scholarly journals Large XCH<sub>4</sub> anomaly in summer 2013 over northeast Asia observed by GOSAT

2016 ◽  
Vol 16 (14) ◽  
pp. 9149-9161 ◽  
Author(s):  
Misa Ishizawa ◽  
Osamu Uchino ◽  
Isamu Morino ◽  
Makoto Inoue ◽  
Yukio Yoshida ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Northeast Asia ◽  
Total Carbon ◽  
East China ◽  
Limited Area ◽  
Atmospheric Methane ◽  
Flux Estimation

Abstract. Extremely high levels of column-averaged dry-air mole fractions of atmospheric methane (XCH4) were detected in August and September 2013 over northeast Asia (∼  20 ppb above the averaged summertime XCH4 over 2009–2012, after removing a long-term trend), as being retrieved from the Short-Wavelength InfraRed (SWIR) spectral data observed with the Thermal And Near-infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT). Similar enhancements of XCH4 were also observed by the ground-based measurements at two Total Carbon Column Observing Network (TCCON) sites in Japan. The analysis of surface CH4 concentrations observed at three monitoring sites around the Japan archipelago suggest that the extreme increase of XCH4 has occurred in a limited area. The model analysis was conducted to investigate this anomalously high XCH4 event, using an atmospheric transport model. The results indicate that the extreme increase of XCH4 is attributed to the anomalous atmospheric pressure pattern over East Asia during the summer of 2013, which effectively transported the CH4-rich air to Japan from the strong CH4 source areas in east China. The two Japanese TCCON sites, ∼  1000 km east–west apart each other, coincidentally located along the substantially CH4-rich air flow from east China. This analysis demonstrates the capability of GOSAT to monitor an XCH4 event on a synoptic scale. We anticipate that the synoptic information of XCH4 from GOSAT data contributes to improve our understanding of regional carbon cycle and the regional flux estimation.

scholarly journals Large XCH<sub>4</sub> anomaly in summer 2013 over Northeast Asia observed by GOSAT

2015 ◽  
Vol 15 (17) ◽  
pp. 24995-25020 ◽  
Author(s):  
M. Ishizawa ◽  
O. Uchino ◽  
I. Morino ◽  
M. Inoue ◽  
Y. Yoshida ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Northeast Asia ◽  
Total Carbon ◽  
East China ◽  
Limited Area ◽  
Atmospheric Methane ◽  
Synoptic Scale ◽  
Comparable Accuracy

Abstract. Extremely high levels of column-averaged dry-air mole fractions of atmospheric methane (XCH4) were detected in August and September 2013 over Northeast Asia (~ 20 ppb above the averaged summertime XCH4 over 2009–2012, after removing a long-term trend), as being retrieved from the Short-Wavelength InfraRed (SWIR) spectral data observed with the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT). Similar enhancements of XCH4 were also observed by the ground-based measurements at two Total Carbon Column Observing Network (TCCON) sites in Japan. The analysis of surface CH4 concentrations observed at three monitoring sites around the Japan islands suggest that the extreme increase of XCH4 has occurred in a limited area. The model analysis was conducted to investigate this anomalously high XCH4 event, using an atmospheric transport model. The results indicate that the extreme increase of XCH4 is attributed to the anomalous atmospheric pressure pattern over East Asia during the summer of 2013, which effectively transported the CH4-rich air to Japan from the strong CH4 source areas in East China. The two Japanese TCCON sites, ~ 1000 km east-west apart each other, coincidentally located along the substantially CH4-rich air flow from East China. The GOSAT orbiting with three-day recurrence successfully observed the synoptic-scale XCH4 enhancement in the comparable accuracy to the TCCON data. This analysis demonstrates the capability of GOSAT to monitor an XCH4 event on a synoptic scale.

scholarly journals Study of the footprints of short-term variation in XCO<sub>2</sub> observed by TCCON sites using NIES and FLEXPART atmospheric transport models

2016 ◽  
Author(s):  
D. A. Belikov ◽  
S. Maksyutov ◽  
A. Ganshin ◽  
R. Zhuravlev ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Temporal Variations ◽  
Particle Dispersion ◽  
Bias Reduction ◽  
Total Carbon ◽  
Short Term

Abstract. The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers (FTS) that record near-infrared (NIR) spectra of the Sun. From these spectra, accurate and precise observations of CO2 column-averaged dry-air mole fraction (denoted XCO2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO2; however, our knowledge of the short-term spatial and temporal variations in XCO2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle) Lagrangian Particle Dispersion Model (LPDM) to determine the footprints of short-term variations in XCO2 observed by operational, past, future, and possible TCCON sites. We propose a footprint-based method for the colocation of satellite and TCCON XCO2 observations, and estimate the performance of the method using the NIES model and five GOSAT XCO2 product datasets. Comparison of the proposed approach with a standard geographic method shows higher number of colocation points and average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and La Réunion sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasizes that the colocation is sensitive to local meteorological conditions and flux distributions.

