Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high ...latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane (XCH4) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CH4 fluxes using the CarbonTracker Europe-CH4 (CTE-CH4) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research’s (SRON) operational and University of Bremen’s Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CH4 emission maximum is later, when the SRON’s operational data are assimilated. The TROPOMI inversions show higher CH4 emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates.
With projections of increasing drought in the future, understanding how the natural carbon cycle responds to drought events is needed to predict the fate of the land carbon sink and future ...atmospheric CO2 concentrations and climate. We quantified the impacts of the 2011 and 2012 droughts on terrestrial ecosystem carbon uptake anomalies over the contiguous US (CONUS) relative to non-drought years during 2010-2015 using satellite observations and the carbon monitoring system-flux inversion modeling framework. Soil moisture and temperature anomalies are good predictors of gross primary production anomalies (R2 > 0.6) in summer but less so for net biosphere production (NBP) anomalies, reflecting different respiration responses. We showed that regional responses combine in complicated ways to produce the observed CONUS responses. Because of the compensating effect of the carbon flux anomalies between northern and southern CONUS in 2011 and between spring and summer in 2012, the annual NBP decreased by 0.10 0.16 GtC in 2011, and increased by 0.10 0.16 GtC in 2012 over CONUS, consistent with previous reported results. Over the 2011 and 2012 drought-impacted regions, the reductions in NBP were ∼40% of the regional annual fossil fuel emissions, underscoring the importance of quantifying natural carbon flux variability as part of an overall observing strategy. The NBP reductions over the 2011 and 2012 CONUS drought-impacted region were opposite to the global atmospheric CO2 growth rate anomaly, implying that global atmospheric CO2 growth rate is an offsetting effect between enhanced uptake and emission, and enhancing the understanding of regional carbon-cycle climate relationship is necessary to improve the projections of future climate.
The powerful El Niño event of 2015-2016 - the third most intense since the 1950s - has exerted a large impact on the Earth's natural climate system. The column-averaged CO2 dry-air mole fraction ...(XCO2) observations from satellites and ground based networks are analyzed together with in situ observations for the period of September 2014 to October 2016. From the differences between satellite (OCO-2) observations and simulations using an atmospheric chemistry-transport model, we estimate that, relative to the mean annual fluxes for 2014, the most recent El Niño has contributed to an excess CO2 emission from the Earth's surface (land+ocean) to the atmosphere in the range of 2.4+/-0.2 PgC (1 Pg = 10(exp 15) g) over the period of July 2015 to June 2016. The excess CO2 flux is resulted primarily from reduction in vegetation uptake due to drought, and to a lesser degree from increased biomass burning. It is about the half of the CO2 flux anomaly (range: 4.4-6.7 PgC) estimated for the 1997/1998 El Niño. The annual total sink is estimated to be 3.9+/-0.2 PgC for the assumed fossil fuel emission of 10.1 PgC. The major uncertainty in attribution arise from error in anthropogenic emission trends, satellite data and atmospheric transport.
Chevallier showed a column CO
(Formula: see text) anomaly of ±0.5 parts per million forced by a uniform net biosphere exchange (NBE) anomaly of 2.5 gigatonnes of carbon over the tropical continents ...within a year, so he claimed that the inferred NBE uncertainties should be larger than presented in Liu
We show that a much concentrated NBE anomaly led to much larger Formula: see text perturbations.
This paper provides an overview of the validation of National Oceanic and Atmospheric Administration (NOAA) operational retrievals of atmospheric carbon trace gas profiles, specifically carbon ...monoxide (CO), methane (CH4) and carbon dioxide (CO2), from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), a NOAA enterprise algorithm that retrieves atmospheric profile environmental data records (EDRs) under global non-precipitating (clear to partly cloudy) conditions. Vertical information about atmospheric trace gases is obtained from the Cross-track Infrared Sounder (CrIS), an infrared Fourier transform spectrometer that measures high resolution Earth radiance spectra from NOAA operational low earth orbit (LEO) satellites, including the Suomi National Polar-orbiting Partnership (SNPP) and follow-on Joint Polar Satellite System (JPSS) series beginning with NOAA-20. The NUCAPS CO, CH4, and CO2 profile EDRs are rigorously validated in this paper using well-established independent truth datasets, namely total column data from ground-based Total Carbon Column Observing Network (TCCON) sites, and in situ vertical profile data obtained from aircraft and balloon platforms via the NASA Atmospheric Tomography (ATom) mission and NOAA AirCore sampler, respectively. Statistical analyses using these datasets demonstrate that the NUCAPS carbon gas profile EDRs generally meet JPSS Level 1 global performance requirements, with the absolute accuracy and precision of CO 5% and 15%, respectively, in layers where CrIS has vertical sensitivity; CH4 and CO2 product accuracies are both found to be within ±1%, with precisions of ≈1.5% and ⪅0.5%, respectively, throughout the tropospheric column.
