Dynamical Prediction of the Ecosystems and the Global Carbon Cycle

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1 Thanks: M. Heimann, C. Roedenbeck, P Wetzel, Brian Cook, R. Joseph, H. Qian, R. Iacono, E. Munoz, W. Higgins, K. Mitchell Dynamical Prediction of the Ecosystems and the Global Carbon Cycle Ning Zeng 1, Jinho Yoon 1, Augustin Vintzileos 2, G. James Collatz 3, Eugenia Kalnay 1, Annarita Mariotti 1, Arun Kumar 2, Antonio Busalacchi 1, Stephen Lord 3 1 University of Maryland 2 NOAA/NCEP 3 NASA/GSFC

2 Targets Prediction (seasonal-interannual), not projection (climate change) Predict atmospheric CO 2 concentration and growth rate. Atmospheric CO 2 can be a eco-climate index indicating anomalies in the global ecosystem as a whole, just like NINO3 can be used as an index for climate anomalies associated with ENSO Predict spatial patterns and temporal variability of carbon fluxes and pool size Examples: forest productivity, agricultural harvest, fire danger

3 Breathing of the biosphere: CO 2 as a major indicator of ecosystems (and climate) Modeled land-atmosphere flux vs. MLO CO2 growth rate Carbon model forced by observed climate variability ENSO, Pinatubo, drought and other signals

4 El Nino 97/98 Inversion Roedenbeck 2003 VEGAS

5 Seasonal-interannual Prediction of Ecosystems and Carbon Cycle Two 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: Feasibility study using a prototype eco-carbon prediction system dynamical vs. statistical (Statistical forecasts for crop yield, infectious disease exist)

6 The NCEP Climate Forecast System (CFS, Saha et al. 2006) CFS captures major ENSO and other seasonal-interannual variability

7 The VEgetation-Global Atmosphere-Soil Model (VEGAS) arbon allocation Photosynthesis Turnover Atmospheric CO2 NPP=60 PgC/y Autotrophic respiration NEE = Rh NPP = + 3 (Interannual) Rh=60 PgC/y Heterotrophic respiration 4 Plant Functional Types: Broadleaf tree Needleleaf tree C3 Grass (cold) C4 Grass (warm) 3 Vegetation carbon pools: Leaf Root Wood 3 Soil carbon pools: Fast Intermediate Slow Fire, wetland/ch4, 13 C etc.

8 A 25-year hindcast experiment using a prototype prediction system Climate Predition CFS (9mon, 15 members) CFS (9mon, 15 members) Spinup Precip Temp Precip Temp Ecosystem+ Carbon Model VEGAS Initialization I VEGAS 1 mo forecast ensemble mean Predicted Eco-carbon Output 9mon, 15 members Output 9mon, 15 members Month 1 Month 2

9 Simple initialization to avoid shock ; eco-carbon data assimilation? Forecasting procedure II L=3 L=2 L=1 Ensemble mean L=0 t-1 t t+1

10 First look: Productivity (NPP)

11 Anomaly Correlation Fta High skills in South America Indonesia southern Africa eastern Australia western US central Asia

12 Beyond ENSO: Drought during

13 Fire during the 2002 Drought Model: dynamical Model: dynamical + Statistical Observation

14 Beyond ENSO: Fire in the US Natural and anthropogenic factors Model Observation

15 Fire carbon flux during El Nino CASA (satellite fire, climate) VEGAS (climate only) Mean El Nino Anomalies Input: satellite fire counts, climate Input: climate only

16 2007 Southern California Fire An operational trial

17 Conclusions Ecosystem and carbon cycle prediction is feasible: encouraging results (better than expected) Memory in the hydro-ecosystem is important in the enhancement of skill several issues such as overestimation at midlatitude regions Some major development needs Initialization: eco-carbon data assimilation? Preprocessing/downscaling/postprocessing Dynamical + statistical Operational

18 Implications for climate service Applications to ecosystem and carbon cycle Identifying more clearly society-relevant aspects A useful framework for studying eco-carbon response and feedback to climate Identifying ways to incorporate eco-carbon dynamics in the next generation of climate prediction models (European GEMS)

19 Thank you! Reference: Zeng et al. (2008) Global Biogeochemical Cycles, in press