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Nicholas M Deutscher - One of the best experts on this subject based on the ideXlab platform.
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spectral sizing of a coarse spectral resolution satellite sensor for xco 2
Atmospheric Measurement Techniques, 2020Co-Authors: Jonas Wilzewski, Anke Roiger, Johan Strandgren, Jochen Landgraf, Dietrich G Feist, Voltaire A Velazco, Nicholas M DeutscherAbstract:Abstract. Verifying anthropogenic carbon dioxide ( CO2 ) emissions globally is essential to inform about the progress of institutional efforts to mitigate anthropogenic climate forcing. To monitor localized emission sources, spectroscopic satellite sensors have been proposed that operate on the CO2 absorption bands in the shortwave-infrared (SWIR) spectral range with ground resolution as fine as a few tens of meters to about a hundred meters. When designing such sensors, fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, such sensors are envisioned to fly in fleets of satellites, requiring low-cost and simple design, e.g., by restricting the spectrometer to a single spectral band. Here, we use measurements of the Greenhouse Gases Observing Satellite (GOSAT) to evaluate the spectral resolution and spectral band selection of a prospective satellite sensor with fine ground resolution. To this end, we degrade GOSAT SWIR spectra of the CO2 bands at 1.6 (SWIR-1) and 2.0 µ m (SWIR-2) to coarse spectral resolution, without a further addition of noise, and we evaluate single-band retrievals of the column-averaged dry-air mole fractions of CO2 ( XCO2 ) by comparison to ground truth provided by the Total Carbon Column Observing Network (TCCON) and by comparison to global “native” GOSAT retrievals with native spectral resolution and spectral band selection. Coarsening spectral resolution from GOSAT's native resolving power of >20 000 to the range of 700 to a few thousand makes the scatter of differences between the SWIR-1 and SWIR-2 retrievals and TCCON increase moderately. For resolving powers of 1200 (SWIR-1) and 1600 (SWIR-2), the scatter increases from 2.4 (native) to 3.0 ppm for SWIR-1 and 3.3 ppm for SWIR-2. Coarser spectral resolution yields only marginally worse performance than the native GOSAT configuration in terms of station-to-station variability and geophysical parameter correlations for the GOSAT–TCCON differences. Comparing the SWIR-1 and SWIR-2 configurations to native GOSAT retrievals on the global scale, however, reveals that the coarse-resolution SWIR-1 and SWIR-2 configurations suffer from some spurious correlations with geophysical parameters that characterize the light-scattering properties of the scene such as particle amount, size, height and surface albedo. Overall, the SWIR-1 and SWIR-2 configurations with resolving powers of 1200 and 1600 show promising performance for future sensor design in terms of random error sources while residual errors induced by light scattering along the light path need to be investigated further. Due to the stronger CO2 absorption bands in SWIR-2 than in SWIR-1, the former has the advantage that measurement noise propagates less into the retrieved XCO2 and that some retrieval information on particle scattering properties is accessible.
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estimates of european uptake of co2 inferred from GOSAT xco2 retrievals sensitivity to measurement bias inside and outside europe
Atmospheric Chemistry and Physics, 2016Co-Authors: Liang Feng, Nicholas M Deutscher, Dietrich G Feist, Isamu Morino, Robert Parker, Paul I Palmer, Rigel Kivi, Ralf SussmannAbstract:Abstract. Estimates of the natural CO2 flux over Europe inferred from in situ measurements of atmospheric CO2 mole fraction have been used previously to check top-down flux estimates inferred from space-borne dry-air CO2 column (XCO2) retrievals. Several recent studies have shown that CO2 fluxes inferred from XCO2 data from the Japanese Greenhouse gases Observing SATellite (GOSAT) and the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) have larger seasonal amplitudes and a more negative annual net CO2 balance than those inferred from the in situ data. The cause of this elevated European uptake of CO2 is still unclear, but some recent studies have suggested that this is a genuine scientific phenomenon. Here, we put forward an alternative hypothesis and show that realistic levels of bias in GOSAT data can result in an erroneous estimate of elevated uptake over Europe. We use a global flux inversion system to examine the relationship between measurement biases and estimates of CO2 uptake from Europe. We establish a reference in situ inversion that uses an Ensemble Kalman Filter (EnKF) to assimilate conventional surface mole fraction observations and XCO2 retrievals from the surface-based Total Carbon Column Observing Network (TCCON). We use the same EnKF system to assimilate two independent versions of GOSAT XCO2 data. We find that the GOSAT-inferred European terrestrial biosphere uptake peaks during the summer, similar to the reference inversion, but the net annual flux is 1.40 ± 0.19 GtC a−1 compared to a value of 0.58 ± 0.14 GtC a−1 for our control inversion that uses only in situ data. To reconcile these two estimates, we perform a series of numerical experiments that assimilate observations with added biases or assimilate synthetic observations for which part or all of the GOSAT XCO2 data are replaced with model data. We find that for our global flux inversions, a large portion (60–90 %) of the elevated European uptake inferred from GOSAT data in 2010 is due to retrievals outside the immediate European region, while the remainder can largely be explained by a sub-ppm retrieval bias over Europe. We use a data assimilation approach to estimate monthly GOSAT XCO2 biases from the joint assimilation of in situ observations and GOSAT XCO2 retrievals. The inferred biases represent an estimate of systematic differences between GOSAT XCO2 retrievals and the inversion system at regional or sub-regional scales. We find that a monthly varying bias of up to 0.5 ppm can explain an overestimate of the annual sink of up to 0.20 GtC a−1. Our results highlight the sensitivity of CO2 flux estimates to regional observation biases, which have not been fully characterized by the current observation network. Without further dedicated measurements we cannot prove or disprove that European ecosystems are taking up a larger-than-expected amount of CO2. More robust inversion systems are also needed to infer consistent fluxes from multiple observation types.
