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In this study, we demonstrate the utility of available correlative measurements of carbon species to identify regional and local air mass characteristics as well as their associated source types. In particular, we combine different regression techniques and enhancement ratio algorithms with carbon monoxide (CO), carbon dioxide (CO 2), and methane (CH 4) total column abundance from 11 sites of the Total Carbon Column Observing Network (TCCON) to infer relative contributions of regional and local sources to each of these sites. The enhancement ratios provide a viable alternative to univariate measures of relationships between the trace gases that are insufficient in capturing source-type and transport signatures. Regional enhancements are estimated from the difference between bivariate regressions across a specific time window of observed total abundance of these species (BERr for bulk enhancement regression ratio) and inferred anomalies (AERr for anomaly enhancement regression ratio) associated with a site-specific background. Since BERr and AERr represent the bulk and local species enhancement ratio, respectively, its difference simply represents the site-specific regional component of these ratios. We can then compare these enhancements for CO 2 and CH 4 with CO to differentiate between combustion and non-combustion air masses. Our results show that while the regional and local influences in enhancements vary across sites, dominant characteristics are found to be consistent with previous studies over these sites and with bottom-up anthropogenic and fire emission inventories. The site in Pasadena shows a dominant local influence (> 60 %) across all species enhancement ratios, which appear to come from a mixture of biospheric and combustion activities. In contrast, Anmyeondo shows more regionally influenced (> 60 %) air masses associated with high-temperature and/or biofuel combustion activities. Ascension Island appears to only show a large regional influence (> 80 %) on CO / CO 2 and CO / CH 4 , which is indicative of transported and combustion-related CO from the nearby African region, consistent with a sharp rise in column CO (3.51 ± 0.43 % ppb yr -1) at this site. These methods have important applications to source analysis using spaceborne column retrievals of these species. [ABSTRACT FROM AUTHOR]

Long-term experimental stratospheric NO 2 and NO partial columns measured by means of solar Fourier-transform infrared (FTIR) spectrometry at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.), Germany, were used to create a set of experiment-based monthly scaling factors (SF exp). The underlying data set is published in a companion paper (Nürnberg et al., 2024) and comprises over 25 years of measurements depicting the daytime variability of stratospheric NO 2 and NO partial columns with respect to local solar time (LST). In accordance with simulation-based scaling factors recently published by Strode et al. (2022), we created SF exp normalized to SZA =72° for NO 2 and NO for every month of the year as a function of solar zenith angle (SZA). Apart from a boundary value problem at minimum SZA values originating from averaging over different times of the month, the obtained scaling factors SF exp (NO 2) and SF exp (NO) as a function of SZA represent the daytime behavior already shown in model simulations and experiments in the literature very well. This shows a well-pronounced increase in the NO 2 and NO stratospheric partial column with the time of the day and a flattening of this increase after noon. In addition to the discussion of SF exp , we validate the simulation-based scaling factors SF sim (NO 2) (Strode et al., 2022) and present simulation-based scaling factors for NO SF sim (NO). The simulation-based scaling factors show excellent agreement with the experiment-based ones; i.e., for NO 2 and NO the mean value of the modulus between the experiment and simulation over all SZAs and months is only 0.02 %. We show that recently used model simulations can describe the real behavior of nitrogen oxide (NO x) variability in the stratosphere very well. Furthermore, we conclude that ground-based FTIR measurements can be used for validation of the output of photochemistry models and for creating experiment-based data sets describing the daytime stratospheric NO x variability as a function of SZA. This is a contribution to improved satellite validation and a better understanding of stratospheric photochemistry. [ABSTRACT FROM AUTHOR]

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the tnzuncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

Observations of nitrogen dioxide (NO 2) and nitrogen oxide (NO) in the stratosphere are relevant to understand long-term changes and variabilities in stratospheric nitrogen oxide (NO x) and ozone (O 3) concentrations. Due to the versatile role of NO 2 and NO in stratospheric O 3 photochemistry, they are important for recovery and build-up of O 3 holes in the stratosphere and therefore can indirectly affect human life. Thus, we present in this work the evaluation of NO 2 and NO stratospheric partial columns (> 16 km altitude) retrieved from ground-based Fourier-transform infrared (FTIR) measurements of over 25 years at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.) and 18 years at Garmisch (47.47° N, 11.06° E; 745 m a.s.l.), Germany. The obtained stratospheric columns are only weakly influenced by tropospheric pollution and show only a very small bias of 2.5 ± 0.2 % when comparing NO 2 above Zugspitze and Garmisch. Stratospheric columns of both NO 2 and NO show a diurnal increase that depends on local solar time (LST). We quantified this behavior by calculating diurnal increasing rates. Here, we find mean values for the NO 2 diurnal increasing rate of (0.89 ± 0.14) × 10 14 and (0.94 ± 0.14) × 10 14 cm -2 h -1 at Zugspitze and Garmisch, respectively. The mean NO morning diurnal increasing rate above Zugspitze is found to be (1.42 ± 0.12) × 10 14 cm -2 h -1. Regarding the seasonal dependency of these increasing rates, for the first time, we were able to experimentally detect a significant seasonal variation in both NO 2 diurnal increasing rates and NO morning diurnal increasing rates with a maximum of (1.13 ± 0.04) × 10 14 cm -1 h -1 for NO 2 and (1.76 ± 0.25) × 10 14 cm -1 h -1 for NO in September and a minimum of (0.71 ± 0.18) × 10 14 cm -1 h -1 in December for NO 2 and a minimum of (1.18 ± 0.41) × 10 14 cm -1 h -1 in November for NO. This similar behavior may be explained by the interconnection of both species in stratospheric photochemistry. The outcome of this work is a retrieval and analysis strategy of FTIR data for NO x stratospheric columns, which can help to further validate photochemical models or improve satellite validations. The first use of this data set is shown in the companion paper (Nürnberg et al., 2023) wherein experiment-based NO x scaling factors describing the diurnal increase in the retrieved partial columns are extracted and recently published model-based scaling factors are validated. [ABSTRACT FROM AUTHOR]

