FLUXNET and Remote Sensing Workshop: Towards Upscaling Flux Information from Towers to the Globe

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FLUXNET and Remote Sensing Workshop: Towards Upscaling Flux Information from Towers to the Globe Space-Based Measurements of CO 2 from the Japanese Greenhouse Gases Observing Satellite (GOSAT) and the NASA Orbiting Carbon Observatory 2 (OCO-2 ) Missions D. Crisp for the ACOS/OCO-2 Team Jet Propulsion Laboratory, California Institute of Technology OCO-2 Science Lead 7 June 2011 Copyright 2011 California 1 Institute of Technology. Government sponsorship acknowledged.

Global Measurements from Space are Essential for Monitoring Atmospheric CO 2 To limit the rate of atmospheric carbon dioxide buildup, we must Control emissions associated with human activities Understand & exploit natural processes that absorb carbon dioxide We cannot manage what we cannot measure Plumes from medium-sized power plants (4 MtC/yr) elevate X CO2 levels by ~2 ppm for 10 s of km downwind [Yang and Fung, 2010]. 2 These variations are superimposed on a background of CO 2 weather

Primary Advantage of Space-based Data: Spatial Coverage at High Resolution Ground based measurements - greater precision and sensitivity to CO 2 near the surface, where sources and sinks are located. Space-based measurements improve spatial coverage & resolution. Source/Sink models - assimilate space an ground-based data to provide global insight into CO 2 sources and sinks 3

High precision is Essential for Monitoring CO 2 Sources and Sinks from Space CO 2 sources and sinks must be inferred from small spatial variations in the (387 ±5 ppm) background CO 2 distribution Largest variations near surface Space based NIR observations constrain column averaged CO 2, X CO2 Small spatial gradients in X CO2 verified by pole-topole aircraft data [Wofsy et al. 2010] 372 380 4

Spatial Resolution and Sampling A Small Footprint: Increases sensitivity to CO 2 point sources The minimum measureable CO 2 flux is inversely proportional to footprint size Increases probability of recording cloud free soundings in partially cloudy regions Reduces biases over rough topography High Sampling Rate: Soundings can be averaged along the track to reduce single sounding random errors OCO-Nadir OCO-Glint GOSAT 5

Coverage: Obtaining Precise Measurements over Oceans as well as Continents The ocean covers 70% of the Earth and absorb/emit 10 times more CO 2 than all human activities combined Coverage of the oceans is essential to minimize errors from CO 2 transport in and out of the observed domain 3-5 ppm Near IR solar measurements of CO 2 over the ocean are challenging Typical nadir reflectances: 0.5 to 1% Most of the sunlight is reflected into a narrow range of angles, producing the familiar glint spot Glint and nadir measurements can be combined to optimize sensitivity over both oceans and continents 6 <0.4 ppm OCO single sounding random errors for nadir and glint [Baker et al. ACPD, 2008].

447-m WLEF Tower Park Falls, WI Validating Space-based X CO2 against the Ground-Based Standard: TCCON FTS The Total Carbon Column Observing Network (TCCON) provides a transfer standard between ground- and spacebased measurements TCCON measures the absorption of direct sunlight by CO 2 and O 2 in the same spectral regions used by OCO-2. Validated against aircraft measurements OCO-2 will acquire thousands of X CO2 soundings over TCCON stations on a single overpass. 7

Measuring CO 2 from Space Record spectra of CO 2 and O 2 absorption in reflected sunlight Retrieve variations in the column averaged CO 2 dry air mole fraction, X CO2 over the sunlit hemisphere Validate measurements to ensure X CO2 accuracy of 1-2 ppm (0.3-0.5%) Initial Surf/Atm State Generate Synthetic Spectrum OCO/AIRS/GOSAT New State (inc. X CO2 ) Instrument Model Difference Spectra Tower FTS Inverse Model Aircraft X CO2 Flask 8

GOSAT-OCO Collaboration The OCO and GOSAT teams formed a close partnership during the implementation phases of these missions to: Cross calibrate the OCO instrument and TANSO-FTS Cross validate OCO and GOSAT X CO2 retrievals against a common standard The primary objectives of this partnership were to: Accelerate understanding of this new data source Facilitate combining results from GOSAT and OCO GOSAT OCO 3-day ground track repeat cycle resolves weather Continuous high resolution measurements along track 9

The Launch of GOSAT & Loss of OCO 24 Feb 2009 GOSAT launched successfully on 23 January 2009 OCO was lost a month later when its launch system failed 10

Scope of the ACOS/GOSAT Collaboration Immediately after the loss of OCO, the GOSAT Project manager invited the OCO Team to participate in GOSAT data analysis The ACOS team is collaborating closely with the GOSAT teams at JAXA and NIES to: Conduct vicarious calibration campaigns in Railroad Valley, Nevada, U.S.A. Retrieve X CO2 from GOSAT spectra - Model development & testing - Data production and delivery Validate GOSAT retrievals by comparing GOSAT retrievals with TCCON measurements and other data Picarro CO 2 11