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does GOSAT capture the true seasonal cycle of carbon dioxide
Atmospheric Chemistry and Physics, 2015Co-Authors: Nicholas M Deutscher, Frederic Chevallier, Hartmut Boesch, Hannakaisa Lindqvist, Christopher W Odell, Sourish Basu, Liang FengAbstract:Abstract. The seasonal cycle accounts for a dominant mode of total column CO2 (XCO2) annual variability and is connected to CO2 uptake and release; it thus represents an important quantity to test the accuracy of the measurements from space. We quantitatively evaluate the XCO2 seasonal cycle of the Greenhouse Gases Observing Satellite (GOSAT) observations from the Atmospheric CO2 Observations from Space (ACOS) retrieval system and compare average regional seasonal cycle features to those directly measured by the Total Carbon Column Observing Network (TCCON). We analyse the mean seasonal cycle amplitude, dates of maximum and minimum XCO2, as well as the regional growth rates in XCO2 through the fitted trend over several years. We find that GOSAT/ACOS captures the seasonal cycle amplitude within 1.0 ppm accuracy compared to TCCON, except in Europe, where the difference exceeds 1.0 ppm at two sites, and the amplitude captured by GOSAT/ACOS is generally shallower compared to TCCON. This bias over Europe is not as large for the other GOSAT retrieval algorithms (NIES v02.21, RemoTeC v2.35, UoL v5.1, and NIES PPDF-S v.02.11), although they have significant biases at other sites. We find that the ACOS bias correction partially explains the shallow amplitude over Europe. The impact of the co-location method and aerosol changes in the ACOS algorithm were also tested and found to be few tenths of a ppm and mostly non-systematic. We find generally good agreement in the date of minimum XCO2 between ACOS and TCCON, but ACOS generally infers a date of maximum XCO2 2–3 weeks later than TCCON. We further analyse the latitudinal dependence of the seasonal cycle amplitude throughout the Northern Hemisphere and compare the dependence to that predicted by current optimized models that assimilate in situ measurements of CO2. In the zonal averages, models are consistent with the GOSAT amplitude to within 1.4 ppm, depending on the model and latitude. We also show that the seasonal cycle of XCO2 depends on longitude especially at the mid-latitudes: the amplitude of GOSAT XCO2 doubles from western USA to East Asia at 45–50° N, which is only partially shown by the models. In general, we find that model-to-model differences can be larger than GOSAT-to-model differences. These results suggest that GOSAT/ACOS retrievals of the XCO2 seasonal cycle may be sufficiently accurate to evaluate land surface models in regions with significant discrepancies between the models.
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consistent satellite xco 2 retrievals from sciamachy and GOSAT using the besd algorithm
Atmospheric Measurement Techniques, 2015Co-Authors: J Heymann, Heinrich Bovensmann, M Buchwitz, J P Burrows, Akihiko Kuze, Hiroshi Suto, M Reuter, Michael Hilker, Oliver Schneising, Nicholas M DeutscherAbstract:Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT–SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.
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estimating global and north american methane emissions with high spatial resolution using GOSAT satellite data
Atmospheric Chemistry and Physics, 2015Co-Authors: Aj Turner, Hartmut Boesch, Daniel J Jacob, Joannes D Maasakkers, Kevin W Bowman, K Wecht, Elizabeth W Lundgren, A E Andrews, S C Biraud, Nicholas M DeutscherAbstract:Abstract. We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a−1, as compared to 24.9–27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern–central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29–44 % of US anthropogenic methane emissions to livestock, 22–31 % to oil/gas, 20 % to landfills/wastewater, and 11–15 % to coal. Wetlands contribute an additional 9.0–10.1 Tg a−1.
Tomoyuki Yamaya - One of the best experts on this subject based on the ideXlab platform.
