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Oral Presentations

BG05 - Greenhouse Gases Budget of Asia in Global Perspectives
Monday, August 03, 2015 | 324 | 08:30-10:30
BG05-D1-AM1-324-001 (BG05-A005)
One Year of Operation: The Orbiting Carbon Observatory-2 (OCO-2)
Florian M. SCHWANDNER1#+, David CRISP2, Annmarie ELDERING2, Michael R. GUNSON2, Vijay NATRAJ2
1 Jet Propulsion Laboratory, California Institute of Technology, United States, 2 Jet Propulsion Laboratory/ California Institute of Technology (Caltech), United States
#Corresponding author: +Presenter

The Orbiting Carbon Observatory-2 (OCO-2) is the first NASA satellite deployed specifically to measure atmospheric column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) with the sensitivity, accuracy, and resolution needed to characterize CO2 regional sources and sinks globally.  It measures the absorption of reflected sunlight in the 0.760μm oxygen A-Band and two CO2 bands near 1.61μm and 2.06μm, at unprecedented spatial resolution.  On July 2nd, 2014, OCO-2 launched and now leads the “A-Train” constellation of satellites.  After on-orbit spacecraft and instrument characterization, “first light” spectra were recorded over Papua New Guinea on 3 August 2014. 

After a 2-month calibration period, the instrument began collecting about one million soundings each day along a < 10.6 km swath in either nadir or glint mode.  Up to 25% are sufficiently cloud free to yield precise estimates of XCO2. A sounding selection algorithm selects the best 6%, spatially representative data. For validation, thousands of soundings are collected in target mode over Total Carbon Column Observing Network (TCCON) stations.  Regular deliveries of calibrated OCO-2 spectra to the NASA Goddard Earth Science Data and Information Services Center (GES DISC) began on December 30, 2014, and XCO2 and other products are delivered by the end of March, 2015.  These data are free to access and use.

Since 2009, The OCO-2 team has closely collaborated with the Japanese GOSAT team to calibrate its spectra, retrieve XCO2, and validate these products against internationally accepted standards. This experience facilitates the early delivery of high quality OCO-2 data products. This will enable new tools for discriminating regional CO2 emissions and sinks over Southeast Asia. OCO-2 encourages initiatives like establishing ground-based validation stations in Asia that follow internationally accepted standards. We are currently collaborating with the GOSAT-2 team and others to establish the first tropical Asia TCCON station in the Philippines.

BG05-D1-AM1-324-002 (BG05-A004)
A Joint Data Assimilation System (Tan-Tracker) to Simultaneously Estimate Surface CO2 Fluxes and 3-D Atmospheric CO2 Concentrations from Observations
Xiangjun TIAN#+, Zhenghui XIE, Yi LIU, Zhaonan CAI, Yu FU
Institute of Atmospheric Physics, Chinese Academy of Sciences, China
#Corresponding author: +Presenter

We have developed a novel framework ("Tan-Tracker") for assimilating observations of atmospheric CO2 concentrations, based on the POD-based (proper orthogonal decomposition) ensemble four-dimensional variational data assimilation method (PODEn4DVar). The high flexibility and the high computational efficiency of the PODEn4DVar approach allow us to include both the atmospheric CO2 concentrations and the surface CO2 fluxes as part of the large state vector to be simultaneously estimated from assimilation of atmospheric CO2observations. Compared to most modern top-down flux inversion approaches, where only surface fluxes are considered as control variables, one major advantage of our joint data assimilation system is that, in principle, no assumption on perfect transport models is needed. In addition, the possibility for Tan-Tracker to use a complete dynamic model to consistently describe the time evolution of CO2 surface fluxes (CFs) and the atmospheric CO2 concentrations represents a better use of observation information for recycling the analyses at each assimilation step in order to improve the forecasts for the following assimilations. An experimental Tan-Tracker system has been built based on a complete augmented dynamical model, where (1) the surface atmosphere CO2 exchanges are prescribed by using a persistent forecasting model for the scaling factors of the first-guess net CO2 surface fluxes and (2) the atmospheric CO2 transport is simulated by using the GEOS-Chem three-dimensional global chemistry transport model. Observing system simulation experiments (OSSEs) for assimilating synthetic in situ observations of surface CO2 concentrations are carefully designed to evaluate the effectiveness of the Tan-Tracker system. In particular, detailed comparisons are made with its simplified version (referred to as TT-S) with only CFs taken as the prognostic variables. It is found that our Tan-Tracker system is capable of outperforming TT-S with higher assimilation precision for both CO2concentrations and CO2 fluxes, mainly due to the simultaneous estimation of CO2 concentrations and CFs in our Tan-Tracker data assimilation system. A experiment for assimilating the real dry-air column CO2 retrievals (XCO2) from the Japanese Greenhouse Gases Observation Satellite (GOSAT) further demonstrates its potential wide applications.

