1. The carbon response during the 2015 El Niño: harbinger of things to come?
Junjie Liu1, Kevin W. Bowman1, David Schimel1, Nicolas C. Parazoo1, Zhe Jiang2, Meemong Lee1, A. Anthony Bloom1, Debra Wunch3, Christian Frankenberg1, 4, Ying Sun1+, Christopher W. O’Dell5, Kevin R. Gurney6, Dimitris Menemenlis1, Michelle Girerach1, David Crisp1, and Annmarie Eldering1
1Jet Propulsion Laboratory
California Institute of Technology
2National Center for Atmospheric Research. 3 University of Toronto. 4. California Institute of Technology
5. Colorado State University
6. Arizona State University.
© 2017 California Institute of Technology. Government sponsorship acknowledged
© 2012 California Institute of Technology. Government sponsorship acknowledged

2. Largest CO2 Growth Rate in 50 years
3.05 ppm yr-1 (2015)
2.93 ppm yr-1 (1998)
2015 had the highest atmospheric growth record in the Mauna Loa record, beating out the 1998 growth rate.
Growth rate was 50% higher than the previous year but anthropogenic emissions were roughly the same.
What were the spatial drivers of this growth rate? How are they related to climate forcing?

3. Atmospheric Observations
NASA CMS-Flux
Carbon Monitoring System-Flux Framework
Surface Observations
Carbon Cycle Models
Inversion System
Atmospheric Observations
Anthropogenic emissions
GEOS-Chem
Terrestrial exchange
4D-var/LETKF
Ocean exchange
GOSAT/OCO-2 SIF, Jason SST, nightlights, etc.
OCO-2 CO2,
GOSAT CO2 and CH4, MOPITT CO
Posterior Carbon Fluxes (CO2, CH4, CO)
Attribution
The NASA Carbon Monitoring System Flux (CMS-Flux) attributes atmospheric carbon variability to spatially resolved fluxes driven by data-constrained process models across the global carbon cycle.

4. Tropical South America
Forcing the situation
Tropical South America
Tropical Africa
Tropical Asia
precip T
2015 was an extreme year:
Driest year over tropical South America
Hottest year over tropical Africa
Warm and dry over tropical Asia

5. Study in contrast
Estimate and contrast fluxes during an “extreme” year (2015) (OCO-2) against a nominal year (2011) (GOSAT).
The total flux inferred from CMS-Flux can be decomposed into a sum of terms representing key processes within the carbon cycle.
Net flux into the atmosphere is positive
Fossil Fuel
Ocean
Biomass burning
NEP
Chemical Source
Source:
OCO-2
GOSAT
FFDAS
ECCO2
Darwin
MOPITT
GOSAT
GEOS-Chem

6. Tropical drivers of the atmospheric growth rate in 2015 relative to 2011
Liu et al, in Rev
The tropics released 2.4 ± 0.34 Gt more carbon into the atmosphere in 2015 than in 2011
The tropics accounted for
78.7% of the global total 3.0 GtC NBE difference,
88% the atmospheric CO2 growth rate differences

7. Contrasting responses to climate forcing
Liu et al, in Rev
The three tropical continents have approximately equal contributions but are associated with different drivers.
Asian flux anomaly is dominated by increased fire and reduced productivity
S. American flux anomaly is dominated by reduced productivity.
African flux anomaly is dominated by increased respiration.