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nadh dependent glutamate synthase plays a crucial role in assimilating ammonium in the arabidopsis root
Physiologia Plantarum, 2014Co-Authors: Noriyuki Konishi, Toshihiko Hayakawa, Tomoyuki Yamaya, Keiki Ishiyama, Ikumi Maru, Kaya Matsuoka, Soichi KojimaAbstract:Plant roots under nitrogen deficient conditions with access to both ammonium and nitrate ions, will take up ammonium first. This preference for ammonium rather than nitrate emphasizes the importance of ammonium assimilation machinery in roots. Glutamine synthetase (GS) and glutamate synthase (GOGAT) catalyze the conversion of ammonium and 2-oxoglutarate to glutamine and glutamate. Higher plants have two GOGAT species, ferredoxin-dependent glutamate synthase (Fd-GOGAT) and nicotinamide adenine dinucleotide (NADH)-GOGAT. While Fd-GOGAT participates in the assimilation of ammonium, which is derived from photorespiration in leaves, NADH-GOGAT is highly expressed in roots and its importance needs to be elucidated. While ammonium as a minor nitrogen form in most soils is directly taken up, nitrate as the major nitrogen source needs to be converted to ammonium prior to uptake. The aim of this study was to investigate and quantify the contribution of NADH-GOGAT to the ammonium assimilation in Arabidopsis (Arabidopsis thaliana Columbia) roots. Quantitative real-time polymerase chain reaction (PCR) and protein gel blot analysis showed an accumulation of NADH-GOGAT in response to ammonium supplied to the roots. In addition the localization of NADH-GOGAT and Fd-GOGAT did not fully overlap. Promoter-β-glucuronidase (GUS) fusion analysis and immunohistochemistry showed that NADH-GOGAT was highly accumulated in non-green tissue like vascular bundles, shoot apical meristem, pollen, stigma and roots. Reverse genetic approaches suggested a reduction in glutamate production and biomass accumulation in NADH-GOGAT transfer DNA (T-DNA) insertion lines under normal CO2 condition. The data emphasize the importance of NADH-GOGAT in the ammonium assimilation in Arabidopsis roots.
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nadh dependent glutamate synthase participated in ammonium assimilation in arabidopsis root
Plant Signaling & Behavior, 2014Co-Authors: Soichi Kojima, Toshihiko Hayakawa, Keiki Ishiyama, Noriyuki Konishi, Marcel Pascal Beier, Ikumi Maru, Tomoyuki YamayaAbstract:Higher plants have 2 GOGAT species, Fd-GOGAT and NADH-GOGAT. While Fd-GOGAT mainly assimilates ammonium in leaves, which is derived from photorespiration, the function of NADH-GOGAT, which is highly expressed in roots,1 needs to be elucidated. The aim of this study was to clarify the role of NADH-GOGAT in Arabidopsis roots. The supply of ammonium to the roots caused an accumulation of NADH-GOGAT, while Fd-GOGAT 1 and Fd-GOGAT 2 showed no response. A promoter–GUS fusion analysis and immunohistochemistry showed that NADH-GOGAT was located in non-green tissues like vascular bundles, shoot apical meristem, pollen, stigma, and roots. The localization of NADH-GOGAT and Fd-GOGAT was not overlapped. NADH-GOGAT T-DNA insertion lines showed a reduction of glutamate and biomass under normal CO2 conditions. These data emphasizes the importance of NADH-GOGAT in the ammonium assimilation of Arabidopsis roots.
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genetic manipulation and quantitative trait loci mapping for nitrogen recycling in rice
Journal of Experimental Botany, 2002Co-Authors: Tomoyuki Yamaya, Toshihiko Hayakawa, Mitsuhiro Obara, Hiroyuki Nakajima, Shohei Sasaki, Tadashi SatoAbstract:Immunocytological studies in this laboratory have suggested that NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) in developing organs of rice (Oryza sativa L. cv. Sasanishiki) is involved in the utilization of glutamine remobilized from senescing organs through the phloem. Because most of the indica cultivars contained less NADH-GOGAT in their sink organs than japonica cultivars, over-expression of NADH-GOGAT gene from japonica rice was investigated using Kasalath, an indica cultivar. Several T0 transgenic Kasalath lines over-producing NADH-GOGAT under the control of a NADH-GOGAT promoter of Sasanishiki, a japonica rice, showed an increase in grain weight (80% as a maximum), indicating that NADH-GOGAT is indeed a key step for nitrogen utilization and grain filling in rice. A genetic approach using 98 backcross-inbred lines (BC(1)F(6)) developed between Nipponbare (a japonica rice) and Kasalath were employed to detect putative quantitative trait loci (QTLs) associated with the contents of cytosolic glutamine synthetase (GS1; EC 6.3.1.2), which is probably involved in the export of nitrogen from senescing organs and those of NADH-GOGAT. Immunoblotting analyses showed transgressive segregations toward lower or greater contents of these enzyme proteins in these BC(1)F(6). Seven chromosomal QTL regions were detected for GS1 protein content and six for NADH-GOGAT. Some of these QTLs were located in QTL regions for various biochemical and agronomic traits affected by nitrogen recycling. The relationships between the genetic variability of complex agronomic traits and traits for these two enzymes are discussed.
