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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 Wisconsin2: CIMSS,University of Wisconsin3: NOAA/NESDIS4: NOAA/NCEP5: ECMWF
Outline
SOI model and applications
Cloud/precipitation overlap
3-year accomplishments
Further plans
SOI Radiative Transfer Model
• 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)
Forward and adjoint simulation example
AMSR-E ObservationsGFS Simulations
Infrared Applications: MSG SEVIRI
MSG SEVIRI Comparison Results
Channel RMSE [K] Bias [K]
6.2 m 1.93 0.22
7.3 m 1.91 -1.25
8.7 m 1.54 1.17
10.8 m 1.38 0.73
12.0 m 1.37 0.64
13.4 m 1.37 1.06
Different cloud/precipitation overlap models
• 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
Different cloud/precipitation overlap models
O’Dell, Bauer, Bennartz, JAS, 2006, submitted
Currently operational at
ECMWF
1Column 2Columns 3columns 3 optimal
Different cloud/precipitation overlap models
Currently operational at
ECMWF
New scheme with much better error
characteristics
O’Dell, Bauer, Bennartz, JAS, 2006, submitted
1Column 2Columns 3columns 3 optimal
3-year Accomplishments
• 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
Further plans
• 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.