Dr. Yukio Yoshida Profile

Dr. Yukio Yoshida

at National Institute for Environmental Studies

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Publications (5)

Proceedings Article | 20 September 2020 Presentation + Paper

Synergy of observations from various satellites for the fast retrieval of atmospheric carbon dioxide amounts

Andrey Bril, Shamil Maksyutov, Yukio Yoshida, Anatoli Chaikovsky, Vladislau Peshcharankou

Proceedings Volume 11531, 115310M (2020) https://doi.org/10.1117/12.2572702

KEYWORDS: Satellites, Earth observing sensors, Earth's atmosphere, Algorithm development, Data processing, Remote sensing, Atmospheric sensing, Carbon dioxide, Carbon, Space operations

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Proceedings Article | 10 October 2019 Presentation + Paper

Evaluating degradations of TANSO-FTS/GOSAT using principal component analysis

Yu Someya, Yukio Yoshida

Proceedings Volume 11151, 1115104 (2019) https://doi.org/10.1117/12.2533376

KEYWORDS: Principal component analysis, Short wave infrared radiation, Sensors, Fourier transforms, Diffusers, Satellites, Gases, Calibration, Atmospheric modeling, Data modeling

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SPIE Journal Paper | 31 October 2018

Development of the empirical orthogonal functions-based algorithm for the retrievals of atmospheric CO₂ total column amount from space-borne observations of reflected sunlight

Andrey Bril, Shamil Maksyutov, Sergey Oshchepkov, Yukio Yoshida, Ryoichi Imasu, Chisa Iwasaki, Anatoli Chaikovsky, Anton Fedarenka

JARS, Vol. 12, Issue 04, 046012, (October 2018) https://doi.org/10.1117/12.10.1117/1.JRS.12.046012

KEYWORDS: Algorithm development, Satellites, Carbon monoxide, Data processing, Atmospheric optics, Earth observing sensors, Detection and tracking algorithms, Clouds, Aerosols, Carbon dioxide

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Proceedings Article | 17 October 2013 Paper

Retrievals of atmospheric CO2, CH4 and optical path modifications from the GOSAT observations

Andrey Bril, Sergey Oshchepkov, Tatsuya Yokota, Yukio Yoshida, Isamu Morino, Osamu Uchino, Dmitry Belikov, Shamil Maksyutov

Proceedings Volume 8890, 889008 (2013) https://doi.org/10.1117/12.2028486

KEYWORDS: Atmospheric optics, Carbon dioxide, Methane, Absorption, Satellites, Fourier transforms, Aerosols, Short wave infrared radiation, Atmospheric particles, Light scattering

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Proceedings Article | 8 November 2012 Paper

Estimation of regional surface CO2 fluxes with GOSAT observations using two inverse modeling approaches

Shamil Maksyutov, Hiroshi Takagi, Dmitry Belikov, Tazu Saeki, Ruslan Zhuravlev, Alexander Ganshin, Alexander Lukyanov, Yukio Yoshida, Sergey Oshchepkov, Andrey Bril, Makoto Saito, Tomohiro Oda, Vinu Valsala, Ryu Saito, Robert Andres, Thomas Conway, Pieter Tans, Tatsuya Yokota

Proceedings Volume 8529, 85290G (2012) https://doi.org/10.1117/12.979664

KEYWORDS: Carbon dioxide, Atmospheric modeling, Data modeling, Carbon, Biological research, Ecosystems, Climatology, Combustion, Vegetation, Satellites

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Inverse estimation of surface C0₂ fluxes is performed with atmospheric transport model using ground-based and GOSAT observations. The NIES-retrieved C0₂ column mixing (X_c02) and column averaging kernel are provided by GOSAT Level 2 product v. 2.0 and PPDF-DOAS method. Monthly mean C0₂ fluxes for 64 regions are estimated together with a global mean offset between GOSAT data and ground-based data. We used the fixed-lag Kalman filter to infer monthly fluxes for 42 sub-continental terrestrial regions and 22 oceanic basins. We estimate fluxes and compare results obtained by two inverse modeling approaches. In basic approach adopted in GOSAT Level4 product v. 2.01, we use aggregation of the GOSAT observations into monthly mean over 5x5 degree grids, fluxes are estimated independently for each region, and NIES atmospheric transport model is used for forward simulation. In the alternative method, the model-observation misfit is estimated for each observation separately and fluxes are spatially correlated using EOF analysis of the simulated flux variability similar to geostatistical approach, while transport simulation is enhanced by coupling with a Lagrangian transport model Flexpart. Both methods use using the same set of prior fluxes and region maps. Daily net ecosystem exchange (NEE) is predicted by the Vegetation Integrative Simulator for Trace gases (VISIT) optimized to match seasonal cycle of the atmospheric C0₂ . Monthly ocean-atmosphere C0₂ fluxes are produced with an ocean pC02 data assimilation system. Biomass burning fluxes were provided by the Global Fire Emissions Database (GFED); and monthly fossil fuel C0₂ emissions are estimated with ODIAC inventory. The results of analyzing one year of the GOSAT data suggest that when both GOSAT and ground-based data are used together, fluxes in tropical and other remote regions with lower associated uncertainties are obtained than in the analysis using only ground-based data. With version 2.0 of L2 X_c02 the fluxes appear reasonable for many regions and seasons, however there is a need for improving the L2 bias correction, data filtering and the inverse modeling method to reduce estimated flux anomalies visible in some areas. We also observe that application of spatial flux correlations with EOF based approach reduces flux anomalies.

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