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Megha Tropiques
MADRAS algorithm status:
BRAINFranck Chopin (LMD/ICARE)Nicolas Viltard (CETP)
Principle of BRAINBRAIN is a bayesian-based algorithm meant to retrieve
rain and precipitation profile from TMI data
Its retrieval database is made of co-located PR and TMI
data
It works over land and ocean with slightly different
principles and database (only 85 Ghz over land)
Colocation example: Orbit 10915Diamonds: PR pixelsBold Diamons: nadir PR PixelPlus: TMI pixelsBold stars: Middle of TMI swath
=> Position of PR and TMI relative center swath changes during the TRMM revolutions
Blue line : nadir PR Pixel
Green Lines: Middle of TMI swath
Principle of BRAIN database building
Flow-diagram of BRAIN retrieval part
DATABASE of Profiles and TB
Retrieval database Test Database
Bayesian approachfor retrieval
Retrieved rain
Retrieval Error
assessment
BRAIN database characteristics and “sanity checks”
Database histogram of rain intensity occurence Error and S. Dev of
error for validation dbase
Brain vs. PR for validation dbase
Retrieval example
“Reference”: PR rain at 37 Ghz resolution
Flow-diagram of BRAIN TB simulation
DATABASE of Profiles and TB
Retrieval database Test Database
Bayesian approachfor retrieval
Retrieved rain
Retrieval Error
assessment
TB Simulationfrom profiles
RTM Error
assessment
MicropysicsTesting
TMI TB
Tbs observed
Tbs simulated from PR swath +cloud model
TB simulation from dbase “scenes” and comparison with TMI
Tbs observed
Tbs simulated from PR swath +cloud model
The 85GHz is particularly sensitive to ice parameterization and specially the density-diameter law used in RTM
Two realisations of TB 85 Ghz H, with only the mass-diameter that was changed...
TB simulation and influence of ice parametrisation in RTM
Flow-diagram of BRAIN for other satellites
DATABASE of Profiles and TB
Retrieval database Test DatabaseTB Simulationfrom profiles
Bayesian approachfor retrieval
Retrieved rain
Retrieval Error
assessment
Database for Other
platforms
RTM Error
assessment
MicrophysicsTesting
TMI TB
Example: adaptation for SSM/I beta version
No transfert radiative performed, just Tb and rain resolution changed
V21H19
H37 H85
GREEN : SSMI HISTOGRAM
RED :RESCALED TRMM
HISTOGRAM
HISTOGRAM COMPARISON BETWEENSSM/I AND TRMM
Flow-diagram of BRAIN integrated with all platforms
DATABASE of Profiles and TB
Retrieval database Test DatabaseTB Simulationfrom profiles
Bayesian approachfor retrieval
Retrieved rain
Retrieval Error
assessment
Database for Other
platforms
RTM Error
assessment
MicrophysicsTesting
Combining different instruments for global estimates
TMI TB
Conclusions
Still a lot of work to be done...Adaptation to MADRAS (code part) should start early 2006 (6
months)MADRAS beta database should start also early 2006 (3 months)Complete base with radiative transfer should be done by end of 2007
with improved ice-phase (probable start after AMMA)Use of 157 Ghz will be studied in parallel
Open questions
What about coupling of MADRAS and SAPHIR ?Should we use ancillary data ?What about coupling with MSG ?