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organization and structure of nadh dependent glutamate synthase gene from rice plants
Biochimica et Biophysica Acta, 1998Co-Authors: Satoshi Goto, Toshihiko Hayakawa, Soichi Kojima, Takumi Akagawa, Tomoyuki YamayaAbstract:Genomic clones for NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) were obtained from a genomic library of rice (Oryza sativa L. cv. Sasanishki). A genomic clone (λOS42, 14 kb) covered an entire structural gene and a 3.7 kb 5′-upstream region from the first methionine. Another clone (λOS23, 14 kb) contained a 2.8 kb 3′-downstream region from the stop codon. A 7047 bp long clone (λOSR51) consisting of full length cDNA for NADH-GOGAT was isolated from a cDNA library prepared using mRNA from roots of rice seedlings treated with 1 mM NH4Cl for 12 h. The presumed transcribed region (11.7 kb) consisted of 23 exons separated by 22 introns. Rice NADH-GOGAT is synthesized as a 2166 amino acid protein with a molecular mass of 236.7 kDa that includes a 99 amino acid presequence. DNA gel blot analysis suggested that NADH-GOGAT occurred as a single gene in rice. Primer extension experiments map the transcription start of NADH-GOGAT to identical positions. The 3.7 kb 5′-upstream region was able to transiently express a reporter gene in cultured rice cells. Putative motifs related to the regulation of NADH-GOGAT gene expression were looked for within the 5′-upstream region by database.
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expression of nadh dependent glutamate synthase protein in the epidermis and exodermis of rice roots in response to the supply of ammonium ions
Planta, 1998Co-Authors: Keiki Ishiyama, Toshihiko Hayakawa, Tomoyuki YamayaAbstract:The mRNA and protein for NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) in root tips of rice (Oryza sativa L. cv. Sasanishiki) plants increases dramatically within 12 h of supplying a␣low concentration (>0.05 mM) of ammonium ions (T.␣Yamaya et al., 1995, Plant Cell Physiol 36: 1197–1204). To identify the specific cells which are responsible for this rapid increase, the cellular localization of NADH-GOGAT protein was investigated immunocytologically with an affinity-purified anti-NADH-GOGAT immunoglobulin G. When root tips (>1 mm) of rice seedlings which had been grown for 26 d in water were immuno-stained, signals for the NADH-GOGAT protein were detected in the central cylinder, in the apical meristem, and in the primordia of the secondary roots. Signals for ferredoxin-dependent GOGAT (Fd-GOGAT; EC 1.4.7.1) protein were also seen in the same three areas. When the roots were supplied with 1 mM ammonium ions for 24 h, there were strong signals for the NADH-GOGAT protein in two cell layers of the root surface, i.e. epidermis and exodermis, in addition to the cells giving signals in the absence of ammonium ions. The supply of ammonium ions was less effective on the profile of signals for Fd-GOGAT. Although the supply of ammonium ions had less effect on the expression of cytosolic glutamine synthetase (GS; EC 6.3.1.2), this enzyme was also found to be located in the epidermis and exodermis, as well as in the central cylinder and cortex. The results indicate that NADH-GOGAT, coupled to the cytosolic GS reaction, is probably important for the assimilation of ammonium ions in the two cell layers of the root surface.
Toshihiko Hayakawa - One of the best experts on this subject based on the ideXlab platform.
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nadh dependent glutamate synthase plays a crucial role in assimilating ammonium in the arabidopsis root
Physiologia Plantarum, 2014Co-Authors: Noriyuki Konishi, Toshihiko Hayakawa, Tomoyuki Yamaya, Keiki Ishiyama, Ikumi Maru, Kaya Matsuoka, Soichi KojimaAbstract:Plant roots under nitrogen deficient conditions with access to both ammonium and nitrate ions, will take up ammonium first. This preference for ammonium rather than nitrate emphasizes the importance of ammonium assimilation machinery in roots. Glutamine synthetase (GS) and glutamate synthase (GOGAT) catalyze the conversion of ammonium and 2-oxoglutarate to glutamine and glutamate. Higher plants have two GOGAT species, ferredoxin-dependent glutamate synthase (Fd-GOGAT) and nicotinamide adenine dinucleotide (NADH)-GOGAT. While Fd-GOGAT participates in the assimilation of ammonium, which is derived from photorespiration in leaves, NADH-GOGAT is highly expressed in roots and its importance needs to be elucidated. While ammonium as a minor nitrogen form in most soils is directly taken up, nitrate as the major nitrogen source needs to be converted to ammonium prior to uptake. The aim of this study was to investigate and quantify the contribution of NADH-GOGAT to the ammonium assimilation in Arabidopsis (Arabidopsis thaliana Columbia) roots. Quantitative real-time polymerase chain reaction (PCR) and protein gel blot analysis showed an accumulation of NADH-GOGAT in response to ammonium supplied to the roots. In addition the localization of NADH-GOGAT and Fd-GOGAT did not fully overlap. Promoter-β-glucuronidase (GUS) fusion analysis and immunohistochemistry showed that NADH-GOGAT was highly accumulated in non-green tissue like vascular bundles, shoot apical meristem, pollen, stigma and roots. Reverse genetic approaches suggested a reduction in glutamate production and biomass accumulation in NADH-GOGAT transfer DNA (T-DNA) insertion lines under normal CO2 condition. The data emphasize the importance of NADH-GOGAT in the ammonium assimilation in Arabidopsis roots.
