why are we in paris? ………..again
DESCRIPTION
Why are We in Paris? ………..again. Melbourne, 2001. Mon dieu! Australian wine. The next meeting must return to Paris!. Mon dieu! Only California wine. These poor Americans!. Fort Collins, 2002. Jena 2003. Crush the German beer! I am going mad!!. Tsukuba 2004. Only Sake??? I WILL DIE!. - PowerPoint PPT PresentationTRANSCRIPT
Why are We in Paris?
………..again
Melbourne, 2001
Mon dieu!Australian wine.
The next meeting must return to Paris!
Fort Collins, 2002 Mon dieu!
Only California wine.
These poor Americans!
Crush the German beer!
I am going mad!!
Jena 2003
Tsukuba 2004
Only Sake???I WILL DIE!
So, Paris it is
………….But, where did we leave off?
Tsukuba BBQ
TransCom Diversity
1 Dutch = 2 IMU
}IMU
(1 Dutch)T = 1 IMU
Matrix operations
And I though groundwater hydrologists were weird!
Peter, piddy that gwondywon?
Shoichi’s partyAhh, just welby,
you dag!
These are dad’s friends?
Just smile and pretend you don’t
speak English
Shiochi’s Party continued
(1 dutch)T = IMU = 1 aggressive dessert
Yes………
I brought my camera!
Inversion Synthesis
Synthesizing independent atmospheric carbon inverse flux estimations in order to:
• Test for robust results
• Determine which methodological elements are “better”
• Test full sensitivity space
• Generate central flux estimates with comprehensive error statistics in relevant metrics
Evolution
• One of 4 new TransCom efforts proposed in Tsukuba
• Tsukuba working group and plenary session generated some elements
• Thus far, no funding acquired to cover 2/3 person-months/year (attempts were made)
• Initial team led by Kevin Gurney, Anna Michalak, Ian Enting
Good news/bad news
The bad news:
• IPCC deadline passed (though there is no explicit carbon cycle chapter)
• Little has been done since Tsukuba
The good news:
• There is interest and enthusiasm - “kick-start” this effort
• Synergize with T3L3 - a convenient test case
Emergence of assimilation estimation in
Carbon Cycle Science
Carbon flux estimation
TBMs
Remote sensing
Inventories
Atmos inversion
Inversion/assimilation
TBMs
Remote sensing
Inventories
Atmos inversion
Assimilation (“model-data fusion” etc.) is a way to optimally combine observations and process model to achieve the most
complete central estimates with errors (PDFs)
The “Pull” on inversion community
Decisionmaking communities are interested in inverse estimates
• Misunderstanding – in particular, error estimation
• Misuse – less robust/more robust
• Mistrust – varying estimates combined with misunderstanding sometimes generate mistrust
It makes sense to do a better job communicating what we do to a broader
audience
The “Push” from the inversion community
We want to know how to do inversions better
• Go from“choices” to optimal parameters
• Separate the “best” from the rest
• Explore the full sensitivity space
Develop leadership, resources, and methodologies to do this
Diagnostics
Synthesis product elements
• Report with executive summary
• Methodological introduction
• Diagnostic methods and their results
• Flux results
• Comparable metrics – temporal means, interpretable IAV segments, regional comparison, errors
• Intepretation – connection to climate variability, emerging methods, policy-relevant connections
• Peer-reviewed “glossy” report, multi-ligual, website (tutorial info, references, links)
Synthesis issues
Protocol? Specifies what is needed for inclusion in diagnostics and compare/contrast
• Needed for diagnostics
• Needed for results comparison
• Background/misc info: model details, methods, etc.
T3L3? Use as test case?
• In a useable form?
• Obsolete now?
Volunteers to help?
Funding?
Timeframe?
Sake…..Itshhh, shhtronger
than beer…..right?
The French are not affected.