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 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 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 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).

Inverse modelling of global methane emissions using TROPOMI

2021 ◽  
Author(s):  
Jacob van Peet ◽  
Sander Houweling ◽  
Julia Marshall ◽  
Tonatiuh Nunez Ramirez ◽  
Arjo Segers
Keyword(s):  
Bias Correction ◽  
A Priori ◽  
Correction Method ◽  
Methane Emissions ◽  
Surface Fluxes ◽  
Inverse Modelling ◽  
Satellite Measurements ◽  
Mixing Ratios ◽  
Surface Measurements ◽  
Total Column

&lt;p&gt;This study investigates the use of total column methane measurements from the TROPOMI satellite instrument for estimating the global sources and sinks of methane. A bias correction method has been developed based on a comparison between the satellite measurements and an inversion using surface measurements only, building on the experience using GOSAT data. The bias correction is applied to the satellite measurements prior to the use of the data in the inversion. Results will be shown of inversions using the TM5 4D-VAR and CarboScope inverse modelling systems applied to two years of TROPOMI data. The inversion-optimized methane mixing ratios are inter-compared and validated against independent surface (WMO-GAW), Aircraft (ATom) and total column (TCCON) observations. The derived methane fluxes are aggregated over selected geographic regions, to compare the optimised methane emissions from TM5-4DVAR, CarboScope, and GOSAT inversions from the Copernicus Atmospheric Monitoring Service.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Methane surface mixing ratios derived from the TROPOMI inversion show a good agreement with the surface measurements in general. Near areas with high aerosol optical thickness (e.g. the Sahara) we see significant adjustments in the surface fluxes, compensating for model-data differences, pointing to influences of residual uncorrected systematic errors in the data. The total column comparison with TCCON measurements shows a slight North-South bias gradient. These finding are investigated in further detail by comparing results using the operational retrieval product to the use of the scientific RemoTeC and WFMD retrievals. Encouragingly, both the TM5 and CarboScope inversions show similar increments in the aggregated fluxes over time. The seasonal cycle in the posterior fluxes is different from that of the a a priori fluxes, which were the same for both inversion systems.&lt;/p&gt;

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 Evaluating consistency between total column CO<sub>2</sub> retrievals from OCO-2 and the in situ network over North America: implications for carbon flux estimation

2021 ◽  
Vol 21 (18) ◽  
pp. 14385-14401
Author(s):  
Bharat Rastogi ◽  
John B. Miller ◽  
Micheal Trudeau ◽  
Arlyn E. Andrews ◽  
Lei Hu ◽  
...  
Keyword(s):  
North America ◽  
Carbon Cycle ◽  
Bias Correction ◽  
Surface Flux ◽  
Systematic Errors ◽  
Surface Fluxes ◽  
Satellite Retrievals ◽  
Flux Estimation ◽  
Total Column

Abstract. Feedbacks between the climate system and the carbon cycle represent a key source of uncertainty in model projections of Earth's climate, in part due to our inability to directly measure large-scale biosphere–atmosphere carbon fluxes. In situ measurements of the CO2 mole fraction from surface flasks, towers, and aircraft are used in inverse models to infer fluxes, but measurement networks remain sparse, with limited or no coverage over large parts of the planet. Satellite retrievals of total column CO2 (XCO2), such as those from NASA's Orbiting Carbon Observatory-2 (OCO-2), can potentially provide unprecedented global information about CO2 spatiotemporal variability. However, for use in inverse modeling, data need to be extremely stable, highly precise, and unbiased to distinguish abundance changes emanating from surface fluxes from those associated with variability in weather. Systematic errors in XCO2 have been identified and, while bias correction algorithms are applied globally, inconsistencies persist at regional and smaller scales that may complicate or confound flux estimation. To evaluate XCO2 retrievals and assess potential biases, we compare OCO-2 v10 retrievals with in situ data-constrained XCO2 simulations over North America estimated using surface fluxes and boundary conditions optimized with observations that are rigorously calibrated relative to the World Meteorological Organization X2007 CO2 scale. Systematic errors in simulated atmospheric transport are independently evaluated using unassimilated aircraft and AirCore profiles. We find that the global OCO-2 v10 bias correction shifts the distribution of retrievals closer to the simulated XCO2, as intended. Comparisons between bias-corrected and simulated XCO2 reveal differences that vary seasonally. Importantly, the difference between simulations and retrievals is of the same magnitude as the imprint of recent surface flux in the total column. This work demonstrates that systematic errors in OCO-2 v10 retrievals of XCO2 over land can be large enough to confound reliable surface flux estimation and that further improvements in retrieval and bias correction techniques are essential. Finally, we show that independent observations, especially vertical profile data, such as those from the National Oceanic and Atmospheric Administration aircraft and AirCore programs are critical for evaluating errors in both satellite retrievals and carbon cycle models.

