GOSAT. -CO 2 and CH 4 measurements from space - Tatsuya Yokota

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International Workshop on Inventory, Modeling and Climate Impacts of Greenhouse Gas emissions (GHG s) and Aerosols in the Asian Region, June 27, 2013 @ Epochal Tsukuba, Tsukuba, Japan GOSAT -CO 2 and CH 4 measurements from space - (GOSAT: Greenhouse gases Observing SATellite) Dec. 17, 2008 Tatsuya Yokota Center for Global Environmental Research (CGER) National Institute for Environmental Studies (NIES), Japan

Contents Significance and objectives of GHGs (CO 2 & CH 4 ) measurements from space GOSAT mission overview CO 2 & CH 4 monitoring status by GOSAT CO 2 flux estimation by using GOSAT data GOSAT TANSO-CAI data contribution GOSAT (IBUKI) launched by H-IIA F-15 vehicle on January 23, (Photo by Mr. Daitoh (NIES)) 1

GOSAT Mission Status Overview GOSAT was launched on 23 January, and has been in operation for more than four years. GOSAT data are available from June 2009 successively. GOSAT is the world's first satellite designed specifically for monitoring greenhouse gases. Researchers worldwide are using GOSAT data. GOSAT observations successfully filled out the gaps in the ground-based monitoring network, except for around the equator and the highlatitude regions. 2

Objectives of the GOSAT Project 1. To obtain the global distributions of greenhouse gas (GHG) concentrations (CO 2 and CH 4 ) and their temporal variations To visualize changing GHG global distributions To fill out the gaps in the network of ground monitoring stations 2. To improve accuracy of the carbon flux (net sources and sinks) estimation on a subcontinental scale 3. To develop technologies for future GHG observing satellites GOSAT-2 3

Carbon Dioxide & Methane Measurements 63+18=81% Contributions of primary greenhouse gases to the increase in atmospheric temperatures based on the best estimates of radiative forcing from 1750 to 2005. (Source: IPCC AR4) 4

Size Main body 3.7 m x 1.8 m x 2.0 m Wing Span 13.7m Mass Total 1750kg Power Total 3.8 KW (EOL) Life Time Orbit 5 years sun synchronous orbit Local time 13:00+/-0:15 Altitude 666km TANSO onboard GOSAT TANSO=Thermal And Near infrared Sensor for carbon Observation Inclination Repeat 98deg 3 days Launch Vehicle H-IIA Schedule Jan. 23 2009 TANSO-FTS (Fourier Transform Spectrometer) SWIR reflected on the earth s surface -TIR radiated from the ground and the atmosphere TANSO-CAI (Cloud and Aerosol Imager) Ultraviolet (UV) (0.38 micron), visible (0.67 micron), NIR (0.87 micron), and SWIR (1.6 micron) (Courtesy of JAXA) 5

Infrared Radiation measurements by GOSAT(TANSO-FTS) Near Infrared (SWIR) Thermal Infrared (TIR) (courtesy of JAXA) 6

TANSO-FTS Level 1B spectra SWIR O 2 A (0.76 μm) WCO 2 (1.6 μm) Band 1P Band 1S Band 2P Band 2S SCO 2 (2.0 μm) Band 3P (5.5 14.5 μm) TIR Band 3S Band 4 7

Cloud and Aerosol Scattering>>S Camera FOV > 30 km TANSO FTS IFOV=10.5 km TANSO CAI IFOV=0.5, 1.5 km SWATH 900km TANSO-CAI Pointing and Footprints IMC ID=5 North TANSO-FTS cross track patters Cross Track X km Camera Y km 1 789 90 3 263 283 5 158 152 7 113 115 9 88 86 @Log.&Lat. 30deg Sun Glint West TANSO-FTS S Polarization Bands South P Equator East Day Side: 1 pm orbit (Courtesy by H. Suto (JAXA)) 8

GOSAT Data Processing Flow L2 (column abundance obtained by each scan) L3 (spatial and temporal average of column abundances) Ground Monitoring Station Data Source: NIES GOSAT project pamphlet 9

TANSO-FTS SWIR L2 (V02.**) XCO 2 & XCH 4 June 2009 - Apr. 2013 CO 2 CH 4 (by Y. Yoshida (NIES)) 10

Monthly global map of XCO 2 and XCH 4 (V02.**) from TANSO-FTS SWIR data June 2009 April 2013 CO 2 CH 4 (Southern H.S.) (Northern H.S.) (Southern H.S.) (Northern H.S.) (by Y. Yoshida (NIES)) 11

XCO 2 Monthly Average GOSAT DATA 12

Data Validation of GOSAT XCO 2 and XCH 4 Data validation activities have conducted by worldwide research groups Column concentrations of CO 2 and CH 4 have been retrieved by several groups (institutes and universities) in the world. These data are validated with TCCON FTS data and/or airplane data. Present GOSAT XCO 2 data quality is within -0.3% bias and 0.5% variation. Bias = -1.2 ppm, Bias = -7 ppb σ = 2.0 ppm σ = 12 ppb 13

Carbon fluxes in 2002-2011 Fossil fuel & cement: 8.3±0.4 (GtC/yr) Land use change (incl. biomass burning): 1.0±0.5 (50%) (9.3 GtC) GFED Atmospheric growth: 4.3±0.1 (23%) Land sink: 2.6±0.8 (31%) Ocean sink: 2.5±0.5 (20%) (C. Le Quéré et al. (2013): The global carbon budget 1959 2011, doi:10.5194/essd-5-165-2013) (5%) 14