BG05-D1-AM1-324-003 (BG05-A001)
Inverse Estimation of CH4 Emissions Using JAMSTEC’ ACTM Forward Model
Prabir PATRA1,2#+
1 Japan Agency for Marine-Earth Science and Technology, Japan, 2 Tohoku University, Japan
#Corresponding author: +Presenter

An inverse modelling system for estimating CH4 emissions from 53 land regions has been developed. We have used atmospheric-CH4 observations at 82 sites for estimating monthly-mean emissions over the period of 2002-2012. The forward transport simulations are conducted using the CCSR/NIES/FRCGC general circulation model-based chemistry transport model, i.e., the JAMSTEC’s ACTM. The chemical loss of CH4 and radical concentrations are parameterized as per the TransCom-CH4 protocol. Five cases of prior CH4 emission scenarios are constructed, by varying mainly the EDGAR42FT anthropogenic emissions. The natural emissions are taken from NASA/GISS, GFEDv3 and VISIT model simulations.

The table below shows the long-term mean CH4 emissions (in Tg/yr) from different continents, with an emphasis on the Asia regions. Detailed results for interannual variations in relation to the climate variability and comparison with other estimated emissions will be discussed during the presentation.

Acknowledgements: We are indebted to atmospheric-CH4 data providers to the WMO WDCGG.

BG05-D1-AM1-324-004 (BG05-A006)
Correction of Atmospheric Methane Mole Fraction Measured at Anmyeondo Station in Korea from 1999 to 2013
Haeyoung LEE#+, Hee-Jung YOO, Hong-Woo CHOI, Eun-Young CHOI, Chulkyu LEE, Bok-Haeung HEO
Korea Meteorological Administration, South Korea
#Corresponding author: +Presenter

Anmyeondo (AMY, 36.538E, 126.328N) station, one of GAW regional stations in Korea, has monitored atmospheric methane since 1999. Historically the methane concentrations have been decided by one point calibration, which were injected every six hour, against the CMDL83 scale from 1999 to Jun 2005, the KRISS scale from July 2005 to October 2013, and the NOAA04 scale from November 2013 using GC-FID (Agilent 6890A). We had experiments about the system performance on its linearity and drift and a comparison experiment between the three different standard scales for correction of previous methane data.

For the system performance, due to a linearity of GC-FID, one-point calibration was reasonable indicating that one standard gas of about 1800 ppb, which AMY has used, covered the range from 1700 to 2100 ppb of atmospheric methane concentrations in this study. In order to correct the instrumental drift, target tank analysis was applied. Since a standard gas was injected every 6 hour it could be used as not only standard gas for the calibration but also a target tank for tracking drifts from the instrument. Through the correction of its drift, methane mole fraction increased 0.7 ppb in mean average during the whole measurement period.

In comparison experiment between NOAA04 scale and KRISS scale, the NOAA04 scale was 0.12% lower than KRISS scale showing that it was in the compatibility goal of GAW in this study while the NOAA04 scale was 1.24% higher than the CMDL83 scale (Dlugokencky et al., 2005).

After the standard scale conversions and drift corrections, atmospheric methane mole fractions increased 19.3 ppb in mean average during the period of the CMDL83 scale and decreased 1.4 ppb during the period of the KRISS scale while the growth rate decreased from 4.91 ppb/yr to 3.5 ppb/yr at AMY during the whole period. 

