Orbiting Carbon Observatory (OCO) The Orbiting Carbon Observatory (OCO) Mission Vijay NatrajGe152 Wednesday, 1 March 2006

Orbiting Carbon Observatory (OCO) Atmospheric CO 2 : the Primary Anthropogenic Driver of Climate Change Atmospheric levels of CO 2 have risen from ~ 270 ppm in 1860 to ~370 ppm today. Accumulation of atmospheric CO 2 has fluctuated from 1 – 6 GtC/yr despite nearly constant anthropogenic emissions. WHY? Since 1860, global mean surface temperature has risen ~1.0 °C with a very abrupt increase since “Keeling Plot”

Orbiting Carbon Observatory (OCO) Only half of CO 2 produced by human activities over the past 30 years has remained in the atmosphere. What are the relative roles of the oceans and land ecosystems in absorbing CO 2 ? Is there a northern hemisphere land sink? What are the relative roles of North America/ Eurasia? What controls carbon sinks? Why does the atmospheric buildup vary with uniform emission rates? How will the sinks respond to climate change? Climate prediction requires an improved understanding of natural CO 2 sinks. Future atmospheric CO 2 increases Their contributions to global change An Uncertain Future: Where are the Missing Carbon Sinks?

Orbiting Carbon Observatory (OCO) Atmospheric CO 2 has been monitored systematically from a network of ~100 surface stations since The ~100 GLOBALVIEW-CO 2 flask network stations and the 26 continental sized zones used for CO 2 flux inversions. This network is designed to measure back- ground CO 2. It cannot retrieve accurate source and sink locations or magnitudes! Bousquet et al., Science 290, 1342 (2000). The Global Carbon Cycle: Many Questions

Orbiting Carbon Observatory (OCO) Why Measure CO 2 from Space? Improved CO 2 Flux Inversion Capabilities Rayner & O’Brien, Geophys. Res. Lett. 28, 175 (2001) Studies using data from the 56 GV-CO 2 stations Flux residuals exceed 1 GtC/yr in some zones Network is too sparse Inversion tests Global X CO2 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 ~ Fig. F.1.3: Carbon flux errors from simulations including data from (A) the existing surface flask network, and (B) satellite measurements of X CO2 with accuracies of 1 ppm on regional scales on monthly time scales Flux Retrieval Errors GtC/year/Zone OCO

Orbiting Carbon Observatory (OCO) 4  5  Why Measure CO 2 from Space? Dramatically Improved Spatiotemporal Coverage The O=C=O orbit pattern (16-day repeat cycle) 4  5 

Orbiting Carbon Observatory (OCO) The Orbiting Carbon Observatory (OCO) Mission Make the first, global, space-based observations of the column integrated dry air mole fraction, X CO2, with 1 ppm precision. Combine satellite data with ground-based measurements to characterize CO 2 sources and sinks on regional scales on monthly to interannual time scales Fly in formation with the A-Train to facilitate coordinated observations and validation plans

Orbiting Carbon Observatory (OCO) X CO2 Retrieved from Bore-Sited CO 2 and O 2 Spectra Taken Simultaneously Clouds/Aerosols, Surface PressureClouds/Aerosols, H 2 O, TemperatureColumn CO 2 High resolution spectroscopic measurements of reflected sunlight in near IR CO 2 and O 2 bands provide the data needed to retrieve X CO2 Column-integrated CO 2 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 the continuum to minimize systematic errors

Orbiting Carbon Observatory (OCO) Spatial Sampling Strategy OCO is designed provide an accurate description of X CO2 on regional scales Atmospheric motions mix CO 2 over large areas as it is distributed through the column Source/Sink model resolution limited to 1 o x 1 o High spatial resolution 1 km x 1.5 km footprints Isolates cloud-free scenes Provides thousands of samples on regional scales 16-day repeat cycle Provides large numbers of samples on monthly time scales 4  5  8  10  Ground tracks over the tip of South America Spatial sampling along ground track