Long-term experimental stratospheric NO2 and NO partial columns measured by means of solar Fourier-transform infrared (FTIR) spectromertry at Zugspitze (47.42° N, 10.98° E, 2964 m a.s.l.), Germany were used to create a set of experiment-based monthly scaling factors (SF exp). The underlying data set is published in a companion paper (Nürnberg et al., 2023) comprising over 25 years of measurements depicting the diurnal variability of stratospheric NO2 and NO partial columns in dependence of local solar time (LST). In analogy to recently published simulation-based scaling factors by Strode et al. (2022), we created SF exp normalized to local solar noon for NO2 and NO for every month of the year as a function of solar zenith angle (SZA). Beside a boundary value problem at minimum SZA values originating in averaging over different times of the month, the obtained scaling factors SF exp(NO2) and SF exp(NO) in dependence of SZA represent very well the diurnal behavior already shown in model simulations and experiment in the literature. This behavior is a well pronounced increase of the NO2 and NO stratospheric partial colum with the time of the day and a flattening of this increase after noon. In addition to the discussion of SF exp, we validate the simulation-based scaling factors SF sim(NO2) (Strode et al., 2022) and present simulation-based scaling factors for NO SF sim(NO). The simulation-based scaling factors show an excellent agreement with our the experiment-based ones, i.e. for NO2 and NO the mean bias of the modulus between experiment and simulation over all SZA and months is only 0.02 %. We show, that recently used model simulations can describe very well the real behavior of nitrogen oxide (NOx) variability in the stratosphere. Furthermore, we conclude that ground-based FTIR measurements can be used for validation of the output of photochemistry models as well as creating experiment-based data sets describing the diurnal stratospheric NOx variability in dependence of SZA. This is a contribution to improved satellite validation and a better understanding of stratospheric photochemistry. [ABSTRACT FROM AUTHOR]

The Far-Infrared Radiation Mobile Observation System (FIRMOS) is a Fourier transform spectroradiometer developed to support the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite mission by validating measurement methods and instrument design concepts, both in the laboratory and in field campaigns. FIRMOS is capable of measuring the downwelling spectral radiance emitted by the atmosphere in the spectral band from 100 to 1000 cm −1 (10–100 µm in wavelength), with a maximum spectral resolution of 0.25 cm −1. We describe the instrument design and its characterization and discuss the geophysical products obtained by inverting the atmospheric spectral radiance measured during a campaign from the high-altitude location of Mount Zugspitze in Germany, beside the Extended-range Atmospheric Emitted Radiance Interferometer (E-AERI), which is permanently installed at the site. Following the selection of clear-sky scenes, using a specific algorithm, the water vapour and temperature profiles were retrieved from the FIRMOS spectra by applying the Kyoto protocol and Informed Management of the Adaptation (KLIMA) code. The profiles were found in very good agreement with those provided by radiosondes and by the Raman lidar operating from the Zugspitze Schneefernerhaus station. In addition, the retrieval products were validated by comparing the retrieved integrated water vapour values with those obtained from the E-AERI spectra. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) accounts for the largest radiative forcing among anthropogenic greenhouse gases. There is, therefore, a pressing need to understand the rate at which CO2 accumulates in the atmosphere, including the interannual variations (IAVs) in this rate. IAV in the CO2 growth rate is a small signal relative to the long-term trend and the mean annual cycle of atmospheric CO2 , 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 CO2 IAV since the satellite can measure over remote terrestrial regions and the open ocean, where traditional in situ CO2 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 CO2 mole fraction (XCO2) 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 XCO2 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. [ABSTRACT FROM AUTHOR]