BG05-D1-AM1-324-005 (BG05-A007)
Use of the Global Eulerian-Lagrangian Coupled Transport Model for Flux Inversion
Dmitry BELIKOV1#+, Shamil MAKSYUTOV2, Alexey YAREMCHUK3, Alexander GANSHIN4, Ruslan ZHURAVLEV4, Shuji AOKI5
1 Hokkaido University, Japan, 2 National Institute for Environmental Studies, Japan, 3 N.N. Andreev Acoustic Institute, Russian Federation, 4 Central Aerological Observatory, Russian Federation, 5 Tohoku University, Japan
#Corresponding author: +Presenter

We present the development of an inverse modeling system employing an adjoint of the global Eulerian-Lagrangian coupled transport model consisting of the National Institute for Environmental Studies (NIES) as Eulerian transport model (TM) and the Lagrangian plume diffusion model (LPDM) FLEXPART. NIES TM is a three-dimensional atmospheric transport model, which solves the continuity equation for a number of atmospheric tracers on a grid spanning the entire globe. The Lagrangian component of the forward and adjoint models uses precalculated responses of the observed concentration to the surface fluxes and 3-D concentrations field simulated with the FLEXPART model. Construction of the adjoint of the Lagrangian part is simple, as LPDMs calculate the sensitivity of measurements to the surrounding emissions field by tracking a large number of “particles” backwards in time. Developing of the adjoint to Eulerian part required significant manual code modification owing to the structure and complexity of the NIES model.

The overall advantages of our method are follows:

1.    No code modification of Lagrangian model is required, making it applicable to combination of global NIES TM and any Lagrangian model;

2.    Once run, the Lagrangian output can be applied to any chemically neutral gas;

3.    High-resolution results can be obtained over limited regions close to the monitoring sites (using the LPDM part), and at coarse resolution for the rest of the globe (using the Eulerian part), minimizing aggregation errors and computation cost.

The results are verified using a series of test experiments. These tests demonstrate the high accuracy of the NIES-FLEXPART adjoint when compared with direct forward sensitivity calculations. The potential for inverse modeling using the adjoint of NIES- FLEXPART coupled model is assessed in a data assimilation framework using simulated observations, demonstrating the feasibility of exploiting measurements for optimizing emission inventories.

BG05-D1-AM1-324-006 (BG05-A010)
Greenhouse Gas Observation and Carbon Flux Estimation Over Asia and Oceania Using Space-Based GOSAT Platform
Tatsuya YOKOTA#+, Yukio YOSHIDA, Isamu MORINO, Osamu UCHINO, Hiroshi TAKAGI, Heon-Sook KIM, Makoto SAITO, Shamil MAKSYUTOV, Nobuko SAIGUSA, Mukai HITOSHI
National Institute for Environmental Studies, Japan
#Corresponding author: +Presenter

The Greenhouse gases Observing SATellite (GOSAT) has operated for about six years since its launch in January 2009. From observational data that GOSAT collected globally, the concentrations of major greenhouse gases (GHGs), carbon dioxide (CO2) and methane (CH4), were retrieved  (disseminated publicly as GOSAT Level 2 data product), and their precisions are now ~0.5% and 0.7%, respectively. Using the Level 2 concentration data, the monthly surface fluxes of CO2 and CH4, on sub-continental and ocean-basin scales, were estimated. The flux estimates (Level 4A data) and the model-simulated three-dimensional GHG distributions (Level 4B data) over the first three years of GOSAT operation (2009 – 2012) are now available. The Level 2 concentration data were also utilized to monitor GHGs’ temporal and spatial changes. The Level 2 data over Asia and Oceania are available, but their number is limited due to persistent cloud coverage throughout the year, thereby influencing the Level 4 flux estimates for these regions. Despite this, several research outcomes on CO2 and CH4 flux estimation for these regions have been obtained. These findings suggest that combining GHG data from satellites, aircrafts, ships, and ground-based monitoring stations is useful in estimating total carbon stock and its changes in these regions.

In 2014, GOSAT went through some technical difficulties in the functioning of its solar paddle and sensor pointing mechanism, and the characteristics of the Fourier transform spectrometer onboard were therefore altered to some degree. However, the GOSAT observation is being continued without major flaws.