Methane ( CH 4) is a potent greenhouse gas with a large temporal variability. To increase the spatial coverage, methane observations are increasingly made from satellites that retrieve the ...column-averaged dry air mole fraction of methane (XCH 4). To understand and quantify the spatial differences of the seasonal cycle and trend of XCH 4 in more detail, and to ultimately help reduce uncertainties in methane emissions and sinks, we evaluated and analyzed the average XCH 4 seasonal cycle and trend from three Greenhouse Gases Observing Satellite (GOSAT) retrieval algorithms: National Institute for Environmental Studies algorithm version 02.75, RemoTeC CH 4 Proxy algorithm version 2.3.8 and RemoTeC CH 4 Full Physics algorithm version 2.3.8. Evaluations were made against the Total Carbon Column Observing Network (TCCON) retrievals at 15 TCCON sites for 2009–2015, and the analysis was performed, in addition to the TCCON sites, at 31 latitude bands between latitudes 44.43°S and 53.13°N. At latitude bands, we also compared the trend of GOSAT XCH 4 retrievals to the NOAA’s Marine Boundary Layer reference data. The average seasonal cycle and the non-linear trend were, for the first time for methane, modeled with a dynamic regression method called Dynamic Linear Model that quantifies the trend and the seasonal cycle, and provides reliable uncertainties for the parameters. Our results show that, if the number of co-located soundings is sufficiently large throughout the year, the seasonal cycle and trend of the three GOSAT retrievals agree well, mostly within the uncertainty ranges, with the TCCON retrievals. Especially estimates of the maximum day of XCH 4 agree well, both between the GOSAT and TCCON retrievals, and between the three GOSAT retrievals at the latitude bands. In our analysis, we showed that there are large spatial differences in the trend and seasonal cycle of XCH 4. These differences are linked to the regional CH 4 sources and sinks, and call for further research.
Nitrous oxide (N2O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to ...human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N2O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N2O ν3 band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N2O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N2O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals.
AIM-North is a proposed satellite mission that would provide observations of unprecedented frequency and density for monitoring northern greenhouse gases (GHGs), air quality (AQ) and vegetation. ...AIM-North would consist of two satellites in a highly elliptical orbit formation, observing over land from ∼40°N to 80°N multiple times per day. Each satellite would carry a near-infrared to shortwave infrared imaging spectrometer for CO
2
, CH
4
, and CO, and an ultraviolet-visible imaging spectrometer for air quality. Both instruments would measure solar-induced fluorescence from vegetation. A cloud imager would make near-real-time observations, which could inform the pointing of the other instruments to focus only on the clearest regions. Multiple geostationary (GEO) AQ and GHG satellites are planned for the 2020s, but they will lack coverage of northern regions like the Arctic. AIM-North would address this gap with quasi-geostationary observations of the North and overlap with GEO coverage to facilitate intercomparison and fusion of these datasets. The resulting data would improve our ability to forecast northern air quality and quantify fluxes of GHG and AQ species from forests, permafrost, biomass burning and anthropogenic activity, furthering our scientific understanding of these processes and supporting environmental policy.
Column-averaged dry air mole fractions of carbon dioxide and methane (XCO2 and XCH4) retrieved from SWIR (Short-Wavelength InfraRed) observations by GOSAT (Greenhouse Gases Observing SATellite) since ...2009 and its successor GOSAT-2 since 2019 are available from NIES (National Institute for Environmental Studies) as SWIR L2 (Level 2) products. This paper shows the current status of the data quality of NIES SWIR L2 products and inter-satellite comparison results. Comparisons of XCO2 and XCH4 obtained from each satellite with ground-based observations from the TCCON (Total Carbon Column Observing Network) reveal that the averaged single measurement precision are less than 1.9 ppm and 10 ppb, respectively, and the site-to-site biases are less than 0.9 ppm and 5 ppb, respectively. The standard deviations of the inter-satellite differences for XCO2 and XCH4 are 2.18 ppm and 12.1 ppb, respectively, on an individual-data basis and 1.77 ppm and 11.7 ppb, respectively, on a monthly-regional-mean basis. While further improvements in the retrieval algorithm and bias-correction method are needed, GOSAT and GOSAT-2 retrievals are generally in good agreement.
The proxy method, using the ratio of total column CH4 to CO2 to reduce the effects of common biases, has been used to retrieve column-averaged dry-air mole fraction of CH4 from satellite data. The ...present study characterizes the remaining scattering effects in the CH4/CO2 ratio component of the Greenhouse gases Observing SATellite (GOSAT) retrieval and uses them for bias correction. The variation of bias between the GOSAT and Total Carbon Column Observing Network (TCCON) ratio component with GOSAT data-derived variables was investigated. Then, it was revealed that the variability of the bias could be reduced by using four variables for the bias correction—namely, airmass, 2 μm band radiance normalized with its noise level, the ratio between the partial column-averaged dry-air mole fraction of CH4 for the lower atmosphere and that for the upper atmosphere, and the difference in surface albedo between the CH4 and CO2 bands. The ratio of partial column CH4 reduced the dependence of bias on the cloud fraction and the difference between hemispheres. In addition to the reduction of bias (from 0.43% to 0%), the precision (standard deviation of the difference between GOSAT and TCCON) was reduced from 0.61% to 0.55% by the correction. The bias and its temporal variation were reduced for each site: the mean and standard deviation of the mean bias for individual seasons were within 0.2% for most of the sites.
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