The Far-Infrared Radiation Mobile Observation System (FIRMOS) is a Fourier transform spectroradiometer developed to support the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite mission by validating measurement methods and instrument design concepts, both in the laboratory and in field campaigns. FIRMOS is capable of measuring the downwelling spectral radiance emitted by the atmosphere in the spectral band from 100 to 1000 cm-1 (10–100 µ m in wavelength), with a maximum spectral resolution of 0.25 cm-1. We describe the instrument design and its characterisation and discuss the geophysical products obtained by inverting the atmospheric spectral radiance measured during a campaign from the high-altitude location of Mount Zugspitze in Germany, beside the Extended-range Atmospheric Emitted Radiance Interferometer (E-AERI), which is permanently installed at the site. Following the selection of clear-sky scenes, using a specific algorithm, the water vapour and temperature profiles were retrieved from the FIRMOS spectra by applying the Kyoto protocol and Informed Management of the Adaptation (KLIMA) code. The profiles were found in very good agreement with those provided by radiosondes and by the Raman lidar operating from the Zugspitze Schneefernerhaus station. In addition, the retrieval products were validated by comparing the retrieved Integrated Water Vapour values with those obtained from the E-AERI spectra. Finally, we found that the trends for the temperature, and the water vapour profiles over time were in good agreement with those provided by ERA5 reanalysis. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) accounts for the largest radiative forcing among anthropogenic greenhouse gases. There is, therefore, a pressing need to understand the rate at which CO2 accumulates in the atmosphere, including the interannual variations (IAV) in this rate. IAV in the CO2 growth rate is a small signal relative to the long-term trend and the mean annual cycle of atmospheric CO2, 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 CO2 IAV since the satellite can measure over remote terrestrial regions and the open ocean where traditional in situ CO2 monitoring is difficult. In this study, we analyze the IAV of column-averaged dry air CO2 mole fraction (XCO2) from OCO-2 between September 2014 to June 2021. The amplitude of IAV variations 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 XCO2 IAV shows a clear relationship with ENSO-driven variations that originate in the tropics and are transported poleward. The XCO2 IAV timeseries shows similar zonal patterns compared to ground-based in situ observations and with column observations from the Total Carbon Column Observing Network (TCCON). At lower degrees of aggregation (i.e., 5°x5° grid cells), there are larger inconsistencies with TCCON suggesting that one or both of the observing systems are affected by bias or systematic retrieval issues that are of a similar magnitude to the IAV signal. Our results suggest that OCO-2 IAV provides meaningful information about climate-driven variations in carbon fluxes and provides new opportunities to monitor climate-driven variations in CO2 over open ocean and remote regions. [ABSTRACT FROM AUTHOR]

Photographs of a 120 [degrees] parhelion and a 22 [degrees] parhelion within persistent contrails are presented. These phenomena result from hexagonal plate-shaped ice crystals oriented horizontally with diameters between 300 [[micro]meter] and 2 mm. From our observations and reinvestigation of previous reports, we conclude that a subset of the population in persistent contrails can consist of highly regular, oriented, hexagonal plates or columns comparable to the most regular crystals in natural cirrus clouds. This is explained by measured ambient humidities below the formation conditions of natural cirrus. The resulting strong azimuthal variability of the scattering phase function impacts the radiative transfer through persistent contrails. Key words: Aircraft, contrail, climatic impact, crystal growth, halo phenomena, ice crystals, optical properties, relative humidity, remote sensing, scattering phase function.

Vibration-rotation absorptions in high-resolution Fourier-transform infrared spectra from a 246-m horizontal path were used to derive local concentrations of trace gases at the Alpine observatory at the Zugspitze summit, Germany (2964 m above sea level). The analysis was performed by using the line-by-line nonlinear least-squares spectral fitting software, SFIT, based on the 1992 HITRAN line parameter compilation. (HITRAN is a high-resolution transmission molecular absorption database.) A comparison to in situ measurements shows an agreement of better than 4.3% for the species CO, C[O.sub.2], and C[H.sub.4]. Using the same spectrometer and analysis software, we obtained the vertical column density of [N.sub.2]O together with an adjusted vertical volume mixing ratio distribution. This translates to a local [N.sub.2]O concentration at the altitude of Zugspitze that agrees with the horizontal path-derived value to within 1%. Key words: Remote sensing, Fourier-transform infrared spectroscopy, open path, in situ, solar absorption, vertical profile.

The long-wave downwelling spectral radiance measurements performed by means of the Far-Infrared Radiation Mobile Observation System (FIRMOS) spectrometer at the summit of the Zugspitze (German Alps) in the winter 2018/19 allowed the retrieval of the optical and micro-physical properties of ice and mixed clouds, showing a good agreement of the statistical relationship between the ice water path and the ice optical depth with the ones from previous works. In this paper the optical depths retrieved from FIRMOS are initially compared with selected cases calculated from backscattering light detection and ranging (lidar) data by using a transmittance method. Then, in order to compare the whole FIRMOS dataset, the power-law relationship between backscattering and extinction is used to apply the Klett method and automatize the routine. Minimizing the root mean square differences, the exponent k of the power-law relationship is assessed to be 0.85 with a variability in the range of 0.60–1.10 for ice clouds and 0.50 with a variability within 0.30–0.70 for mixed clouds. [ABSTRACT FROM AUTHOR]

