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![Page 1: Synthesis of Arctic System Carbon Cycle Research Through Model-Data Fusion Studies Using Atmospheric Inversion and Process-Based Approaches (SASS PI Meeting.](https://reader034.fdocuments.net/reader034/viewer/2022042718/56649ecd5503460f94bda4d3/html5/thumbnails/1.jpg)
Synthesis of Arctic System Carbon Cycle Research Through Model-Data Fusion Studies Using Atmospheric Inversion and Process-Based
Approaches(SASS PI Meeting – 26-27 March 2006)
A. David McGuireInstitute of Arctic Biology - University of Alaska Fairbanks
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Project Participants
• McGuire - UAF
• Melillo, Kicklighter, Peterson - MBL
• McClelland – Texas A&M
• Follows, Prinn - MIT
• Zhuang - Purdue
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Project Overview
• Background
• General Questions
• General Strategy
• Tasks
• Time Line
• Education and Outreach
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Interactions of High Latitude Ecosystems with the Earth’s Climate System
Regional Climate Global Climate
High Latitude Ecosystems
ImpactsWater and
energyexchange
Exchange ofradiatively
active gases(CO2 and
CH4)
Delivery of
freshwater to Arctic Ocean
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32-44% of global soil carbon stored in high-latitudes
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Land
Atmosphere
CO2 CH4
Arctic Ocean
DOC, DIC, POC
Permafrost
CO2
PacificOcean
AtlanticOcean
Total C
Key Fluxes of Carbon in the Arctic System
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General Questions Guiding Research
1. What are the geographic patterns of fluxes of CO2 and CH4
over the Pan-Arctic region and how is the balance changing over time? (Spatial Patterns and Temporal Variability)
2. What processes control the sources and sinks of CO2 and CH4 over the Pan-Arctic region and how do the controls
change with time? (Processes and Interactions)
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ArcticTerrestrialand MarineEcosystemsObservations of
Arctic System CO2 and CH4 dynamics:- experiments- fluxes- inventories- disturbance regimes- remote sensing- atmospheric and marine concentrations
Process-based estimatesof Arctic System
CO2 and CH4 dynamics
Atmospheric inversion estimatesof Arctic System CO2 and CH4 dynamics
General Strategy: Model-Data Fusion
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Tasks
1. Conduct model-data fusion studies with process-based models of various components of high latitude terrestrial C
dynamics including a. Terrestrial CO2 (McGuire lead) and CH4 exchange (Zhuang
lead), and b. Transfer of C from high latitude terrestrial ecosystems to
the mouth of rivers in the Pan-Arctic Drainage Basin (Melillo/Peterson/McClelland/Kicklighter lead)
2. Conduct model-data fusion studies with a process-based model of marine CO2 exchange in oceans adjacent to the high
latitude terrestrial regions (Follows lead)
3. Improve atmospheric inversions of CO2 and CH4 across high latitude regions through better incorporation of data and process-understanding on CO2 and CH4 dynamics (Prinn lead).
4. Project synthesis (All).
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Soil
Temperatures
at
Different
Depths
Upper Boundary Conditions
Heat Balance Surface
Snow Cover
Mosses
Frozen Ground
Thawed Ground
Frozen Ground
Lower Boundary Conditions
Heat Conduction
Heat Conduction
Heat Conduction
Moving phase plane
Moving phase plane
Lower Boundary
H(t)
Soil Thermal Model
H(t) Organic Soil
Mineral Soil
Output
Prescribed Temperature
Prescribed Temperature
Snow DepthMoss Depth
Organic Soil DepthMineral Soil Depth
Vegetation type;Snow pack; Soil moistureSoil temperature
Terrestrial Ecosystem Model (TEM) couples biogeochemistry and soil thermal dynamics
Tool for Process-Based Terrestrial CO2 Exchange
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Observed and simulated atmospheric CO2 concentrations at Mould Bay Station, Canada
(-119.35oW, 76.25oN) during the 1980s
-75 -60 -45 -30 -15 0 10 25 g C m-2 yr-1
Sink Source
90°
60°
30°
Spatial patterns of change in vegetation carbon over the twenty year period spanning from 1980-2000 as simulated by the Terrestrial Ecosystem Model (TEM)
Strategy to evaluate seasonal exchange of carbon dioxide simulated by terrestrial biosphere models
Incorporation of freeze-thaw dynamics into the Terrestrial Ecosystem model improves the simulation of the seasonal and decadal exchange of carbon dioxide exchange with the atmosphere
(Zhuang, Euskirchen, McGuire, Melillo, Romanovsky)
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Soil ThermalModule(STM)
Hydrological Module(HM)
Terrestrial Ecosystem
Model(TEM)
MethaneConsumptionand Emission
Module
(MCEM)
Soil Temperature Profile Active Layer Depth
Water Table andSoil Moisture Profile
Labile carbon Vegetation Characteristics
40 35 20 10 0 –1
Source Sink
(g CH4 m-2 year-1)
Tool for Process-Based Terrestrial CH4 Exchange
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Atmospheric CH4 Concentration (AM)
Ebullition (EB)
Plant-MediatedEmission (PM)
Diffusion (DSA)
Methane Consumption and Emission Module
(Oxic Soil)
CH4 Consumption (MC)
(Anoxic Soil)CH4 Production (MP)
Water Table
Lower Boundary
Soil / Water Surface
