Dynamical Prediction of the Terrestrial Ecosystem

and the Global Carbon Cycle: a 25-year Hindcast Experiment

Jin-Ho Yoon Jin-Ho Yoon

Dept. Atmospheric and Oceanic Science Dept. Atmospheric and Oceanic Science University of MarylandUniversity of Maryland

Co-Authors: Ning Zeng, Augustin Vintzileos, G. James Collatz, Eugenia Kalnay, Annarita Mariotti, Arun Kumar, Antonio Busalacchi, Stephen Lord

Collaborators: C. Roedenbeck, P Wetzel, E. Maier-Reimer, Brian Cook, H. Qian, R. Iacono, E. Munoz

March 5, 2008 CPASW

‘‘Breathing’ of the biosphere: CO2 as a Breathing’ of the biosphere: CO2 as a major indicator of climate major indicator of climate

Terrestrial carbon model forced by observed climate variability ENSO, Pinatubo, drought and other signals

Modeled land-atmo flux vs. MLO CO2 growth rate

Seasonal-interannual Seasonal-interannual Prediction of Ecosystem and Prediction of Ecosystem and

Carbon CycleCarbon CycleTwo strands of recent research made this a real possibility

• Significantly improved skill in atmosphere-ocean prediction system, such as CFS at NCEP

• Development of dynamic ecosystem and carbon cycle models that are capable of capturing major interannual variabilities, when forced by realistic climate anomalies

A pilot study at U Maryland: Feasibility study using a prototype eco-carbon prediction system dynamical vs. statistical

TargetsTargets

• Predict spatial patterns and temporal variability of carbon fluxes and pool size Example: Reduced biosphere productivity and enhanced fire and CO2 from Amazon.

• Predict atmospheric CO2 concentration and growth rate. Atmospheric CO2 can be a ‘climate index’ indicating anomalies in the global ecosystem

The NCEP Climate Forecast System The NCEP Climate Forecast System (CFS, Saha et al. 2006)(CFS, Saha et al. 2006)

CFS captures major ENSO and other seasonal-interannual variability

PhotosynthesisAutotrophic respiration

Carbon allocation

Turnover

Heterotrophic respiration

4 Plant Functional Types:Broadleaf treeNeedleleaf treeC3 Grass (cold)C4 Grass (warm)

3 Vegetation carbon pools:LeafRootWood

3 Soil carbon pools:FastIntermediateSlow

Atmospheric CO2

The VEgetation-Global Atmosphere-Soil Model (VEGAS)

NPP=60 Pg/y

Rh=60Pg/y

NEE = Rh – NPP = + 3 (Interannual)

Forecasting Procedure IForecasting Procedure I

CFS (9mon, 15 members)

VEGAS

Output9mon, 15 members

Month 2

CFS (9mon, 15 members)

VEGAS

Output9mon, 15 members

Month 1

1 mo forecastensemble mean

IInitialization

ClimatePredition

Ecosystem+Carbon Model

PredictedEco-carbon

SpinupPrecip

Temp

Precip

Temp

Forecasting procedure IIForecasting procedure II

L=1

L=0

L=3

L=2

tt-1 t+1

Ensemble mean

NEE(‘validation') and MLO CO2NEE(‘validation') and MLO CO2

NEE (land-atmo C flux): VEGAS forced by observed climate (Precip, T) This will be called ‘validation’ as there is no true observation availableOcean contribution smaller, so NEE can be compared with atmo CO2 Using regression of inversion/OCMIP with Nino3.4/MEI?

NEE(‘validation') and Inversion NEE(‘validation') and Inversion (from MPI)(from MPI)

First look: Productivity (NPP) First look: Productivity (NPP)

'Observed'

Predicted global cabon flux (Fta)

Lead time from 0 to 8 months

1. CFS/VEGAS captures most of the interannual variability, but2. Amplitude is underestimated

Anomaly Correlation FtaAnomaly Correlation Fta

High skills in• South America• Indonesia• southern Africa• eastern Australia• western US • central Asia

Summary of skill for anomaly correlationSummary of skill for anomaly correlation

Correlation

Regression

Correlation .vs. Regression (Amplitude)Correlation .vs. Regression (Amplitude)

Benchmark Forecast: Benchmark Forecast: Do we need dynamical forecast?Do we need dynamical forecast?

Relaxation or Damping of climate forcingAnomaly at L=0 will persist or

damped to zero with decorrelation time scale.

Persistence

DampingL=1L=0 L=2

Benchmark ForecastBenchmark ForecastDo we need dynamic forecast system?Do we need dynamic forecast system?

Benchmark ForecastBenchmark Forecast

Beyond ENSO: Beyond ENSO: Drought during 1998-2002Drought during 1998-2002

Beyond ENSO: Fire in the US Beyond ENSO: Fire in the US Natural and anthropogenic factorsNatural and anthropogenic factors

Observation

Model

Conclusions: predictionConclusions: prediction

• Encouraging results (better than expected)

Seasonal prediction of Prec/Tas(CFS) + Dynamic ecosystem model (VEGAS)

Parallel project on ‘Fire danger (potential) prediction’.

Working on ‘operational mode’.

Issues• Overestimation at midlatitude

Implications of prediction• Applications to ecosystem and carbon cycle

• A new framework for study eco-carbon response and feedback to climate

• Identifying ways of incorporating eco-carbon dynamics in the next generation of climate prediction models

Conclusions: predictionConclusions: prediction

Thank you!Thank you!

Questions?Questions?

The NCEP Climate Forecast System The NCEP Climate Forecast System (CFS, Saha et al. 2006)(CFS, Saha et al. 2006)

Summary of skill for anomaly correlationSummary of skill for anomaly correlation