Measurements of the spectrum of the atmospheric emission in the far-infrared (FIR) range, between 100 and 667 cm-1 (100–15 µm) are scarce because of the detection complexity and of the strong absorption of air at ground level preventing the sounding of the FIR from low altitude. Consequently, FIR measurements need to be made from high-altitude sites or on board airborne platforms or satellites. This paper describes the dataset of FIR spectral radiances of the atmosphere and snow surface emission measured in the 100–1000 cm-1 range by the Far-Infrared Radiation Mobile Observation System (FIRMOS) instrument during a 2-month campaign carried out from the ground at about 3000 m of altitude on the top of Mt. Zugspitze in the German Alps in 2018–2019. This campaign is part of the preparatory activity of a new space FIR mission, named Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM), which is under development by the European Space Agency (ESA). The dataset acquired during the campaign also includes all the additional measurements needed to provide a full characterisation of the observed atmospheric state and the local atmospheric and surface conditions. It includes co-located spectral measurements in the infrared range from 400 to 1800 cm-1 ; lidar backscatter profiles; radio soundings of temperature, humidity and aerosol backscatter profiles; local weather parameters; and snow/ice microphysical properties. These measurements provide a unique dataset that can be used to perform radiative closure experiments to improve modelling parameters in the FIR that are not well-characterised, such as water vapour spectroscopy, scattering properties of cirrus clouds, and the FIR emissivity of the surface covered by snow. The consolidated dataset is freely available via the ESA campaign dataset website at 10.5270/ESA-38034ee. [ABSTRACT FROM AUTHOR]

We examined biases in the global GEOS-Chem chemical transport model for the period of February–May 2010 using weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation and dry-air mole fractions of CH 4 (XCH 4) from the Greenhouse gases Observing SATellite (GOSAT). The ability of the observations and the WC 4D-Var method to mitigate model errors in CH 4 concentrations was first investigated in a set of observing system simulation experiments (OSSEs). We then assimilated the GOSAT XCH 4 retrievals and found that they were capable of providing information on the vertical structure of model errors and of removing a significant portion of biases in the modeled CH 4 state. In the WC 4D-Var assimilation, corrections were added to the modeled CH 4 state at each model time step to account for model errors and improve the model fit to the assimilated observations. Compared to the conventional strong-constraint (SC) 4D-Var assimilation, the WC method was able to significantly improve the model fit to independent observations. Examination of the WC state corrections suggested that a significant source of model errors was associated with discrepancies in the model CH 4 in the stratosphere. The WC state corrections also suggested that the model vertical transport in the troposphere at middle and high latitudes is too weak. The problem was traced back to biases in the uplift of CH 4 over the source regions in eastern China and North America. In the tropics, the WC assimilation pointed to the possibility of biased CH 4 outflow from the African continent to the Atlantic in the mid-troposphere. The WC assimilation in this region would greatly benefit from glint observations over the ocean to provide additional constraints on the vertical structure of the model errors in the tropics. We also compared the WC assimilation at 4 ∘ × 5 ∘ and 2 ∘ × 2.5 ∘ horizontal resolutions and found that the WC corrections to mitigate the model errors were significantly larger at 4 ∘ × 5 ∘ than at 2 ∘ × 2.5 ∘ resolution, indicating the presence of resolution-dependent model errors. Our results illustrate the potential utility of the WC 4D-Var approach for characterizing model errors. However, a major limitation of this approach is the need to better characterize the specified model error covariance in the assimilation scheme. [ABSTRACT FROM AUTHOR]

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (≈4 nmol/mol) below the 2000–2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere contributed less than one‐quarter of the observed tropospheric anomaly. The observed anomaly is consistent with recent chemistry‐climate model simulations, which assume emissions reductions similar to those caused by the COVID‐19 crisis. COVID‐19 related emissions reductions appear to be the major cause for the observed reduced free tropospheric ozone in 2020. Plain Language Summary: Worldwide actions to contain the COVID‐19 virus have closed factories, grounded airplanes, and have generally reduced travel and transportation. Less fuel was burnt, and less exhaust was emitted into the atmosphere. Due to these measures, the concentration of nitrogen oxides and volatile organic compounds (VOCs) decreased in the atmosphere. These substances are important for photochemical production and destruction of ozone in the atmosphere. In clean or mildly polluted air, reducing nitrogen oxides and/or VOCs will reduce the photochemical production of ozone and result in less ozone. In heavily polluted air, in contrast, reducing nitrogen oxides can increase ozone concentrations, because less nitrogen oxide is available to destroy ozone. In this study, we use data from three types of ozone instruments, but mostly from ozonesondes on weather balloons. The sondes fly from the ground up to 30 kilometers altitude. In the first 8 km, we find significantly reduced ozone concentrations in the northern extratropics during spring and summer of 2020, less than in any other year since at least 2000. We suggest that reduced emissions due to the COVID‐19 crisis have lowered photochemical ozone production and have caused the observed ozone reductions in the troposphere. Key Points: In spring and summer 2020, stations in the northern extratropics report on average 7% (4 nmol/mol) less tropospheric ozone than normalSuch low tropospheric ozone, over several months, and at so many sites, has not been observed in any previous year since at least 2000Most of the reduction in tropospheric ozone in 2020 is likely due to emissions reductions related to the COVID‐19 pandemic [ABSTRACT FROM AUTHOR]

