Why CO 2 ?

1. C O O Atmosphere ? ? Human Activity Ocean Land Why CO2? ISSUES: Carbon dioxide (CO2) is the • Principal atmospheric component of the global carbon cycle • Primary anthropogenic driver of climate change • Only half of CO2 produced by human activities over the past 30 years has remained in the atmosphere. • Where are the sinks? • Will this continue?

3. The Global Carbon Cycle Natural carbon fluxes account for 300 GtC/yr and exist in near equilibrium. 6 GtC/yr The ~6 GtC/yr produced by human activity represents only 2% of the 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. 1000 900 Atmospheric CO2 800 700 600 ppm 500 400 300 200 1850 1900 1950 2000 2050 2100 20 Global Mean Temperature 19 18 17 Celsius 16 15 14 13 1850 1900 1950 2000 2050 2100 An Uncertain FutureWhere are the Missing Carbon Sinks? • What are the relative roles of the oceans and land ecosystems in absorbing CO2? • Is there a Northern hemisphere land sink? • Relative roles of North America/ Eurasia • What controls carbon sinks? • Why does the atmospheric buildup vary substantially with uniform emission rates? • How will sinks respond to climate change • Climate prediction requires an improved understanding of natural CO2 sinks • Future atmospheric CO2 increases • Their contributions to global change OCO will dramatically reduce these uncertainties

6. An Uncertain Future:Where are the Missing Carbon Sinks? • Only half of the CO2 released into the atmosphere since 1970 years has remained there. The rest has been absorbed by land ecosystems and oceans • What are the relative roles of the oceans and land ecosystems in absorbing CO2? • Is there a northern hemisphere land sink? • What are the relative roles of North America and Eurasia • What controls carbon sinks? • Why does the atmospheric buildup vary with uniform emission rates? • How will sinks respond to climate change? • Reliable climate predictions require an improved understanding of CO2 sinks • Future atmospheric CO2 increases • Their contributions to global change

7. 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).

8. 1.2 1.2 0.6 0.6 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 Flux Errors OCO Flux Retrieval Errors GtC/year/Zone Flux Retrieval Errors GtC/year/Zone FLASK SATELLITE Fig. F.1.3: 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

9. Why Measure CO2 from Space?Improved CO2 Flux Inversion Capabilities • Current State of Knowledge • Global maps of carbon flux errors for 26 continent/ocean-basin-sized zones retrieved from inversion studies • Studies using data from the 56 GV-CO2 stations • Flux residuals exceed 1 GtC/yr in some zones • Network is too sparse • Inversion tests • global XCO2 pseudo-data with 1 ppm accuracy • flux errors reduced to <0.5 GtC/yr/zone for all zones • Global flux error reduced by a factor of ~3. Flux Retrieval Error GtC/yr/zone Rayner & O’Brien, Geophys. Res. Lett. 28, 175 (2001)

10. 45 Why Measure CO2 from Space?Dramatically Improved Spatiotemporal Coverage The O=C=O orbit pattern (16-day repeat cycle)

11. O=C=O Measurement Objectives 45 Objective: Characterize the geographic distribution of CO2 sources and sinks on regional to continental scales over seasonal to interannual time scales Approach: • Space-based atmospheric carbon monitoring system • Global coverage (land and ocean) • high spatial resolution (4o x 5o) • weekly to monthly time scales • High measurement precision • Column CO2 measurement precision • ~1ppm (0.3% of 370 ppm) • Resolve East-West gradients as well as interhemispheric gradients in CO2 • Advanced Modeling tools used to retrieve • CO2 column amounts from observations • Sources and sinks from global CO2 maps • Correlative Measurement Program • Validation, bias removal, diurnal cycles • Laboratory Measurements Coverage in Each 16-Day Repeat Cycle

12. Proposed Sampling Strategy Addresses All Science Objectives Ground tracks over the tip of South America • OCO will 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 1o x 1o • High spatial resolution • Isolates cloud-free scenes • Provides thousands of samples on regional scales • 16 Day Repeat Cycle • Provides large numbers of samples on monthly time scales 810 45 Spatial sampling along ground track B) Satellite

