

38. Molecular subsystem of the Wind Lidar on ISS 0 - 10 S

39. Molecular subsystem of the Wind Lidar on ISS 10 -20 S

40. Summary Platform attitude drift does not appear to be a major factor in DWL data quality using pointing knowledge over pointing control. Clouds will be a major factor in DWL coverage – Direct detection (molecular) is negatively effected by the high clouds in the tropics. – However, coherent provides winds within most of the high level clouds and within the lower troposphere below. The hybrid technology approach provides the best vertical coverage for science investigations in the tropics – A direct detection subsystem is critical to tropospheric/stratospheric exchange investigations – The coherent subsystem is critical for accurate, high spatial resolution measurements in cloudy scenes and in the lower troposphere.

43. Japanese JEM-EF – Accommodates 9 experiment payloads – Nominal 500kg payloads – 3kW 120VDC per payload – 5 Mbits/second download data rates for single payload –.8 x 1.0 x 1.8 meters – Access to cooling loop for thermal management

44. JEM-EF

45. Key accommodation issues related to instrument performance High frequency vibrations (> 1 Hz) Slow attitude changes (+- 10 degrees) Power to PL (average and peak) Thermal management Orbital debris Data rates (uplink and downlink)

46. Accommodations Summary The ISS offers an attractive orbit for focusing the Wind Lidar resources on the lower latitudes where ageostrophy is most dominant. Assuming that an ISS mission would be regarded as a research science with a focus on the tropics, instrument lifetime, duty cycle and data downloads would be negotiable. At this time, no accommodation “show stoppers” have been identified. Just completed a NASA evaluation within the IDL and MDL at GSFC

47. Molecular subsystem of the Wind Lidar on ISS 52N – 52S

48. Aerosol/cloud subsystem of the Wind Lidar on ISS 52N – 52S