scholarly journals Study of the footprints of short-term variation in XCO<sub>2</sub> observed by TCCON sites using NIES and FLEXPART atmospheric transport models

2017 ◽  
Vol 17 (1) ◽  
pp. 143-157 ◽  
Author(s):  
Dmitry A. Belikov ◽  
Shamil Maksyutov ◽  
Alexander Ganshin ◽  
Ruslan Zhuravlev ◽  
Nicholas M. Deutscher ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Temporal Variations ◽  
Particle Dispersion ◽  
Bias Reduction ◽  
Total Carbon ◽  
Short Term

Abstract. The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier transform spectrometers (FTSs) that record near-infrared (NIR) spectra of the sun. From these spectra, accurate and precise observations of CO2 column-averaged dry-air mole fractions (denoted XCO2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO2; however, our knowledge of the short-term spatial and temporal variations in XCO2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle dispersion model) Lagrangian particle dispersion model (LPDM) to determine the footprints of short-term variations in XCO2 observed by operational, past, future and possible TCCON sites. We propose a footprint-based method for the collocation of satellite and TCCON XCO2 observations and estimate the performance of the method using the NIES model and five GOSAT (Greenhouse Gases Observing Satellite) XCO2 product data sets. Comparison of the proposed approach with a standard geographic method shows a higher number of collocation points and an average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and Reunion Island sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasises that the collocation is sensitive to local meteorological conditions and flux distributions.

scholarly journals Validation of nine years of MOPITT V5 NIR using MOZAIC/IAGOS measurements: biases and long-term stability

2014 ◽  
Vol 7 (11) ◽  
pp. 3783-3799 ◽  
Author(s):  
A. T. J. de Laat ◽  
I. Aben ◽  
M. Deeter ◽  
P. Nédélec ◽  
H. Eskes ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
A Priori ◽  
Validation Data ◽  
Chemistry Transport Model ◽  
Large Variability ◽  
Long Term Stability ◽  
Spatio Temporal ◽  
Good Agreement

Abstract. Validation results from a comparison between Measurement Of Pollution In The Troposphere (MOPITT) V5 Near InfraRed (NIR) carbon monoxide (CO) total column measurements and Measurement of Ozone and Water Vapour on Airbus in-service Aircraft (MOZAIC)/In-Service Aircraft for a Global Observing System (IAGOS) aircraft measurements are presented. A good agreement is found between MOPITT and MOZAIC/IAGOS measurements, consistent with results from earlier studies using different validation data and despite large variability in MOPITT CO total columns along the spatial footprint of the MOZAIC/IAGOS measurements. Validation results improve when taking the large spatial footprint of the MOZAIC/IAGOS data into account. No statistically significant drift was detected in the validation results over the period 2002–2010 at global, continental and local (airport) scales. Furthermore, for those situations where MOZAIC/IAGOS measurements differed from the MOPITT a priori, the MOPITT measurements clearly outperformed the MOPITT a priori data, indicating that MOPITT NIR retrievals add value to the MOPITT a priori. Results from a high spatial resolution simulation of the chemistry-transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) showed that the most likely explanation for the large MOPITT variability along the MOZAIC-IAGOS profile flight path is related to spatio-temporal CO variability, which should be kept in mind when using MOZAIC/IAGOS profile measurements for validating satellite nadir observations.

scholarly journals Attribution of recent increases in atmospheric methane through 3-D inverse modelling

2018 ◽  
Author(s):  
Joe McNorton ◽  
Chris Wilson ◽  
Manuel Gloor ◽  
Rob Parker ◽  
Hartmut Boesch ◽  
...  
Keyword(s):  
Growth Rate ◽  
Transport Model ◽  
Energy Sector ◽  
Total Carbon ◽  
Sensitivity Analyses ◽  
Northern Eurasia ◽  
Atmospheric Methane ◽  
Chemical Transport Model ◽  
Bottom Up ◽  
Source And Sink

