Variability and quasi-decadal changes in the methane budget over the period 2000–2012

Abstract. Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

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Variability and quasi-decadal changes in the methane budget over the period 2000–2012

10.5194/acp-2017-296 ◽

2017 ◽

Cited By ~ 2

Author(s):

Marielle Saunois ◽

Philippe Bousquet ◽

Benjamin Poulter ◽

Anna Peregon ◽

Philippe Ciais ◽

...

Keyword(s):

Biomass Burning ◽

Methane Emissions ◽

Data Driven ◽

Atmospheric Methane ◽

Top Down ◽

Bottom Up ◽

Ch4 Emissions ◽

Ensemble Mean ◽

The Mean ◽

The Tropics

Abstract. Following the recent Global Carbon project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling frameworks) and bottom-up models, inventories, and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seems to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the EDGARv4.2 inventory, which should be revised to smaller values in a near future. Though the sectorial partitioning of six individual top-down studies out of eight are not consistent with the observed change in atmospheric 13CH4, the partitioning derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that, the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. Besides, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. The methane loss (in particular through OH oxidation) has not been investigated in detail in this study, although it may play a significant role in the recent atmospheric methane changes.

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An analysis of atmospheric CH<sub>4</sub> concentrations from 1984 to 2008 with a single box atmospheric chemistry model

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-30259-2012 ◽

2012 ◽

Vol 12 (11) ◽

pp. 30259-30282 ◽

Cited By ~ 1

Author(s):

Z. Tan ◽

Q. Zhuang

Keyword(s):

Growth Rate ◽

Atmospheric Chemistry ◽

Methane Flux ◽

Methane Emissions ◽

Atmospheric Methane ◽

Significant Drop ◽

Oxidizing Power ◽

The Mean

Abstract. We present a single box atmospheric chemistry model involving atmospheric methane (CH4), carbon monoxide (CO) and radical hydroxyl (OH) to analyze atmospheric CH4 concentrations from 1984 to 2008. When OH is allowed to vary, the modeled CH4 is 20 ppb higher than observations from the NOAA/ESRL and AGAGE networks for the end of 2008. However, when the OH concentration is held constant at 106 molecule cm−3, the simulated CH4 shows a trend approximately equal to observations. Both simulations show a clear slowdown in the CH4 growth rate during recent decades, from about 13 ppb yr−1 in 1984 to less than 5 ppb yr−1 in 2003. Furthermore, if the constant OH assumption is credible, we think that this slowdown is mainly due to a pause in the growth of wetland methane emissions. In simulations run for the Northern and Southern Hemispheres separately, we find that the Northern Hemisphere is more sensitive to wetland emissions, whereas the southern tends to be more perturbed by CH4 transportation, dramatic OH change, and biomass burning. When measured CO values from NOAA/ESRL are used to drive the model, changes in the CH4 growth rate become more consistent with observations, but the long-term increase in CH4 is underestimated. This shows that CO is a good indicator of short-term variations in oxidizing power in the atmosphere. The simulation results also indicate the significant drop in OH concentrations in 1998 (about 5% lower than the previous year) was probably due to an abrupt increase in wetland methane emissions during an intense EI Niño event. Using a fixed-lag Kalman smoother, we estimate the mean wetland methane flux is about 128 Tg yr−1 through the period 1984–2008. This study demonstrates the effectiveness in examining the role of OH and CO in affecting CH4.

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Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1

10.5194/acp-2019-529 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jian He ◽

Vaishali Naik ◽

Larry W. Horowitz ◽

Ed Dlugokencky ◽

Kirk Thoning

Keyword(s):

