scholarly journals On the use of satellite-derived CH<sub>4</sub> : CO<sub>2</sub> columns in a joint inversion of CH<sub>4</sub> and CO<sub>2</sub> fluxes

2015 ◽  
Vol 15 (15) ◽  
pp. 8615-8629 ◽  
Author(s):  
S. Pandey ◽  
S. Houweling ◽  
M. Krol ◽  
I. Aben ◽  
T. Röckmann
Keyword(s):  
Joint Inversion ◽  
Surface Fluxes ◽  
Surface Measurement ◽  
Ratio Method ◽  
Co2 Fluxes ◽  
Hard Constraints ◽  
Surface Measurements ◽  
Total Column ◽  
Dual Tracer ◽  
Better Than

Abstract. We present a method for assimilating total column CH4 : CO2 ratio measurements from satellites for inverse modeling of CH4 and CO2 fluxes using the variational approach. Unlike conventional approaches, in which retrieved CH4 : CO2 are multiplied by model-derived total column CO2 and only the resulting CH4 is assimilated, our method assimilates the ratio of CH4 and CO2 directly and is therefore called the ratio method. It is a dual tracer inversion, in which surface fluxes of CH4 and CO2 are optimized simultaneously. The optimization of CO2 fluxes turns the hard constraint of prescribing model-derived CO2 fields into a weak constraint on CO2, which allows us to account for uncertainties in CO2. The method has been successfully tested in a synthetic inversion setup. We show that the ratio method is able to reproduce assumed true CH4 and CO2 fluxes starting from a prior, which is derived by perturbing the true fluxes randomly. We compare the performance of the ratio method with that of the traditional proxy approach and the use of only surface measurements for estimating CH4 fluxes. Our results confirm that the optimized CH4 fluxes are sensitive to the treatment of CO2, and that hard constraints on CO2 may significantly compromise results that are obtained for CH4. We find that the relative performance of ratio and proxy methods have a regional dependence. The ratio method performs better than the proxy method in regions where the CO2 fluxes are most uncertain. However, both ratio and proxy methods perform better than the surface-measurement-only inversion, confirming the potential of spaceborne measurements for accurately determining fluxes of CH4 and other greenhouse gases (GHGs).

scholarly journals On the use of satellite derived CH<sub>4</sub> / CO<sub>2</sub> columns in CH<sub>4</sub> flux inversions

2015 ◽  
Vol 15 (6) ◽  
pp. 8801-8838
Author(s):  
S. Pandey ◽  
S. Houweling ◽  
M. Krol ◽  
I. Aben ◽  
T. Röckmann
Keyword(s):  
Inverse Modeling ◽  
Surface Fluxes ◽  
Surface Measurement ◽  
Ratio Method ◽  
Co2 Fluxes ◽  
Hard Constraints ◽  
Surface Measurements ◽  
Ratio Approach ◽  
Dual Tracer ◽  
Better Than

Abstract. We present a new method for assimilating CH4 measurements from satellites, which have been retrieved using the proxy-ratio approach, for inverse modeling of CH4 fluxes. Unlike conventional approaches, in which retrieved CH4 / CO2 ratios are multiplied by model derived total column CO2 and only the resulting CH4 is assimilated, our method assimilates the ratio of CH4 and CO2 directly and is therefore called the ratio method. It is a dual tracer inversion, in which surface fluxes of CH4 and CO2 are optimized simultaneously. The optimization of CO2 fluxes turns the hard constraint of prescribing model derived CO2 fields into a weak constraint on CO2, which allows us to account for uncertainties in CO2. The method has been successfully tested in a synthetic inversion setup using the TM5-4DVAR inverse modeling system. We show that the ratio method is able to reproduce assumed true CH4 and CO2 fluxes starting from a prior, which is derived by perturbing the true fluxes randomly. We compare the performance of the ratio method with that of the traditional proxy approach and the use of only surface measurements for estimating CH4 fluxes. Our results confirm that the optimized CH4 fluxes are sensitive to the treatment of CO2, and that hard constraints on CO2 may significantly compromise results that are obtained for CH4. We see that the relative performance of ratio and proxy methods have a regional dependence. The ratio method performs better than the proxy method in regions where the CO2 fluxes are most uncertain. However, both ratio and proxy methods perform better than the surface measurement-only inversion confirming the potential of space borne measurements for accurately determining fluxes of CH4 and other GHGs.