13. Nadir Mode Glint Mode Target Mode Measurement Strategy Maximizes Information Content and Measurement Validation Opportunities • 1:15 PM near polar orbit • 15 minutes ahead of the A-Train • Same ground track as AQUA • Global coverage every 16 days • Science data taken on day side • Nadir mode: Highest spatial resolution • Glint mode: Highest SNR over ocean • Target mode: Validation • Airmass dependence • Same path as FTIR • Calibration data taken on night side

14. 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

15. Will it Work? • Accuracies of 1ppm needed to identify CO2 sources and sinks. • Realistic, end-to-end, Observational System Simulation Experiments • Reflected radiances for a range of atmospheric/surface conditions • line-by-line multiple scattering models • Comprehensive description of • mission scenario • instrument characteristics • Results: The OCO payload will • meet or exceed the requirements for measuring CO2 • provide rigorous constraints on the distribution and optical properties of clouds and aerosols End-to-end retrievals of XCO2 from individual simulated nadir soundings at SZAs of 35o and 75o. The model atmospheres include sub-visual cirrus clouds (0.02c 0.05), light to moderate aerosol loadings (0.05a 0.15), over ocean and land surfaces. INSET: Distribution of XCO2 errors (ppm) for each case

16. Validation Program Ensures Accuracy and Minimizes Spatially Coherent Biases • Ground-based in-situ measurements • NOAA CMDL Flask Network + Tower Data • TAO/Taurus Buoy Array • Uplooking FTIR measurements of XCO2 • 3 OCO • 4 NDSC • Aircraft measurements of CO2 profile • Complemented by Laboratory and on-orbit calibration Buoy Network CMDL

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

18. 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 Hz. This results in 24 spectra/sec and 3000 spectra per 45 region every 16 days. 2D 1024  1024 arrays are available in Si (visible) and HgCdTe (NIR) from Rockwell Sciences.

19. 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).

20. 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

21. 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).

22. Q4 Science Impacts of X-band Failure • OCO will meet its 1 ppm relative accuracy requirement under both scenarios The Baseline Science Mission will be achieved Based on Fig. F.1.10

23. Q15 OCO Geolocation Requirements (cont.) Response: • OCO requires no ancillary data to measure XCO2 • XCO2 measurements are relatively insensitive to the details of the underlying terrain and surface characteristics • Observations from the high resolution O2 A-band spectrometer will be used to characterize the topographic variability within each spatial footprint • Effects of surface albedo are discussed in Question #18 The claimed need for 5 km geolocation (F-18) is deemed inadequate for mapping CO2 retrievals onto terrain and surface characteristics

24. Q17 Question #17 Question 17: Due to the critical effect of changing surface albedo, it is essential that the entire spectra are collected simultaneously. Please clarify. Response • OCO uses grating spectrometers • All wavelength information for a given spatial sample is recorded simultaneously on array detectors • Each spatial sample is read out almost simultaneously • 1.4 msec per spectrum

25. Q18 Question18 Question 18: Please quantify the error in the CO2 column measurement resulting from surface albedo variations and uncertainties. A formal, detailed error analysis is not required here. However, you do need to demonstrate that this error source, which is not explicitly considered in the proposal, is not important relative to the error budget and specified 1 ppm accuracy level. Response: The wavelength-dependent albedo is retrieved as an independent variable in each spectral channel.

26. 2.06 Q18 Albedo Is Retrieved Explicitly • The wavelength dependent albedo is determined from the continuum level within each spectral band as part of the simultaneous retrieval • Surface albedo changes much more slowly with wavelength than gas vibration-rotation features • The OCO spectral resolution has been chosen to resolve the spectral lines from the continuum in each band • Because the entire spectrum is collected almost simultaneously in each channel, the XCO2 retrieval depends only on the spatial average of the albedo within each footprint

27. Q18 Albedo Is Retrieved Explicitly • The end-to-end retrieval simulations included wavelength-dependent albedos, which were retrieved as part of the XCO2 retrieval process. • Albedo types considered: dark ocean, desert, snow, conifer forests and snow • Errors associated with uncertainties in the albedo retrieval are a small part of the total error budget • The XCO2 retrieval algorithm is only weakly dependent on the absolute value of the surface albedo (through its effects on the SNR) • Atmospheric O2 and CO2 columns depend on differences between the line core and continuum Demonstrate that this error source, which is not explicitly considered in the proposal, is not important relative to the error budget and specified 1 ppm accuracy level. Fig. F.1.9: End to end test of the OCO retrieval algorithm