Atmospheric Chemistry ◽

Latitudinal Gradient ◽

Methane Emissions ◽

Anthropogenic Emissions ◽

Atmospheric Methane ◽

Recent Past ◽

Methane Budget ◽

Global Trend ◽

Emission Changes ◽

Global Emissions

Abstract. Changes in atmospheric methane abundance have implications for both chemistry and climate as methane is both a strong greenhouse gas and an important precursor for tropospheric ozone. A better understanding of the drivers of trends and variability in methane abundance over the recent past is therefore critical for building confidence in projections of future methane levels. In this work, the representation of methane in the atmospheric chemistry model AM4.1 is improved by optimizing total methane emissions (to an annual mean of 576 ± 32 Tg yr−1) to match surface observations over 1980–2017. The simulations with optimized global emissions are in general able to capture the observed global trend, variability, seasonal cycle, and latitudinal gradient of methane. Simulations with different emission adjustments suggest that increases in methane sources (mainly from energy and waste sectors) balanced by increases in methane sinks (mainly due to increases in OH levels) lead to methane stabilization (with an imbalance of 5 Tg yr−1) during 1999–2006, and that increases in methane sources combined with little change in sinks (despite small decreases in OH levels) during 2007–2012 lead to renewed methane growth (with an imbalance of 14 Tg yr−1 for 2007–2017). Compared to 1999–2006, both methane emissions and sinks are greater (by 31 Tg yr−1 and 22 Tg yr−1, respectively) during 2007–2017. Our results also indicate that the energy sector is more likely a major contributor to the methane renewed growth after 2006 than wetland, as increases in wetland emissions alone are not able to explain the renewed methane growth with constant anthropogenic emissions. In addition, a significant increase in wetland emissions would be required starting in 2006, if anthropogenic emissions declined, for wetland emissions to drive renewed growth in methane, which is a less likely scenario. Simulations with varying OH levels indicate that 1 % change in OH levels could lead to an annual mean of ~ 4 Tg yr−1 difference in the optimized emissions and 0.08 year difference in the estimated tropospheric methane lifetime. Continued increases in methane emissions along with decreases in tropospheric OH concentrations during 2008–2015 prolong methane lifetime and therefore amplify the response of methane concentrations to emission changes. Uncertainties still exist in the partitioning of emissions among individual sources and regions.

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Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia

10.5194/acp-2020-649 ◽

2020 ◽

Author(s):

Yi Yin ◽

Frederic Chevallier ◽

Philippe Ciais ◽

Philippe Bousquet ◽

Marielle Saunois ◽

...

Keyword(s):

Growth Rate ◽

Carbon Monoxide ◽

Satellite Observations ◽

Anthropogenic Emissions ◽

Atmospheric Methane ◽

Sources And Sinks ◽

Ch4 Emissions ◽

Significant Acceleration ◽

Oxidation Chain ◽

The Tropics

Abstract. After stagnating in the early 2000s, the atmospheric methane growth rate has been positive since 2007 with a significant acceleration starting in 2014. While causes for previous growth rate variations are still not well determined, this recent increase can be studied with dense surface and satellite observations. Here, we use an ensemble of six multi-tracer atmospheric inversions that have the capacity to assimilate the major tracers in the methane oxidation chain – namely methane, formaldehyde, and carbon monoxide – to simultaneously optimize both the methane sources and sinks at each model grid. We show that the recent surge of the atmospheric growth rate between 2010–2013 and 2014–2017 is most likely explained by an increase of global CH4 emissions by 17.5 ± 1.5 Tg yr−1 (mean ± 1σ), while variations in CH4 sinks remained small. The inferred emission increase is consistently supported by both surface and satellite observations, with leading contributions from the tropics wetlands (~ 35 %) and anthropogenic emissions in China (~ 20 %). Such a high consecutive atmospheric growth rate has not been observed since the 1980s and corresponds to unprecedented global total CH4 emissions.

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Methane emissions from weaned lambs measured at 13, 17, 25 and 35 weeks of age compared with mature ewes consuming a fresh forage diet

Australian Journal of Experimental Agriculture ◽

10.1071/ea07258 ◽

2008 ◽

Vol 48 (2) ◽

pp. 240 ◽

Cited By ~ 8

Author(s):

T. W. Knight ◽

G. Molano ◽

H. Clark ◽

A. Cavanagh

Keyword(s):

