Near-Real Time Analysis of the Modern Carbon

Cycle by Model-Data Fusion

Scott Denning, David Baker, Chris O’Dell, Denis O’Brien, Tomohiro Oda, Nick Parazoo, Ian Baker, Becky McKeown (CSU Atmospheric Science & CIRA)

Andy Jacobson, Pieter Tans (NOAA ESRL),

Scott Doney, Ivan Lima (WHOI),

Jim Collatz, Randy Kawa (NASA GSFC)

Acknowledgements:Support by NOAA, NASA, DoE

Component Models

• Fossil Fuel Emissions (EDGAR plus DMSP, monthly)

• Ocean Biogeochemistry, Ecosystems, & Air-Sea Gas Exchange (WHOI, daily)

• Terrestrial photosynthesis & respiration (SiB4, hourly)

• Biomass burning (GFED, 8-day)

• Atmospheric Transport (GEOS5-PCTM, 3-hourly)

• CarbonTracker: CASA+GFED+Ocean+TM5+in-situ

Global Fossil Fuel Emissions (2009)

Supply-Based Inventory Methods

(“follow the fuel”)

Regional Emissions Estimates

Oda et al (2010) emissions scaled to DMSP lights

Ocean Carbon Model• Physical ocean model assimilates sea-

surface topography and SST (based on SODA, Carton et al)

• Physics assimilation provides w and delivers nutrients to surface

• Ocean ecosystem model and biogeochemistry assimilates SeaWiFS and MODIS to predict sea-surface pCO2

• Surface winds from GEOS to compute gas exchange and CO2 flux

Terrestrial Ecosystems

• Extension of SiB w/Prognostic phenology MODIS data assimilation for fPAR/LAI

• Crop physiology, phenology, and mapping

• Time-scale separation of GPP & Resp

• Development and testing in field experiments with mesoscale model

Atmospheric Transport Models

• Parameterized Chemical Transport Model (PCTM) developed at NASA GSFC

– Identical algorithms & code from GEOS-5

– Driven by stored winds, turbulence, cloud mass fluxes from model reanalysis

– 0.5° x 0.67° lat x lon, 55 levels

• TM5

– 3° x 2° lat x lon, 40 levels

– Driven by ECMWF winds and clouds

CarbonTracker: Optimization of in-situ CO2 data

SiB+WHOI+FF+GFED+T3sinks->PCTM

XCO2 Sampled Daily on GOSAT Orbit

ALL

FILTERED

12

N = 865806

GOSAT Column CO2 from Space

ACOS B2.9 Coverage

N ~ 250000

GOSAT−PCTM GOSAT−CT

CT−PCTMDark Blue: 

Oceans (glint, high gain)Cyan: 

land, medium gain (desert areas only, bright)

Green: land, high gain (all other land areas, dark)

Bias [ppm]: • Dark land -1.03 -0.80 -0.23• Bright land 0.31 0.20

0.11• Ocean 0.07 0.31 -

0.24

Standard deviation [ppm]:• Dark land 1.89 1.86 0.86• Bright land 1.70 1.61

0.49• Ocean 1.36 1.34

0.35

Comparison of GOSAT to ModelsACOS- PCTM

ACOS - CT

PCTM - CT

Conclusions• Two different comprehensive analysis systems

agree with > 250k GOSAT XCO2 retrievals to better than 2 ppm (bias < 1 ppm; s < 2 ppm)

• Ocean(!) and medium-gain land retrievals seem to agree better with models than high-gain land

• Scope for “removing retrieval biases” using fits to albedo, airmass, etc may reduce single-shot random errors to better than 1 ppm

• System can be used to estimate source/sink in near real time (a few weeks after the fact)