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 Law Optical 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/CSD Working Group on Space-Based Lidar Winds, Snowmass, Colorado, July 17-21, 2007

Lidar Working Group on Space-Based 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.

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 HRDL wind and aerosol products for understanding Marine Boundary Layers Composite 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

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

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

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

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 PPI Scan at 45° Elevation: With Shear Mean of 30m data – 500m RG data

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 PPI Scan at 45° Elevation: With Shear Closest 30m data – 500m RG data

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

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 PPI Scan at 45° Elevation: With Shear

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

Instrument and atmospheric variance profiles Atmospheric vertical variance Wideband SNR Instrument precision

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 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 Profile Wind speed “error”, Mean: 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?

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 HRDL-TexAQS 2006: Relative 2µm Aerosol Backscatter Major Saharan dust events

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

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 Surface area size distributions and HRDL SNR ABCDE Image credit: D. Coffman, PMEL, NOAA Integrated 2-10µm surface area HRDL SNR at 215 m altitude Correlation ~0.9

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 Particle size distributions: concentrations and backscatter Likely hard target returns

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 Backscatter dependence on RH and Particle Solubility Strong dependence on RH Some dependence on Solubility

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

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