Space-Based Detection of Atmospheric Carbon Dioxide: The Orbiting Carbon Observatory (O=C=O)

1. Space-Based Detection of Atmospheric Carbon Dioxide:The Orbiting Carbon Observatory (O=C=O)

2. The Greenhouse Effect

3. Natural carbon fluxes account for 300 GtC/yr and exist in near equilibrium. The Global Carbon Cycle 6 GtC/yr The ~6 GtC/yr produced by human activity represents only 2% of the entire carbon flux, but it may “tip the balance”

4. Atmospheric CO2: the Primary Anthropogenic Driver of Climate Change “Keeling Plot” Since 1860, global mean surface temperature has risen ~1.0 °C with a very abrupt increase since 1980. Atmospheric levels of CO2 have risen from ~ 270 ppm in 1860 to ~370 ppm today. Accumulation of atmospheric CO2 has fluctuated from 1 – 6 GtC/yr despite nearly constant anthropogenic emissions. WHY? Does increasing atmospheric CO2 drive increases in global temperature? Do increasing temperatures increase atmospheric CO2 levels?

5. Global CO2 Emissions Projections suggest rapid rise in CO2 emissions from Developing Nations, surpassing the emissions from Developed Nations by 2020. CO2 emissions from oil are projected to dominate the anthropogenic contributions over the next 20 years

6. Note the clear North/South bias in industrial emissions CO2 Emissions from Fossil Fuel Burning

7. CO2 Emissions from Land Use Change

8. The Global Carbon Cycle: Many Questions • Atmospheric CO2 has been monitored systematically from a network of ~100 surface stations since 1957 • Over the past 20 years • only ~1/2 of the CO2 associated with fossil and biomass fuel combustion has remained in the atmosphere • the remainder has been absorbed by the ocean and land ecosystems • Carbon sinks are not well understood • Is there a Northern hemisphere land sink? • Relative roles of North America/ Eurasia • What controls sources and sinks? • Why does the atmospheric buildup vary from 1 - 6 GtC/year in the presence of roughly constant emission rates? • How will the efficiency of these sinks evolve as the climate changes? • An Integrated, global strategy needed to answer these questions. • The US Carbon Cycle Science Program • USGCRP, NSF, DoE, USDA, NOAA, NASA, USGS The ~100 GLOBALVIEW-CO2 flask network stations and the 26 continental sized zones used for CO2 flux inversions. This network is designed to measure back-ground CO2. It can not retrieve accurate source and sink locations or magnitudes! Bousquet et al., Science290, 1342 (2000).

9. 1.2 1.2 OCO Flux Retrieval Errors GtC/year/Zone Flux Retrieval Errors GtC/year/Zone 0.6 0.6 FLASK SATELLITE 0.0 0.0 Measurements Needed to Revolutionize Our Understanding of the Global Carbon Cycle Fig. F.1.2 Flux Errors vs Measurement Accuracy Accurate, spatially resolved global measurements of XCO2 will revolutionize our understanding of the carbon cycle if measurement can be acquired • With accuracies of 1 ppm • On regional scales (8o X 10o) • On monthly time scales Carbon flux errors from simulations including data from (A) the existing surface flask network, and (B) satellite measurements of XCO2 with accuracies of 1ppm on regional scales on monthly time scales

10. O=C=O Improves GlobalCO2 Flux Inversion Retrievals Error in retrieved global carbon flux (GtC/yr) vs. space-based XCO2 measurement accuracy.The OCO 1- ppm accuracy significantly outperforms the GV-CO2 network (dashed–line) or any of the other planned missions that will generate column CO2 data products. Solid curve from Rayner & O’Brien, Geophys. Res. Lett. 28, 175 (2001)

11. Why Measure CO2 from Space?Improved CO2 Flux Inversion Capabilities • Global maps of carbon flux errors for 26 continent/ocean-basin-sized zones retrieved from inversion studies (Bousquet model). • Studies using data from the 56 GV-CO2 stations produce flux residuals that exceed 1 GtC/yr in some zones and show a pattern characteristic of an underdetermined solution (the network is too sparse). • Inversion tests using global XCO2 pseudo-data with 1 ppm accuracy reduce the flux errors to <0.5 GtC/yr/zone for all zones and reduce the global flux error by a factor of 2 – 3. 1.0 0.5 0.0 Flux Retrieval Error GtC/yr/zone 1.0 0.5 0.0 Rayner & O’Brien, Geophys. Res. Lett. 28, 175 (2001)

12. 45 Why Measure CO2 from Space? Dramatically Improved Spatiotemporal Coverage The O=C=O orbit pattern (16-day repeat cycle)

