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AO: Areas solicited for contribution

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Comparisons with photometer. Measurements from Milagro campaign. Airborne Aerosol Comparisons ... lidar and a sun photometer to retrieve aerosol backscatter to ... – PowerPoint PPT presentation

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Title: AO: Areas solicited for contribution


1
AO Areas solicited for contribution
  • Validation using other satellite, airborne, or
    ground-based experiments providing independent
    measurements of wind profiles, clouds, and
    aerosols
  • Experiments to assess accuracy, resolution, and
    stability of the ADM-Aeolus instrument ALADIN
  • Assessment and validation of Aeolus retrieval and
    data processing

2
US Cal-Val Effort Investigators
  • Mike Hardesty, NOAA/ESRL
  • Dave Bowdle, University of Alabama Huntsville
  • Jason Dunion, NOAA/AOML
  • Ed Eloranta, University of Wisconsin
  • Dave Emmitt, Simpson Weather Associates
  • Brian Etherton, University of North Carolina
    Charlotte
  • Rich Ferrare NASA Langley
  • Iliana Genkova, University of Wisconsin
  • Bruce Gentry, NASA Goddard
  • Gary Gimmestad Georgia Tech Research Instrument
  • Ross Hoffman, AER, Inc.
  • Chris Hostetler NASA Langley
  • John Hair, NASA Langley
  • Michael Kavaya, NASA Langley
  • Matt McGill, NASA Goddard
  • Lars Peter Riishojgaard JCSDA
  • Chris Velden, University of Wisconsin
  • Zhaoxia Pu, University of Utah

3
Goals of the US Aeolus Cal/Val Effort
  • Obtain and analyze aircraft measurements of wind
    speed, aerosol structure, aerosol backscatter,
    aerosol extinction, cloud climatologies and
    relevant parameters under the Aeolus flight track
    using remote sensors and dropsondes, Develop
    a data set extending over the life of the mission
    from surface remote sensors and in situ sensors
    (radiosondes, dropsondes, aircraft winds) by
    gathering and analyzing measurements when Aeolus
    measurement volume coincides with sensor
    observational locations, Investigate
    correlations, differences and synergisms between
    Aeolus and Atmospheric Motion Vector winds
    derived from cloud and water vapor motion
    Investigate Aeolus data quality based on data
    assimilation studies

4
Current status
  • Proposals were reviewed within ESA and by members
    of ADM Advisory Group
  • Proposers were asked to address certain points
    and to submit revised proposals
  • Our revised proposal was accepted
  • Next step Locate funding

5
Airborne Wind Studies
  • Lower troposphere studies (Hardesty and Emmitt)
  • Apply low energy, high prf systems (HRDL and
    TODWL to investigate Aeolus performance in high
    aerosol regions
  • Study effects of mesoscale atmospheric
    inhomogeneities on Aeolus measurements
  • Structured aerosol field
  • Broken cloud fields
  • Wind shear and horizontal circulations, vertical
    motions
  • Full tropospheric studies (Gentry and Kavaya)
  • Apply TwiLite instrument for comparisons with
    Aeolus of direct detection winds as opportunities
    present (focus on severe storms)
  • Apply DAWN lidar for free tropospheric studies to
    investigate effects of clouds, wind gradients,
    etc., as opportunities present
  • Potentially compare Aeolus with notional hybrid
    of DAWN and TwilLite can fly together.

6
Airborne Aerosol Comparisons
  • Apply LaRC Airborne High Spectral Resolution
    Lidar to validate Aerolus aerosol/cloud
    extinction and backscatter data products
    (Hostetler, Hair, Ferrare)
  • Conduct flights along the Aeolus sampling curtain
    under different atmospheric conditions and
    measurement scenarios
  • Compare estimates of backscatter and extinction
    directly computed by HSRL with Aerolus
    measurements

Comparisons with photometer
Measurements from Milagro campaign
7
Airborne Aerosol Comparisons
  • Apply NASA Cloud Physics lidar for Aeolus studies
    (McGill)
  • Operate NASA CPL from a high altitude aircraft
  • Provide observations of cloud and aerosol layers
    at 1064, 532, and 355 nm
  • For elevated layers direct determination of
    optical depth is provided without assumptions on
    lidar ration

8
Surface Wind Comparisons
  • Use surface or in situ instruments (lidars, wind
    profilers, radiosondes) for long term comparison
    over the life the mission (Hardesty, Bowdle,
    Kavaya)
  • Measurements taken when Aeolus measurement volume
    coincides with instrument location
  • Perform comparisons when Aeolus measurements are
    within the domain of a mesoscale atmospheric
    model (Bowdle)
  • Use local observations to validate the model,
    then use the model to validate the instrument
  • Comparison of model, surface instruments, and
    Aeolus will address validity of applying models
    for instrument validation

9
Surface Aerosol Comparisons
  • Develop a data set for comparison of cloud and
    aerosol backscatter and extinction from a visible
    HSRL lidar operating in far northern latitudes,
    investigate wavelength differences in HSRL
    measurements (Eloranta)
  • Apply a 355 nm backscatter lidar and a sun
    photometer to retrieve aerosol backscatter to
    extinction ratios and optical depths (Gimmestad).
    Apply a forward model to compare Aeolus and
    locally measured raw data characteristics

10
Dropsonde and satellite comparisons
  • Investigate Aeolus performance in the Saharan
    Aerosol Layer and in the vicinity of tropical
    cyclones through comparisons with dropsondes
    (Dunion and Etherton). Investigate capability of
    Aeolus to represent winds in the clean tropical
    environment
  • Compare Aeolus global-coverage line of sight
    winds with current state of the art feature
    tracked atmospheric motion vectors (Genkova and
    Velden).
  • Investigate complementarities of the two data
    sets by comparing ADM winds with the global AMV
    data
  • Investigate how ADM wind profiles can be used to
    assess uncertainty in AMVs, based on assumption
    that cloud and water vapor features are ideal
    tracers

11
Data Assimilation
  • Joint Center will study ADM observations in the
    context of two data assimilation systems GFS and
    GEOS-5 (Riischojgaard)
  • Monitor innovation statistics for level 1 and 2
    products
  • Make available two different level-2 ADM wind
    data products
  • Implement KNMI-developed level-2 processor to
    create its own alternative level product
  • Perform data impact experiments with ADM Level 2
    LOS observations
  • Three phases Preparation, data acquisition,
    extended analysis

12
Next steps
  • Proposals being reviewed now
  • Notification sometime in spring
  • First meeting of cal/val team likely in mid
    summer
  • If proposal is accepted, US team will have to
    develop funding strategy to support the effort
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