Contribution of satellite data to carbon flux estimation 15

A Priori Flux Data Used in the Inversion Anthropogenic Emission Data ODIAC Monthly data Resolution: 1 km 1 km ( Remapped to 1 1 ) Ver. 3.0 includes emissions from ships and airliners Data prepared for 2009 Oda et al., 2010 Atmos. Chem. Phys. JCDAS Analysis Data NIES-08.1 Transport Model Terrestrial Biosphere-Atmosphere Flux Data Generated with vegetation process model VISIT Biomass burning data (GFED ver.3.0) included Daily data Resolution: 0.5 0.5 ( Remapped to 1 1 ) Ito, 2010 Saito et al., 2010 J. Climate van der Werf et al. 2010 ACP Ocean-Atmosphere Flux Data Generated with ocean pco 2 data assimilation system Monthly data Resolution 1 1 (by T. Takagi & S. Maksyutov (NIES)) Valsala et al., 2008 J. Climate Valsala et al., 2010 Tellus 16

Improved regional CO 2 fluxes Demonstrated the utility of satellite-based concentration data in the estimation of global CO 2 fluxes Result of regional CO 2 flux estimation (Level 4A) July 2009 (Summer in Northern Hemisphere) Regional CO 2 Flux Estimates Data released: estimates for June 2009 to May 2010 CO 2 Flux Uncertainties JAXA/NIES/MOE JAXA/NIES/MOE January 2010 (Winter in Northern Hemisphere) Land Ocean Net Absorption JAXA/NIES/MOE Net Emission JAXA/NIES/MOE Large Uncertainty 17

Regional CO 2 Flux Estimates and Improvement of the Uncertainties Regional Uncertainty Reduction Rate of the Annual CO 2 Fluxes Takagi et al (2011). 18

Regional CO 2 Flux Estimates and Improvement of the Uncertainties [gc/m 2 /day] Emission w/o Observational Data (Model prior) GV +GOSAT [%] Absorption GV only Monthly Uncertainty Reduction Rate Regional Uncertainty Reduction Rate of the Annual CO 2 Fluxes Takagi et al (2011). 19

Regional CO 2 Flux Estimates and Improvement of the Uncertainties [gc/m 2 /day] Emission w/o Observational Data (Model prior) GV +GOSAT [%] Absorption GV only Monthly Uncertainty Reduction Rate Regional Uncertainty Reduction Rate of the Annual CO 2 Fluxes Takagi et al (2011). 20

Example of the GOSAT Level 4B Data Product Model Simulated global CO 2 concentrations in three dimensions calculated from monthly regional CO 2 flux estimates (GOSAT Level 4A data product) by using an atmospheric tracer transport model. Note that anthropogenic emissions and biomass burning data are given as known from other data in this simulation. (ppm) Daily mean animation of global CO 2 on a 2.5 2.5 latitude-longitude grid at an altitude of ~ 800 m (June 2009 May 2010) 21

Other GOSAT contributions TANSO-CAI data 22

Ash plume Observation by GOSAT in April and May 2010 Eruption of Eyjafjallajokull Volcano http://img.visir.is/apps/pbcsi.dll/bilde?site=xz&date=20100414&category=fret TIR01&ArtNo=619874521 23

GOSAT TANSO-CAI Composite Image:2010/4/15 24

GOSAT TANSO-CAI Composite Image:2010/4/16 25

Observation of Asian Sands Advection Beijing Tokyo Feb 22 & Mar 9 Mar 10 26

Observation of Asian Sands Advection Almost no Asian Sands Asian Sands Feb 22 Mar 9 27

Observation of Asian Sands Advection Feb 22 & Mar 9 Mar 10 2 月 22 日 3 Mar 月 9 日 9 3 月 9 日 28

Observation of Asian Sands Advection Asian Sands From China 2 月 22 日 Mar 10 3 月 10 日 3 月 9 日 29

Smoke billowing from the forest fires on the Indonesian island of Sumatra (June 2013) 2 月 22 日 3 月 9 日 30

Smoke billowing from the forest fires on the Indonesian island of Sumatra (June 2013) 2 月 22 日 3 月 9 日 31

Smoke billowing from the forest fires on the Indonesian island of Sumatra (June 21, 2013) Singapore 2 月 22 日 3 月 9 日 32

TANSO-CAI L3 NDVI (V01.00) 2010.01.02-02.01 2009.06.03-07.02 33

Future perspectives (Visions) Perspective on future GOSAT missions (modified slide by MOE @Rio+20 (2012)) - Filling out blank areas - Reducing GHG uncertainty Improving accuracy of GHG concentration and carbon flux Contributing to Global MRV system Long-term space-based monitoring of GHG GOSAT (2009 ~) GOSAT-2 (2018~) (GOSAT-3) (GOSAT-4 and subsequent) Possible contribution of GOSAT series Elucidating global carbon cycle through precise observation of CO 2 and CH 4 Improvement in climate change prediction Early detection of major changes in climate system Identifying changes in global environment Monitoring of GHG reduction (mitigation efforts) (Incl. REDD+ activities) Contribution to climate policy making 34

Concluding Remarks GHG concentrations estimated from satellite data are not so much highly accurate (1 ppm < x < 4 ppm (1%) for XCO 2 ) by now, but have increased the regional coverage of measurements and have contributed to reduce uncertainties in the carbon flux estimates. Aerosol and dust information obtained from the GOSAT TANSO CAI data would be also useful for environmental monitoring. GOSAT Project Webpage: http://www.gosat.nies.go.jp/index_e.html Data distribution http://data.gosat.nies.go.jp/ 35

Dec. 17, 2008 END