scholarly journals Global CO<sub>2</sub> fluxes estimated from GOSAT retrievals of total column CO<sub>2</sub>

2013 ◽  
Vol 13 (17) ◽  
pp. 8695-8717 ◽  
Author(s):  
S. Basu ◽  
S. Guerlet ◽  
A. Butz ◽  
S. Houweling ◽  
O. Hasekamp ◽  
...  
Keyword(s):  
Bias Correction ◽  
Seasonal Cycle ◽  
Joint Inversion ◽  
Surface Fluxes ◽  
Global Land ◽  
Net Uptake ◽  
Surface Measurements ◽  
Source Sink ◽  
The Tropics ◽  
Total Column

Abstract. We present one of the first estimates of the global distribution of CO2 surface fluxes using total column CO2 measurements retrieved by the SRON-KIT RemoTeC algorithm from the Greenhouse gases Observing SATellite (GOSAT). We derive optimized fluxes from June 2009 to December 2010. We estimate fluxes from surface CO2 measurements to use as baselines for comparing GOSAT data-derived fluxes. Assimilating only GOSAT data, we can reproduce the observed CO2 time series at surface and TCCON sites in the tropics and the northern extra-tropics. In contrast, in the southern extra-tropics GOSAT XCO2 leads to enhanced seasonal cycle amplitudes compared to independent measurements, and we identify it as the result of a land–sea bias in our GOSAT XCO2 retrievals. A bias correction in the form of a global offset between GOSAT land and sea pixels in a joint inversion of satellite and surface measurements of CO2 yields plausible global flux estimates which are more tightly constrained than in an inversion using surface CO2 data alone. We show that assimilating the bias-corrected GOSAT data on top of surface CO2 data (a) reduces the estimated global land sink of CO2, and (b) shifts the terrestrial net uptake of carbon from the tropics to the extra-tropics. It is concluded that while GOSAT total column CO2 provide useful constraints for source–sink inversions, small spatiotemporal biases – beyond what can be detected using current validation techniques – have serious consequences for optimized fluxes, even aggregated over continental scales.

scholarly journals Global CO<sub>2</sub> fluxes estimated from GOSAT retrievals of total column CO<sub>2</sub>

2013 ◽  
Vol 13 (2) ◽  
pp. 4535-4600 ◽  
Author(s):  
S. Basu ◽  
S. Guerlet ◽  
A. Butz ◽  
S. Houweling ◽  
O. Hasekamp ◽  
...  
Keyword(s):  
Bias Correction ◽  
Seasonal Cycle ◽  
Joint Inversion ◽  
Surface Fluxes ◽  
Global Land ◽  
Net Uptake ◽  
Surface Measurements ◽  
Source Sink ◽  
The Tropics ◽  
Total Column

Abstract. We present one of the first estimates of the global distribution of CO2 surface fluxes using total column CO2 measurements retrieved from the Greenhouse gases Observing SATellite (GOSAT). We derive optimized fluxes from June 2009 to December 2010. We estimate fluxes from surface CO2 measurements to use as baselines for comparing GOSAT data-derived fluxes. Assimilating only GOSAT data, we can reproduce the observed CO2 time series at surface and TCCON sites in the tropics and the northern extra-tropics. In contrast, in the southern extra-tropics GOSAT XCO2 leads to enhanced seasonal cycle amplitudes compared to independent measurements, and we identify it as the result of a land-sea bias in our GOSAT XCO2 retrievals. A bias correction in the form of a global offset between GOSAT land and sea pixels in a joint inversion of satellite and surface measurements of CO2 yields plausible global flux estimates which are more tightly constrained than in an inversion using surface CO2 data alone. We show that assimilating the bias-corrected GOSAT data on top of surface CO2 data (a) reduces the estimated global land sink of CO2, and (b) shifts the terrestrial net uptake of carbon from the tropics to the extra-tropics. It is concluded that while GOSAT total column CO2 provide useful constraints for source-sink inversions, small spatiotemporal biases – beyond what can be detected using current validation techniques – have serious consequences for optimized fluxes, even aggregated over continental scales.