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nadh dependent glutamate synthase participated in ammonium assimilation in arabidopsis root
Plant Signaling & Behavior, 2014Co-Authors: Soichi Kojima, Toshihiko Hayakawa, Keiki Ishiyama, Noriyuki Konishi, Marcel Pascal Beier, Ikumi Maru, Tomoyuki YamayaAbstract:Higher plants have 2 GOGAT species, Fd-GOGAT and NADH-GOGAT. While Fd-GOGAT mainly assimilates ammonium in leaves, which is derived from photorespiration, the function of NADH-GOGAT, which is highly expressed in roots,1 needs to be elucidated. The aim of this study was to clarify the role of NADH-GOGAT in Arabidopsis roots. The supply of ammonium to the roots caused an accumulation of NADH-GOGAT, while Fd-GOGAT 1 and Fd-GOGAT 2 showed no response. A promoter–GUS fusion analysis and immunohistochemistry showed that NADH-GOGAT was located in non-green tissues like vascular bundles, shoot apical meristem, pollen, stigma, and roots. The localization of NADH-GOGAT and Fd-GOGAT was not overlapped. NADH-GOGAT T-DNA insertion lines showed a reduction of glutamate and biomass under normal CO2 conditions. These data emphasizes the importance of NADH-GOGAT in the ammonium assimilation of Arabidopsis roots.
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organization and structure of ferredoxin dependent glutamate synthase gene and intracellular localization of the enzyme protein in rice plants
Plant Biotechnology, 2003Co-Authors: Toshihiko Hayakawa, Keiki Ishiyama, Naoya Hirose, Hiroyuki Nakajima, Takahiro Sakai, Masae Takezawa, Kazutaka Naito, Mutsumi Hinonakayama, Takumi Akagawa, Satoshi GotoAbstract:A 5822bp long cDNA clone encoding the full length ferredoxin-dependent glutamate synthase (Fd-GOGAT; EC 1.4.7.1) protein was isolated from roots of rice (Oryza sativa L. cv. Sasanishiki). Its sequence was identical to those of partial cDNAs for Fd-GOGAT from green leaves and shoots of rice. The predicted open reading frame (4848bp) encodes a 1616 amino acid protein with a molecular mass of 175034 Da that includes a 96-amino acid presequence. The combined nucleotide sequence of genomic clones for Fd-GOGAT isolated from rice was 20899 bp long and contained an entire structural gene, a 5672bp 5’-upstream region from the first methionine and a 779bp 3’-downstream region from the stop codon. The predicted transcribed region (15.4kb) consisted of 33 exons separated by 32 introns. The evolution among diverse GOGAT proteins, expression of Fd-GOGAT gene and intracellular localization of this protein in rice roots are also described.
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genetic manipulation and quantitative trait loci mapping for nitrogen recycling in rice
Journal of Experimental Botany, 2002Co-Authors: Tomoyuki Yamaya, Toshihiko Hayakawa, Mitsuhiro Obara, Hiroyuki Nakajima, Shohei Sasaki, Tadashi SatoAbstract:Immunocytological studies in this laboratory have suggested that NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) in developing organs of rice (Oryza sativa L. cv. Sasanishiki) is involved in the utilization of glutamine remobilized from senescing organs through the phloem. Because most of the indica cultivars contained less NADH-GOGAT in their sink organs than japonica cultivars, over-expression of NADH-GOGAT gene from japonica rice was investigated using Kasalath, an indica cultivar. Several T0 transgenic Kasalath lines over-producing NADH-GOGAT under the control of a NADH-GOGAT promoter of Sasanishiki, a japonica rice, showed an increase in grain weight (80% as a maximum), indicating that NADH-GOGAT is indeed a key step for nitrogen utilization and grain filling in rice. A genetic approach using 98 backcross-inbred lines (BC(1)F(6)) developed between Nipponbare (a japonica rice) and Kasalath were employed to detect putative quantitative trait loci (QTLs) associated with the contents of cytosolic glutamine synthetase (GS1; EC 6.3.1.2), which is probably involved in the export of nitrogen from senescing organs and those of NADH-GOGAT. Immunoblotting analyses showed transgressive segregations toward lower or greater contents of these enzyme proteins in these BC(1)F(6). Seven chromosomal QTL regions were detected for GS1 protein content and six for NADH-GOGAT. Some of these QTLs were located in QTL regions for various biochemical and agronomic traits affected by nitrogen recycling. The relationships between the genetic variability of complex agronomic traits and traits for these two enzymes are discussed.
