The influence of instrumental line shape degradation on NDACC gas retrievals: Total column and profile

We simulated instrumental line shape (ILS) degradations with respect to typical types of misalignment, and compared their influence on each NDACC (Network for Detection of Atmospheric Composition Change) gas. The sensitivities of the total column, the root mean square (rms) of the fitting residual, the total random uncertainty, the total systematic uncertainty, the total uncertainty, degrees of freedom for signal (DOFs), and the profile with respect to different levels of ILS degradation for all current standard NDACC gases, i.e. O3, HNO3, HCl, HF, ClONO2, CH4, CO, N2O, C2H6, and HCN, were investigated. The influence of an imperfect ILS on NDACC gases’ retrieval was assessed, and the consistency under different meteorological conditions and solar zenith angles (SZAs) were examined. The study concluded that the influence of ILS degradation can be approximated by the linear sum of individual modulation efficiency (ME) amplitude influence and phase error (PE) influence. The PE influence is of secondary importance compared with the ME amplitude. Generally, the stratospheric gases are more sensitive to ILS degradation than the tropospheric gases, and the positive ME influence is larger than the negative ME. For a typical ILS degradation (10 %), the total columns of stratospheric gases O3, HNO3, HCl, HF, and ClONO2 changed by 1.9, 0.7, 4, 3, and 23 %, respectively, while the columns of tropospheric gases CH4, CO, N2O, C2H6, and HCN changed by 0.04, 2.1, 0.2, 1.1, and 0.75 %, respectively. In order to suppress the fractional difference in the total column for ClONO2 and other NDACC gases within 10 and 1 %, respectively, the maximum positive ME degradations for O3, HNO3, HCl, HF, ClONO2, CO, C2H6, and HCN should be less than 6, 15, 5, 5, 5, 5, 9, and 13 %, respectively; the maximum negative ME degradations for O3, HCl, and HF should be less than 6, 12, and 12 %, respectively; the influence of ILS degradation on CH4 and N2O can be regarded as being negligible

Retrieval of atmospheric CH_4 vertical information from ground-based FTS near-infrared spectra

International audienceThe Total Carbon Column Observing Network (TCCON) column-averaged dry air mole fraction of CH 4 (X CH 4) measurements have been widely used to validate satellite observations and to estimate model simulations. The GGG2014 code is the standard TCCON retrieval software used in performing a profile scaling retrieval. In order to obtain several vertical pieces of information in addition to the total column, in this study, the SFIT4 retrieval code is applied to retrieve the CH 4 mole fraction vertical profile from the Fourier transform spectrometer (FTS) spectrum at six sites (Ny-Ålesund, Sodankylä, Bialystok, Bremen, Orléans and St Denis) during the time period of 2016-2017. The retrieval strategy of the CH 4 profile retrieval from ground-based FTS near-infrared (NIR) spectra using the SFIT4 code (SFIT4NIR) is investigated. The degree of freedom for signal (DOFS) of the SFIT4NIR retrieval is about 2.4, with two distinct pieces of information in the troposphere and in the stratosphere. The averaging kernel and error budget of the SFIT4NIR retrieval are presented. The data accuracy and precision of the SFIT4NIR retrievals, including the total column and two partial columns (in the troposphere and stratosphere), are estimated by TCCON standard retrievals, ground-based in situ measurements, Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) satellite observations, TCCON proxy data and AirCore and aircraft measurements. By comparison against TCCON standard retrievals, it is found that the retrieval uncertainty of SFIT4NIR X CH 4 is similar to that of TCCON standard retrievals with systematic uncertainty within 0.35 % and random uncertainty of about 0.5 %. The tropospheric and strato-spheric X CH 4 from SFIT4NIR retrievals are assessed by comparison with AirCore and aircraft measurements, and there is a 1.0 ± 0.3 % overestimation in the SFIT4NIR tropospheric X CH 4 and a 4.0 ± 2.0 % underestimation in the SFIT4NIR stratospheric X CH 4 , which are within the systematic uncertainties of SFIT4NIR-retrieved partial columns in the tropo-sphere and stratosphere respectively

