Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon...
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Transcript of Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon...
![Page 1: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/1.jpg)
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,
Or, what networks can and cannot do
![Page 2: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/2.jpg)
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
![Page 3: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/3.jpg)
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
![Page 4: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/4.jpg)
Carbon Uptake Period: the number of days on which NEE is negative (flux from atmosphere to ecosystem)
![Page 5: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/5.jpg)
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
![Page 6: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/6.jpg)
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)
![Page 7: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/7.jpg)
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.
![Page 8: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/8.jpg)
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.
![Page 9: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/9.jpg)
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???
![Page 10: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/10.jpg)
ObservedNEE
NDVI
Direct and Remote Measurements
Growing season length has similar interannual variability
![Page 11: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/11.jpg)
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
![Page 12: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/12.jpg)
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
![Page 13: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/13.jpg)
“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
![Page 14: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/14.jpg)
Space for time
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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
![Page 16: Satellite data, ecosystem models and site data: contributions of the IGBP flux network to carbon cycle science David Schimel, Galina Churkina, Eva Falge,](https://reader036.fdocuments.in/reader036/viewer/2022081519/56649f1b5503460f94c3179f/html5/thumbnails/16.jpg)
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