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?. Potential of Simulator Assessments led by GRP. Hiro Masunaga Hydrospheric Atmospheric Research Center, Nagoya University. Satellite data simulator. Satellite data simulators Simulate satellite data, of course. T, q v , q r , … → satellite measured radiance

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Potential of simulator assessments led by grp

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Potential of Simulator Assessments led by GRP

HiroMasunaga

Hydrospheric Atmospheric Research Center, Nagoya University


Satellite data simulator
Satellite data simulator

  • Satellite data simulators

    • Simulate satellite data, of course.

      • T, qv, qr, … → satellite measured radiance

    • Radiative transfer code + user interfaces

      • Sub-grid cloud generator (COSP)

      • Antenna pattern convolution, PSD library (SDSU)

    • Growing need for multiple sensor package

      • TRMM/GPM: PR/DPR + TMI/GMI (+ VIRS)

      • A-Train: CPR + CALIOP + MODIS + AMSR-E + AMSU + AIRS …

  • Applications

    • Climate/Cloud-resolving model evaluation

    • Retrieval algorithm development for future missions

    • Radiance based data assimilation

GRP 22nd meeting, Tokyo


Multi sensor simulator p ackages
Multi-sensor simulator packages

  • COSP: CFMIP Observation Simulator Package

    • CFMIP (http://cfmip.metoffice.com/COSP.html)

  • CRTM: Community Radiative Transfer Model

    • NOAA (http://www.star.nesdis.noaa.gov/smcd/spb/CRTM/)

  • ECSIM: EarthCARE Simulator

    • ESA (Voors et al, 2007)

  • J-simulator: Joint Simulator for Satellite Sensors

    • JAXA/U Tokyo (http://www22.atwiki.jp/j-simulator/pages/14.html)

  • RTTOV: Radiative Transfer Model for TOVS

    • UK MetOffice/ECMWF (Matricardi et al. 2004; Bauer et al., 2006)

  • SDSU: Satellite Data Simulator Unit

    • Nagoya U (http://precip.hyarc.nagoya-u.ac.jp/sdsu/)

  • Goddard SDSU

    • NASA GSFC (http://atmospheres.gsfc.nasa.gov/cloud_modeling/sdsu.html)

  • ISSARS: Instrument Simulator Suite for Atmos Remote Sensing

    • JPL (under development)

  • GRP 22nd meeting, Tokyo


    Who would need it
    Who would need it?

    • Algorithm developers?

      • Most likely have their own RT codes already.

    • GCM/CRM developers

      • Would be happy if user-friendly simulators are available.

      • Best (or least?) motivated to diagnose and refine model performance.

    • GCM/CRM users

      • Would be also happy with simulators.

      • Best available to spend time on model assessment.

    Satellite simulators have potential user demands primarily from the modeling communities.

    GRP 22nd meeting, Tokyo


    Why do we need it
    Why do we need it?

    N(D), ρp,…

    N(D), ρp,…

    Masunaga et al., BAMS (2010)

    GRP 22nd meeting, Tokyo


    • Goddard SDSU applied to a

    • WRF simulation

    • AMSR-E 36.5 GHz V (top)

    • MODIS 11 m (middle)

    • CloudSatdBZ(bottom)

    • Masunaga et al., BAMS (2010)

    GRP 22nd meeting, Tokyo


    Cloud and precip top heights cth and pth
    Cloud and Precip Top Heights (CTH and PTH)

     TRMM PR&VIRS

     NICAM+SDSU

     CloudSat CPR

     NICAM+SDSU

    CTH

    CTH

    MJO wet

    MJO dry

    MJO wet

    MJO dry

    CPR echo-top height

    Infrared Tb

    PTH

    PTH

    CPR 10-dBZ height

    PR echo-top height

    Too much snow

    In the cloud model

    ?

    ?

    MJO wet

    MJO dry

    MJO wet

    MJO dry

    GRP 22nd meeting, Tokyo


    Missing 94 ghz echoes above 8 km
    Missing 94-GHz Echoes above 8 km

    The 94-GHz back-scattering coefficient begins to be saturated due to non-Rayleigh scattering as snow content increases.

    94-GHz

    GRP 22nd meeting, Tokyo


    Rayleigh regime

    Wavelength >> 2πr

    Geometric optics regime

    Wavelength << 2πr

    2r

    GRP 22nd meeting, Tokyo


    A modification to snow microphysics
    A Modification to snow microphysics

    Snowflake mass spectrum = m(D)n(D)=aDb N0exp(-lD)

    where a=2.5x10-2 kg m-2 and b=2 (original=Grabowski, 1998)

    a=5x10-4 kg m-1 and b=1 (modified)

    Less saturated

    SWC=1g/m3

    0.1

    g/m3

    Smaller snowflakes

    GRP 22nd meeting, Tokyo


    Psd impact on the cth pth histogram
    PSD Impact on the CTH/PTH Histogram

    TRMM

    MJO wet

    MJO dry

    MJO wet

    MJO dry

    NICAM

    Modified

    Original

    MJO wet

    MJO wet

    MJO dry

    MJO dry

    MJO wet

    MJO wet

    MJO dry

    MJO dry

    GRP 22nd meeting, Tokyo


    Model assessment with simulators
    Model assessment with simulators

    Model

    Grid resolution,

    PBL schemes,…

    Satellite data simulator

    GCM

    cumulus/cloud parameterizations, …

    Particle Scattering

    Size distribution, Crystal habit, …

    CRM

    cloud microphysics, …

    Measuring principles

    Vis, IR, or Microwave

    Passive or active

    GRP 22nd meeting, Tokyo


    Tasks
    Tasks

    • Close communication is crucial among scientists with different background (modeling vs. remote sensing) to foster new ideas to develop assessment metrics.

      • Simulator-related sessions in int’l conferences

        • ex.) AGU fall meetings in a past few years.

    • GRP led efforts for simulator-based assessment

    GRP 22nd meeting, Tokyo


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