scholarly journals Quantifying lower tropospheric methane concentrations using GOSAT near-IR and TES thermal IR measurements

2015 ◽  
Vol 8 (8) ◽  
pp. 3433-3445 ◽  
Author(s):  
J. R. Worden ◽  
A. J. Turner ◽  
A. Bloom ◽  
S. S. Kulawik ◽  
J. Liu ◽  
...  
Keyword(s):  
Near Infrared ◽  
Surface Fluxes ◽  
Vertical Profiles ◽  
Monthly Average ◽  
Near Ir ◽  
Surface Measurements ◽  
Increased Sensitivity ◽  
The Impact ◽  
Total Column ◽  
Methane Concentrations

Abstract. Evaluating surface fluxes of CH4 using total column data requires models to accurately account for the transport and chemistry of methane in the free troposphere and stratosphere, thus reducing sensitivity to the underlying fluxes. Vertical profiles of methane have increased sensitivity to surface fluxes because lower tropospheric methane is more sensitive to surface fluxes than a total column, and quantifying free-tropospheric CH4 concentrations helps to evaluate the impact of transport and chemistry uncertainties on estimated surface fluxes. Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Aura Tropospheric Emission Spectrometer (TES) and XCH4 (dry-mole air fraction of methane) from the Greenhouse gases Observing SATellite – Thermal And Near-infrared for carbon Observation (GOSAT TANSO, herein GOSAT for brevity). The calculated precision of these estimates ranges from 10 to 30 ppb for a monthly average on a 4° × 5° latitude/longitude grid making these data suitable for evaluating lower-tropospheric methane concentrations. Smoothing error is approximately 10 ppb or less. Comparisons between these data and the GEOS-Chem model demonstrate that these lower-tropospheric CH4 estimates can resolve enhanced concentrations over flux regions that are challenging to resolve with total column measurements. We also use the GEOS-Chem model and surface measurements in background regions across a range of latitudes to determine that these lower-tropospheric estimates are biased low by approximately 65 ppb, with an accuracy of approximately 6 ppb (after removal of the bias) and an actual precision of approximately 30 ppb. This 6 ppb accuracy is consistent with the accuracy of TES and GOSAT methane retrievals.

scholarly journals First direct observation of the atmospheric CO<sub>2</sub> year-to-year increase from space

2007 ◽  
Vol 7 (16) ◽  
pp. 4249-4256 ◽  
Author(s):  
M. Buchwitz ◽  
O. Schneising ◽  
J. P. Burrows ◽  
H. Bovensmann ◽  
M. Reuter ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
Current Knowledge ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Surface Measurement ◽  
Spectral Radiance ◽  
Satellite Measurements ◽  
Temporal Sampling ◽  
Northern Hemispheric ◽  
Total Column

Abstract. The reliable prediction of future atmospheric CO2 concentrations and associated global climate change requires an adequate understanding of the CO2 sources and sinks. The sparseness of the existing surface measurement network limits current knowledge about the global distribution of CO2 surface fluxes. The retrieval of CO2 total vertical columns from satellite observations is predicted to improve this situation. Such an application however requires very high accuracy and precision. We report on retrievals of the column-averaged CO2 dry air mole fraction, denoted XCO2, from the near-infrared nadir spectral radiance and solar irradiance measurements of the SCIAMACHY satellite instrument between 2003 and 2005. We focus on northern hemispheric large scale CO2 features such as the CO2 seasonal cycle and show - for the first time - that the atmospheric annual increase of CO2 can be directly observed using satellite measurements of the CO2 total column. The satellite retrievals are compared with global XCO2 obtained from NOAA's CO2 assimilation system CarbonTracker taking into account the spatio-temporal sampling and altitude sensitivity of the satellite data. We show that the measured CO2 year-to-year increase agrees within about 1 ppm/year with CarbonTracker. We also show that the latitude dependent amplitude of the northern hemispheric CO2 seasonal cycle agrees with CarbonTracker within about 2 ppm with the retrieved amplitude being systematically larger. The analysis demonstrates that it is possible using satellite measurements of the CO2 total column to retrieve information on the atmospheric CO2 on the level of a few parts per million.

