11C JPLOSSE by K6p19B

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									National Aeronautics and
Space Administration

Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California




                                     Kevin W. Bowman
                             contributions from:
               Annmarie Eldering, Joao Teixiera, Meemong Lee
      National Aeronautics and
      Space Administration

      Jet Propulsion Laboratory
                                            Science Requirements to
      California Institute of Technology
      Pasadena, California                 Measurement Requirements.
Uncertainty in climate feedbacks                                        CLARREO design
                                                  Spatio-temporal
                       AM2
                                                  sampling
  + feedback


                                                 Spectral and spatial
                            Low cloud amount         resolution,
                                                  frequency range
                                                        SNR
               CAM2
  - feedback




                                                                 Virtual observations
                   Impact analysis




      Can CLARREO reduce climate
      projection uncertainty within mission
      lifetime?
     National Aeronautics and
     Space Administration

     Jet Propulsion Laboratory
     California Institute of Technology
     Pasadena, California
                                          JPL Simulation System Architecture


1. Phenomena                    2. Observation          Mission
   Database                        Scenario
                                                       Concepts
 Preparation                        Design                                     Measurement
                                                                               Community
Phenomena                                           4. Instrument
                                3. Input Signal                        Instrument
  Model                                              Performance
                                   Database
                                                     Requirement        Concepts
 MOZART                           Generation
                                                     Formulation
 GeosChem
 IMPACT,
 Model E,
 CAM3,
                                   Radiance
 CM2,                              Transfer         5. Measurement   6. Geophysical
 Regional-                          Model               Database        Retrieval        Algorithms
 WRF                              LBLRTM               Generation       Analysis
                                  LIDORT
                                  CRTM
Model                                                 Instrument
Community                                             Response
                                                        Model
                                                                     7. Geophysical
                                                                        Database
                                                                                       8. Prediction
                                                                                         Accuracy
                                           Generic                     Generation         Analysis
                                                                                                       3
                                           TES, OMI,AIRS,
                                           CLARREO
                                                                                      OSSE overview==
      National Aeronautics and
      Space Administration

      Jet Propulsion Laboratory
      California Institute of Technology
      Pasadena, California
                                           Observation Scenario Design

“Orbiter” is a mission design tool that can be used to simulate different orbits,
spatio-temporal coverage, spectrometer parameters (spectral resolution,
range, etc.)




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National Aeronautics and
Space Administration

Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
                                     Spectrometer parameters

                                             Key spectrometer parameters such
                                             as spectral resolution and signal-to-
                                             noise ratio can be chosen




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National Aeronautics and
Space Administration

Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
                                     Wavelength range
                                                 Spectra can be
                                                 calculated from far-
                                                 infrared, mid-infrared
                                                 through visible
                                                 wavelengths based on
                                                 the sampled
                                                 atmosphere




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               National Aeronautics and
               Space Administration

               Jet Propulsion Laboratory
               California Institute of Technology
               Pasadena, California
                                                             Spectrometer simulation
                                                                                             SNR
           Resolution



                       Linearity                                                                   Full well
                                                                        Transmission, QE
    Kernel shape


                                                    Radiance to                                   Saturation
        Convolution                                 Photons              Attenuation              clipping
Fov, Res                                                                                                               Noise
                    (W/m^2) /micron                                                                            x       gain
                                                                                                                               offset
 Resample                                                                            Sensed                        Photon
                                                                                                      +
               ((W/cm^2) / sr) / cm-1
                                                                                    Spectrum                        Noise
           +             Instrument offset
                                                                  ADC              Digitization
  RTM
  Spectrum
                                                                                   Measurement
                                                                                                          +            Electron
                                                                                   Spectrum                            Noise
               Wavelength range

Lat, Lon, Altitude, Time
       National Aeronautics and
       Space Administration

       Jet Propulsion Laboratory
       California Institute of Technology
       Pasadena, California
                                            Radio Occultation Measurement
Geometry of an acquisition


                                                                     P    PW
                                                               N  a1  a2 2
                                                                     T    T
     National Aeronautics and
     Space Administration

     Jet Propulsion Laboratory
     California Institute of Technology
     Pasadena, California
                                               Radio Occultation Simulation

        Input                               Forward      GPS Signal
    Refractivity                          Propagation     at Receiver
                                                                        Add Noise
       profile                            Phase Screen   Amplitude &
    or 3D fields                           or Raytrace       Phase




                                                           Bending
     Retrieved                                                          Doppler Shift
                                           Inversion        Angle
    Refractivity                                                          optional
                                             (Abel)       vs Impact
      Profile                                                            diffraction-
                                                          Parameter
                                                                         correction
         P     P
N  a1      a2 W
         T     T2
      National Aeronautics and
      Space Administration