We present a multiyear time series of column abundances of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) measured using Fourier-transform infrared (FTIR) spectrometers at 10 sites affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC). Six are high-latitude sites: Eureka, Ny-Ålesund, Thule, Kiruna, Poker Flat, and St. Petersburg, and four are midlatitude sites: Zugspitze, Jungfraujoch, Toronto, and Rikubetsu. For each site, the interannual trends and seasonal variabilities of the CO time series are accounted for, allowing background column amounts to be determined. Enhancements above the seasonal background were used to identify possible wildfire pollution events. Since the abundance of each trace gas emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution. A GEOS-Chem tagged CO simulation with Global Fire Assimilation System (GFASv1.2) biomass burning emissions was used to determine the source attribution of CO concentrations at each site from 2003 to 2018. For each detected wildfire pollution event, FLEXPART back-trajectory simulations were performed to determine the transport times of the smoke plume. Accounting for the loss of each species during transport, the enhancement ratios of HCN and C2H6 with respect to CO were converted to emission ratios. We report mean emission ratios with respect to CO for HCN and C2H6 of 0.0047 and 0.0092, respectively, with a standard deviation of 0.0014 and 0.0046, respectively, determined from 23 boreal North American wildfire events. Similarly, we report mean emission ratios for HCN and C2H6 of 0.0049 and 0.0100, respectively, with a standard deviation of 0.0025 and 0.0042, respectively, determined from 39 boreal Asian wildfire events. The agreement of our emission ratios with literature values illustrates the capability of ground-based FTIR measurements to quantify biomass burning emissions. We provide a comprehensive dataset that quantifies HCN and C2H6 emission ratios from 62 wildfire pollution events. Our dataset provides novel emission ratio estimates, which are sparsely available in the published literature, particularly for boreal Asian sources. [ABSTRACT FROM AUTHOR]

Total columns of the trace gases nitric acid (HNO3) and hydrogen chloride (HCl) are sensitive to variations in the lower stratospheric age of air, a quantity that describes transport time scales in the stratosphere. Analyses of HNO3 and HCl columns from the Network for the Detection of Atmospheric Composition Change panning 77°S to 79°N have detected changes in the extratropical stratospheric transport circulation from 1994 to 2018. The HNO3 and HCl analyses combined with the age of air from a simulation using the MERRA2 reanalysis show that the Southern Hemisphere lower stratosphere has become 1 month/decade younger relative to the Northern Hemisphere, largely driven by the Southern Hemisphere transport circulation. The analyses reveal multiyear anomalies with a 5‐ to 7‐year period driven by interactions between the circulation and the quasi‐biennial oscillation in tropical winds. This hitherto unrecognized variability is large relative to hemispheric transport trends and may bias ozone trend regressions. Plain Language Summary: Our analyses of the 25‐year Network for the Detection of Atmospheric Composition Change column HNO3 and HCl data records from nine stations provide observational evidence that air in the Southern Hemisphere lower stratosphere has been getting younger relative to the Northern Hemisphere at a rate of 1 month/decade since 1994. This stands in contrast to several model studies that predict that Antarctic ozone hole recovery in this century will increase the Southern Hemisphere age of air relative to the Northern Hemisphere. The analyses also reveal extratropical variability with a 5‐ to 7‐year period driven by interactions between the circulation and tropical winds. This previously unrecognized, low‐frequency variability is much larger than hemispheric transport trends and is likely to cause bias in trends calculated using data records shorter than about two decades. Understanding and quantifying changes in the transport circulation matters to our ability to model how our protective O3 layer will evolve in the future. Key Points: Trace gas data show southern stratospheric air is getting younger relative to the Northern Hemisphere, in contrast to model predictionsBoth extratropical hemispheres have dynamically driven 5‐ to 7‐year periodicity with large amplitude relative to the age trendMultidecadal data sets are required to quantify transport trends that are not confounded by large extratropical variability [ABSTRACT FROM AUTHOR]

The GEOS-Chem simulation of atmospheric CH4 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 CH4 , with smaller biases and a higher correlation to the independent data. We found large resolution-dependent differences such as a latitude-dependent XCH4 bias, with higher column abundances of CH4 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 CH4 column abundances between the two resolutions over major source regions such as China. These differences resulted in up to 30 % differences in inferred regional CH4 emission estimates from the two model resolutions. We performed several experiments using 222Rn , 7Be , and CH4 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 CH4 abundances in the lower troposphere over China at 4∘×5∘ than at 2∘×2.5∘. Although we found that the CH4 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 CH4 emissions, should be evaluated in future studies using online transport in the native general circulation model as a benchmark simulation. [ABSTRACT FROM AUTHOR]

