Minutes of the sixth International Radiative Transfer Workshop, June 2004

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BREDBECK  2004  Minutes
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Wednesday, 23/06/04

Group Work summary 
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SSP Interface (Rekha)
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* PyArts will do averaging from DDA and puts the data into the database
* PyArts module to export data from the database to arts


Limb sounder group(Carmen)
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* input for limb sounding instruments - odin, smiles, mls
* discussed instrumental characteristics, vertical and horizontal
   resolution, orbits
* frequency optimization
SE - information about working groups at EUMETSAT of IASI for nadir
   instruments


Sensor polarization (Mattias)
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* surface reflection and polarization
  - Christian to finish section on polarization in AUG
  - check the angle dependence of rotating mirror for AMSU-B
SE - (90 - scan angle)
SE - from vertical to horizontal as you go from nadir to limb
* sensor demonstration
* reconsider mixer part - dual mixers
* put example control files in ARTS package
SB - follow the convention in ARTS for example files (.arts.in)
PE - a documentation for the example files in AUG.


Retrieval algorithms (Adrian)
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* discussion on different retrieval approaches
  - Patrick showed Bayesian approach
  - peter brought forward stochastic approach
  - levenber-marquardt and other methods were discussed
  - Regularization methods also were discussed


Matlab group (Oliver)
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* ATOVS part - reading routines in Matlab are much slower
  - conclusion - compiler has to be checked
ME, OL, CJ -  discussion on Matlab compilation
CE - implementing GMT in atmlab
OL - It is already decided to use GMT for AMSULAB


Polarization (Claas)
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* discussed claas's results
  - 2 main sources 
  - negative Q, the main source is coming from below
  - positive Q, polarization coming from sides
  - An orientation distribution will give the same effect as using a
    horizontal particle with a different aspect ratio
CM - justification - randomly oriented particle is similar to 
  spherical particle


Size distribution (Bengt)
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* particle size distribution in cirrus clouds
  - cory has used heymsfields distributions on
  - further look is to look at effect of this different distributions
     on radiative properties
  - using ARTS to study this
* can give an estimate on the retrieval error


UTH retrieval (Carlos)
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* AMSU data to derive a long range UTH climatology 
* 3 different approaches in Chalmers and Bremen
  - simple linear regression with 1 amsu-b channel, 5-9%
  - complicated NN regression with amsu-a and, 7.5%
  - multi physical regression with amsu-a and amsu-b, 3-8%
* 3 approaches use different definitions for UTH
  - weighted UTH, mean UTH, mean UTH resp.
* different data - ECMWF, radiosonde, ECMWF resp.
* issues 
  - which training dataset is better?
  - why present regressions seems to over-estimate low UTH values
    and under-estimate high UTH values
* future 
  - 3 articles on all methods 
  - testing all regression to evaluate relative performance using ECMWF data
  - AMSU synthetic database including more realistic - clouds, ground
PE -  Peter's work of retrieval of isolines also could be added
SE - why not using Bayesian algorithm, regression will carry on the
     errors in the training data set to the retrieval
CJ - speed is an issue 
SB - climate studies, basically we want to look at radiances 
   -how sensitive is the radiance to upper troposphere humidity 
SE - This would bring the same biases in the ECMWF to the retrieval
A long discussion on this followed.


GMT plots (Oliver)
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- Nice map plots
- GMT is free
  
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