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organization and structure of nadh dependent glutamate synthase gene from rice plants
Biochimica et Biophysica Acta, 1998Co-Authors: Satoshi Goto, Toshihiko Hayakawa, Soichi Kojima, Takumi Akagawa, Tomoyuki YamayaAbstract:Genomic clones for NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) were obtained from a genomic library of rice (Oryza sativa L. cv. Sasanishki). A genomic clone (λOS42, 14 kb) covered an entire structural gene and a 3.7 kb 5′-upstream region from the first methionine. Another clone (λOS23, 14 kb) contained a 2.8 kb 3′-downstream region from the stop codon. A 7047 bp long clone (λOSR51) consisting of full length cDNA for NADH-GOGAT was isolated from a cDNA library prepared using mRNA from roots of rice seedlings treated with 1 mM NH4Cl for 12 h. The presumed transcribed region (11.7 kb) consisted of 23 exons separated by 22 introns. Rice NADH-GOGAT is synthesized as a 2166 amino acid protein with a molecular mass of 236.7 kDa that includes a 99 amino acid presequence. DNA gel blot analysis suggested that NADH-GOGAT occurred as a single gene in rice. Primer extension experiments map the transcription start of NADH-GOGAT to identical positions. The 3.7 kb 5′-upstream region was able to transiently express a reporter gene in cultured rice cells. Putative motifs related to the regulation of NADH-GOGAT gene expression were looked for within the 5′-upstream region by database.
Tatsuya Yokota - One of the best experts on this subject based on the ideXlab platform.
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optimization of the photon path length probability density function simultaneous ppdf s method and evaluation of co retrieval performance under dense aerosol conditions
Sensors, 2019Co-Authors: Chisa Iwasaki, Yukio Yoshida, Tatsuya Yokota, Sergey Oshchepkov, Andrey Bril, Ryoichi Imasu, V I Zakharov, K Gribanov, Nikita RokotyanAbstract:The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO₂) and methane (XCH₄) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO₂ retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO₂ concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO₂ adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO₂. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO₂ from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO₂ was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO₂ analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified.
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Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions
MDPI AG, 2019Co-Authors: Chisa Iwasaki, Yukio Yoshida, Tatsuya Yokota, Sergey Oshchepkov, Andrey Bril, Ryoichi Imasu, K Gribanov, Vyacheslav Zakharov, Nikita RokotyanAbstract:The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO2 retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO2 concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO2 adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO2. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO2 from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO2 was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO2 analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified
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validation of xch 4 derived from swir spectra of GOSAT tanso fts with aircraft measurement data
Atmospheric Measurement Techniques, 2014Co-Authors: Makoto Inoue, Isamu Morino, Osamu Uchino, Yuki Miyamoto, Tazu Saeki, Yukio Yoshida, Tatsuya Yokota, Colm Sweeney, P P TansAbstract:Abstract. Column-averaged dry-air mole fractions of methane (XCH4), retrieved from Greenhouse gases Observing SATellite (GOSAT) short-wavelength infrared (SWIR) spectra, were validated by using aircraft measurement data from the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. In the calculation of XCH4 from aircraft measurements (aircraft-based XCH4), other satellite data were used for the CH4 profiles above the tropopause. We proposed a data-screening scheme for aircraft-based XCH4 for reliable validation of GOSAT XCH4. Further, we examined the impact of GOSAT SWIR column averaging kernels (CAK) on the aircraft-based XCH4 calculation and found that the difference between aircraft-based XCH4 with and without the application of the GOSAT CAK was less than ±9 ppb at maximum, with an average difference of −0.5 ppb. We compared GOSAT XCH4 Ver. 02.00 data retrieved within ±2° or ±5° latitude–longitude boxes centered at each aircraft measurement site with aircraft-based XCH4 measured on a GOSAT overpass day. In general, GOSAT XCH4 was in good agreement with aircraft-based XCH4. However, over land, the GOSAT data showed a positive bias of 1.5 ppb (2.0 ppb) with a standard deviation of 14.9 ppb (16.0 ppb) within the ±2° (±5°) boxes, and over ocean, the average bias was 4.1 ppb (6.5 ppb) with a standard deviation of 9.4 ppb (8.8 ppb) within the ±2° (±5°) boxes. In addition, we obtained similar results when we used an aircraft-based XCH4 time series obtained by curve fitting with temporal interpolation for comparison with GOSAT data.
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validation of xco 2 derived from swir spectra of GOSAT tanso fts with aircraft measurement data
Atmospheric Chemistry and Physics, 2013Co-Authors: Makoto Inoue, Isamu Morino, Osamu Uchino, Yuki Miyamoto, Yukio Yoshida, Tatsuya Yokota, Toshinobu Machida, Yousuke Sawa, H Matsueda, Colm SweeneyAbstract:Abstract. Column-averaged dry air mole fractions of carbon dioxide (XCO2) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were validated with aircraft measurements by the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. To calculate XCO2 based on aircraft measurements (aircraft-based XCO2), tower measurements and model outputs were used for additional information near the surface and above the tropopause, respectively. Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAKs) and the shape of a priori profiles on the aircraft-based XCO2 calculation. The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than ±0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2. We compared GOSAT data retrieved within ±2 or ±5° latitude/longitude boxes centered at each aircraft measurement site to aircraft-based data measured on a GOSAT overpass day. The results indicated that GOSAT XCO2 over land regions agreed with aircraft-based XCO2, except that the former is biased by −0.68 ppm (−0.99 ppm) with a standard deviation of 2.56 ppm (2.51 ppm), whereas the averages of the differences between the GOSAT XCO2 over ocean and the aircraft-based XCO2 were −1.82 ppm (−2.27 ppm) with a standard deviation of 1.04 ppm (1.79 ppm) for ±2° (±5°) boxes.