Verifying anthropogenic carbon dioxide (CO2) emissions globally is essential to inform about the progress of institutional efforts to mitigate anthropogenic climate forcing. To monitor localized emission sources, spectroscopic satellite sensors have been proposed that operate on the CO2 absorption bands in the shortwave-infrared (SWIR) spectral range with ground resolution as fine as a few tens of meters to about a hundred meters. When designing such sensors, fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, such sensors are envisioned to fly in fleets of satellites, requiring low-cost and simple design, e.g., by restricting the spectrometer to a single spectral band. Here, we use measurements of the Greenhouse Gases Observing Satellite (GOSAT) to evaluate the spectral resolution and spectral band selection of a prospective satellite sensor with fine ground resolution. To this end, we degrade GOSAT SWIR spectra of the CO2 bands at 1.6 (SWIR-1) and 2.0 µ m (SWIR-2) to coarse spectral resolution, without a further addition of noise, and we evaluate single-band retrievals of the column-averaged dry-air mole fractions of CO2 (XCO2) by comparison to ground truth provided by the Total Carbon Column Observing Network (TCCON) and by comparison to global "native" GOSAT retrievals with native spectral resolution and spectral band selection. Coarsening spectral resolution from GOSAT's native resolving power of >20000 to the range of 700 to a few thousand makes the scatter of differences between the SWIR-1 and SWIR-2 retrievals and TCCON increase moderately. For resolving powers of 1200 (SWIR-1) and 1600 (SWIR-2), the scatter increases from 2.4 (native) to 3.0 ppm for SWIR-1 and 3.3 ppm for SWIR-2. Coarser spectral resolution yields only marginally worse performance than the native GOSAT configuration in terms of station-to-station variability and geophysical parameter correlations for the GOSAT–TCCON differences. Comparing the SWIR-1 and SWIR-2 configurations to native GOSAT retrievals on the global scale, however, reveals that the coarse-resolution SWIR-1 and SWIR-2 configurations suffer from some spurious correlations with geophysical parameters that characterize the light-scattering properties of the scene such as particle amount, size, height and surface albedo. Overall, the SWIR-1 and SWIR-2 configurations with resolving powers of 1200 and 1600 show promising performance for future sensor design in terms of random error sources while residual errors induced by light scattering along the light path need to be investigated further. Due to the stronger CO2 absorption bands in SWIR-2 than in SWIR-1, the former has the advantage that measurement noise propagates less into the retrieved XCO2 and that some retrieval information on particle scattering properties is accessible. [ABSTRACT FROM AUTHOR]

We present a multi-year time series of column abundances of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) measured using Fourier transform infrared (FTIR) spectrometers at ten sites affiliated with the Network for Detection of Atmospheric Composition Change (NDACC). Six are high-latitude sites: Eureka, Ny-Alesund, Thule, Kiruna, Poker Flat, and St. Petersburg, and four are mid-latitude sites: Zugspitze, Jungfraujoch, Toronto, and Rikubetsu. For each site, the inter-annual trends and seasonal variabilities of the CO time series are accounted for, allowing ambient concentrations to be determined. Enhancements above ambient levels were used to identify possible wildfire pollution events. Since the abundance of each trace gas emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution, while complementary measurements of aerosol optical depth from nearby AERONET sites confirm the presence of wildfire smoke. A GEOS-Chem tagged CO simulation with Global Fire Assimilation System (GFAS) biomass burning emissions was used to determine the source attribution of CO concentrations at each site from 2003-2018. The influence of the various wildfire sources is found to differ between sites while North American and Asian boreal wildfires fires were found to be the greatest contributors to episodic CO enhancements in the summertime at all sites. [ABSTRACT FROM AUTHOR]

We examined biases in the global GEOS-Chem chemical transport model for the period of February-May 2010 using weak constraint (WC) four-dimensional variational (4D-Var) data assimilation and dry-air mole fractions of CH4 (XCH4) from the Greenhouse gases Observing SATellite (GOSAT). The ability of the observations and the WC 4D-Var method to mitigate model errors in CH4 concentrations was first investigated in a set of observing system simulation experiments (OSSEs). We then assimilated the GOSAT XCH4 retrievals and found that they were capable of differentiating the vertical distribution of model errors and of removing a significant portion of biases in the modelled CH4 state. In the WC 4D-Var assimilation, corrections were added to the modeled CH4 state at each model time step to account for model errors and improve the model fit to the assimilated observations. Compared to the conventional strong constraint (SC) 4D-Var assimilation, the WC method was able to significantly improve the model fit to independent observations. Examination of the WC state corrections suggested that a significant source of the model errors was associated with discrepancies in the model CH4 in the stratosphere. The WC state corrections also suggested that the model vertical transport in the troposphere at mid- and high-latitudes is too weak. The problem was traced back to biases in the uplift of CH4 over the source regions in eastern China and North America. In the tropics, the WC assimilation pointed to the possibility of biased CH4 outflow from the African continent to the Atlantic in the mid-troposphere. The WC assimilation in this region would greatly benefit from glint observations over the ocean to provide additional constraints on the vertical structure of the model errors in the tropics. We also compared the WC assimilation at the 4° × 5° and 2° × 2.5° horizontal resolutions and found that the WC corrections to mitigate the model errors were significantly larger at 4° × 5° than at 2° × 2.5° resolution, indicating the presence of resolution-dependent model errors. Our results illustrate the potential utility of the WC 4D-Var approach for characterizing model errors. However, a major limitation of this approach is the need to better characterize the specified model error covariance in the assimilation scheme. [ABSTRACT FROM AUTHOR]

