BJohnson_1473_IGARSS_2011_oral_final.pptx
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    BJohnson_1473_IGARSS_2011_oral_final.pptx BJohnson_1473_IGARSS_2011_oral_final.pptx Presentation Transcript

    • Ice-Phase Precipitation Remote Sensing Using
      Combined Passive and Active Microwave Observations
      Benjamin T. Johnson
      UMBC/JCET & NASA/GSFC (Code 613.1)
      Benjamin.T.Johnson@nasa.gov
      Gail Skofronick-Jackson
      NASA/GSFC (Code 613.1)
      IGARSS 2011 – Vancouver, Canada
    • Figure 1.: whiteout conditions during a snow storm.
      2/22
    • Introduction
      • Midlatitude/Winter precipitation is difficult to measure using radars or radiometers alone.
      • Precipitating clouds consist of a wide range of particles with variable shape, size, number density, and composition, and microwave radiation is sensitive to these properties
      • Furthermore, ice clouds, water clouds, and gases and attenuate/emit microwave radiation
      B. Johnson IGARSS 2011
      3/22
    • Physically-based microwave precipitation remote sensing methods require (at least):
      • A physical description of the atmosphere and surface properties
      • Physical descriptions of hydrometeors (PSD, shape(s), composition)
      • Appropriate relationships between physical and scattering/extinction/backscattering properties
      • An inversion method for retrieving the desired physical properties given observations
      B. Johnson IGARSS 2011
      4/22
    • Relevant Key Problems
      • Uncertainties the physical description of the atmosphere: distribution of CLW, WV; particle composition, size distribution, and shape.
      • No current method for validating MW scattering properties of ice-phase hydrometeors.
      Present Retrieval Approach
      • Physical method using “consistency matching” -- adjust simulations until consistent with PMW and radar observations across multiple wavelengths (e.g., Meneghini, 1997).
      • Pros: Simple to implement, works equally over land and water
      • Cons: “matches” may not represent reality, geometric issues ignored (NUBF, beam matching)
      • Important note: the uncertainty due to unknown particle shape is orders of magnitude greater than other known sources of uncertainties.
      B. Johnson IGARSS 2011
      5/22
    • Retrieval Schematic
      (1) Radar-only Retrieval
      Large set of
      Radar-Retrieved
      Vertical Profiles of PSD/IWC
      Observed Reflectivities
      (Zku, Zka)
      Inversion
      Z-S, DWR, etc.
      Attenuation “Correction”
      (2) Forward Model
      Physical - Radiative
      Database
      Physical Model
      Precip. & Atmos.
      Hydrometeor
      Model
      Ext., Scat., p(Q), Z
      Radiative Transfer
      Model
      (3) Radar/Radiometer Retrieval
      Simulated Radiances
      (TBsim)
      TB Constrained PSD/IWC Profiles
      PMW Retrieval
      Algorithm
      Observed Radiances
      (TBobs)
      6/22
    • Observed Reflectivities and Passive Microwave
      TBs during the 2003 Wakasa Bay Experiment
      B. Johnson IGARSS 2011
      7/22
    • (Const. Density Spheres)
      Retrieval Inputs
      at each vertical level
      Environment:
      Pressure, Temperature, Humidity, Cloud Water Content
      Microphysics:
      Particle Density, Shape, PSD Type
      Observables:
      Zm,14, Zm,35, DWR
      Forward Dual Wavelength Ratio Retrieval Method
      Update PIA for air, clouds, and precip.
      (A14, A35)
      Starting at storm top (ztop) down to z=0
      PIA-corrected Reflectivities
      Ze,14, Ze,35
      B. Johnson IGARSS 2011
      8/22
      Match DWR with D0 (3.67/L) in Database; compute N0
      Is
      DWR  1?
      no
      yes
      Ze,35-IWC retrieval, infer D0 / N0
    • WBAY 03: Dual Wavelength Ratio, and retrieved N0, and D0
      (assuming a single constant particle density)
      B. Johnson IGARSS 2011
      9/22
    • 10/22
    • 11/22
    • 12/22
    • Part 1 comments:
      • The basic retrieval works surprisingly well using only constant-density spheres
      • approx. 5 K RMS error in precipitating regions, simply by adjusting the CLW and particle density.
      • However, constant-density spheres likely are not representative of the true distribution of mass and sizes of particles within the observed volume of the atmosphere…
      Improvements:
      • Inclusion of well-known size-density relationships for spheres (following Brown and Ruf, 2007),
      • Include sets of non-spherical “realistically shaped” hydrometeors
      B. Johnson IGARSS 2011
      13/22
    • (Fixed IWC = 1.0 g m-3)
      Constant Density Spheres
      Mass-Density Relationships
      Magono and Nakamura (1965)
      Mitchell et al. (1990)
      Locatelli and Hobbs (1974)
      Barthazy (1998)
      UW-NMS (Tripoli, 1992)
      14/22
    • Retrieved log10(IWC) [g m-3] using size-density relationships (Brown and Ruf, 2007)
      15/22
    • B. Johnson IGARSS 2011
      16/22
    • Retrieved IWC [g m-3] :: “Realistic” particle shapes, exponential PSD
      B. Johnson IGARSS 2011
      17/22
    • 18/22
    • 19/22
    • Final comments:
      • The present method is designed for testing advances in the physical-radiative properties of a physically based retrieval algorithm
      • The choice of particle shape and size distribution appears to be the largest uncertainty in physically-based precipitation retrieval algorithms (most certainly renders them ill-posed)
      • So, prior knowledge of the particle shapes and sizes should significantly constrain physically based retrievals
      • However, this requires that one has already computed the necessary physical-radiative properties ahead of time!
      B. Johnson IGARSS 2011
      20/22
    • Next Steps for this work:
      • (un-break my radiative transfer model… )
      • Create complete database of IWC as a function of reflectivity, dual-wavelength ratio, and particle shape.
      • Add other non-spherical shapes (in progress, e.g., Kuo, G. Liu, others)
      • Add melting particles (in progress)
      • Apply retrieval to GPM satellite simulator data (T. Matsui, WK Tao, et al.) as a alg. dev. testbed.
      • Incorporate database(s) into official GPM combined radar/radiometer algorithm
      • currently assumes constant-density spheres(?)
      B. Johnson IGARSS 2011
      21/22
    • B. Johnson IGARSS 2011
      22/22