Upper Boundary
(Zhuang et al., 2004 GBC)
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Net Methane Fluxes in the 1990s
Net Methane Fluxes
= 49 Tg CH4 yr-1
Emissions= 56 Tg CH4 yr-1
Consumption= -7 Tg CH4 yr-1
(Zhuang et al., 2004GBC)
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Vegetation
Soil OrganicMatter
Soil Inorganic Carbon
CO2(g)
abvR
CO2(aq)
HCO3-
CO3-2
rootR
RH
CO2 (g)CO2 (g)
AlkalinityCO2(aq)
Shaded area = Modified TEM
soilR
DOC Stream Export
CO2 (g)
ChemicalWeathering
POC
GPP
erodePOCleachDOC
harvest
leachCO2 leachALK
evadeCO2
fire
Tool for Transfer of C from Land to Ocean
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U. S. Geological Survey:National Research Program
National Stream Quality Accounting NetworkDistrict Offices AK, CA, GA, OR, TX, WI
Alaska Science Center
Universities: Florida State University
University of Southern MississippiYale University
With thanks to:Environment Canada
Water Survey of CanadaYukon Territorial Government
Alaska Inter-Tribal CouncilAlaska Department of Fish and Game
Bureau of Land ManagementNational Park Service
U S Fish and Wildlife ServiceCitizen Volunteers
Yukon River Project ParticipantsYukon River Project Participants
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2002 between Eagle and Stevens Village
2003 between Stevens Village and Pilot Station
2004 between Whitehorse, Canada, and Eagle
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0.36 Tg C12 km3
0.79 Tg C24 km3
2.63 Tg C76 km3
3.63 Tg C104 km3
6.55 Tg C188 km3
00
0.50.5
11
1.51.5
22
2.52.5
33
3.53.5
44
4.54.5
55
PorcupinePorcupineRiverRiver
Tanana RiverTanana River Yukon RiverYukon Riverat Eagleat Eagle
Yukon RiverYukon Riverat Stevens at Stevens
VillageVillage
Yukon RiverYukon Riverat Pilot at Pilot StationStation
Flu
x (
g C
yr
Flu
x (
g C
yr-1-1
x 1
0 x
101
212 ))
DIC
PIC PIC
DOCDOC
POCPOC
Total C ExportTotal Water Discharge
Carbon Flux, Water Year 2002Carbon Flux, Water Year 2002
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Annual DOC Leaching from Contemporary Ecosystems in the Yukon River Watershed
during the 1990s
0 1 20.5 4 8 16 22
g C m-2 yr-1
TEM 6.0
Total: 1.0 Tg C yr-1
or 1.15 g C m-2 yr-1
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PARTNERS Rivers
River km3/yMackenzie 308Yukon 200Kolyma 132Lena 525Yenisey 620Ob’ 404
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Tools for Ocean C Transfers
• MIT Ocean Circulation Model
• MIT Ocean Biogeochemistry Model
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Physical Framework
• MITgcm • Global configuration, 1/4o resolution• Cubed-sphere grid configuration• Polar oceans resolved, dynamic ice model• Dimitris Menemenlis (JPL), Chris Hill (MIT) et al.
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Physical model – flow speed
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Current Ocean Biogeochemistry Model
• Explicit C, P, O, Fe, Alk (Ca) cycles• Prognostic variables DIC, O2, PO4, DOP, FeT, Alk• Air-sea exchange of CO2, O2• DOC
– linked to DOP with fixed stoichiometry– No continental sources– “Semi-labile”, 6 month lifetime
• Simple parameterization of export production (P, Fe, light limitation)
• Optional explicit ecosystem (2 phytoplankton classes, single grazer, explicit Si cycle)
• Physics – coarse res, generally no Arctic Ocean!
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Previous work:Interannual variability of air-sea CO2 flux
Ocean modelMcKinley et al. (2004)
Atmospheric inverse modelBousquet et al. (2000)
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This work: Biogeochemistry
• “Offline” model driven by ECCO2 physics• Hemispheric configuration• Estimate air-sea fluxes, distributions, etc
1992 – 2001• Continental sources/treatment of DOC, DIC• Explore sensitivity to lifetime of DOC• Simple export production model (explicit
ecosystem)
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Tool for Atmospheric Inversions of CO2 and CH4
• MATCH: Model of Atmospheric Transport and Chemistry
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Inverse Modeling
Air Parcel Air Parcel
Air Parcel
Sources Sinks
transport transport
sinkssourcestransport ++=∂∂
tC
Sample Sample
solved formodeledobserved
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Dargaville, McGuire, and Rayner2002 (Climatic Change)
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Figure 2. MATCH simulates effect of North Atlantic Oscillation on CH4
AGAGE observations (red) versus MATCH (black) at MaceHead, Ireland
NAO (+) winds
NAO (-) winds
MIRROR PLOT
MIRROR PLOT
Ref: Chen & Prinn, 2005; Chen, 2004
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Time Line of Research
• First Year – Organize data sets and finish up any necessary model development
• Second Year – Conduct model-data fusion studies with the models
• Third Year – Project Synthesis
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Education and Outreach
• Undergraduate and Graduate CurriculumCoursesMIT Course on Global Climate Change
• Undergraduate, Graduate, and Postdoc ResearchGraduate Students – PurdueMIT – UROP
Postdocs – UAF, MIT
• Public OutreachPresentations: Policy Meetings/WorkshopsMIT Global Change ForumMIT Knight Science Journalism Fellows
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End of slideshow