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effects of atmospheric light scattering on spectroscopic observations of greenhouse gases from space part 2 algorithm intercomparison in the GOSAT data processing for co2 retrievals over tccon sites
Journal of Geophysical Research, 2013Co-Authors: Sergey Oshchepkov, Nicholas M Deutscher, Yukio Yoshida, Tatsuya Yokota, Andrey Bril, Debra Wunch, P O Wennberg, Geoffrey C Toon, Christopher W OdellAbstract:GOSAT is a joint effort of the Japan Aerospace Exploration Agency (JAXA), the National Institute for Environmental Studies (NIES), and the Ministry of the Environment (MOE), Japan. Part of this work on ACOS B2.9 was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. GOSAT spectra were kindly provided to the California Institute of Technology through a memorandum of understanding between JAXA and NASA. U. S. funding for TCCON is provided by NASA’s Terrestrial Ecology Program (grant number NNX11AG01G), the Orbiting Carbon Observatory Program, the Atmospheric CO2 Observations from Space (ACOS) Program, and the Department of Energy/Atmospheric Radiation Measurement (DOE/ARM) Program. The Darwin TCCON site was built at Caltech with funding from the OCO project and is operated by the University of Wollongong, with travel funds for maintenance and equipment costs funded by the OCO-2 project. We acknowledge funding to support Darwin and Wollongong from the Australian Research Council, Projects LE0668470, DP0879468, DP110103118, and LP0562346. Lauder TCCON measurements are funded by New Zealand Foundation of Research Science and Technology contracts C01X0204 and CO1X0406. We acknowledge financial support of the Bia- lystok and Orleans TCCON sites from the Senate of Bremen and EU projects IMECC, GEOMON and InGOS as well as maintenance and logistical work provided by AeroMeteo Service (Bialystok) and the RAMCES team at LSCE (Gif-sur-Yvette, France) and additional operational funding from the NIES GOSAT project. The Garmisch TCCON team acknowledges funding by the EC-INGOS project. Development of RemoTeC was partly funded by ESA through the GHG-CCI project (S. Guerlet) and by Deutsche Forschungsgemeinschaft (DFG) through grant BU2599/1-1 (A. Butz). The JRA-25/JCDAS data sets used for atmospheric transport modeling were provided by the cooperative, long-term reanalysis project by the Japan Meteorological Agency (JMA) and Central Research Institute of Electric Power Industry (CRIEPI). The authors thank Dr. Sasano, Director of the Center for Global Environmental Research at the NIES, the members of the NIES GOSAT and NASA ACOS projects.
Yukio Yoshida - One of the best experts on this subject based on the ideXlab platform.
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optimization of the photon path length probability density function simultaneous ppdf s method and evaluation of co retrieval performance under dense aerosol conditions
Sensors, 2019Co-Authors: Chisa Iwasaki, Yukio Yoshida, Tatsuya Yokota, Sergey Oshchepkov, Andrey Bril, Ryoichi Imasu, V I Zakharov, K Gribanov, Nikita RokotyanAbstract:The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO₂) and methane (XCH₄) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO₂ retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO₂ concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO₂ adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO₂. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO₂ from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO₂ was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO₂ analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified.
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Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions
MDPI AG, 2019Co-Authors: Chisa Iwasaki, Yukio Yoshida, Tatsuya Yokota, Sergey Oshchepkov, Andrey Bril, Ryoichi Imasu, K Gribanov, Vyacheslav Zakharov, Nikita RokotyanAbstract:The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO2 retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO2 concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO2 adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO2. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO2 from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO2 was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO2 analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified
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validation of xch 4 derived from swir spectra of GOSAT tanso fts with aircraft measurement data
Atmospheric Measurement Techniques, 2014Co-Authors: Makoto Inoue, Isamu Morino, Osamu Uchino, Yuki Miyamoto, Tazu Saeki, Yukio Yoshida, Tatsuya Yokota, Colm Sweeney, P P TansAbstract:Abstract. Column-averaged dry-air mole fractions of methane (XCH4), retrieved from Greenhouse gases Observing SATellite (GOSAT) short-wavelength infrared (SWIR) spectra, were validated by using aircraft measurement data from the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. In the calculation of XCH4 from aircraft measurements (aircraft-based XCH4), other satellite data were used for the CH4 profiles above the tropopause. We proposed a data-screening scheme for aircraft-based XCH4 for reliable validation of GOSAT XCH4. Further, we examined the impact of GOSAT SWIR column averaging kernels (CAK) on the aircraft-based XCH4 calculation and found that the difference between aircraft-based XCH4 with and without the application of the GOSAT CAK was less than ±9 ppb at maximum, with an average difference of −0.5 ppb. We compared GOSAT XCH4 Ver. 02.00 data retrieved within ±2° or ±5° latitude–longitude boxes centered at each aircraft measurement site with aircraft-based XCH4 measured on a GOSAT overpass day. In general, GOSAT XCH4 was in good agreement with aircraft-based XCH4. However, over land, the GOSAT data showed a positive bias of 1.5 ppb (2.0 ppb) with a standard deviation of 14.9 ppb (16.0 ppb) within the ±2° (±5°) boxes, and over ocean, the average bias was 4.1 ppb (6.5 ppb) with a standard deviation of 9.4 ppb (8.8 ppb) within the ±2° (±5°) boxes. In addition, we obtained similar results when we used an aircraft-based XCH4 time series obtained by curve fitting with temporal interpolation for comparison with GOSAT data.