13. The Orbiting Carbon Observatory (O=C=O) • Baseline Science Mission: • Provide the first global XCO2 measurements from space with a relative accuracy of 1 ppm on 2.5105 km2 scales every 16 days for 2 years • Combine XCO2 measurements with ground-based data to retrieve the geographic distribution of CO2 sources and sinks on seasonal to interannual timescales • Use NADIR, GLINT and TARGET modes to provide independent data validation approaches • Formation fly with the A-Train to allow coordinated observations and enhance the OCO data value

14. O=C=O Performance Improves with Spatial Averaging Accuracy of OCO XCO2 retrievals as a function of the number of soundings for optimal (red) and degraded performance (blue) for a typical case (37.5 solar zenith angle, albedo=0.05, and moderate aerosol optical depth, a{0.76 m} = 0.15). Results from end-to-end sensitivity tests (solid lines) are shown with shaded envelopes indicating the range expected for statistics driven by SNR (N1/2) and small-scale biases (N1/4).

15. OCO Measurement Strategy • High resolution spectra of reflected sunlight in near IR CO2 and O2 bands used to retrieve the column average CO2 dry air mole fraction, XCO2 • Column-integrated CO2 abundance • Maximum contribution from surface • Other data needed (provided by OCO) • Surface pressure, albedo, atmospheric temperature, water vapor, clouds, aerosols • Why high spectral resolution? • Lines must be resolved from thecontinuum to minimize systematic errors

16. OCO Spatial Sampling Strategy • OCO is designed provide an accurate description of XCO2 on regional scales • Atmospheric motions mix CO2 over large areas as it is distributed through the column • Source/Sink model resolution limited to 1ox1o • OCO flies in the A-train, 15 minutes ahead of the Aqua platform • 1:15 PM equator crossing time yields same ground track as AQUA • Global coverage every 16 days • OCO samples at high spatial resolution • Nadir mode: 1 km x 1.5 km footprints • Isolates cloud-free scenes • Provides thousands of samples on regional scales • Glint Mode: High SNR over oceans • Target modes: Calibration

17. The Pushbroom Spectrometer Concept It is possible to obtain many ground-track spectra simultaneously if the instantaneous field of view (IFOV) is imaged onto a 2D detector array. In this case, wavelength information is dispersed across one dimension and cross-track scenes are dispersed along the other dimension. The instrument acquires spectra continuously along the ground track at a rate of 4.5Hz. This results in 70 spectra/sec and 9000 spectra per 45 region every 16 days. 2D 1024  1024 arrays are available in Si (visible) and HgCdTe (NIR) from Rockwell Sciences.

18. Cloud and Aerosol Interference Clouds, aerosols and sub-visible cirrus (high altitude ice clouds) prevent measurement of the entire atmospheric column. An analysis of available global data suggests that a space-based instrument will see “cloud-free” scenes only ~ 10% of the time. Geographically persistent cloud cover will be especially problematic and will induce biases in the data. Number of cloud-free scenes per month anticipated for space-based sampling averaged into 36 (LatLon) bins based on AVHRR cloud data. D. O’Brien (2001).

19. Sub-visible Cirrus Clouds VISIBLE Clouds, aerosols and sub-visible cirrus (high altitude ice clouds) prevent measurement of the entire atmospheric column. Sub-visible cirrus clouds are effective at scattering near infrared light because the light wavelengths and particle sizes are both ~ 1 – 2 mm. An analysis of available global data suggests that a space-based instrument will see “cloud-free” scenes only ~ 10% of the time. Geographically persistent cloud cover will be especially problematic and will induce biases in the data. 1.38 mm MODIS data

20. OCO Science Data Flow Space-borne Data Acquisition Level 2 Calibration & Validation Data Spectral Radiances Level 3 Ancillary Data FTIR: XCO2 GVCO2: [CO2] AIRS: T, P, H2O MODIS: Aerosol NCEP Fields Global 1ppm Precision XCO2 Maps Inversion Models Data Assimilation Models Level 4 JAN JUL Temporally Varying CO2 Source/Sink Maps APR OCT O=C=O Data Product Pipeline The OCO data flow smoothly from space through an automated pipeline which yields Leve 1 and 2 data products. Level 3 and Level 4 products are produced by individual Science Team members. Preliminary tests of the retrieval algorithm demonstrate the OCO mission concept: Kuang et al., Geophys. Res. Lett., 29 (15) 2001GL014298 (2002).

21. Rigorous Physics Based Retrieval Algorithms Level 1 Calibration XCO2 Retrieval Level 2 Source/Sink Retrieval Level 3 • Inverse Models • Assimilation Models Level 4

22. Summary The Orbiting Carbon Observatory (O=C=O) will provide space-based measurements of atmospheric CO2 with the 1 ppm accuracy, temporal frequency and spatial resolution needed to characterize the variability of CO2 sinks on regional scales. O=C=O data products will revolutionize carbon cycle science as well as guide policy decisions in carbon management strategies on the national and international levels. O=C=O data products will be made freely available. Work continues to integrate O=C=O activities with planned field campaigns and modeling efforts of the carbon cycle science community.