A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals

National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite provides observations of total column‐averaged CO2 mole fractions (X_(CO₂)) at high spatial resolution that may enable novel constraints on surface‐atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO₂ observations and reliable representations of atmospheric transport. Since X_(CO₂) observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along‐track OCO‐2 soundings. We compare high‐pass‐filtered (<250 km, spatial scales that primarily isolate mesoscale or finer‐scale variations) along‐track spatial variability in X_(CO₂) and X_(H₂O) from OCO‐2 tracks to temporal synoptic and mesoscale variability from ground‐based X_(CO₂) and X_(H₂O) observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along‐track, high‐frequency variability for OCO‐2 X_(H₂O). For X_(CO₂), both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO‐2 retrieval state vector are important drivers of the along‐track variance budget

A Geostatistical Framework for Quantifying the Imprint of Mesoscale Atmospheric Transport on Satellite Trace Gas Retrievals

National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 (OCO-2) satellite provides observations of total column-averaged CO2 mole fractions (XCO2) at high spatial resolution that may enable novel constraints on surface-atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO2 observations and reliable representations of atmospheric transport. Since XCO2 observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along-track OCO-2 soundings. We compare high-pass-filtered (<250 km, spatial scales that primarily isolate mesoscale or finer-scale variations) along-track spatial variability in XCO2 and XH2O from OCO-2 tracks to temporal synoptic and mesoscale variability from ground-based XCO2 and XH2O observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along-track, high-frequency variability for OCO-2 XH2O. For XCO2, both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO-2 retrieval state vector are important drivers of the along-track variance budget.Plain Language SummaryNumerous efforts have been made to quantify sources and sinks of atmospheric CO2 at regional spatial scales. A common approach to infer these sources and sinks requires accurate representation of variability of CO2 observations attributed to transport by weather systems. While numerical weather prediction models have a fairly reasonable representation of larger-scale weather systems, such as frontal systems, representation of smaller-scale features (<250 km), is less reliable. In this study, we find that the variability of total column-averaged CO2 observations attributed to these fine-scale weather systems accounts for up to half of the variability attributed to local sources and sinks. Here, we provide a framework for quantifying the drivers of spatial variability of atmospheric trace gases rather than simply relying on numerical weather prediction models. We use this framework to quantify potential sources of errors in measurements of total column-averaged CO2 and water vapor from National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 satellite.Key PointsWe developed a framework to relate high-frequency spatial variations to transport-induced temporal fluctuations in atmospheric tracersWe use geostatistical analysis to quantify the variance budget for XCO2 and XH2O retrieved from NASA’s OCO-2 satelliteAccounting for random errors, systematic errors, and real geophysical coherence in remotely sensed trace gas observations may yield improved flux constraintsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151988/1/jgrd55658.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151988/2/jgrd55658_am.pd

Simultaneous retrieval of atmospheric CO_2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON)

Educate to prevent: science-based materials on food hygiene and safety

Uma importante estratégia para a redução do impacto das doenças de origem alimentar é a prevenção e a promoção da saúde. A população escolar foi escolhida como público-alvo para aumentar a literacia para a saúde e promover práticas saudáveis e seguras relacionadas com os alimentos, através do projeto “Educar para Prevenir”. Foram produzidos e publicados materiais educativos para o público escolar e professores. Estes materiais, que compreendem três diferentes tipos de ferramentas, foram publicados como um kit. O desenvolvimento destes materiais baseou-se na recolha de dados de surtos de doenças de origem alimentar, de 2009 a 2013, do Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA). O risco de ocorrência e os fatores contributivos, bem como as boas práticas, foram identificados e usados como base para a elaboração dos materiais educativos. Adicionalmente, foram usados materiais da Organização Mundial da Saúde como o programa “Cinco Chaves para uma Alimentação Mais Segura”. Nas próximas etapas deste projeto serão produzidos novos materiais para estudantes contendo informação sobre a composição nutricional dos alimentos e a compreensão da rotulagem alimentar.An important strategy to reduce food borne diseases burden is prevention and health promotion. The student’s population was chosen as the target audience for improving health literacy and promoting healthy and safe practices relating to food trough the Project “Educar para Prevenir” (Education for Prevention). School educational materials on food safety, on teacher level, were developed and published, aiming the different school levels. These materials comprised 3 different kinds of tools were published as a kit. The development of these materials was based on data collected foodborne outbreaks from 2009 to 2013, at the National Institute of Health (INSA). The occurrence risk and contributing factors were identified as well as the good practices and were the basis for the elaboration of the educational materials. In addition, some World Health Organization materials, such as “Five Keys to Safer Food” programme, were used. On the next steps of the project include new materials for students will be produced, including information about nutritional composition of the food and understanding of the food labelling.info:eu-repo/semantics/publishedVersio

Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model

The GEOS-Chem simulation of atmospheric CH$_{4}$ was evaluated against observations from the Thermal and Near Infrared Sensor for Carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Total Carbon Column Observing Network (TCCON). We focused on the model simulations at the 4°×5° and 2°×2.5° horizontal resolutions for the period of February–May 2010. Compared to the GOSAT, TCCON, and ACE-FTS data, we found that the 2°×2.5° model produced a better simulation of CH$_{4}$, with smaller biases and a higher correlation to the independent data. We found large resolution-dependent differences such as a latitude-dependent XCH$_{4}$ bias, with higher column abundances of CH$_{4}$ at high latitudes and lower abundances at low latitudes at the 4°×5° resolution than at 2°×2.5°. We also found large differences in CH$_{4}$ column abundances between the two resolutions over major source regions such as China. These differences resulted in up to 30 % differences in inferred regional CH$_{4}$ emission estimates from the two model resolutions. We performed several experiments using 222Rn, 7Be, and CH$_{4}$ to determine the origins of the resolution-dependent errors. The results suggested that the major source of the latitude-dependent errors is excessive mixing in the upper troposphere and lower stratosphere, including mixing at the edge of the polar vortex, which is pronounced at the 4°×5° resolution. At the coarser resolution, there is weakened vertical transport in the troposphere at midlatitudes to high latitudes due to the loss of sub-grid tracer eddy mass flux in the storm track regions. The vertical air mass fluxes are calculated in the model from the degraded coarse-resolution wind fields and the model does not conserve the air mass flux between model resolutions; as a result, the low resolution does not fully capture the vertical transport. This produces significant localized discrepancies, such as much greater CH$_{4}$ abundances in the lower troposphere over China at 4°×5° than at 2°×2.5°. Although we found that the CH$_{4}$ simulation is significantly better at 2°×2.5° than at 4°×5°, biases may still be present at 2°×2.5° resolution. Their importance, particularly in regards to inverse modeling of CH$_{4}$ emissions, should be evaluated in future studies using online transport in the native general circulation model as a benchmark simulation

Characteristics of interannual variability in space-based XCO2_2 global observations

Atmospheric carbon dioxide (CO$_2$) accounts for the largest radiative forcing among anthropogenic greenhouse gases. There is, therefore, a pressing need to understand the rate at which CO$_2$ accumulates in the atmosphere, including the interannual variations (IAVs) in this rate. IAV in the CO$_2$ growth rate is a small signal relative to the long-term trend and the mean annual cycle of atmospheric CO$_2$, and IAV is tied to climatic variations that may provide insights into long-term carbon–climate feedbacks. Observations from the Orbiting Carbon Observatory-2 (OCO-2) mission offer a new opportunity to refine our understanding of atmospheric CO$_2$ IAV since the satellite can measure over remote terrestrial regions and the open ocean, where traditional in situ CO$_2$ monitoring is difficult, providing better spatial coverage compared to ground-based monitoring techniques. In this study, we analyze the IAV of column-averaged dry-air CO$_2$ mole fraction (XCO$_2$) from OCO-2 between September 2014 and June 2021. The amplitude of the IAV, which is calculated as the standard deviation of the time series, is up to 1.2 ppm over the continents and around 0.4 ppm over the open ocean. Across all latitudes, the OCO-2-detected XCO$_2$ IAV shows a clear relationship with El Niño–Southern Oscillation (ENSO)-driven variations that originate in the tropics and are transported poleward. Similar, but smoother, zonal patterns of OCO-2 XCO2 IAV time series compared to ground-based in situ observations and with column observations from the Total Carbon Column Observing Network (TCCON) and the Greenhouse Gases Observing Satellite (GOSAT) show that OCO-2 observations can be used reliably to estimate IAV. Furthermore, the extensive spatial coverage of the OCO-2 satellite data leads to smoother IAV time series than those from other datasets, suggesting that OCO-2 provides new capabilities for revealing small IAV signals despite sources of noise and error that are inherent to remote-sensing datasets