scholarly journals The potential of Orbiting Carbon Observatory-2 data to reduce the uncertainties in CO<sub>2</sub> surface fluxes over Australia using a variational assimilation scheme

2020 ◽  
Vol 20 (14) ◽  
pp. 8473-8500
Author(s):  
Yohanna Villalobos ◽  
Peter Rayner ◽  
Steven Thomas ◽  
Jeremy Silver
Keyword(s):  
Boundary Conditions ◽  
Dispersion Model ◽  
Grid Point ◽  
Surface Fluxes ◽  
Co2 Fluxes ◽  
Error Statistics ◽  
Error Covariance ◽  
Horizontal Grid ◽  
Assimilation Scheme ◽  
Total Column

Abstract. This paper addresses the question of how much uncertainties in CO2 fluxes over Australia can be reduced by assimilation of total-column carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite instrument. We apply a four-dimensional variational data assimilation system, based around the Community Multiscale Air Quality (CMAQ) transport-dispersion model. We ran a series of observing system simulation experiments to estimate posterior error statistics of optimized monthly-mean CO2 fluxes in Australia. Our assimilations were run with a horizontal grid resolution of 81 km using OCO-2 data for 2015. Based on four representative months, we find that the integrated flux uncertainty for Australia is reduced from 0.52 to 0.13 Pg C yr−1. Uncertainty reductions of up to 90 % were found at grid-point resolution over productive ecosystems. Our sensitivity experiments show that the choice of the correlation structure in the prior error covariance plays a large role in distributing information from the observations. We also found that biases in the observations would significantly impact the inverted fluxes and could contaminate the final results of the inversion. Biases in prior fluxes are generally removed by the inversion system. Biases in the boundary conditions have a significant impact on retrieved fluxes, but this can be mitigated by including boundary conditions in our retrieved parameters. In general, results from our idealized experiments suggest that flux inversions at this unusually fine scale will yield useful information on the carbon cycle at continental and finer scales.

scholarly journals Inverse modeling of CO<sub>2</sub> sources and sinks using satellite observations of CO<sub>2</sub> from TES and surface flask measurements

2011 ◽  
Vol 11 (12) ◽  
pp. 6029-6047 ◽  
Author(s):  
R. Nassar ◽  
D. B. A. Jones ◽  
S. S. Kulawik ◽  
J. R. Worden ◽  
K. W. Bowman ◽  
...  
Keyword(s):  
Joint Inversion ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Global Ocean ◽  
Sources And Sinks ◽  
Global Land ◽  
Surface Measurements ◽  
Low Sensitivity ◽  
The Tropics ◽  
Inversion Analysis