Retrieving X CO2 from GOSAT Data The OCO Retrieval Algorithm was modified to retrieve X CO2 from GOSAT measurements Full-physics forward model Inverse model based on optimal estimation Calibrated GOSAT Spectra (L1B Data) State Vector CO 2 profile (full) H 2 O profile (scale factor) Temperature profile (offset) Aerosol Profiles Surface Pressure Albedo (Mean, Slope) Forward Model Spectra + Jacobians State Vector First Guess Wavelength Shift (+ stretch) Apriori + Covariance Inverse Model (Optimal Estimation) Update State Vector not converged converged Calculate XCO 2 Diagnostics 12

Screening Improves Accuracy Pre-screening for Clouds: A Spectroscopic cloud screening algorithm based on the O 2 A-band is currently being used for GOSAT Errors can be further reduced by post-screening retrievals: Measurement SNR Convergence Goodness of spectral fit Surface pressure error Evidence for clouds or optically thick aerosols A postiori retrieval error 13

A Year of ACOS/GOSAT X CO2 14

Comparisons of GOSAT and TCCON Wunch et al. ACOS GOSAT retrievals show A consistent global bias of ~2% (7 ppm) in X CO2 when compared with TCCON and aircraft measurements. X CO2 variations that are a factor of 2-3 larger than that from TCCON. 15

Sources of Bias in the X CO2 Maps About half of the global 2% bias is caused by airmass bias associated with a ~10 hpa (1%) high surface pressure bias Radiometric and spectroscopic calibration errors Non linearity and ILS corrections currently being implemented Uncertainties in the O 2 A-band absorption cross sections Oversimplified treatment of line mixing and line shape Improvements in the CO 2 spectroscopy and aerosol retrieval approach are also being implemented to address P remaining bias s P s (a priori) GOSAT Typical O 2 A-band retrieval residuals. 16

Bias Correction from Validation Program ACOS X CO2 products retrieved over the southern hemisphere, which has little known variability, have been assessed to identify other sources of bias Wunch et al. have identified biases associated with: Difference between ABO2 and SCO2 albedos Surface pressure difference dp=p ret -P ECMWF Air mass A-band Signal Level A multivariate formula has been developed to correct these biases 17 HIPPO-1 and HIPPO-2 show little CO2 variability over the Southern Hemisphere. The corrections substantially improve the fits over SH TCCON sites

Impact of Know Biases on Retrieved Global X CO2 Distribution 18

The Loss of OCO and the Birth of OCO-2 NASA s Orbiting Carbon Observatory (OCO) was designed to provide the measurements needed to estimate the atmospheric CO 2 dry air mole fraction (X CO2 ) with the sensitivity, accuracy, and sampling density needed to quantify regional scale carbon sources and sinks over the globe and characterize their behavior over the annual cycle. 1:55 AM 24 Feb 2009 February 2009: The OCO spacecraft was lost when its launch vehicle s fairing failed to deploy December 2009: The U.S. Congress added funding to the NASA FY2010 budget to restart the OCO Mission The OCO-2 spacecraft bus and instrument are currently on track for a February 2013 launch 19

Comparison of GOSAT and OCO-2 GOSAT (2009) Optimized for spectral and spatial coverage Collects 10,000 soundings every day - 10-15% are sufficiently cloud free for CO 2 &CH 4 retrievals, limited coverage of oceans. 3-4 ppm (1%) precision: can detect strong sources GOSAT OCO-2 (2013) Optimized for high sensitivity and resolution Collects up to 10 6 measurements each day over a narrow swath Smaller footprint ensures that >20% all soundings are cloud free 1 ppm (0.3%) precision adequate to detect weak sources & sinks Produces global maps in Nadir and Glint on alternate 16-day repeat cycles, to yield global maps in both models once each month 20

OCO Mission Overview 3-Channel Spectrometer Dedicated Spacecraft bus Dedicated Launch Vehicle Routine Mission Operations Formation Flying as part of the A-Train Constellation NASA NEN (GSFC) and SN (TDRSS) Products Delivered to a NASA Archive Validation Program Science Data Operations Center (JPL) L2 X CO2 Retrieval Calibrate Data Please visit http://oco.jpl.nasa.gov for more information 21

Conclusions Space-based remote sensing observations hold substantial promise for future long-term monitoring of CO 2 and other greenhouse gases The principal advantages of space based measurements include: Spatial coverage (especially over oceans and tropical land) Sampling density (needed to resolve CO 2 weather) The principal challenge is the need for high precision To reach their full potential, space based CO 2 measurements must be validated against surface measurements to ensure their accuracy. The TCCON network is providing the transfer standard Need a long-term vision to establish and address community priorities Must incorporate ground, air, space-based assets and models Must balance calls for new observations with need to maintain climate data records 22