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validation of xco 2 derived from swir spectra of GOSAT tanso fts with aircraft measurement data
Atmospheric Chemistry and Physics, 2013Co-Authors: Makoto Inoue, Isamu Morino, Osamu Uchino, Yuki Miyamoto, Yukio Yoshida, Tatsuya Yokota, Toshinobu Machida, Yousuke Sawa, H Matsueda, Colm SweeneyAbstract:Abstract. Column-averaged dry air mole fractions of carbon dioxide (XCO2) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were validated with aircraft measurements by the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. To calculate XCO2 based on aircraft measurements (aircraft-based XCO2), tower measurements and model outputs were used for additional information near the surface and above the tropopause, respectively. Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAKs) and the shape of a priori profiles on the aircraft-based XCO2 calculation. The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than ±0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2. We compared GOSAT data retrieved within ±2 or ±5° latitude/longitude boxes centered at each aircraft measurement site to aircraft-based data measured on a GOSAT overpass day. The results indicated that GOSAT XCO2 over land regions agreed with aircraft-based XCO2, except that the former is biased by −0.68 ppm (−0.99 ppm) with a standard deviation of 2.56 ppm (2.51 ppm), whereas the averages of the differences between the GOSAT XCO2 over ocean and the aircraft-based XCO2 were −1.82 ppm (−2.27 ppm) with a standard deviation of 1.04 ppm (1.79 ppm) for ±2° (±5°) boxes.
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effects of atmospheric light scattering on spectroscopic observations of greenhouse gases from space part 2 algorithm intercomparison in the GOSAT data processing for co2 retrievals over tccon sites
Journal of Geophysical Research, 2013Co-Authors: Sergey Oshchepkov, Nicholas M Deutscher, Yukio Yoshida, Tatsuya Yokota, Andrey Bril, Debra Wunch, P O Wennberg, Geoffrey C Toon, Christopher W OdellAbstract:GOSAT is a joint effort of the Japan Aerospace Exploration Agency (JAXA), the National Institute for Environmental Studies (NIES), and the Ministry of the Environment (MOE), Japan. Part of this work on ACOS B2.9 was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. GOSAT spectra were kindly provided to the California Institute of Technology through a memorandum of understanding between JAXA and NASA. U. S. funding for TCCON is provided by NASA’s Terrestrial Ecology Program (grant number NNX11AG01G), the Orbiting Carbon Observatory Program, the Atmospheric CO2 Observations from Space (ACOS) Program, and the Department of Energy/Atmospheric Radiation Measurement (DOE/ARM) Program. The Darwin TCCON site was built at Caltech with funding from the OCO project and is operated by the University of Wollongong, with travel funds for maintenance and equipment costs funded by the OCO-2 project. We acknowledge funding to support Darwin and Wollongong from the Australian Research Council, Projects LE0668470, DP0879468, DP110103118, and LP0562346. Lauder TCCON measurements are funded by New Zealand Foundation of Research Science and Technology contracts C01X0204 and CO1X0406. We acknowledge financial support of the Bia- lystok and Orleans TCCON sites from the Senate of Bremen and EU projects IMECC, GEOMON and InGOS as well as maintenance and logistical work provided by AeroMeteo Service (Bialystok) and the RAMCES team at LSCE (Gif-sur-Yvette, France) and additional operational funding from the NIES GOSAT project. The Garmisch TCCON team acknowledges funding by the EC-INGOS project. Development of RemoTeC was partly funded by ESA through the GHG-CCI project (S. Guerlet) and by Deutsche Forschungsgemeinschaft (DFG) through grant BU2599/1-1 (A. Butz). The JRA-25/JCDAS data sets used for atmospheric transport modeling were provided by the cooperative, long-term reanalysis project by the Japan Meteorological Agency (JMA) and Central Research Institute of Electric Power Industry (CRIEPI). The authors thank Dr. Sasano, Director of the Center for Global Environmental Research at the NIES, the members of the NIES GOSAT and NASA ACOS projects.
