atmospheric ar/n 2 a "new" tracer of oceanic and atmospheric circulation
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Atmospheric Ar/N 2 A "New" Tracer of Oceanic and Atmospheric Circulation. LDEO 11/05/03. Mark Battle (Bowdoin College) Michael Bender (Princeton) Melissa B. Hendricks (Princeton) David T. Ho (Princeton/Columbia) Robert Mika (Princeton) Galen McKinley (MIT/INE Mexico) - PowerPoint PPT PresentationTRANSCRIPT
Atmospheric Ar/N2 A "New" Tracer of Oceanic and
Atmospheric Circulation
Mark Battle (Bowdoin College)
Michael Bender (Princeton) Melissa B. Hendricks
(Princeton) David T. Ho
(Princeton/Columbia) Robert Mika (Princeton) Galen McKinley (MIT/INE
Mexico)Song-Miao Fan (Princeton)
Tegan Blaine (Scripps) Ralph Keeling (Scripps)
Natalie Mahowald (NCAR)
LDEO11/05/03
Funding from:NSF
NOAA GCRPFord Res. Labs
NDSEGFP
GRL Vol 30, #15 (2003)
On the agenda:
• What makes a good tracer
• Why Ar/N2
• How (and where) we measure Ar/N2
• What we observe• Comparison with models• Dirty laundry• Conclusions and future prospects
My perspective on transport modeling
Inferring fluxes
But…
How do we assess our understanding of transport?
Choose a computer model
Run a tracer with known sources through the model
Compare with model predictionswith the real world
Not all tests of transport are equal
• Different aspects of atmospheric transport are important for different species
• Ar/N2 is a good analog for CO2
The ideal tracer(one experimentalist’s perspective)
• Conservative
• Known sources and sinks, globally distributed
• Seasonally varying over land and ocean
• Measurable with great signal to noise
Ar/N2: The almost ideal tracer(one experimentalist’s perspective)
• Conservative
• Known sources and sinks, globally distributed
• Seasonally varying over land and ocean
• Measurable with great signal to noise
chemically and biologically inert
Ar/N2: The almost ideal tracer(one experimentalist’s perspective)
• Conservative
• Known sources and sinks, globally distributed
• Seasonally varying over land and ocean
• Measurable with great signal to noise
chemically and biologically inert
oceanic sources driven by heat fluxes
Ar/N2: The almost ideal tracer(one experimentalist’s perspective)
• Conservative
• Known sources and sinks, globally distributed
• Seasonally varying over land and ocean
• Measurable with great signal to noise
chemically and biologically inert
oceanic sources driven by heat fluxes
seasonal, but ocean only
Ar/N2: The almost ideal tracer(one experimentalist’s perspective)
• Conservative
• Known sources and sinks, globally distributed
• Seasonally varying over land and ocean
• Measurable with great signal to noise
chemically and biologically inert
oceanic sources driven by heat fluxes
seasonal, but ocean only
well, maybe not great…
The Ar/N2 source/sink
Atmosphere
Ar: 1.2O2: 26.8N2: 100
The Ar/N2 source/sink
Heat Fluxes
Ar/N2
Atmosphere
Ar: 1.2O2: 26.8N2: 100
The Ar/N2 source/sink
Atmosphere
Ar: 1.2O2: 26.8N2: 100
Heat Fluxes
Ar/N2
Ar/N2
O2/N2
(thermal)
A quick word on units:
Ar/N2 changes are small
Ar/N2 per meg (Ar/N2sa – Ar/N2st)/(Ar/N2st) x106
1 per meg = 0.001 per mil
Our measurement technique:
• Paired 2-l glass flasks• IRMS (Finnigan Delta+XL) 40/28 and
32/28• Custom dual-inlet system• Standards: High pressure Al cylinder
For more details: GRL paper or
David Ho
Princeton’s custom inlet system
Princeton Ar/N2 cooperative flask sampling network
Climatology ofAr/N2 seasonal
cycle
Monthly average
values shown
Multiple years (~3) stacked
Testing models with observations
Observed & modeled heat fluxes
Solubility equations
Atmospheric transport
model
Predicted Ar/N2
ECMWFor
MIT OGCM (NCEP/COADS)
TM2or
GCTMor
MATCH
Data-Model comparison
•Overall agreement
Data-Model comparison
•Overall agreement
•Phase problems
Syowa
TransportMatters
(tough to get rightover Ant-arctica)
MacQuarie
Heat fluxesMatter
(probably ECMWF-NCEP
difference)
SST relaxation term in MIT OGCM
Cape Grim
Transportand
heat fluxesmatter
Barrow
Modelgrid-cellselectionmatters
Data-Model comparison
•Overall agreement
•Phase problems
•SYO: Transport matters
•MAC: Heat fluxes matter
•CGT: Both terms matter
•BRW: Gridsize matters
Climatology ofAr/N2 seasonal
cycle
Monthly average
values shown
Multiple years (~3) stacked
What about that nasty scatter?
• Problems with analysis
• Problems with collection
• Real atmospheric variability
What about that nasty scatter?
• Problems with analysisIRMS precision ( on one aliquot = 4.0)
Transfer from flask to IRMS ( = 8.6) Total analytic uncertainty ( on a single flask =
6.7)Average two flasks.
What about that nasty scatter?
• Problems with collectionDoes bottle air = ambient air?From one bottle to next: Yes! ( = 2.6)From one site to next: No!
Improving collections
New samplinghardware at Cape
Grim
(and elsewhere)
What about that nasty scatter?
• Real atmospheric variabilityOceanic ( = 0.6 – 1.2)
Atmospheric ( = 0.8 – 2.1)
Interannual vs. Synoptic
InterannualVariability
Ocean+
Atmosphere
In summary…
• Problems with analysisNot negligible ( = 5.1 on a “collection”)
• Problems with collectionBig deal site-to-siteNew hardware helps!
• Real atmospheric variabilityDoesn’t look too big, but…Synoptic?
Conclusions and the future…
• Ar/N2 a promising “new” tracer
• General data-model agreement• Better observations to come• Continental interior sites?
• Need Ar/N2 as active tracer in OGCMs
• Working on variability with MATCH
Correlated variability in Ar/N2 and O2/N2