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Performance characteristics and design trades for an ISS Hybrid Doppler Wind Lidar

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 M ission S cience W orkshop Miami, 2011. Outline. Instrument design issues and data products The DLSM and OSSEs

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Performance characteristics and design trades for an ISS Hybrid Doppler Wind Lidar

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  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. Data Goals for Wind Lidar on ISS Numbers in () are desired

  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)

  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 * Doppler Lidar Simulation Model • 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.

  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)

  15. Clouds and Aerosols

  16. 532 nm Total Attenuated Backscatter

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

  18. 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.

  19. Simulated thin and sub-visual cirrus

  20. GWOS/ISS Single shot threshold sensitivity

  21. Volcanic Subvisual Cirrus Clouds Background Maritime PBL Continental PBL Land m Natural Variability of 2 m Backscatter CALIPSO (derived from 532um) Mid-Upper Troposphere Enhanced Lower Troposphere Ocean GWOS/ISS Surface 10 10 10 10 10 10 10 10 10 -11 -10 -9 -8 -7 -6 -5 -4 -3 Backscatter (m sr ) -1 -1

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

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

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

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

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

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

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

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

  30. 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.

  31. 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

  32. JEM-EF

  33. 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)

  34. 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

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

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

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