Abstract. The atmospheric methane (CH4) growth rate has varied considerably in recent decades. Unexplained renewed growth after 2006 followed seven years of stagnation and coincided with an isotopic trend toward CH4 more depleted in 13C, suggesting changes in sources and/or sinks. Using surface observations of both CH4 and the isotopologue ratio value (δ13CH4) to constrain a global 3D chemical transport model (CTM), we have performed a synthesis inversion for source and sink attribution. Our method extends on previous studies by providing monthly and regional attribution of emissions from 6 different sectors and changes in atmospheric sinks for the extended 2003–2015 period. Regional evaluation of the model CH4 tracer with independent column observations from the Greenhouse gases Observing SATellite (GOSAT) shows improved performance when using posterior fluxes (R = 0.94–0.96, RMSE = 8.3–16.5 ppb), relative to prior fluxes (R = 0.60–0.92, RMSE = 48.6–64.6 ppb). Further independent validation with data from the Total Carbon Column Observing Network (TCCON) shows a similar improvement in the posterior fluxes (R = 0.90, RMSE = 21.4 ppb) compared to the prior (R = 0.71, RMSE = 55.3 ppb). Based on these improved posterior fluxes, the inversion results suggest the most likely cause of the renewed methane growth is a post-2006 1.8 ± 0.4 % decrease in mean OH, a 12.9 ± 2.7 % increase in energy sector emissions, mainly from Africa/Middle East and Southern Asia/Oceania, and a 2.6 ± 1.8 % increase in wetland emissions, mainly from Northern Eurasia. The posterior wetland increases are in general agreement with bottom-up estimates, but the energy sector growth is greater than estimated by bottom-up methods. The model results are consistent across a range of sensitivity analyses performed. When forced to assume a constant (annually repeating) OH distribution, the inversion requires a greater increase in energy sector (13.6 ± 2.7 %) and wetland (3.6 ± 1.8 %) emissions but also introduces an 11.5 ± 3.8 % decrease in biomass burning emissions. Assuming no prior trend in sources and sinks slightly reduces the posterior growth rate in energy sector and wetland emissions and further increases the amplitude of the negative OH trend. We find that possible tropospheric Cl variations do not to influence δ13CH4 and CH4 trends, although we suggest further work on Cl variability is required to fully diagnose this contribution. While the study provides quantitative insight into possible emissions variations which may explain the observed trends, uncertainty in prior source and sink estimates and a paucity of δ13CH4 observations limit the accuracy of the posterior estimates.

scholarly journals An Eulerian Limited-Area Atmospheric Transport Model

1999 ◽  
Vol 38 (2) ◽  
pp. 190-210 ◽  
Author(s):  
Lennart Robertson ◽  
Joakim Langner ◽  
Magnuz Engardt
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Limited Area ◽  
Atmospheric Transport Model

scholarly journals Spatio-Temporal Consistency Evaluation of XCO2 Retrievals from GOSAT and OCO-2 Based on TCCON and Model Data for Joint Utilization in Carbon Cycle Research

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 354 ◽  
Author(s):  
Yawen Kong ◽  
Baozhang Chen ◽  
Simon Measho
Keyword(s):  
Carbon Cycle ◽  
Mole Fraction ◽  
Transport Model ◽  
Total Carbon ◽  
Temporal Consistency ◽  
Model Data ◽  
Sources And Sinks ◽  
Spatio Temporal ◽  
The Impact

The global carbon cycle research requires precise and sufficient observations of the column-averaged dry-air mole fraction of CO 2 (XCO 2 ) in addition to conventional surface mole fraction observations. In addition, assessing the consistency of multi-satellite data are crucial for joint utilization to better infer information about CO 2 sources and sinks. In this work, we evaluate the consistency of long-term XCO 2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2) in comparison with Total Carbon Column Observing Network (TCCON) and the 3D model of CO 2 mole fractions data from CarbonTracker 2017 (CT2017). We create a consistent joint dataset and compare it with the long-term model data to assess their abilities to characterize the carbon cycle climate. The results show that, although slight increasing differences are found between the GOSAT and TCCON XCO 2 in the northern temperate latitudes, the GOSAT and OCO-2 XCO 2 retrievals agree well in general, with a mean bias ± standard deviation of differences of 0.21 ± 1.3 ppm. The differences are almost within ±2 ppm and are independent of time, indicating that they are well calibrated. The differences between OCO-2 and CT2017 XCO 2 are much larger than those between GOSAT and CT XCO 2 , which can be attributed to the significantly different spatial representatives of OCO-2 and the CT-transport model 5 (TM5). The time series of the combined OCO-2/GOSAT dataset and the modeled XCO 2 agree well, and both can characterize significantly increasing atmospheric CO 2 under the impact of a large El Niño during 2015 and 2016. The trend calculated from the dataset using the seasonal Kendall (S-K) method indicates that atmospheric CO 2 is increasing by 2–2.6 ppm per year.