On 13 October 2017, the Tropospheric Monitoring Instrument (TROPOMI) was launched on the Copernicus Sentinel-5 Precursor satellite in a sun-synchronous orbit. One of the mission's operational data products is the total column concentration of carbon monoxide (CO), which was released to the public in July 2018. The current TROPOMI CO processing uses the HITRAN 2008 spectroscopic data with updated water vapor spectroscopy and produces a CO data product compliant with the mission requirement of 10 % precision and 15 % accuracy for single soundings. Comparison with ground-based CO observations of the Total Carbon Column Observing Network (TCCON) show systematic differences of about 6.2 ppb and single-orbit observations are superimposed by a significant striping pattern along the flight path exceeding 5 ppb. In this study, we discuss possible improvements of the CO data product. We found that the molecular spectroscopic data used in the retrieval plays a key role for the data quality where the use of the Scientific Exploitation of Operational Missions – Improved Atmospheric Spectroscopy Databases (SEOM-IAS) and the HITRAN 2012 and 2016 releases reduce the bias between TROPOMI and TCCON due to improved CH4 spectroscopy. SEOM-IAS achieves the best spectral fit quality (root-mean-square, rms, differences between the simulated and measured spectrum) of 1.5×10-10 mol s -1 m -2 nm -1 sr -1 and reduces the bias between TROPOMI and TCCON to 3.4 ppb, while HITRAN 2012 and HITRAN 2016 decrease the bias even further below 1 ppb. HITRAN 2012 shows the worst fit quality (rms = 2.5×10-10 mol s -1 m -2 nm -1 sr -1) of the tested cross sections and furthermore introduces an artificial bias of about -1.5×1017 molec cm -2 between TROPOMI CO and the CAMS-IFS model in the Tropics caused by the H2O spectroscopic data. Moreover, analyzing 1 year of TROPOMI CO observations, we identified increased striping patterns by about 16 % percent from November 2017 to November 2018. For that, we defined a measure γ , quantifying the relative pixel-to-pixel variation in CO in the cross-track and along-track directions. To mitigate this effect, we discuss two destriping methods applied to the CO data a posteriori. A destriping mask calculated per orbit by median filtering of the data in the cross-track direction significantly reduced the stripe pattern from γ=2.1 to γ=1.6. However, the destriping can be further improved, achieving γ=1.2 by deploying a Fourier analysis and filtering of the data, which not only corrects for stripe patterns in the cross-track direction but also accounts for the variability of stripes along the flight path. [ABSTRACT FROM AUTHOR]

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 Summary: Numerous 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 Points: We 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 constraints [ABSTRACT FROM AUTHOR]

Verifying anthropogenic carbon dioxide (CO2) emissions globally is essential to inform about the progress of institutional efforts to mitigate man-made climate forcing. To monitor localized emission sources, spectroscopic satellite sensors have been proposed that operate on the CO2 absorption bands in the shortwave-infrared (SWIR) spectral range with ground resolution as fine as a few tens to about a hundred meters. When designing such sensors, fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, such sensors are envisioned to fly in fleets of satellites, requiring low-cost and simple design, e.g. by restricting the spectrometer to a single spectral band. Here, we use measurements of the Greenhouse Gases Observing Satellite (GOSAT) to evaluate the spectral resolution and spectral band selection of a prospective satellite sensor with fine ground resolution. To this end, we degrade GOSAT SWIR spectra of the CO2 bands at 1.6 (SWIR-1) and 2.0 μm (SWIR-2) to coarse spectral resolution, and we evaluate retrievals of the column-averaged dry-air mole-fractions of CO2 (XCO2) by comparison to ground-truth provided by the Total Carbon Column Observing Network (TCCON) and by comparison to global native GOSAT retrievals with native spectral resolution and spectral band selection. Coarsening spectral resolution from GOSAT's native resolving power of > 20,000 to the range of 700 to a few thousand makes the scatter of differences between the SWIR-1 and SWIR-2 retrievals and TCCON increase moderately. For resolving powers of 1,600 (SWIR-1) and 1,200 (SWIR-2), the scatter increases from 2.4 ppm (native) to 3.0 ppm for SWIR-1 and 3.3 ppm for SWIR-2. Coarser spectral resolution yields only marginally worse performance than the native GOSAT configuration in terms of station-to-station variability and geophysical parameter correlations for the TCCON-GOSAT differences. Comparing the SWIR-1 and SWIR-2 configurations to native GOSAT retrievals on the global scale, however, reveals that the coarse resolution SWIR-1 and SWIR-2 configurations suffer from some spurious correlations with geophysical parameters that characterize the light-scattering properties of the scene such as particle amount, size, height and surface albedo. Overall, the SWIR-1 and SWIR-2 configurations with resolving powers of 1,600 and 1,200 show promising performance for future sensor design in terms of random error sources while residual errors induced by light-scattering along the lightpath need to be investigated further. Due to the stronger CO2 absorption bands in SWIR-2 than in SWIR-1, the former has the advantage that measurement noise propagates less into the retrieved XCO2 and that some retrieval information on particle scattering properties is accessible. [ABSTRACT FROM AUTHOR]

Using five long-running ground-based atmospheric observatories in Europe, we demonstrate the utility of long-term, stationary, ground-based measurements of atmospheric total columns for verifying annual methane emission inventories. Our results indicate that the methane emissions for the region in Europe between Orléans, Bremen, Białystok, and Garmisch-Partenkirchen are overestimated by the state-of-the-art inventories of the Emissions Database for Global Atmospheric Research (EDGAR) v4.2 FT2010 and the high-resolution emissions database developed by the Netherlands Organisation for Applied Scientific Research (TNO) as part of the Monitoring Atmospheric Composition and Climate project (TNO-MACC_III), possibly due to the disaggregation of emissions onto a spatial grid. Uncertainties in the carbon monoxide inventories used to compute the methane emissions contribute to the discrepancy between our inferred emissions and those from the inventories. [ABSTRACT FROM AUTHOR]

