Satellite data, ecosystem models and site data: contributions of the IGBP flux

network to carbon cycle science

David Schimel, Galina Churkina, Eva Falge, Rob Braswell, James Trembath,

[schimel@ucar.edu]

Or, what networks can and cannot do

Net Ecosystem ExchangeA very difficult modeling problem

Average NPPs are 3000-6000 kg haNEEs are 0-1700 kg haThe NEE signal is typically <20% of NPP (or respiration)

The uncertainties of NPP and NEE data are 25-50% of the mean, typically. Biases are common.

Model biases in NPP and respiration that are too small to correct using typical measurements can cause significant biases in modeled NEE

The small difference between two large fluxes (NEE = <1 - 20% of NPP)

NEE = GPP - Ra - RhNBP/NPP5% Russian Forests10% Russian Wetlands16% Russian Grass/Shrublands25% in EU CANIF sites~1% in natural conditions

Carbon Uptake Period: the number of days on which NEE is negative (flux from atmosphere to ecosystem)

A Global Scaling Exercise(from the Department of Irresponsible Extrapolation)

CUP from flux data

CU

P fr

om N

DV

I

+ ENF

* DBF

grass crop

CUP from flux data

NE

E f

rom

flu

x da

ta

Growing season length appears to be a robust predictor of Eddy Flux NEE

Mapped Forest Carbon Uptake Period, using NDVI data,threshold tuned to FLUXNET

The NDVI CUP is the satellite-estimated number of days withnegative NEE (carbon uptake)

Forest NEE extrapolated from CUP

Using: forest type map, separate regressions for broad and needle leafed forests and a satellite-based CUP, all aggregated to 0.5o.

D.I.E.

Extrapolated Forest Sector NEEExtrapolated Forest Sector NEE(High bias)

North America 1.9 Gt/yEurasia 1.6 Gt/y

Why?

Mean Forest CUP Fraction deciduous(days ) (%)

North America 180 26Eurasia 210 22

CUP and “broadleaf-ness” are spatially correlated

D.I.E.

Where do we go from here?Where do we go from here?

The network is dominated by sites with large positive NEE: are we observing a representative sample? If so, what does this mean?

Specifically:

The flux network is biased towards aggrading stands 40-100 years old

The eddy flux measurements may have a high bias because of unfavorable measurement conditions at night.

Larch covers much of Siberia, does it follow either regression???

ObservedNEE

NDVI

Direct and Remote Measurements

Growing season length has similar interannual variability

gC/m

2 /da

yModeled and Observed NEE

gC/m

2 /da

y

Most of the systematic error occurs in the beginning and the end of growing season

Global regression suggests an average ~3 g m2 CUP day

Time-series suggest ~0.6 g m2 CUP day

D.I.E.

Space for time problems

“Space for process” problems: Century simulated global respiration vsTo and the To response function: what networks cannot do

No matter how well you sample, the To partial derivative can’t be estimated from the spatial pattern

Space for time

Implications for network design:

Time-series of forcing and response are needed to understand process: spatial patterns cannot substitute.

Systematic sampling of ecosystem states within CUP ranges, e.g., management intensity, age, nutrient status is crucial

Ground measurements to link satellite and ground-based measurements, e.g., canopy optical properties, sun photometer, navigation aids, airborne time series data, are needed for extrapolation

Process-level focus on seasonal transitions, e.g., spring and fall focus on plant and soil measurements, snow cover, are crucial

The planned restructuring of the IGBP must strengthen the role of experimental networks, and increase their interaction with synthesis and modeling efforts!

A major criteria for any new structure for the IGBP: will it strengthen the networks?

The experimental networks of the IGBP are a unique feature of the program and distinguish it from modeling and synthetic efforts such as the IPCC and Millennium Assessment