      Jet Propulsion Laboratory
      California Institute of Technology
      Pasadena, California
                                           Simulation philosophy

•   In order to reduce uncertainty in climate model projects:
     – Choose uncertainties in climate processes that are strongly covariate with the
       uncertainty in the future climate state, i.e., E[ qpresent xfuture] ~ large
     – Make observations that are sensitive to the variations in those processes
•   The current IPCC indicates that climate feedbacks are the greatest source
    of uncertainty in future climate projections.
•   Cloud feedbacks are the most uncertain.
•   Low-level cloud feedbacks, in particular, the response of stratocumulus to
    anthropogenic forcing are the most uncertain.
•   Processes driving stratocumulus formation occur at small spatial scales, ~1-
    10 km
•   Consequently, observations must be commensurate with those scales.
•   Current global climate models can not resolve these scales
•   Regional climate models can.
    National Aeronautics and
    Space Administration

    Jet Propulsion Laboratory
    California Institute of Technology
    Pasadena, California
                                         Tasks

• Use the UCLA/JPL JIFRESSE regional climate model to
  simulate stratocumulus clouds (and possibly cirrus)
  forced by the NCAR CAM3
• Sample fields with
   – spatial scales: 4, 15, 50,100 km
   – spectral resolution: 1, .5, .1 cm^-1, 0.02 microns
   – Calculated from far-infrared through visible
• Calculate covariance between model values (cloud top
  height, particle size, etc.) and radiance output for
  differing spatial, spectral resolutions and coverage
• Based on covariance, assess
   – spatial, spectral requirements
National Aeronautics and
Space Administration

Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
                                     Backup
   National Aeronautics and
   Space Administration

   Jet Propulsion Laboratory
   California Institute of Technology
   Pasadena, California
                                        CLARREO Challenges

• Global climate models generally can not resolve
  scales below 100 km.
• Critical climate feedbacks, in particular, cloud
  feedbacks are governed by processes that
  operate on scales 10 km or less.
• Regional models driven by global models can be
  used to explore these scales
• Synergistic use of Far-IR, IR, and Visible spectra
  can provide greater sensitivity to these finer
  scale processes than each band separately.
   National Aeronautics and
   Space Administration

   Jet Propulsion Laboratory
   California Institute of Technology
   Pasadena, California
                                        Far-IR, IR, Vis synergy

• Argue that the combination of Far-IR, IR, Vis
  wavelengths taken together provide more info
  that separately.
• This assertion can/should influence instrument
  design.
• Current examples, AIRS-MODIS synergy
National Aeronautics and
Space Administration

Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
                                        Mission definition
                           Orbiter-2D                Orbiter tool:
                                                          Interactive orbit design,
                                                          Footprint analysis,
                                                          Coverage analysis, and
                                                          Exploration range setting.

                                                     Exploration range
                                                          Observation scenario
                                                          Instrument performance.

                                                     The exploration range can be
                                                          submitted to OSSE system
                                                          for input radiance spectra
                                                          and measurement spectra
                                                          simulation.




                                                              OSSE overview==

                                                                                15
   National Aeronautics and
   Space Administration

   Jet Propulsion Laboratory
   California Institute of Technology
   Pasadena, California
                                        Radiance simulation


• Using community
  models with
  proven heritage
  for
  ‘monochromatic’
  simulations
  including
  scattering, where
  appropriate
• LBLRTM
• LIDORT                                                 OSSE overview==
                                                                        16
National Aeronautics and
Space Administration

Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
                         Low Cloud Climate feedbacks
         National Aeronautics and
         Space Administration

         Jet Propulsion Laboratory
         California Institute of Technology

IPCC 2007: “Cloud feedbacks remain the largest source of uncertainty”
         Pasadena, California




                B.Soden/G.Stephens



 GFDL and NCAR have opposite low cloud cover sensitivity to CO2 doubling
                   National Aeronautics and
                   Space Administration

                   Jet Propulsion Laboratory
                   California Institute of Technology
                                                          CLARREO OSSE analysis
                   Pasadena, California

Ensemble
perturbations:
                                                                            CLARREO design   Virtual observations
• Physical parameters, e.g.
                                                        Spatio-temporal
mixing coefficient                                      sampling
• Initial conditions, e.g. ocean
state
• Numerical parameters, e.g.
time-step
• Structural, e.g., stochastic
parameterizations                                       Spectral
                                                        resolution, range
                                                        SNR




       Uncertainty analysis




 Does instrument characteristics (spectral,
 spatio-temporal resolution) sufficient to
 reduce climate uncertainty within mission
 lifetime?

								
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