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 Mission Concept

• 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
• lt 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
Science Synergies for the Hybrid DWL Approach

• 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)

5
NPOESS Hybrid DWL
6
The Hybrid Instrument

• 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)

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 lt 4 m/s error Blue lt 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 (NASAs CAMEX and NOAAs 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
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 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

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