In this presentation, we will summarize the six-year-long GHG observation by GOSAT and outline the surface flux estimates obtained, in particular, for Asia and Oceania. We will also explain the status of the GOSAT data product distribution and show you a future plan of GOSAT observation over the Asia-Oceania regions.

BG05 - Greenhouse Gases Budget of Asia in Global Perspectives
Monday, August 03, 2015 | 324 | 11:00-12:30
BG05-D1-AM2-324-007 (BG05-A011)
The CSIRO Australian Tropical Atmospheric Research Station (ATARS) – Greenhouse Gas Measurements & Research Program
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
#Corresponding author: +Presenter

The tropics have a major impact on the global atmosphere, through both natural and anthropogenic processes. Many of these processes and their impacts on climate are poorly understood, which is due significantly to a deficiency of high quality atmospheric observation programs in these important regions.

To address this deficiency, a high precision atmospheric observation network for greenhouse gases (GHG) and related trace gas species is being expanded in the Southeast Asian-Australian region.

The Cape Grim Baseline Air Pollution Station (CGBAPS) is the central reference observation site for the existing Australian regional GHG network. CGBAPS is one of only three designated GHG key comparison stations in the WMO/GAW program and is the only one in the Southern Hemisphere. A recent addition to this network is the pilot Australian Tropical Atmospheric Research Station (ATARS) established at Gunn Point, near Darwin in Australia’s Northern Territory (12.249S, 131.045E, elevation 25 metres). This site incorporates high precision in-situ measurement and flask air sample collection programs for a range of GHG and related trace gas species. In addition, there are research programs for reactive gases, aerosols, radon and short lived biogenic halocarbons.

The Gunn Point site is an Australian Bureau of Meteorology research radar station (since 1997). The site has been involved in numerous tropical meteorology field campaigns and experiments including: “HIWC”, “Mctex”, “TRMM”, “Dawex”, and “TWPICE”. This combination of research capabilities with both chemical composition and physical dynamical aspects of the tropical atmosphere provides a unique opportunity to develop a unique tropical atmosphere research capability.

The status of this new site will be presented here, including the expanding research program and current GHG data from this new site.

BG05-D1-AM2-324-008 (BG05-A002)
A Regional Carbon Data Assimilation System and Its Preliminary Evaluation in East Asia
Meigen ZHANG1#+, Zhen PENG2, Xiangjun TIAN1
1 Institute of Atmospheric Physics, Chinese Academy of Sciences, China, 2 Nanjing University, China
#Corresponding author: +Presenter

In order to optimize surface CO2 fluxes at grid scales, a regional surface CO2 flux inversion system (Carbon Flux Inversion system and Community Multi-scale Air Quality, CFI-CMAQ) has been developed by applying the ensemble Kalman filter (EnKF) to constrain the CO2 concentrations and applying the ensemble Kalman smoother (EnKS) to optimize the surface CO2 fluxes. The smoothing operator is associated with the atmospheric transport model to constitute a persistence dynamical model to forecast the surface CO2 flux scaling factors. In this implementation, the “signaltonoise” problem can be avoided; plus, any useful observed information achieved by the current assimilation cycle can be transferred into the next assimilation cycle. Thus, the surface CO2 fluxes can be optimized as a whole at the grid scale in CFI-CMAQ. The performance of CFI-CMAQ was quantitatively evaluated through a set of Observing System Simulation Experiments (OSSEs) by assimilating CO2 retrievals from GOSAT (Greenhouse Gases Observing Satellite). The results showed that the CO2 concentration assimilation using EnKF could constrain the CO2 concentration effectively, illustrating that the simultaneous assimilation of CO2 oncentrations can provide convincing CO2 initial analysis fields for CO2 flux inversion. In addition, the CO2 flux optimization using EnKS demonstrated that CFI-CMAQ could, in general, reproduce true fluxes at grid scales with acceptable bias. Two further sets of numerical experiments were conducted to investigate the sensitivities of the inflation factor of scaling factors and the smoother window. The results showed that the ability of CFI-CMAQ to optimize CO2 fluxes greatly relied on the choice of the inflation factor. However, the smoother window had a slight influence on the optimized results. CFI-CMAQ performed very well even with a short lag-window (e.g. 3 days).

