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Towards Passive Microwave Radiance Assimilation of Clouds and Precipitation Ralf Bennartz 1 , Tom Greenwald 2 , Andrew Heidinger 3 , Chris O’Dell 1 , Martin Stengel 1 , Kenneth Campana 4 , Peter Bauer 5 1: Atmos. & Oceanic Sci. ,University of Wisconsin 2: CIMSS ,University of Wisconsin

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Towards passive microwave radiance assimilation of clouds and precipitation

Towards Passive Microwave Radiance Assimilation of Clouds and Precipitation

Ralf Bennartz1, Tom Greenwald2, Andrew Heidinger3,

Chris O’Dell1,Martin Stengel1, Kenneth Campana4, Peter Bauer5

1: Atmos. & Oceanic Sci.,University of Wisconsin

2: CIMSS,University of Wisconsin

3: NOAA/NESDIS

4: NOAA/NCEP

5: ECMWF


Towards passive microwave radiance assimilation of clouds and precipitation

  • Outline and Precipitation

  • SOI model and applications

  • Cloud/precipitation overlap

  • 3-year accomplishments

  • Further plans


Soi radiative transfer model
SOI Radiative Transfer Model and Precipitation

• Hybrid multi-stream solution method (doubling plus iteration)

(Heidinger et al. 2006; O’Dell et al. 2006)

• Implementation

- Less scattering: 2-stream solution

- More scattering: 4-stream solution

• Forward, tangent linear and adjoint models integrated into CRTM


Accuracy of results eddington and soi versus monte carlo model
Accuracy of Results and Precipitation(Eddington and SOI versus Monte-Carlo model)


Towards passive microwave radiance assimilation of clouds and precipitation

GFS Simulations

AMSR-EObservations




Towards passive microwave radiance assimilation of clouds and precipitation

  • Different cloud/precipitation overlap models and Precipitation

  • Conventional approach uses cloud cover to subdivide NWP pixel in cloudy/precipitation

  • New approach derives two or three optimal columns based on subscale distribution of precipitation columns with similar optical properties

  • Numerically efficient (2-3 radiative transfer calculations per NWP grid point)

  • Highly accurate against independent column/Max-Random-overlap reference

  • Optimal approach reduces errors due to cloud overlap from maximum values of 5-10 K to values < 1K


Towards passive microwave radiance assimilation of clouds and precipitation

1Column

2Columns

3columns

3 optimal

Currently operational at ECMWF

O’Dell, Bauer, Bennartz, JAS, 2006, submitted


Towards passive microwave radiance assimilation of clouds and precipitation

1Column

2Columns

3columns

3 optimal

New scheme with much better error characteristics

Currently operational at ECMWF

O’Dell, Bauer, Bennartz, JAS, 2006, submitted


Towards passive microwave radiance assimilation of clouds and precipitation

  • 3-year Accomplishments and Precipitation

  • Fast forward RT model (SOI) developed, tested and integrated in CRTM (3 publications)

  • Tangent linear and adjoint model developed, tested, and integrated in CRTM

  • Bias GFS/SOI statistics for passive microwave and infrared

  • Fast and accurate new cloud overlap scheme for use in NWP radiance assimilation (forward/adjoint); manuscript submitted


Towards passive microwave radiance assimilation of clouds and precipitation

  • Further plans and Precipitation

  • Monitor bias statistics over longer time period, especially:

    • Fully include scattering (need more complete GFS input data)

    • Biases in IR including scattering

  • Precipitation assimilation:

    • Include cloud diagnostics to generate precipitation rate

    • Further test and integrate cloud overlap with NCEP/GFS.