Products and Science Achievements of Gosat Satellite Series

2020 ◽  
Author(s):  
Tsuneo Matsunaga ◽  
Akihiko Kuze ◽  
Ryoichi Imasu
Keyword(s):  
Gosat Satellite

scholarly journals Accurate mobile remote sensing of XCO<sub>2</sub> and XCH<sub>4</sub> latitudinal transects from aboard a research vessel

2015 ◽  
Vol 8 (12) ◽  
pp. 5023-5038 ◽  
Author(s):  
F. Klappenbach ◽  
M. Bertleff ◽  
J. Kostinek ◽  
F. Hase ◽  
T. Blumenstock ◽  
...  
Keyword(s):  
Absorption Spectrometry ◽  
Total Carbon ◽  
Research Vessel ◽  
Weather Forecasts ◽  
Technical Developments ◽  
Solar Tracker ◽  
Network Instrument ◽  
Monitoring Service ◽  
Gosat Satellite ◽  
Better Than

Abstract. A portable Fourier transform spectrometer (FTS), model EM27/SUN, was deployed onboard the research vessel Polarstern to measure the column-average dry air mole fractions of carbon dioxide (XCO2) and methane (XCH4) by means of direct sunlight absorption spectrometry. We report on technical developments as well as data calibration and reduction measures required to achieve the targeted accuracy of fractions of a percent in retrieved XCO2 and XCH4 while operating the instrument under field conditions onboard the moving platform during a 6-week cruise on the Atlantic from Cape Town (South Africa, 34° S, 18° E; 5 March 2014) to Bremerhaven (Germany, 54° N, 19° E; 14 April 2014). We demonstrate that our solar tracker typically achieved a tracking precision of better than 0.05° toward the center of the sun throughout the ship cruise which facilitates accurate XCO2 and XCH4 retrievals even under harsh ambient wind conditions. We define several quality filters that screen spectra, e.g., when the field of view was partially obstructed by ship structures or when the lines-of-sight crossed the ship exhaust plume. The measurements in clean oceanic air, can be used to characterize a spurious air-mass dependency. After the campaign, deployment of the spectrometer alongside the TCCON (Total Carbon Column Observing Network) instrument at Karlsruhe, Germany, allowed for determining a calibration factor that makes the entire campaign record traceable to World Meteorological Organization (WMO) standards. Comparisons to observations of the GOSAT satellite and concentration fields modeled by the European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) demonstrate that the observational setup is well suited to provide validation opportunities above the ocean and along interhemispheric transects.

scholarly journals Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories

2019 ◽  
Vol 11 (21) ◽  
pp. 2489 ◽  
Author(s):  
Fenjuan Wang ◽  
Shamil Maksyutov ◽  
Aki Tsuruta ◽  
Rajesh Janardanan ◽  
Akihiko Ito ◽  
...  
Keyword(s):  
High Resolution ◽  
Methane Emission ◽  
Statistical Data ◽  
Trace Gases ◽  
Inverse Model ◽  
Anthropogenic Emissions ◽  
Atmospheric Research ◽  
Assimilation System ◽  
Gosat Satellite ◽  
Country Specific

We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 yr−1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.

scholarly journals Comparisons of CH<sub>4</sub> ground-based FTIR measurements near Saint Petersburg with GOSAT observations

2014 ◽  
Vol 7 (4) ◽  
pp. 1003-1010 ◽  
Author(s):  
N. M. Gavrilov ◽  
M. V. Makarova ◽  
A. V. Poberovskii ◽  
Yu. M. Timofeyev
Keyword(s):  
Fourier Transform ◽  
Greenhouse Gases ◽  
Satellite Data ◽  
Fourier Transform Infrared ◽  
Similar Data ◽  
Saint Petersburg ◽  
Spectroscopic Observations ◽  
Atmospheric Column ◽  
Standard Deviations ◽  
Gosat Satellite

Abstract. Atmospheric column-average methane mole fractions measured with ground-based Fourier-transform spectroscopy near Saint Petersburg, Russia (59.9° N, 29.8° E, 20 m a.s.l.) are compared with similar data obtained with the Japanese GOSAT (Greenhouse gases Observing SATellite) in the years 2009–2012. Average CH4 mole fractions for the GOSAT data version V01.xx are −15.0 ± 5.4 ppb less than the corresponding values obtained from ground-based measurements (with the standard deviations of biases at 13.0 ± 4.2 ppb). For the GOSAT data version V02.xx, the average values of the differences are −1.9 ± 1.8 ppb with standard deviations of 14.5 ± 1.3 ppb. This verifies that FTIR (Fourier transform infrared) spectroscopic observations near Saint Petersburg have similar biases with GOSAT satellite data as FTIR measurements at other ground-based networks and aircraft CH4 estimations.