Dry Matter ◽

Sulfur Hexafluoride ◽

Methane Emissions ◽

The Other ◽

Dry Matter Intake ◽

Ch4 Emission ◽

Tracer Technique ◽

Ch4 Emissions ◽

The Mean ◽

Measurement Period

Daily methane (CH4) emissions and dry matter intake (DMI) were measured on 14 mature ewes (3–4 years old) and 13 lambs when the lambs were 13, 17, 25 and 35 weeks of age. During the four CH4 measurement periods, all animals were kept in individual metabolism cages and fed pasture cut daily and fed at 1.5 times maintenance. Feed was offered in equal amounts at 0800 and 1500 hours daily. Methane emissions were measured using the sulfur hexafluoride tracer technique and values reported were the mean of measurement on 4–5 days for each animal. In the intervals between CH4 measurements, ewes and lambs grazed separate paddocks containing predominantly ryegrass. Daily CH4 emissions for the ewes ranged from 21.5 to 22.5 ± 1.50 g/day and were significantly higher than those of the lambs which ranged from 10.7 to 17.5 ± 1.50 g/day. Averaged across all four periods, the overall mean CH4 emission for lambs was 8% lower (P < 0.05) than for ewes (21.9 v. 23.8 ± 0.95 g CH4/kg DMI). However, within each measurement period, the emissions of CH4/kg DMI from lambs was significantly lower (P < 0.05) than those of ewes only in the fourth period when the lambs were 35 weeks of age (17.9 v. 21.9 g/kg DMI for lambs and ewes, respectively). The pasture offered to both ewes and lambs in this period was of higher quality than in the other periods (organic matter digestibility of 80% DM v. 68–71% DM at other times) and CH4 emission per kg DMI was lower in both groups of animals than in the other periods. This study supports the hypothesis that young sheep have lower CH4 emissions per unit of intake than mature animals. However, the age at which the lambs produced similar CH4/kg DMI to adult sheep could not be determined precisely because of the changes in pasture quality between different measurement periods.

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High-resolution inversion of methane emissions in the Southeast US using SEAC<sup>4</sup>RS aircraft observations of atmospheric methane: anthropogenic and wetland sources

10.5194/acp-2017-1151 ◽

2017 ◽

Author(s):

Jian-Xiong Sheng ◽

Daniel J. Jacob ◽

Alexander J. Turner ◽

Joannes D. Maasakkers ◽

Melissa P. Sulprizio ◽

...

Keyword(s):

Regional Scale ◽

Methane Emissions ◽

Gas Production ◽

Anthropogenic Sources ◽

Anthropogenic Source ◽

Atmospheric Methane ◽

Error Characterization ◽

The Mean ◽

Southeast Us ◽

Oil Gas

Abstract. We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US in August–September 2013 to estimate methane emissions in that region through an inverse analysis with up to 0.25 ° x 0.3125 ° (25 x 25 km2) resolution and with full error characterization. The Southeast US accounts for about half of total US anthropogenic emissions according to the gridded EPA national inventory and also has extensive wetlands. Our inversion uses state-of-science emission inventories as prior estimates, including a gridded version of the anthropogenic EPA Greenhouse Gas Inventory and the mean of the WetCHARTs ensemble for wetlands. Inversion results are independently verified by comparison with surface (NOAA/ESRL) and column (TCCON) methane observations. Our posterior estimates for the Southeast US are 12.8 ± 0.9 Tg a−1 for anthropogenic sources (no significant change from the gridded EPA inventory) and 9.4 ± 0.8 Tg a−1 for wetlands (27 % decrease from the mean in the WetCHARTs ensemble). The largest source of error in the WetCHARTs wetlands ensemble is the landcover map specification of wetland areal extent. We find no regional bias in the anthropogenic EPA inventory, including for different source sectors, in contrast with previous inverse analyses that found the EPA inventory to be too low at national scales. These previous inversions relied on prior anthropogenic source patterns from the EDGAR v4.2 inventory that have considerable error, and also assumed low wetland emissions. Despite the regional-scale consistency, we find significant local errors in the EPA inventory for oil/gas production fields, suggesting that emission factors are more variable than assumed in the inventory.