scholarly journals Evaluating consistency between total column CO<sub>2</sub> retrievals from OCO-2 and the in-situ network over North America: Implications for carbon flux estimation

2021 ◽  
Author(s):  
Bharat Rastogi ◽  
John B. Miller ◽  
Micheal Trudeau ◽  
Arlyn E. Andrews ◽  
Lei Hu ◽  
...  
Keyword(s):  
North America ◽  
Carbon Cycle ◽  
Bias Correction ◽  
Surface Flux ◽  
Systematic Errors ◽  
Surface Fluxes ◽  
Satellite Retrievals ◽  
Flux Estimation ◽  
Total Column

Abstract. Feedbacks between the climate system and the carbon cycle represent a key source of uncertainty in model projections of Earth’s climate, in part due to our inability to directly measure large scale biosphere-atmosphere carbon fluxes. In-situ measurements of CO2 mole fraction from surface flasks, towers and aircraft are used in inverse models to infer fluxes, but measurement networks remain sparse, with limited or no coverage over large parts of the planet. Satellite retrievals of total column CO2 (XCO2), such as those from NASA’s Orbiting Carbon Observatory-2 (OCO-2), can potentially provide unprecedented global information about CO2 spatiotemporal variability. However, for use in inverse modeling, data need to be extremely stable, highly precise and unbiased to distinguish abundance changes emanating from surface fluxes from those associated with variability in weather. Systematic errors in XCO2 have been identified and, while bias correction algorithms are applied globally, inconsistencies persist at regional and smaller scales that may complicate or confound flux estimation. To evaluate XCO2 retrievals and assess potential biases, we compare OCO-2 v10 retrievals with in-situ data-constrained XCO2 simulations over North America estimated using surface fluxes and boundary conditions optimized with observations that are rigorously calibrated relative to the WMO X2007 CO2 scale. Systematic errors in simulated atmospheric transport are independently evaluated using unassimilated aircraft and AirCore profiles. We find that the global OCO-2 v10 bias correction shifts the distribution of retrievals closer to the simulated XCO2, as intended. Comparisons between bias corrected and simulated XCO2 reveal differences that vary seasonally. Importantly, the difference between simulations and retrievals is of the same magnitude as the imprint of recent surface flux in the total column. This work demonstrates that systematic errors in OCO-2v10 retrievals of XCO2 over land can be large enough to confound reliable surface flux estimation and that further improvements in retrieval and bias correction techniques are essential. Finally, we show that independent observations, especially vertical profile data, such as from NOAA’s aircraft and AirCore programs are critical for evaluating errors in both satellite retrievals and carbon-cycle models.

scholarly journals A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion

2017 ◽  
Vol 10 (6) ◽  
pp. 2201-2219 ◽  
Author(s):  
Yosuke Niwa ◽  
Yosuke Fujii ◽  
Yousuke Sawa ◽  
Yosuke Iida ◽  
Akihiko Ito ◽  
...  
Keyword(s):  
Transport Model ◽  
Surface Fluxes ◽  
Identical Twin ◽  
Inversion Problem ◽  
Model Errors ◽  
Optimization Scheme ◽  
Error Covariance ◽  
Optimal Setting ◽  
Source Sink ◽  
Quasi Newton

Abstract. A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

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