Minutes of the seventh International Radiative Transfer Workshop,
June 2005
Monday
Tuesday
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Wednesday, 22/06/05
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Participants:
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CD - Cory Davis
SB - Stefan Bühler
DF - Dietrich Feist
AD - Amy Dorothy
OL - Oliver Lemke
PE - Patrick Eriksson
AB - Alessandro Batta
NC - Nathalie Courcoux
JM - Jana Mendrok
MK - Mashrab Kuvatov
SM - Stefan Müller
CM - Christian Melsheimer
UR - Uwe Raffalski
SR - Sreerekha Ravi
AJ - Adam Jaczewski
BR - Bengt Rydberg
MP - Mattias Palm
CE - Claudia Emde
Chair: CD
Presentation of the working groups
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CD: Scattering models: ARTS-MC, ARTS-DOIT, Alessandros model,
Janas model, RTTOV-SCAT
- Discussion about comparisons
- suggestion by Alessandro, uplooking simulation, 3D,
with polarization, rain
SB: ARTS users
- problems in using ARTS/QPack for up-looking instruments
- always problems with compatibility, feedback needed
- contact webpage to be created
- DF: installation of ARTS on Mac
- practical part: sort out problems in retrieval
AD: Cloud microphysical assumptions
- many free parameters
- consider bulk properties
- more information from other sources should be used, e.g. radar
DF: ARTS Beamcat
- Script for producing arts linefiles from beamcat produced by DF and OL
CE: New ARTS development
- new agenda concept
- analytical jacobians, ppath array structure
- data format, xml not practical for some cases
- Monte Carlo: include sensor characteristics for EOS MLS and surface
- include new option: sensor inside cloudbox
- port absorption from ARTS-1-0 to ARTS-1-1
- general ARTS-1-1 paper
- Documentation, new ARTS Wiki, try to keep user guide complete
- discussion about implementation of fast scattering model
MK: AMSU UTH and climatology
- water vapor daily cycle in Mediterranian Sea
- investigate this area in AMSU-B data, is it possible to investigate
boundary layer?
- trend over several days
- cycle could not be seen in AMSU data
- suggestion by AB: use meteosat data
DF: ECMWF AMSU comparisons
- AJ found bias, 3K in centre of H2O line, 15K in surface channels
- Start with 3K bias
- bias is a technical bug, could not be sorted out
- NC: no bias between RTTOV and ARTS
- possible explanation: antenna patterns, less impact on nadir radiances
Talk session
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PE: Odin-SMR cloud ice retrieval
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- Odin: 2 instruments: SMR, OSIRIS
- used Odin-SMR data, stratospheric mode (501.18 - 502.38 GHz)
- tangent points below 9.5 km
- measurement principle, blackbody radiation below ~10km
- with cloud BT decreases, would become more complicated for higher
tangent altitudes
- lower retrieval limit about 10 km
- example spectra and retrievals, cloud detection
- ice columns above 260 hPa - similar results for SMR-MH97 and ECMWF
- similar retrievals are done for EOS-MLS
- particle size distributions, large deviations, main uncertainty
- outlook: improve Odin-SMR retrievals, collaboration with EOS-MLS,
Chair: PE
CD: AURA-MLS cloud observations
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- dI for thin clouds approx. proportional to IMC
- polarization signals can be quite large, explained by horizontally
aligned ice particles
- AURA-MLS: First dual polarized measurements
- Focus on radiometer 1, measures H and V, centered at O2 line
-> not ideal for cloud detection
- polarized simulation for different particle shapes
- BT depression does not depend much on shape, but polarization
- polarization signal lerge for horizontally aligned particles
- understanding Q: low tangent altitudes -> Q>0
- measurements: polarization signal abou 10% of BT depression
- interpretation of observations: moderate aspect ratios reproduce
measurements
- conclusion: randomly oriented particle assumption seems to be justified
- MLS observations and MODIS cloud height
Discussion
(CE) higher polarization signal for other radiometers - may be assumption of
randomly oriented particles not valid
(PE) with 122 GHz mainly convective clouds are observed -> randomly oriented
particles, probably different in thin cirrus
BR: Gereration of cirrus retreival test data base
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- database content: ~100 000 cloud cases, depending on number of parameters
to be retrieved
- retrieval parameters: Column IWC, IWC profiles,
size parameters (mean mass diameter, median mass diameter, ...), shape
- Cloudnet radar data, Products: radar reflectivity factor,
inverted IWC and LWC
- microphysical assumptions: use PyARTS for computations, but not very
realistic size assumption, gamma size distribution
- try to match gamma-distr. parameters by Heymsfield 2003
- simulations using DOIT for CIWSIR frequencies
- database is under construction, plan: use information from radar
Discussion:
- (CE): Gamma distribution can be reproduced using one particle type
(CD): Does not work because you have altitude dependant size distributions
(JM) Pseudo-spherical RT modelling for emitting and scattering atmospheres
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- devide solar term and emission term cause problems in IR (2.5 - 4.0 microns)
- features from troposphere can be observed in limb geometry because of
scattering into the LOS
- rte with four partial derivatives
- simplified spherical RTE (integral form of RTE, 1D, local panarity of
atmosphere
- existing modules used: Absorption (F. Schreier)
precalculated optical properties, DISORT
- parabolic parameterization of extinction for calculation of optical depth
- source terms: emission, solar radiation in spherical geometry
multiple scattering term in plane-parallel geometry
- with solar radiation 2D problem
- validation using ARTS and KOPRA
model without multiple scattering compared to KOPRA
with multiple scattering compared to ARTS
- comparison with MCScia for different solar angles with single scattering
with multiple scattering
problems with very low sun cases
- reconstruction of measured MIPAS spectra
- intercomparison with McSCIA for more setups
(MP) Taking Bayes's Theorem seriously
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- inverse problem -> Bayes theorem
- application: electromagnetic conductivity imaging (ECI)
- discretizations in cells of constant conductivities
- ECI as probability problem
- Likelyhood : Gaussian noise A priori: Pott's model
- Motivation for using MCMC
- Definition and properties of MCMC algorithm
- Example: largest errors at conductivity boundaries
- Finding optimal size of state space, problem: correlated samples
- Metropolis coupled MCMC
(PE) Article using method in JGR, Tamminen and Kyrölä
(SB) Include this into MC retrieval scheme similar to Evans methods
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