Quantifying methane emissions from fossil fuel sources using a Bayesian inverse model and observations of ethane with an uncertain emissions ratio

2021 ◽  
Author(s):  
Alice Ramsden ◽  
Anita Ganesan ◽  
Luke Western ◽  
Alistair Manning ◽  
Matthew Rigby ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Synthetic Data ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Sources ◽  
Atmospheric Methane ◽  
Livestock Farming ◽  
Emission Ratio

&lt;p&gt;Methane is an important greenhouse gas with a range of anthropogenic sources, including livestock farming and fossil fuel production. It is important that methane emissions can be correctly attributed to their source, to aid climate change policy and emissions mitigation efforts. For source attribution, many &amp;#8216;top-down&amp;#8217; models of atmospheric methane use spatial maps of sources from emissions inventory data coupled with an atmospheric transport model. However, this can cause difficulties if sources are co-located or if there is uncertainty in the sources&amp;#8217; spatial distributions.&lt;/p&gt;&lt;p&gt;To help with this issue and reduce overall uncertainty in estimates of methane emissions, recent methods have used observations of a secondary trace gas and its correlation with methane to infer methane emissions from a target sector. Most previous work has assumed a fixed emissions ratio between the two gases, which often does not reflect the true range of possible emission ratios. In this work, measurements of atmospheric ethane and its emissions ratio relative to methane are used to infer emissions of methane from fossil fuel sources. Instead of assuming a fixed emission ratio, our method allows for uncertainty in the emission ratio to be statistically propagated through the inverse model and incorporated into the sectoral estimates of methane emissions. We further demonstrate the inaccuracies that can result in an assessment of fossil fuel methane emissions if this uncertainty is not considered.&lt;/p&gt;&lt;p&gt;We present this novel method for modelling sectoral methane emissions with examples from a synthetic data experiment and give results from a case study of UK methane emissions. Methane and ethane observations from a tall tower network across the UK were used with this model to produce monthly estimates of UK fossil fuel methane emissions with improved uncertainty characterisation.&lt;/p&gt;

scholarly journals Detecting long-term changes in point source fossil CO<sub>2</sub> emissions with tree ring archives

2016 ◽  
Author(s):  
E. D. Keller ◽  
J. C. Turnbull ◽  
M. W. Norris
Keyword(s):  
Point Source ◽  
Co2 Emissions ◽  
Tree Ring ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Point Sources ◽  
Long Term Changes

Abstract. We examine the utility of tree ring 14C archives for detecting long term changes in fossil CO2 emissions from a point source. Trees assimilate carbon from the atmosphere during photosynthesis, in the process faithfully recording the average atmospheric 14C content in each new annual tree ring. Using 14C as a proxy for fossil CO2, we examine interannual variability over six years of fossil CO2 observations between 2004-05 and 2011-12 from two trees growing near the Kapuni Natural Gas Plant in rural Taranaki, New Zealand. We quantify the amount of variability that can be attributed to transport and meteorology by simulating constant point source fossil CO2 emissions over the observation period with the atmospheric transport model WindTrax. We compare model simulation results to observations and calculate the amount of change in emissions that we can detect with new observations over annual or multi-year time periods given both measurement uncertainty of 1ppm and the modelled variation in transport. In particular, we ask, what is the minimum amount of change in emissions that we can detect using this method, given a reference period of six years? We find that changes of 42% or more could be detected in a new sample from one year at the same observation location, or 22% in the case of four years of new samples. This threshold lowers and the method becomes more practical the more the size of the signal increases. For point sources 10 times larger than the Kapuni plant (a more typical size for power plants worldwide), it would be possible to detect sustaine d emissions changes on the order of 10% given suitable meteorology and observations.

scholarly journals Technical note: A geostatistical fixed-lag Kalman smoother for atmospheric inversions

2008 ◽  
Vol 8 (2) ◽  
pp. 7755-7779
Author(s):  
A. M. Michalak
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Correlation ◽  
Technical Note ◽  
Surface Fluxes ◽  
Carbon Dioxide Fluxes ◽  
Kalman Smoother ◽  
Geostatistical Approach ◽  
Flux Estimation

Abstract. Inverse modeling methods are now commonly used for estimating surface fluxes of carbon dioxide, using atmospheric mass fraction measurements combined with a numerical atmospheric transport model. The geostatistical approach to flux estimation takes advantage of the spatial and/or temporal correlation in fluxes and does not require prior flux estimates. In this work, a geostatistical implementation of a fixed-lag Kalman smoother is developed to improve the computational efficiency of the inverse problem. This method makes it feasible to perform multi-year inversions, at fine resolutions, and with large amounts of data. The new method is applied to the recovery of global gridscale carbon dioxide fluxes for 1997 to 2001 using pseudodata representative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

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