1. Application of Greenhouse Gas Satellite Observations at Environment Canada Ray Nassar Climate Research Division - CCMR ray.nassar@ec.gc.ca NOAA-NASA-EUMETSAT Satellite Workshop Miami, FL - 2011 March 30

2. Outline Overview of surface and satellite CO 2 observations TES and flask CO 2 flux inversion work Development of Environment Canada Carbon Assimilation System (EC-CAS) Future plans/directions

3. Global Greenhouse Gas Measurement Network World Data Centre for Greenhouse Gases NOAA (US), Europe, Environment Canada, CSIRO (Australia), JMA (Japan)... WMO - World Data Centre for Greenhouse Gases (WDCGG)

4. Satellite Observations of CO 2 AIRS SCIAMACHY IASI GOSAT TANSO-FTS TES March-April-May multi-year average Yokota et al. (2009) Crevoisier et al. (2009) Chahine et al. (2008) Buchwitz et al. (2007) Kulawik et al. (2010) Limb (TIR): ACE-FTS, MIPAS HIRS Chédin et al. (2003) TIR emission NIR reflectance *GOSAT has both TIR and NIR observations

5. Susan Kulawik, JPL Tropospheric Emission Spectrometer (TES) CO 2 S. S. Kulawik, D.B.A. Jones, R. Nassar, F.W. Irion, J.R. Worden, K.W. Bowman, T. Machida, H. Matsueda, Y. Sawa, S.C. Biraud, M. Fisher, A.R. Jacobson (2010), Characterization of Tropospheric Emission Spectrometer (TES) CO 2 for carbon cycle science, ACP, 10, 5601-5623 TES - Fourier Transform Spectrometer on Aura in the A-Train Observes TIR emission 650-3050 cm -1 (or 3.3-15.4  m) at ~1:40/13:40 local time Small footprint (5.3 x 8.3 km 2 ) helps to avoid clouds Coarse CO 2 profile sensitivity is given by the averaging kernel matrix Peak sensitivity at 511 hPa (~5 km) between ~40°S-40°N Rows of Averaging Kernel

6. CO 2 Flux Inversion Approach GEOS-Chem model using GEOS-5 assimilated meteorology from NASA Global Modeling and Assimilation Office (GMAO) - 2º latitude x 2.5º longitude CO 2 fluxes: fossil fuels (CDIAC monthly from national inventories, international shipping/aviation), biosphere (balanced diurnal CASA + annual climatology, biomass and biofuel burning, ocean flux, chemical production from CO, CH 4 and other carbon Determine CO 2 sensitivities for 40 regions for 2006 Sampled model at TES observation locations (ocean only, 40°S-40°N) and times to calculate 5°x5° monthly averages at 511 hPa Sampled model at 59 surface flask locations (NOAA and EC) to obtain monthly averages Conduct time-independent, annual Bayesian inversions with monthly TES and/or flask data A priori flux uncertainties: Baker et al. (2006) for land regions and Gruber et al. (2009) for ocean regions Accept fossil fuel inventories and solve for “natural” fluxes (ocean, terrestrial exchange + biomass + biofuel) ~ 1.1 Pg C/yr 3-D CO 2 Chemical Production Nassar et al. (2010), Geoscientific Model Development, 3, 689-716 (University of Toronto)

7. R. Nassar, D.B.A. Jones, S.S. Kulawik, J.R. Worden, K.W. Bowman, R.J. Andres, P. Suntharalingam, J.M. Chen, C.A.M. Brenninkmeijer, T.J. Schuck, T.J. Conway, D.E. Worthy (2011), Inverse modeling of CO 2 sources and sinks using satellite observations of CO 2 from TES and surface flask measurements, ACPD, 11, 4263-4311 2006 CO 2 Fluxes by Combining TES and Flask data

8. TES and flask data together give the best agreement with independent ship (NOAA) and aircraft (CARIBIC) flask data as a result of the complementary vertical and horizontal information TES and Flask CO 2 are Complementary ship station aircraft Nassar et al. (2011), ACPD, 11, 4263-4311 Ships Aircraft

9. Comparison of CO 2 Flux Inversions for 2006 Nassar et al. (2011), ACPD, 11, 4263-4311 Persistent discrepancies between the inversion systems highlight the need for more sophisticated approaches including better accounting of error terms