Poster Presentations

  BG05-D3-PM2-P-009 (BG05-A003)
GOSAT Satellite Carbon Dioxide Data Assimilation Experiment Based on Tan-Tracker System
Rui HAN+, Xiangjun TIAN#
Institute of Atmospheric Physics, Chinese Academy of Sciences, China
#Corresponding author: +Presenter

The performance of a joint data assimilation system(Tan-Tracker) based on PODEn4Dvar assimilation method, which intent to reach high flexibility and high computational efficiency, has been assessed by designing a data assimilation experience of GOSAT satellite carbon dioxide data as observations. Firstly, We simulatedatmospheric 3-D CO2 concentrations and CO2 surface fluxes (CFs) of the first half year of 2010 using GEOS-Chem(Goddard Earth Observing System-Chemistry) model. Subsequently, the simulated results, worked as background field, were put into the Tan-Tracker system to assimilate the Japanese Greenhouse Gases Observation Satellite (GOSAT) column average dry-air mole fraction data of CO2(XCO2), data version ACOS_V3.3, to optimize the concentrations together with CFs at the same assimilation window to get the assimilated atmospheric 3-D CO2 concentrations and CFs. Simulated and assimilated retrieved XCO2model(XCO2Sim and XCO2TT) at the satellite scan location, latitude and longitude, were compared with the GOSAT XCO2(XCO2Obs) by month. Root-Mean Square Error(RMSE) of XCO2model and XCO2Obs was dramatic decline(about 40%) after assimilating, with the change of correlation coefficient (CORR) of XCO2model and XCO2Obswas less obvious, for each month. A marked fall of errors between XCO2model and XCO2Obs were found at Northern Africa(Sahara), Indian Peninsula, Southern Africa, Southern North America and Western Australia after assimilating. While the assimilated result of the latter half of year 2010 was not as good as simulated, futher research of the usability and parameters correction of GOSAT XCO2 data is needed.

  BG05-D3-PM2-P-010 (BG05-A009)
Signature of Fossil Fuel Emission of CO2 from Large Point Sources in GOSAT XCO2 Data
Rajesh JANARDANAN ACHARI1#+, Tomohiro ODA2, Shamil MAKSYUTOV1, Johannes KAISER3, Makoto SAITO1, Alexamder GANSHIN4, Yukio YOSHIDA1, Tatsuya YOKOTA1
1 National Institute for Environmental Studies, Japan, 2 Colorado State University, National Oceanic and Atmospheric Administration, United States, 3 Max Planck Institute for Chemistry, Germany, 4 Central Aerological Observatory, Russian Federation
#Corresponding author: +Presenter

We analyzed three and half years (June 2009 through December 2012) of GOSAT column-averaged CO2 (XCO2) data for presence of fossil fuel emission signature by estimating XCO2 abundance at each observation location where high-resolution (0.10) inventory-based (ODIAC) transport model simulated above 0.1 ppm enhancement in fossil XCO2, relative to mean clean background observations in global 100x100 regions. Corrections for contributions from biospheric and biomass burning fluxes were made based on simulated values using high resolution fluxes from Vegetation Integrative SImulator of Trace gases (VISIT) model and Global Fire Assimilation System (GFAS). We assume influence from oceanic CO2 fluxes to continental fine-scale variability is relatively small. Observed and simulated fossil fuel enhancements were clustered and averaged according to the simulated discrete enhancement levels (each 0.2 ppm levels) for each month and 100x100 region. The results were aggregated for the whole analysis period and the observed values were linearly regressed against simulated ones. Results show near linear relations between observed and inventory based XCO2 enhancements, for the globe and  large continental regions which contribute significantly to the global atmospheric CO2 through emission from fossil fuel use. Our finding of linear scaling between satellite derived and observation based fossil fuel enhancements shows the utility of GOSAT to verify fossil fuel emission inventory. Considerably better performance can be expected for emission monitoring if sufficient number of observations of Large Point Sources and surrounding cleaner areas by GOSAT or similar satellites.