Intercomparison of low- and high-resolution infrared spectrometers for ground-based solar remote sensing measurements of total column concentrations of CO2, CH4, and CO

The Total Carbon Column Observing Network (TCCON) is the baseline ground-based network of instruments that record solar absorption spectra from which accurate and precise column-averaged dry-air mole fractions of CO$_{2}$ (XCO$_{2}$), CH$_{4}$ (XCH$_{4}$), CO (XCO), and other gases are retrieved. The TCCON data have been widely used for carbon cycle science and validation of satellites measuring greenhouse gas concentrations globally. The number of stations in the network (currently about 25) is limited and has a very uneven geographical coverage: the stations in the Northern Hemisphere are distributed mostly in North America, Europe, and Japan, and only 20 % of the stations are located in the Southern Hemisphere, leaving gaps in the global coverage. A denser distribution of ground-based solar absorption measurements is needed to improve the representativeness of the measurement data for various atmospheric conditions (humid, dry, polluted, presence of aerosol), various surface conditions such as high albedo (>0.4) and very low albedo, and a larger latitudinal distribution. More stations in the Southern Hemisphere are also needed, but a further expansion of the network is limited by its costs and logistical requirements. For this reason, several groups are investigating supplemental portable low-cost instruments. The European Space Agency (ESA) funded campaign Fiducial Reference Measurements for Ground-Based Infrared Greenhouse Gas Observations (FRM4GHG) at the Sodankylä TCCON site in northern Finland aims to characterise the assessment of several low-cost portable instruments for precise solar absorption measurements of XCO$_{2}$, XCH$_{4}$, and XCO. The test instruments under investigation are three Fourier transform spectrometers (FTSs): a Bruker EM27/SUN, a Bruker IRcube, and a Bruker Vertex70, as well as a laser heterodyne spectroradiometer (LHR) developed by the UK Rutherford Appleton Laboratory. All four remote sensing instruments performed measurements simultaneously next to the reference TCCON instrument, a Bruker IFS 125HR, for a full year in 2017. The TCCON FTS was operated in its normal high-resolution mode (TCCON data set) and in a special low-resolution mode (HR125LR data set), similar to the portable spectrometers. The remote sensing measurements are complemented by regular AirCore launches performed from the same site. They provide in situ vertical profiles of the target gas concentrations as auxiliary reference data for the column retrievals, which are traceable to the WMO SI standards. The reference measurements performed with the Bruker IFS 125HR were found to be affected by non-linearity of the indium gallium arsenide (InGaAs) detector. Therefore, a non-linearity correction of the 125HR data was performed for the whole campaign period and compared with the test instruments and AirCore. The non-linearity-corrected data (TCCONmod data set) show a better match with the test instruments and AirCore data compared to the non-corrected reference data. The time series, the bias relative to the reference instrument and its scatter, and the seasonal and the day-to-day variations of the target gases are shown and discussed. The comparisons with the HR125LR data set gave a useful analysis of the resolution-dependent effects on the target gas retrieval. The solar zenith angle dependence of the retrievals is shown and discussed. The intercomparison results show that the LHR data have a large scatter and biases with a strong diurnal variation relative to the TCCON and other FTS instruments. The LHR is a new instrument under development, and these biases are currently being investigated and addressed. The campaign helped to characterise and identify instrumental biases and possibly retrieval biases, which are currently under investigation. Further improvements of the instrument are ongoing. The EM27/SUN, the IRcube, the modified Vertex70, and the HR125LR provided stable and precise measurements of the target gases during the campaign with quantified small biases. The bias dependence on the humidity along the measurement line of sight has been investigated and no dependence was found. These three portable low-resolution FTS instruments are suitable to be used for campaign deployment or long-term measurements from any site and offer the ability to complement the TCCON and expand the global coverage of ground-based reference measurements of the target gases