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

Project Participants

• McGuire - UAF

• Melillo, Kicklighter, Peterson - MBL

• McClelland – Texas A&M

• Follows, Prinn - MIT

• Zhuang - Purdue

Project Overview

• Background

• General Questions

• General Strategy

• Tasks

• Time Line

• Education and Outreach

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

32-44% of global soil carbon stored in high-latitudes

Land

Atmosphere

CO2 CH4

Arctic Ocean

DOC, DIC, POC

Permafrost

CO2

PacificOcean

AtlanticOcean

Total C

Key Fluxes of Carbon in the Arctic System

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)

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

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).

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

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)

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

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)

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)

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

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

2002 between Eagle and Stevens Village

2003 between Stevens Village and Pilot Station

2004 between Whitehorse, Canada, and Eagle

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

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

PARTNERS Rivers

River km3/yMackenzie 308Yukon 200Kolyma 132Lena 525Yenisey 620Ob’ 404

Tools for Ocean C Transfers

• MIT Ocean Circulation Model

• MIT Ocean Biogeochemistry Model

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.

Physical model – flow speed

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!

Previous work:Interannual variability of air-sea CO2 flux

Ocean modelMcKinley et al. (2004)

Atmospheric inverse modelBousquet et al. (2000)

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)

Tool for Atmospheric Inversions of CO2 and CH4

• MATCH: Model of Atmospheric Transport and Chemistry

Inverse Modeling

Air Parcel Air Parcel

Air Parcel

Sources Sinks

transport transport

sinkssourcestransport ++=∂∂

tC

Sample Sample

solved formodeledobserved

Dargaville, McGuire, and Rayner2002 (Climatic Change)

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

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

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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