scholarly journals Towards constraints on fossil fuel emissions from total column carbon dioxide

2013 ◽  
Vol 13 (8) ◽  
pp. 4349-4357 ◽  
Author(s):  
G. Keppel-Aleks ◽  
P. O. Wennberg ◽  
C. W. O'Dell ◽  
D. Wunch
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Fossil Fuel ◽  
Atmospheric General Circulation Model ◽  
Source Region ◽  
Circulation Model ◽  
Policy Tool ◽  
Total Column ◽  
Gosat Satellite ◽  
Fossil Fuel Emissions

Abstract. We assess the large-scale, top-down constraints on regional fossil fuel emissions provided by observations of atmospheric total column CO2, XCO2. Using an atmospheric general circulation model (GCM) with underlying fossil emissions, we determine the influence of regional fossil fuel emissions on global XCO2 fields. We quantify the regional contrasts between source and upwind regions and probe the sensitivity of atmospheric XCO2 to changes in fossil fuel emissions. Regional fossil fuel XCO2 contrasts can exceed 0.7 ppm based on 2007 emission estimates, but have large seasonal variations due to biospheric fluxes. Contamination by clouds reduces the discernible fossil signatures. Nevertheless, our simulations show that atmospheric fossil XCO2 can be tied to its source region and that changes in the regional XCO2 contrasts scale linearly with emissions. We test the GCM results against XCO2 data from the GOSAT satellite. Regional XCO2 contrasts in GOSAT data generally scale with the predictions from the GCM, but the comparison is limited by the moderate precision of and relatively few observations from the satellite. We discuss how this approach may be useful as a policy tool to verify national fossil emissions, as it provides an independent, observational constraint.

scholarly journals Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015

2019 ◽  
Author(s):  
Joannes D. Maasakkers ◽  
Daniel J. Jacob ◽  
Melissa P. Sulprizio ◽  
Tia R. Scarpelli ◽  
Hannah Nesser ◽  
...  
Keyword(s):  
Methane Emissions ◽  
Bayesian Optimization ◽  
Atmospheric Methane ◽  
Gas Emissions ◽  
Prior Estimate ◽  
Error Standard Deviation ◽  
Log Normal ◽  
Chinese Coal ◽  
Oil Gas ◽  
Gosat Satellite

Abstract. We use 2010–2015 observations of atmospheric methane columns from the GOSAT satellite instrument in a global inverse analysis to improve estimates of methane emissions and their trends over the period, as well as the global concentration of tropospheric OH (the hydroxyl radical, methane's main sink) and its trend. Our inversion solves the Bayesian optimization problem analytically including closed-form characterization of errors. This allows us to (1) quantify the information content from the inversion towards optimizing methane emissions and its trends, (2) diagnose error correlations between constraints on emissions and OH concentrations, and (3) generate a large ensemble of solutions testing different assumptions in the inversion. We show how the analytical approach can be used even when prior error standard deviation distributions are log-normal. Inversion results show large overestimates of Chinese coal emissions and Middle East oil/gas emissions in the EDGAR v4.3.2 inventory, but little error in the US where we use a new gridded version of the EPA national greenhouse gas inventory as prior estimate. Oil/gas emissions in the EDGAR v4.3.2 inventory show large differences with national totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and our inversion is generally more consistent with the UNFCCC data. The observed 2010–2015 growth in atmospheric methane is attributed mostly to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH trends is small in comparison. We find that the inversion provides strong independent constraints on global methane emissions (546 Tg a−1) and global mean OH concentrations (atmospheric methane lifetime against oxidation by tropospheric OH of 10.8 ± 0.4 years), indicating that satellite observations of atmospheric methane could provide a proxy for OH concentrations in the future.

scholarly journals Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations

2020 ◽  
Author(s):  
Yuzhong Zhang ◽  
Daniel J. Jacob ◽  
Xiao Lu ◽  
Joannes D. Maasakkers ◽  
Tia R. Scarpelli ◽  
...  
Keyword(s):  
Growth Rates ◽  
Inverse Analysis ◽  
Methane Emissions ◽  
Bayesian Optimization ◽  
Atmospheric Methane ◽  
Tropical Wetlands ◽  
Fire Emissions ◽  
Livestock Emissions ◽  
Oil Gas ◽  
Gosat Satellite