8. Pattern of Extreme forcing
Contour: GPP-weighted precipitation diff ; shaded: difference larger than 2σ2
Contour: GPP-weighted T diff ; shaded: difference larger than 2σ2
The number of dry month difference between 2015 and 2011
The monthly mean precipitation over tropical S. America and tropical Asia was lower by 2.9 σ and 2.2 σ.
In both regions, the dry season (monthly precipitation less than 100 mm) lengthened by about 1-3 months from 2011 to 2015.
Tropical Africa T were higher by 1.6 σ.
Liu et al, in Rev

9. Pattern of response to extreme forcing
Masked regions with precip difference larger than 2σ2
Masked regions with T difference larger than 2σ2
In tropical S. America where precipitation was 3.5 σ lower than average accounted for virtually all
of the 0.9 ± 0.24 GtC increase.
In tropical Africa, about half of the NBE increase (0.4 ± 0.18 GtC) occurred in regions where temperature differences exceeded 4 σ, covering less than 30% of the land area.
In tropical Asia, which was both
excessively dry and hot,
biomass burning dominated flux. In contrast to 97-98, BB only account for 17% of total tropical NBE
Liu et al, in Rev

10. Conclusions
CO2 growth rate mitigation requires attribution of forcing and feedbacks at the spatial scales on which they occur.
The tropics released 2.4 ± 0.34 Gt more carbon into the atmosphere in 2015 than in 2011 accounting for 78.7% of the global total 3.0 GtC NBE difference, and 88% of the atmospheric CO2 growth rate differences.
While tropical continental contributions were roughly the same, the dominant carbon processes were different: S. America (GPP), Africa (Resp), and Asia (Fire)
Fluxes associated with climate “extremes” were the dominant drivers of the tropical fluxes.

11. Backup

12. Orbital Carbon Observatory (OCO-2)
Collect spectra of CO2 & O2 absorption in reflected sunlight over the globe
16 day repeat cycle
10km
1.29x2.25-km footprint; eight cross-track footprints create a swath width of 10.3 km
Oco-2 – an approach to get global measurements
Long time coming = failure, thus OCO-2
Technique
1 million soundings per day
Need to be precise
Have a small footprint – good to avoid clouds
May be useful to explore fine scale details
Launched in June, 2014 into an afternoon, polar sun-synchronous orbit as part of the NASA “A-Train” constellation, OCO-2 provides dry-column mole fraction CO2 (XCO2).
Compared to TCCON, median differences are less than 0.5 ppm and RMS differences typically below 1.5 ppm (Wunch et al, 2016 AMTD)

13. GPP inferred from solar induced fluorescence
Frankenberg et al, 2011
Frankenberg et al, 2011
Optimal estimation provides a framework to determine GPP that accounts for uncertainty in the fluorescence, prior uncertainty in GPP, satellite coverage and timing.
xa=mean Trendy GPP
y: GOSAT SIF at time {ti}
F(x): Observation operator: GPP to GOSAT overpass
Sn: Error in GOSAT SIF, Sa:Ensemble Trendy spread
Parazoo et al, 2013

14. Respiration: combustion
Measurements of Pollution in the Atmosphere
Carbon monoxide is a by-product of incomplete combustion.
MOPITT provides CO verticals with near surface sensitivity.
CMS-Flux estimates CO from MOPITT and converts to CO2
CO2 from biomass burning is calculated from CO/CO2 ratios (Andreae and Merlet, GBC, 2001)
Emission factors are a function of dry mass (given) and burning efficiency, which is a function of plant function type.
Emission factors

15. Do 2015 OCO-2 and 2011 GOSAT have relative bias?
OCO-2 XCO2 (2015)
GOSAT XCO2 (2011)
TCCON XCO2
TCCON XCO2
The relative differences between OCO-2 XCO2 and GOSAT XCO2 were negligible when both were compared to XCO2 from Total Carbon Column Observing Network

16. Validating against independent aircraft observations
Globe, 2011, rms(prior)=1.1ppm, rms(post)=0.3ppm
NA, 2011, rms(prior)=1.2ppm, rms(post)=0.3ppm
Globe, 2015, rms(prior)=1.8ppm, rms(post)=0.4ppm
NA, 2015, rms(prior)=1.8ppm, rms(post)=0.4ppm
trop, 2011, rms(prior)=0.2ppm, rms(post)=0.2ppm
trop, 2015, rms(prior)=0.6ppm, rms(post)=0.5ppm
The posterior CO2 concentrations have been improved after assimilating satellite XCO2 observations