28. XCO2 (ppm) DXCO2 (ppm) Q20 OCO Sampling Biases: Level 3 ProductsGlobal XCO2 Maps (16-day average) • 1:15 PM local sampling time chosen because • Production of CO2 by respiration is offset by photosynthetic uptake • Instantaneous XCO2 measurement is within 0.3 ppm of the diurnal average (see figure) • Airborne measurements of CO2 profiles from COBRA and ABLE-2B substantiate this view • Atmospheric transport desensitizes OCO measurements to the clear-sky bias • Air passes through clouds on a time-scale short compared to the time needed to affect significant changes in XCO2 (no cloud bias evident in figure) • Mixing greatly reduces the influence of local events & point sources on XCO2 MAY Fig. F.2.4: a) Calculated monthly mean, 24 hour average XCO2 (ppm) during May using the NCAR Match model driven by biosphere and fossil fuel sources of CO2. b) XCO2 differences (ppm) between the monthly mean, 24 hour average and the 1:15 PM value

29. Q20 OCO Sampling Bias: Level 4a ProductsGeographic Distribution of CO2 Sources & Sinks • Level 4a: Inverted Sources and Sinks • OCO measurements of XCO2 will not be evenly distributed in time and space. • The inversion approaches incorporated into the OCO Mission Science strategy account for spatial and temporal inhomogeneity in observations. • The power of OCO in constraining sources and sinks comes from the ~108 new observations over a two-year period and the relatively high density of XCO2 observations in the tropics (where constraints from contemporary surface networks are weak). • Inversions of OCO data in combination with FTIR, aircraft, and flask observations, will revolutionize our understanding of the global carbon cycle.

30. Q20 OCO Sampling Bias: Level 4b ProductsCarbon Cycle Data Assimilation • Level 4b: Carbon Cycle Data Assimilation • Data assimilation will calculate the 3-D CO2 field by combining OCO XCO2 data with • in situ CO2 observations • Uplooking FTIR XCO2 • Atmospheric transport model • Analogous to modern weather forecasting • Spatially and temporally biased observations assimilated into a physical model to produce maps with continuous spatial and temporal information. XCO2 Assimilation Strategy

31. Q21 Question # 21 Question 21: Level 2 data consists of a constellation of point measurements obtained in clear sky conditions. What are the spatial and temporal statistics of these measurements as a function of latitude? In particular, how will the geographical sampling of the instrument be affected by the relatively larger amount of cloudiness which tends to occur in the tropics relative to other latitudes? How will this degrade the quality of the Level 3 and Level 4 data, and how will this affect your science? Response: • OCO acquires 740 soundings per degree of latitude along the orbit track • With 14.65 orbits/day, and a 16 day repeat cycle, • Ground tracks are separated by ~1.5o of longitude • Over a 16 day period, each 4o x 5o sub-region is traversed 3.3 times, yielding ~10,000 XCO2 soundings (assuming no clouds) • Only a small fraction of these samples are needed to meet the baseline science requirements

32. Q21 Effects of Clouds on Sampling How will the geographical sampling of the instrument be affected by the relatively larger amount of cloudiness which tends to occur in the tropics relative to other latitudes? • Response: • Observational System Simulation Experiments (OSSE’s) using the OCO orbit and 8 km x 8 km footprint (based on ISCCP data) • There is no strong tropical bias in the number of CO2 soundings • High cirrus produce a sampling bias in the tropics, but their effects are compensated by the low solar zenith angle and high SNR Rayner et al. (2002) Average number of cloud-free hits each month in each 4 x 5 degree latitude bin, averaged over the year.

33. 0.0 0.5 1.0 Q21 Probability of Viewing Cloud-Free Scenes Increases with Spatial Resolution • OSSE’s confirm that the probability of viewing cloud-free scenes increases as the sample footprint size decreases • The high spatial resolution (1 km x 1.5 km) provided by OCO will yield more cloud free scenes July 8 km x 8 km 24 km x 24 km 40 km x 40 km Probability of clear-sky scene Rayner, Law and O’Brien III (2001)

34. Q22 Airborne Demonstration of +0.1% Retrieval Precision for Column O2 • Retrieval of tropospheric column O2 to + 0.1% demonstrated using reflected near infrared sunlight with an airborne O2 A-band instrument D. M. O’Brien et al., J. Atmos. Oceanic Tech. 15, 1272 (1998).