Orbiting Carbon Observatory (OCO) Operational Strategy Maximizes Information Content and Measurement Validation Opportunities Nadir Mode Target Mode Glint Mode 1:15 PM near polar (98.2 o ) orbit 15 minutes ahead of EOS 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 Comparison with surface FTS stations Calibration data taken on night side Solar, limb, dark, lamp

Orbiting Carbon Observatory (OCO) Q20 Sampling Biases 1:15 PM local sampling time chosen because Production of CO 2 by respiration is offset by photosynthetic uptake Instantaneous X CO2 measurement is within  0.3 ppm of the diurnal average (see figure) 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 X CO2 Mixing greatly reduces the influence of local events & point sources on X CO2 Fig. F.2.4: a) Calculated monthly mean, 24 hour average X CO2 (ppm) during May using the NCAR Match model driven by biosphere and fossil fuel sources of CO 2. b) X CO2 differences (ppm) between the monthly mean, 24 hour average and the 1:15 PM value X CO2 (ppm)  X CO2 (ppm) MAY

Orbiting Carbon Observatory (OCO) Will it Work? Accuracies of 1 ppm needed to identify CO 2 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 Retrieve X CO2 from single clear sky nadir sounding to ppm precision Rigorous constraints on the distribution and optical properties of clouds and aerosols End-to-end retrievals of X CO2 from individual simulated nadir soundings at SZAs of 35 o and 75 o. 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 X CO2 errors (ppm) for each case

Orbiting Carbon Observatory (OCO) Cloud, Aerosol and Cirrus Interference 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 µm. 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 (O’Brien, 2001).

Orbiting Carbon Observatory (OCO) O=C=O Performance Improves with Spatial Averaging Accuracy of OCO X CO2 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 (N 1/2 ) and small-scale biases (N 1/4 ).

Orbiting Carbon Observatory (OCO) 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 FTS measurements of X CO2 3 funded by OCO 4 upgraded NDSC Aircraft measurements of CO 2 profile Complemented by Laboratory and on-orbit calibration Buoy Network CMDL

Orbiting Carbon Observatory (OCO) 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 4.5 Hz. This results in 70 spectra/sec and 9000 spectra per 4  5  region every 16 days.

Orbiting Carbon Observatory (OCO) OCO Data Product Pipeline AIRS: T, P, H 2 O Data Assimilation Models OCT JUL APR JAN Inversion Models Calibration & Validation Data Temporally Varying CO 2 Source/Sink Maps Global 1 ppm X CO2 Maps Spectral Radiances Space-borne Data Acquisition Level 3 Level 2 Level 4 Ancillary Data FTIR: X CO2 GVCO2: [CO 2 ] MODIS: Aerosol NCEP Fields The OCO data flow from space through an automated pipeline which yields Level 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).

Orbiting Carbon Observatory (OCO) Retrieval Algorithm Forward Model Instrument Simulator Global CO 2 Maps O 2 A Band CO 2 X CO2 Retrieval Process Radiative Transfer Model Calculate Input Parameter Monochromatic RT Calculation Frequency Loop Adjustment To The Atmospheric /Surface State x Inversion Model Calculated Spectrum f(x) and Jacobians df/dx Convergence ? Incoming Spectra yes no

Orbiting Carbon Observatory (OCO) Summary X CO2 (ppm) OCO will provide critical data for Understanding the carbon cycle Essential for developing carbon management strategies Predicting weather and climate Understanding sources/sinks essential for predicting CO 2 buildup O 2 A Band will provide global surface pressure measurements OCO validates technologies critically needed for future operational CO 2 monitoring missions Satisfies a measurement need that has been identified by NPOESS, for example Climate Forcing/Response T/H 2 O/O 3 AIRS/TES/MLS CloudsCloudSat AerosolsCALIPSO CO 2 OCO