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.