Abstract. We infer CO2 surface fluxes using satellite observations of mid-tropospheric CO2 from the Tropospheric Emission Spectrometer (TES) and measurements of CO2 from surface flasks in a time-independent inversion analysis based on the GEOS-Chem model. Using TES CO2 observations over oceans, spanning 40° S–40° N, we find that the horizontal and vertical coverage of the TES and flask data are complementary. This complementarity is demonstrated by combining the datasets in a joint inversion, which provides better constraints than from either dataset alone, when a posteriori CO2 distributions are evaluated against independent ship and aircraft CO2 data. In particular, the joint inversion offers improved constraints in the tropics where surface measurements are sparse, such as the tropical forests of South America. Aggregating the annual surface-to-atmosphere fluxes from the joint inversion for the year 2006 yields −1.13±0.21 Pg C for the global ocean, −2.77±0.20 Pg C for the global land biosphere and −3.90±0.29 Pg C for the total global natural flux (defined as the sum of all biospheric, oceanic, and biomass burning contributions but excluding CO2 emissions from fossil fuel combustion). These global ocean and global land fluxes are shown to be near the median of the broad range of values from other inversion results for 2006. To achieve these results, a bias in TES CO2 in the Southern Hemisphere was assessed and corrected using aircraft flask data, and we demonstrate that our results have low sensitivity to variations in the bias correction approach. Overall, this analysis suggests that future carbon data assimilation systems can benefit by integrating in situ and satellite observations of CO2 and that the vertical information provided by satellite observations of mid-tropospheric CO2 combined with measurements of surface CO2, provides an important additional constraint for flux inversions.

scholarly journals Inverse modeling of CO<sub>2</sub> sources and sinks using satellite observations of CO<sub>2</sub> from TES and surface flask measurements

2011 ◽  
Vol 11 (2) ◽  
pp. 4263-4311 ◽  
Author(s):  
R. Nassar ◽  
D. B. A. Jones ◽  
S. S. Kulawik ◽  
J. R. Worden ◽  
K. W. Bowman ◽  
...  
Keyword(s):  
Joint Inversion ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Global Ocean ◽  
Sources And Sinks ◽  
Global Land ◽  
Surface Measurements ◽  
Low Sensitivity ◽  
The Tropics ◽  
Inversion Analysis

Abstract. We infer CO2 surface fluxes using satellite observations of mid-tropospheric CO2 from the Tropospheric Emission Spectrometer (TES) and measurements of CO2 from surface flasks in a time-independent inversion analysis based on the GEOS-Chem model. Using TES CO2 observations over oceans, spanning 40° S–40° N, we find that the horizontal and vertical coverage of the TES and flask data are complementary. This complementarity is demonstrated by combining the datasets in a joint inversion, which provides better constraints than from either dataset alone, when a posteriori CO2 distributions are evaluated against independent ship and aircraft CO2 data. In particular, the joint inversion offers improved constraints in the tropics where surface measurements are sparse, such as the tropical forests of South America, which the joint inversion suggests was a weak sink of −0.17 ± 0.20 Pg C in 2006. Aggregating the annual surface-to-atmosphere fluxes from the joint inversion yields −1.13 ± 0.21 Pg C for the global ocean, −2.77 ± 0.20 Pg C for the global land biosphere and −3.90 ± 0.29 Pg C for the total global natural flux (defined as the sum of all biospheric, oceanic, and biomass burning contributions but excluding CO2 emissions from fossil fuel combustion). These global ocean, global land and total global fluxes are shown to be in the range of other inversion results for 2006. To achieve these results, a latitude dependent bias in TES CO2 in the Southern Hemisphere was assessed and corrected using aircraft flask data, and we demonstrate that our results have low sensitivity to variations in the bias correction approach. Overall, this analysis suggests that future carbon data assimilation systems can benefit by integrating in situ and satellite observations of CO2 and that the vertical information provided by satellite observations of mid-tropospheric CO2 combined with measurements of surface CO2, provides an important additional constraint for flux inversions.

scholarly journals The potential of OCO-2 data to reduce the uncertainties in CO<sub>2</sub> surface fluxes over Australia using a variational assimilation scheme

2019 ◽  
Author(s):  
Yohanna Villalobos ◽  
Peter Rayner ◽  
Steven Thomas ◽  
Jeremy Silver
Keyword(s):  
Dispersion Model ◽  
Surface Fluxes ◽  
Co2 Fluxes ◽  
Error Statistics ◽  
Satellite Measurements ◽  
Error Covariance ◽  
Horizontal Grid ◽  
Assimilation Scheme ◽  
Data Assimilation System ◽  
Total Column