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Methane emissions from dairy cattle divergently selected for bloat susceptibility

Australian Journal of Experimental Agriculture ◽

10.1071/ea07296 ◽

2008 ◽

Vol 48 (2) ◽

pp. 234 ◽

Cited By ~ 12

Author(s):

C. S. Pinares-Patiño ◽

G. Molano ◽

A. Smith ◽

H. Clark

Keyword(s):

Titanium Dioxide ◽

Dry Matter ◽

Sulfur Hexafluoride ◽

Methane Emissions ◽

Dry Matter Intake ◽

Tracer Technique ◽

Ch4 Emissions ◽

The Mean ◽

Female Cattle ◽

Mixed Age

Bloat susceptibility is a genetically inherited trait and this study explored whether cattle divergently selected for this trait (low or high bloat susceptibility) also differ in methane (CH4) emissions. Twelve low bloat (402 ± 12 kg liveweight, LW) and 12 high bloat (334 ± 13 kg LW) Friesian × Jersey mixed age (2–4 years old) non-lactating and non-pregnant female cattle were used in a late autumn (June) grazing experiment involving two periods (P1 and P2). Methane emissions were measured during 5 (P1) or 4 (P2) consecutive days using the sulfur hexafluoride (SF6) tracer technique. In P1 only, titanium dioxide (TiO2) was used for faecal output and feed dry matter intake (DMI) estimations and it was found that the selection lines did not differ in DMI per unit of LW (17.3 ± 1.3 v. 15.4 ± 1.3 g DMI/kg LW, P > 0.05; for low and high bloat cows, respectively). In both periods, the mean absolute CH4 emissions from low bloat cows were significantly higher (P < 0.001) than from high bloat cows (144.5 ± 6.3 v. 107.4 ± 7.2 and 147.9 ± 4.6 v. 119.6 ± 6.5 g/day for P1 and P2, respectively), but on per unit of LW basis, CH4 emissions from low and high bloat animals were not different from each other (P > 0.05) either at P1 (346 ± 16 v. 312 ± 11 mg/kg LW) or P2 (345 ± 11 v. 347 ± 10 mg/kg LW). In P1, when DMI was estimated using TiO2, the selection lines did not differ (P > 0.05) in CH4 yields per unit of intake (20.6 ± 0.8 v. 21.3 ± 1.4 g/kg DMI for low and high bloat, respectively). Previous studies with the same herd showed that the selection lines did not differ in DMI per unit of LW, which was confirmed by the present study from estimations of DMI by TiO2 dosing in P1. It is concluded that low and high bloat susceptible genotypes did not differ in their CH4 yields per unit of feed intake.

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Speleothem records of changes in tropical hydrology over the Holocene and possible implications for atmospheric methane

The Holocene ◽

10.1177/0959683611400194 ◽

2011 ◽

Vol 21 (5) ◽

pp. 735-741 ◽

Cited By ~ 19

Author(s):

Stephen J. Burns

Keyword(s):

Southern Hemisphere ◽

Northern Hemisphere ◽

Methane Production ◽

Methane Emissions ◽

Atmospheric Methane ◽

Direct Response ◽

The Holocene ◽

Tropical Hydrology ◽

The Tropics ◽

Methane Concentrations

Recent speleothem records from the tropics of both hemispheres document a gradual decrease in the intensity of the monsoons in the Northern Hemisphere and increase in the Southern Hemisphere monsoons over the Holocene. These changes are a direct response of the monsoons to precession-driven insolation variability. With regard to atmospheric methane, this shift should result in a decrease in Northern Hemisphere tropical methane emissions and increase in Southern Hemisphere emissions. It is plausible that that overall tropical methane production experienced a minimum in the mid-Holocene because of decreased seasonality in rainfall at the margins of the tropics. Changes in tropical methane production alone might, therefore, explain many of the characteristics of Holocene methane concentrations and isotopic chemistry.

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Limitations of the radon tracer method (RTM) to estimate regional greenhouse gas (GHG) emissions – a case study for methane in Heidelberg

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-17907-2021 ◽

2021 ◽

Vol 21 (23) ◽

pp. 17907-17926

Author(s):

Ingeborg Levin ◽

Ute Karstens ◽

Samuel Hammer ◽

Julian DellaColetta ◽

Fabian Maier ◽

...