10. Integrated Global Carbon Assimilation System Source: GEO Carbon Strategy

11. Developing Canadian GHG Assimilation Capabilities Starting well behind the US, Europe, Japan with less available human resources and money Aim to develop a competitive system at Environment Canada using most advanced techniques Will take advantage of Environment Canada expertise with: - Numerical Weather Prediction (NWP) and stratospheric data assimilation using the Global Environmental Multiscale model (GEM) - Carbon-climate modelling expertise at Canada Centre for Climate Modeling and Analysis (CCCma) - Application of atmospheric satellite observations and data from ground- based networks

12. Global Environmental Multiscale (GEM) Model Canadian operational weather forecast system: Côté et al. (1998), MWR, 126, 1373-1395 Ingests data from GOES-E/W, METEOSAT-E/W, MTSAT, ATOVS, AIRS, IASI, COSMIC, … 4DVar and Ensemble Kalman Filter (EnKF) versions: Buehner et al. (2010), MWR, 138, 1550-1566 and 1567-1586 GEM extended for tracer transport Model for Air quality and Chemistry (GEM-MACH) GEM-AQ: Kaminski et al. (2008), ACP, 8, 3255-3281 GEM applied to GHGs CO 2 and CH 4 work: Chan et al. in preparation Work on coupling to biospheric models (Biome-BGC, BEPS, CTEM) now in progress

13. Development led by Saroja Polavarapu (EC), Ray Nassar (EC), Dylan Jones (UofT) Adapt GEM operational Ensemble Kalman Filter (EnKF) to CO 2 flux estimation –Augmented state: both CO 2 concentrations and CO 2 fluxes –Sequential estimation using past and future observations – Kalman Smoother –Ensemble approach: perturb initial concentrations, fluxes, meteorology, model error, etc. giving multiple ensemble members to estimate the sizes of error components Forward model development –Assess and reduce transport errors e.g. lack of mass conservation implications –Apply best available inventories for fossil fuels (national + shipping/aviation), biomass and biofuel burning, and ocean flux –Couple to a biosphere carbon model –CO 2 chemical production from oxidation of CO, CH 4 and other carbon Observations –CO 2, CH 4, CO in situ data and satellite observations (NIR/TIR sounders) –Implement quality control and bias correction schemes, and rigorously account for representativeness errors for each instrument and species Environment Canada Carbon Assimilation System (EC-CAS) plan

14. Satellite Observations v1.2 averaged at 2°x2.5° NIR reflectance XCO 2 : GOSAT, OCO-2 (~2013) TIR emission CO 2 : GOSAT, IASI, AIRS, TES Other carbon species (CO, CH 4 ) GOSAT XCO 2 2009-09 350400 Will this be enough?

15. Fraserdale (ON) 50°N Alert (Nunavut) 82°N Higuchi et al. (2003), Tellus 55B, 115-125 surface Park Falls (46°N) XCO 2 (column) MATCH model in situ Olsen & Randerson (2004), JGR 109, D02301 surface Observing the Northern CO 2 Diurnal Cycle Boreal Forests www.borealforest.org Strong diurnal cycle of near-surface CO 2 over Boreal Forests, but not north of tree line XCO 2 diurnal amplitude < 1 ppm over forests, not observable in sun-sync LEO

16. PCW-PHEMOS Trischenko & Garand (2011) Polar Communications and Weather (PCW) mission (2017): 2 operational met satellites in Highly Elliptical Orbit (HEO) for quasi-geostationary observations along with a communications package Polar Highly Elliptical Molniya Orbit Science (PHEMOS) suite of imaging spectrometers Weather Climate and Air quality (WCA) option is now entering phase-A study (see talk by J.C. McConnell on Thursday) Quasi-continuous coverage of GHGs over the high latitudes (~40-90°N) using TIR+NIR would help constrain GHG sources/sinks at fine temporal scales

17. Summary Combining surface-based and satellite observations of CO 2 for constraining CO 2 fluxes has now been demonstrated, and shown to have complementary vertical and horizontal information More sophisticated GHG assimilation systems are possible and are being developed by many organizations including Environment Canada Utilization of NIR reflectance (columns with surface sensitivity), TIR emission (mid/upper troposphere) and ground-based data appears to be the way forward LEO constellations or GEO/HEO are needed to constrain fluxes at the spatial and temporal scales desirable to address important science questions and policy needs