Abstract. We conduct a global inverse analysis of 2010–2018 GOSAT satellite observations to better understand the factors controlling atmospheric methane and its accelerating increase over the 2010–2018 period. The inversion optimizes 2010–2018 anthropogenic methane emissions and their trends on a 4º × 5º grid, monthly regional wetland emissions, and annual hemispheric concentrations of tropospheric OH (the main sink of methane) also for individual years. We use an analytical solution to the Bayesian optimization problem that provides closed-form estimates of error covariances and information content for the solution. Our inversion successfully reduces the errors against the independent methane observations from the TCCON network and reproduces the interannual variability of the methane growth rate inferred from NOAA background sites. We find that prior estimates of fuel-related emissions reported by individual countries to the United Nations are too high for China (coal) and Russia (oil/gas), and too low for Venezuela (oil/gas) and the U.S. (oil/gas). We show that the 2010–2018 increase in global methane emissions is mainly driven by tropical wetlands (Amazon and tropical Africa), boreal wetlands (Eurasia), and tropical livestock (South Asia, Africa, Brazil), with no significant trend in oil/gas emissions. While the rise in tropical livestock emissions is consistent with bottom-up estimates of rapidly growing cattle populations, the rise in wetland emissions needs to be better understood. The sustained acceleration of growth rates in 2016–2018 relative to 2010–2013 is mostly from wetlands, while the peak methane growth rates in 2014–2015 are also contributed by low OH concentrations (2014) and high fire emissions (2015). Our best estimate is that OH did not contribute significantly to the 2010–2018 methane trend other than the 2014 spike, though error correlation with global anthropogenic emissions limits confidence in this result.

scholarly journals Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments

2021 ◽  
Vol 21 (18) ◽  
pp. 14159-14175
Author(s):  
Zhen Qu ◽  
Daniel J. Jacob ◽  
Lu Shen ◽  
Xiao Lu ◽  
Yuzhong Zhang ◽  
...  
Keyword(s):  
Transport Model ◽  
Joint Inversion ◽  
Methane Emissions ◽  
Spatial Inhomogeneity ◽  
Anthropogenic Source ◽  
Atmospheric Methane ◽  
Error Statistics ◽  
South Central ◽  
Prior Estimate ◽  
Gosat Satellite

Abstract. We evaluate the global atmospheric methane column retrievals from the new TROPOMI satellite instrument and apply them to a global inversion of methane sources for 2019 at 2∘ × 2.5∘ horizontal resolution. We compare the results to an inversion using the sparser but more mature GOSAT satellite retrievals and to a joint inversion using both TROPOMI and GOSAT. Validation of TROPOMI and GOSAT with TCCON ground-based measurements of methane columns, after correcting for retrieval differences in prior vertical profiles and averaging kernels using the GEOS-Chem chemical transport model, shows global biases of −2.7 ppbv for TROPOMI and −1.0 ppbv for GOSAT and regional biases of 6.7 ppbv for TROPOMI and 2.9 ppbv for GOSAT. Intercomparison of TROPOMI and GOSAT shows larger regional discrepancies exceeding 20 ppbv, mostly over regions with low surface albedo in the shortwave infrared where the TROPOMI retrieval may be biased. Our inversion uses an analytical solution to the Bayesian inference of methane sources, thus providing an explicit characterization of error statistics and information content together with the solution. TROPOMI has ∼ 100 times more observations than GOSAT, but error correlation on the 2∘ × 2.5∘ scale of the inversion and large spatial inhomogeneity in the number of observations make it less useful than GOSAT for quantifying emissions at that scale. Finer-scale regional inversions would take better advantage of the TROPOMI data density. The TROPOMI and GOSAT inversions show consistent downward adjustments of global oil–gas emissions relative to a prior estimate based on national inventory reports to the United Nations Framework Convention on Climate Change but consistent increases in the south-central US and in Venezuela. Global emissions from livestock (the largest anthropogenic source) are adjusted upward by TROPOMI and GOSAT relative to the EDGAR v4.3.2 prior estimate. We find large artifacts in the TROPOMI inversion over southeast China, where seasonal rice emissions are particularly high but in phase with extensive cloudiness and where coal emissions may be misallocated. Future advances in the TROPOMI retrieval together with finer-scale inversions and improved accounting of error correlations should enable improved exploitation of TROPOMI observations to quantify and attribute methane emissions on the global scale.

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