Simulating a Dual Technology DWL at 833km

Simulating a Dual Technology DWL at 833km

G. D. Emmitt and S. A. Wood, SWAM. J. Kavaya, NASA/LaRC

B.Gentry, NASA/GSFC

Working Group on Space-based Lidar WindsJune 28- July 1, 2005

Welches, Oregon

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 – < 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)

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.

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)

Parameter Coherent Directmol

Wavelength (microns) 2.05 .355

Energy/pulse (Joules) .250 .2 (@.355)

PRF (design) (Hz) 10 100

Optical Efficiency (total) .7 .3

Mixing Efficiency .4 N/A

Detector Efficiency .8 .8

Collector Diameter (meters)

.2 1.0 (HOE)

Integration Time (sec) 12 12

Wallplug Efficiency .03 .07 (@ 1.064)

Weight TBD TBD

Total Power (watts)

(w/o scanner)

82 (peak and average)

850 Peak

(250 average)

NPOESS Hybrid DWL

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)

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

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

Locations for current wind profiles from rawinsondes

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

Coherent sub-system coverage

Full tropospheric/lower stratospheric wind soundings, 10% duty cycle with direct detection subsystem combined with

coherent detection coverage of lower troposphere

Direct sub-system coverage

Example Adaptive Targeting coverage

Example of AT coverage with CONUS interests only

Red: direct detection coverage; Blue: coherent detection coverage

Example of vertical AT coverage

With backgroundaerosol distribution

With convectivelypumped aerosoldistribution

Red: < 4 m/s errorBlue: < 1.5 m/s error

Adaptive Targeting OSSE(performed at NASA/GSFC)EXAMPLE TARGETED LOCATIONS FOR DWL OSSE

( White symbols: full lidar coverage; Red symbols: targeted cove rage)

1999

Forecast impact of 10% duty cycle AT

Model: GEOS -2 Recon. Verification: ECMWF Nature Run

Control: - Conventional Data + Perfect TOVSCTW - Control + Cloud Tracked Winds1 m/s Wind - Control + Doppler Wind Lidar (RMSE = 1 m/s)Adaptive Targeting - Control + Adaptive Targeting of DWL Observations (~10% duty cyc le)

Current wind profiles for NWP P3I coherent 100% duty

P3I direct 10% duty Full potential for an NPOESS orbit

Blue indicates percent of 300 x 300 km areasnot sampled by observing system

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

Backup slides

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.

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 improvehurricane 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

DWLs greatly improvehurricane track predictions