35. Q22 Flight Instrument Validation • Prior to launch the OCO flight instrument will • Measure the CO2 column looking up towards sun • Be compared to the OCO FTIR spectrometers. m CO 1.58 m Band 2 1.57 1.58 1.59 Wavelength (mm) Ground-based FTIR solar spectrum in the OCO 1.58 mm CO2 band recorded at Table Mountain Facility, Wrightwood, CA (May 2002, S. Sander)

36. Q8a Question 8a Question 8a: Quantify the science impacts of the descope options • Response: • The OCO Team has identified 5 descope options • 1. Relax geolocation requirement from 5 km to ~10 km • 2. Leave A-Train • 3. Reduce sampling rate from 4.5 to 3.0 Hz • 4. Limit science observation to NADIR viewing • 5. Delete 2.06mm channel

37. Q8a Q8a The Execution of All Descope Options Defines the Minimum Science Mission Section F.2.6, pp. F-17-18

38. Q8a Q8a OCO XCO2 Retrieval Performance Quantified for Baseline & Minimum Missions • OCO delivers global XCO2 measurements with 1 ppm relative accuracy in the Baseline Science Mission & Minimum Science Mission. Baseline Mission Minimum Mission Simulations conducted with the end-to-end OCO retrieval algorithm After Fig. F.1.10, p. F-8

39. Q8a Descope 1Relaxed Geolocation Requirements Response: • Relaxing the geolocation requirement from 5 km to ~10 km complicates the validation of the OCO data but does not affect the data accuracy. • Detailed response provided in Question 15 • A relaxed geolocation requirement increases difficulty in collocating OCO validation measurements using TARGET mode. • FTIR’s located in spatially uniform areas • The relaxed geolocation requirement will not affect the ability to correlate the OCO measurements with those from the A-Train • OCO swath is substantially smaller than that of A-Train instruments.

40. 33% Reduction Q8a Descope 3Reduced Sampling Rate • Response: • Reducing sampling rate from 4.5 Hz to 3.0 Hz will • Reduce the number of samples in each 4 x 5 region by 33% • Increases footprint area by 50% • Slightly increased cloud contamination • Results quantified in the response to Question 21

41. Q8a Descope 4Delete TARGET & GLINT Modes • Response: • Deleting GLINT mode will reduce sensitivity over oceans and at high latitudes • OCO still meets its 1 ppm XCO2 relative accuracy goal operating only in NADIR mode • Deleting TARGET mode decreases the number of independent validation methods OCO retrieval performance for several NADIR viewing scenarios Fig. F.1.9, p. F-7

42. Q8a Descope 5Delete 2.06 mm Channel • Response: • Deleting the 2.06 mm channel requires significantly more soundings to be averaged to meet the 1 ppm XCO2 relative accuracy goal Fig. F.1.8 quantifies the RSS errors for retrievals with all three spectrometers (c) and without the 2.06 mm channel (b).

43. Q8a Descope 5Delete 2.06 mm Channel (con’t) • The Baseline configuration reaches the 1 ppm accuracy goal in 10 – 50 soundings while it requires 50 – 10,000 soundings to achieve this goal without the 2.06 mm channel. • To achieve 1 ppm requires • Increasing sampling grid from 4 x 5 to 8 x 10 • Increasing interval from 16 days to 1 month Fig. F.1.10 quantifies the simulated observatory performance as a function of the number of soundings for the baseline configuration (red) and the instrument with the 2.06 mm channel deleted (blue).

44. OCO Addresses the High Science Priorities • Climate Forcing/Response • T/H2O/O3 AIRS/TES/MLS • Clouds CloudSat • Aerosols CALIPSO • CO2 OCO • OCO provides critical data for • Understanding the carbon cycle • Essential for developing carbon management strategies • Predicting weather and climate • Understanding sources/sinks essential for predicting CO2 buildup • O2 A-Band will provide global surface pressure measurements • OCO validates technologies critically needed for future operational CO2 monitoring missions XCO2 (ppm)