Keyword(s):

Greenhouse Gas ◽

Inversion Layer ◽

Ghg Emissions ◽

Point Sources ◽

Atmospheric Methane ◽

Tracer Method ◽

Top Down ◽

Bottom Up ◽

Ch4 Emissions ◽

Annual Variations

Abstract. Correlations of nighttime atmospheric methane (CH4) and 222radon (222Rn) observations in Heidelberg, Germany, were evaluated with the radon tracer method (RTM) to estimate the trend of annual nocturnal CH4 emissions from 1996–2020 in the footprint of the station. After an initial 30 % decrease in emissions from 1996 to 2004, there was no further systematic trend but small inter-annual variations were observed thereafter. This is in accordance with the trend of total emissions until 2010 reported by the EDGARv6.0 inventory for the surroundings of Heidelberg and provides a fully independent top-down verification of the bottom-up inventory changes. We show that the reliability of total nocturnal CH4 emission estimates with the RTM critically depends on the accuracy and representativeness of the 222Rn exhalation rates estimated from soils in the footprint of the site. Simply using 222Rn fluxes as estimated by Karstens et al. (2015) could lead to biases in the estimated greenhouse gas (GHG) fluxes as large as a factor of 2. RTM-based GHG flux estimates also depend on the parameters chosen for the nighttime correlations of CH4 and 222Rn, such as the nighttime period for regressions and the R2 cut-off value for the goodness of the fit. Quantitative comparison of total RTM-based top-down flux estimates with bottom-up emission inventories requires representative high-resolution footprint modelling, particularly in polluted areas where CH4 emissions show large heterogeneity. Even then, RTM-based estimates are likely biased low if point sources play a significant role in the station footprint as their emissions may not be fully captured by the RTM method, for example, if stack emissions are injected above the top of the nocturnal inversion layer or if point-source emissions from the surface are not well mixed into the footprint of the measurement site. Long-term representative 222Rn flux observations in the footprint of a station are indispensable in order to apply the RTM method for reliable quantitative flux estimations of GHG emissions from atmospheric observations.

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Space-borne observation of methane from atmospheric infrared sounder version 6: validation and implications for data analysis

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-8-8563-2015 ◽

2015 ◽

Vol 8 (8) ◽

pp. 8563-8597 ◽

Cited By ~ 11

Author(s):

X. Xiong ◽

F. Weng ◽

Q. Liu ◽

E. Olsen

Keyword(s):

Data Analysis ◽

Cloud Amount ◽

Retrieval Algorithm ◽

Atmospheric Methane ◽

Atmospheric Infrared Sounder ◽

Northern Latitudes ◽

Standard Product ◽

The Mean ◽

The Tropics ◽

Recent Version

Abstract. Atmospheric Methane (CH4) is generated as a standard product in recent version of the hyperspectral Atmospheric Infrared Sounder (AIRS-V6) aboard NASA's Aqua satellite at the NASA Goddard Earth Sciences Data and Information Services Center (NASA/GES/DISC). Significant improvements in AIRS-V6 was expected but without a thorough validation. This paper first introduced the improvements of CH4 retrieval in AIRS-V6 and some characterizations, then presented the results of validation using ~ 1000 aircraft profiles from several campaigns spread over a couple of years and in different regions. It was found the mean biases of AIRS CH4 at layers 343–441 and 441–575 hPa are −0.76 and −0.05 % and the RMS errors are 1.56 and 1.16 %, respectively. Further analysis demonstrates that the errors in the spring and in the high northern latitudes are larger than in other seasons or regions. The error is correlated with Degree of Freedoms (DOFs), particularly in the tropics or in the summer, and cloud amount, suggesting that the "observed" spatiotemporal variation of CH4 by AIRS is imbedded with some artificial impact from the retrieval sensitivity in addition to its variation in reality, so the variation of information content in the retrievals needs to be taken into account in data analysis of the retrieval products. Some additional filtering (i.e. rejection of profiles with obvious oscillation as well as those deviating greatly from the norm) for quality control is recommended for the users to better utilize AIRS-V6 CH4, and their implementation in the future versions of the AIRS retrieval algorithm is under consideration.

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