Abstract. This paper addresses the question of how much uncertainties in CO2 fluxes over Australia can be reduced by assimilation of total-column carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite instrument. We apply a four-dimensional variational data assimilation system, based around the Community Multiscale Air Quality (CMAQ) transport-dispersion model. We ran a series of observing system simulation experiments to estimate posterior error statistics of optimized monthly mean CO2 fluxes in Australia. Our assimilations were run with a horizontal grid resolution of 81 km using OCO-2 data for 2015. We found that on average, the total Australia flux uncertainty was reduced by up to 40 % using only OCO-2 nadir measurements. Using both nadir and glint satellite measurements produces uncertainty reductions up to 80 %, which represents 0.55 PgC y−1 for the whole continent. Uncertainty reductions were found to be greatest in the more productive regions of Australia. The choice of the correlation structure in the prior error covariance was found to play a large role in distributing information from the observations. Overall the results suggest that flux inversions at this unusually fine scale will yield useful information on the Australian carbon cycle.

scholarly journals Inverse modeling of GOSAT-retrieved ratios of total column CH<sub>4</sub> and CO<sub>2</sub> for 2009 and 2010

2016 ◽  
Author(s):  
S. Pandey ◽  
S. Houweling ◽  
M. Krol ◽  
I. Aben ◽  
F. Chevallier ◽  
...  
Keyword(s):  
South America ◽  
Greenhouse Gas ◽  
Inverse Modeling ◽  
Time Scale ◽  
Ratio Method ◽  
Inversion Method ◽  
Co2 Fluxes ◽  
Ch4 Flux ◽  
The Impact ◽  
Total Column

Abstract. This study investigates the constraint provided by greenhouse gas measurements from space on surface fluxes. Imperfect knowledge of the light path through the atmosphere, arising from scattering by clouds and aerosols, can heavily bias column measurements retrieved from space. To minimize the impact of such biases, ratios of total column retrieved CH4 and CO2 (Xratio) have been used. We apply the ratio inversion method described in Pandey et al. (2015) to retrievals from the Greenhouse Gas Observing SATellite (GOSAT). The ratio inversion method uses the measured Xratio as a weak constraint on CO2 fluxes. In contrast, the more common approach of inverting proxy CH4 retrievals (Frankenberg et al., 2005) prescribes atmospheric CO2 fields and optimizes only CH4 fluxes. The TM5-4DVAR inverse modeling system is used to simultaneously optimize the fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy inversions using model-derived-XCO2 mixing ratios (XCO2model) from CarbonTracker and MACC. The performance of the inverse models is evaluated using aircraft measurements from the HIPPO, CONTRAIL and AMAZONICA projects. Xratio and XCO2model are compared with TCCON retrievals to quantify the relative importance of errors in these components of the proxy XCH4 retrieval (XCH4proxy). We find that the retrieval errors in Xratio (mean = 0.61 %) are generally larger than the errors in XCO2model (mean = 0.24 % and 0.01 % for CarbonTracker and MACC, respectively). On the annual time scale, the CH4 fluxes from the different satellite inversions are generally in agreement with each other, suggesting that errors in XCO2model do not limit the overall accuracy of the CH4 flux estimates. On the seasonal time scale, however, larger differences are found due to uncertainties in XCO2model, particularly over Australia and in the tropics. The ratio method stays closer to the a priori CH4 flux in these regions, because it is capable of simultaneously adjusting the CO2 fluxes. Over Tropical South America, comparison to independent measurements shows that CO2 fields derived from the ratio method are less realistic than those used in the proxy method. However, the CH4 fluxes are more realistic, because the impact of unaccounted systematic uncertainties is more evenly distributed between CO2 and CH4. The ratio inversion estimates an enhanced CO2 release from Tropical South America during the dry season of 2010, which is in accordance with the findings of Gatti et al. (2014) and Vanderlaan et al. (2015). The performance of the ratio method is encouraging, because despite the added non-linearity due to the assimilation of Xratio and the significant increase in the degree of freedom by optimizing CO2 fluxes, still consistent results are obtained.

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