Using TODWL and Optical Particle Counters to Investigate Aerosol Backscatter Signatures from Organized Structures in the Marine Boundary Layer D.A. Bowdle University of Alabama in Huntsville G.D. Emmitt and S.A. Wood Simpson Weather Associates Working Group on Space-Based Lidar Winds Frisco, Colorado, June 29 - July 1, 2004

CONTENTS EXPERIMENT ANALYSIS RESULTS SUMMARY

Joint research project by ONR and NPOESS IPO Investigate data processing issues related to future space-based wind lidar operations Develop calibration/validation procedures for all wind profiling systems (ground-based, airborne, space-based) Conduct basic research on lower tropospheric winds and aerosols in the marine and continental boundary layers MOTIVATION

TODWL Transceiver µm, coherent detection 4-6 mJ, 330 nsec (FWHM), 80 Hz 10 cm telescope two axis scanner,  30 &  120 deg, side door mount digitization rate 100 MHz ~7-10% total system efficiency INSTRUMENTS Aircraft Platform NPS CIRPAS Twin Otter Naval Postgraduate School Center for Interdisciplinary Remotely-piloted Aircraft Studies Optical Particle Counters TODWL Scanner PCASP  m FSSP  m CAPS  m

OPERATIONS LocationSchedule Flight PlansMBL Database Straight and level km runs Along-wind and cross-wind runs Multiple altitudes over same ground track Near surface, near and above inversion Series 1: February 9-15, 2002 Series 2: March 12-15, 2002 Series 3: February 8-21, 2003 Series 1: Monterey area & San Joaquin River Series 2: Monterey area Monterey to Boulder via Las Vegas Series 3: Monterey area, ocean & land 8 flights, approx 30 hours multiple scanning patterns concentrate on February 20, 2003

MEASUREMENTS* beam direction beam direction (neglecting pitch) scattering volume ViVi V ac R i,j = | V ac | (  j +  t i ) ii particle probes ground track, heading, ground velocity (neglecting yaw, sideslip) X j = | V ac |  t j *Backscatter-related scan patterns along-track RHI step-and-stare forward stare nadir stare

BACKSCATTER EQUATION* - 1 For a diffuse atmospheric target, with volume backscatter coefficient , For calibrations against a hard target, with diffuse reflectance , *generalized from ACLAIM backscatter analysis [Steve Hannon, 1999] Combining the above equations gives a non-dimensionalized formulation:

BACKSCATTER EQUATION - 2 When TODWL points straight forward, make the following assumptions: Combine the terms that have no range dependence Express the backscatter equation using non-dimensional variables baseline terms perturbation terms

ANALYTICAL APPROACH For a pulsed coherent 2-  m Doppler lidar, analysis of ABSOLUTE BACKSCATTER VARIABILITY requires absolute backscatter calibration at range R ht ; requires correction for nominal range response function; requires correction for atmospheric extinction; requires correction for atmospheric refractive turbulence; assumes system stability during a given data run; RELATIVE BACKSCATTER VARIABILITY avoids all of the above requirements.

exclude wild velocities exclude backscatter dropouts exclude major pulse tail artifacts account for aircraft pitch ANALYTICAL METHODS Dropouts & Anomalies CorrelationFiltering TODWL time-range plots (Hovmuller) aerosol time-size plots scale analysis variance analysis for TODWL - compute mean V &  at each range - compute residual V &  at each pixel for OPC, compute mean, residual N m (Normalized) Turbulent Residuals 1-s data – good V’ and  ’ most ranges 1-s data – poor OPC count statistics filtered V’ &  ’ may not resolve waves filtered OPC improves count statistics

RESULTS* SAMPLING CONDITIONS sharp inversion ~450 m; winds below inversion NNW ~17 m/s; RH ~70% at ~30 m, ~90% --> 45% across inversion, ~30% above inversion horizontal legs at ~35 m (x1), ~400 m (x1), ~900 m (x3), 1400 m (x1) HOVMULLER PLOTS IN RADIAL VELOCITY AND SNR stratification by aircraft pitch eliminates unphysical “striping”, and markedly reduces the observed variation along individual coherent features stratified plots still exhibit residual non-coherent variation along features radial velocity variation across scene up to 8 m/s; along features <1 m/s SNR variation across scene (fixed range) up to 6 dB, along features TBD promising results from preliminary attempts to correct for atmospheric attenuation and lidar range response, even before pitch stratification velocity-backscatter correlations observed below, at, above inversion OPTICAL PARTICLE COUNTERS large particles, with poor count statistics, often dominate 2-  m backscatter *Planned graphics unavailable due to severe case of Microsoft fever

CONCLUSIONS ATMOSPHERIC FEATURES turbulent waves in aerosol and velocity, multiple scales aerosol-velocity correlations will bias DWL LEO winds, even in clear air nature & magnitude of bias will depend on shot integration strategy ANALYTICAL CHALLENGES beam elevation offset, pitch fluctuations, altitude fluctuations measured vs. modeled absolute backscatter OPC operational status OPC count statistics SCIENCE POTENTIAL substantial information content remains untapped in TODWL database

RECOMMENDATIONS - 1 INSTRUMENTATION AND OPERATIONS TODWL – modify programmed scans to account for pitch offset in mounting  TODWL – add option for automatic dither in beam elevation  TODWL – improve frequency, quality of ground-based radiometric calibrations  OPC – verify PCASP, FSSP, CAPS operational status on every flight  OPC - add flight-level sensor that has higher volume sampling rate OPC ANALYSIS METHODS  replace contiguous-point temporal smoothing by feature-composited averaging  replace measured size distributions from individual OPC’s by aerosol-model- constrained composites from FSSP, PCASP, CAPS forward, CAPS backward  augment composited size distributions using Monte Carlo & Poisson statistics

RECOMMENDATIONS - 2 ANALYSIS POTENTIAL – MEAN CONDITIONS Backscatter: model using cabin data (OPC); derive from TODWL Attenuation: model using cabin data (OPC, T, RH); derive from TODWL Coherence Length: model using cabin data (V, T, RH); derive from TODWL ANALYSIS POTENTIAL – TURBULENT CONDITIONS scale analysis: power spectrum, structure function, autocorrelation analysis of variance: composite wave, inter-wave, intra-wave, sensor, sampling aerosol microphysics: identify and quantify sources of aerosol variability

ACKNOWLEDGMENTS This work was funded by the Office of Naval Research through the Center for Interdisciplinary Remotely-piloted Aircraft Studies and by the Integrated Program Office of NPOESS SPAWAR and ONR 35/SBIR Program provided the lidar and supported its integration into the CIRPAS Twin Otter IPO co-funded the lidar adaptation to the Twin Otter. IPO solely funded the mission planning, flight hours, data collection, and the post-flight installation of the lidar in a trailer for inter-flight research.