sara c. tucker, alan brewer, mike hardesty, scott sandberg, ann weickmann, dan law

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007

A study of range resolution effects on accuracy and

precision of velocity estimates Applications of ship-based 2µm Doppler lidar

data

to space-based lidar performance Sara C. Tucker*, Alan Brewer, Mike

Hardesty, Scott Sandberg, Ann Weickmann*, Dan

LawOptical Remote Sensing Group, Chemical Sciences Division

(CSD)Earth System Research Laboratory, NOAA

*Also with: Cooperative Institute for Research in Environmental Science

University of Colorado, Boulder, CO, NOAA/ESRL/CSDWorking Group on Space-Based Lidar Winds, Snowmass, Colorado, July 17-21, 2007


HRDL Winds Characterizations of the Gulf of Mexico and Galveston Bay

• Aerosol measurements: used to determine the expected levels of return signal available in this region

– Closure in aerosol studies at 355 nm using ozone profiling lidar (OPAL), cavity ring-down, and in-situ instruments. Will attempt to scale the backscatter and extinction numbers to HRDL wavelength for comparison studies.

– Comparisons with CALIPSO and HSRL

• Winds and turbulence information: used to determine the potential performance, including errors, based on sample rate/volumes, etc, in space-based Doppler lidar measurements.

• Cloud coverage: used to determine the percentage of time a satellite can make measurements at each altitude in this area.


HRDL wind and aerosol products for understanding Marine

Boundary LayersComposite products

• Horizontal mean wind profiles

• Profiles of relative aerosol strength and aerosol layering

• Vertical winds and vertical mixing/turbulence statistics

• Horizontal (near surface) mixing/turbulence statistics

• Aerosol and mixed layer (i.e. Boundary layer) heights

• Wind speed and directional shear profiles

Individual Scan Products

• Boundary layer dynamic features: rolls, surface streaks, thunderstorm outflows, etc

• Ship/oil-platform plume detection


Objective: To study the effect of variability in the small-scale wind fields, and mean wind shear, on expected performance.

• Reprocess NOAA’s High Resolution Doppler Lidar (HRDL) TexAQS 2006 measurements with 500m range gates and then,

• look at accuracy and precision of velocity estimates as compared to 30 m products.


Accuracy and Precision

• Accuracy – how far off is the mean? Bias.• Precision – what is the standard deviation of the

measurements?• Averaging more ACFs or Spectra typically means better

precision – but may not mean the results are accurate.

High accuracy, low precision

Low accuracy, high precision


System and processing parameters

Typical processing• 10 lag ACF• 30 m range gate • =10 averaged

ACF/gate 1000 ACF/estimate

Reprocessing• 10 lag ACF• 501 m range gate • =167 averaged

ACF/gate 16,667 ACF/estimate

• 3 m sampling (10 ns)• 200 ns PW: 30 m• 100 pulse averaging• Scanning: 5 deg/sec


PPI Scan at 45° Elevation: With Shear

Mean of 30m data – 500m RG data



Closest 30m data – 500m RG data


Resulting Wind Profiles


Instrument and atmospheric variance profiles

Atmospheric vertical variance

Wideband SNR

Instrument precision


500 m Range Gate Study: Preliminary Results

• Average SNR usually about the same as 500 m range gates except in cases of strong turbulence and/or approaching “saturation.”

• Precision Improvements:

– 16.67 x more points (for a total of 16,667) should yield ~4X improvement in precision – for same SNR.

– We see ~2X improvement in precision. In other words, instrument “variance” drops by an average factor of ~4 instead of 16.67.

• Profile Wind speed “error”, Mean: -0.03 m/s, Std. Dev: 0.50 m/s.• Profile Wind direction “error”, Mean: 0.34°, Std. Dev: 4.24°.

• Next for the 500 m. range gate study

– Closer look at differences in atmospheric variance estimates – are we underestimating instrument variance?

– This study assumed full azimuth scanning at 45° - what happens if we only have 2 stare angles?


HRDL-TexAQS 2006: Relative 2µm Aerosol Backscatter

Major Saharan dust events


2µm backscatter

• True, HRDL was not calibrated for aerosol for TexAQS.

• HRDL avg. power constant throughout experiment (within 5% error on power-meter measurement).

• HRDL provided “relative” aerosol layer info during the experiment.

• In-situ measurements of particle size distribution, composition, absorption, extinction, etc. available

• Aerosol backscatter is affected by:– Humidity

– Composition

– Distributions/ Concentration


Surface area size distributions and HRDL SNR

A B C D E

Image credit: D. Coffman, PMEL, NOAA

Integrated 2-10µm surface areaHRDL SNR at 215 m altitude

Correlation ~0.9


Particle size distributions: concentrations and backscatter

Likely hard

target returns


Backscatter dependence on RH and Particle Solubility

Strong dependence on RH

Some dependence on Solubility


2µm Backscatter: Caveats

• CNR fit depends on:– Refractive turbulence– Transmission/extinction (estimated in Mie models)

• Ship plume – strong refractive turbulence• Possible long-term system changes due to high vibration• Mie scattering models still “young”

– Particle refractive index is highly composition dependent): Incorporate variable mass fractions of Ammonium Sulfate, Sea Salt, and Dust


Continuing work• Boundary Layer Heights – 600 m over Gulf

• Streak Analysis and integration of

HRDL data with models

• Comparisons of HRDL with in-situ-based calculations of Backscatter, then…

• Compare HSRL and CALIPSO and characterize the relationship between 1 and 2 micron backscatter in this area.

• Extend the process to other areas.

sara c. tucker*, alan brewer, mike hardesty, scott sandberg, ann weickmann*, dan law

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sara c. tucker, alan brewer, mike hardesty, scott sandberg, ann weickmann, dan law