On 13 October 2017, the European Space Agency (ESA) successfully launched the Sentinel-5 Precursor satellite with the Tropospheric Monitoring Instrument (TROPOMI) as its single payload. TROPOMI is the first of ESA's atmospheric composition Sentinel missions, which will provide complete long-term records of atmospheric trace gases for the coming 30 years as a contribution to the European Union's Earth Observing program Copernicus. One of TROPOMI's primary products is atmospheric carbon monoxide (CO). It is observed with daily global coverage and a high spatial resolution of 7&$215;7 km². The moderate atmospheric resistance time and the low background concentration leads to localized pollution hotspots of CO and allows the tracking of the atmospheric transport of pollution on regional to global scales. In this contribution, we demonstrate the groundbreaking performance of the TROPOMI CO product, sensing CO enhancements above cities and industrial areas and tracking, with daily coverage, the atmospheric transport of pollution from biomass burning regions. The CO data product is validated with two months of Fourier-transform spectroscopy (FTS) measurements at nine ground-based stations operated by the Total Carbon Column Observing Network (TCCON). We found a good agreement between both datasets with a mean bias of 6 ppb (average of individual station biases) for both clear-sky and cloudy TROPOMI CO retrievals. Together with the corresponding standard deviation of the individual station biases of 3.8 ppb for clear-sky and 4.0 ppb for cloudy sky, it indicates that the CO data product is already well within the mission requirement. [ABSTRACT FROM AUTHOR]

This paper assesses the quality of IASI (Infrared Atmospheric Sounding Interferometer)/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3; v20151001) software for 9 years (2008-July 2017) through an extensive intercomparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). Compared with the previous version of FORLI-O3 (v20140922), several improvements have been introduced in FORLI-O3 v20151001, including absorbance look-up tables recalculated to cover a larger spectral range, with additional numerical corrections. This leads to a change of ~ 4% in the total ozone column (TOC) product, which is mainly associated with a decrease in the retrieved O3 concentration in the middle stratosphere (above 30 hPa/25 km). IASI-A and IASI-B TOCs are consistent, with a global mean difference of less than 0.3% for both daytime and nighttime measurements; IASI-A is slightly higher than IASI-B. A global difference of less than 2.4% is found for the tropospheric (TROPO) O3 column product (IASI-A is lower than IASI-B), which is partly due to a temporary issue related to the IASIA viewing angle in 2015. Our validation shows that IASIA and IASI-B TOCs are consistent with GOME-2 (Global Ozone Monitoring Experiment-2), Dobson, Brewer, SAOZ (Système d'Analyse par Observation Zénithale) and FTIR (Fourier transform infrared) TOCs, with global mean differences in the range of 0.1%-2% depending on the instruments compared. The worst agreement with UV-vis retrieved TOC (satellite and ground) is found at the southern high latitudes. The IASI-A and ground-based TOC comparison for the period from 2008 to July 2017 shows the long-term stability of IASI-A, with insignificant or small negative drifts of 1%-3%decade-1. The comparison results of IASI-A and IASI-B against smoothed FTIR and ozonesonde partial O3 columns vary with altitude and latitude, with the maximum standard deviation being seen for the 300-150 hPa column (2%-40%) due to strong ozone variability and large total retrievals errors. Compared with ozonesonde data, the IASIA and IASI-B O3 TROPO column (defined as the columnbetween the surface and 300 hPa) is positively biased in the high latitudes (4%-5%) and negatively biased in the midlatitudes and tropics (11%-13% and 16%-19%, respectively). The IASI-A-to-ozonesonde TROPO comparison for the period from 2008 to 2016 shows a significant negative drift in the Northern Hemisphere of -8:6±3:4% decade-1, which is also found in the IASI-A-to-FTIR TROPO comparison. When considering the period from 2011 to 2016, the drift value for the TROPO column decreases and becomes statistically insignificant. The observed negative drifts of the IASIA TROPO O3 product (8%-16% decade-1) over the 2008- 2017 period might be taken into consideration when deriving trends from this product and this time period. [ABSTRACT FROM AUTHOR]

Using five long-running ground-based atmospheric observatories in Europe, we demonstrate the utility of long-term, stationary, ground-based measurements of atmospheric total columns for verifying annual methane emission inventories. Our results indicate that the methane emissions for the region in Europe between Orleans, Bremen, Bialystok, and Garmisch are overestimated by the state-of-the-art inventories Emission Database for Global Atmospheric Research (EDGAR) v4.2 FT2010 and TNO-MACC_III, possibly due to the disaggregation of emissions onto a grid. Uncertainties in the carbon monoxide inventories used to compute the methane emissions may contribute to the discrepancy between our inferred emissions and those from the inventories. [ABSTRACT FROM AUTHOR]

The primary instrument on the Greenhouse gases Observing SATellite (GOSAT) is the Thermal And Near infrared Sensor for carbon Observations (TANSO) Fourier transform spectrometer (FTS). TANSO-FTS uses three shortwave infrared (SWIR) bands to retrieve total columns of CO2 and CH4 along its optical line of sight and one thermal infrared (TIR) channel to retrieve vertical profiles of CO2 and C< volume mixing ratios (VMRs) in the troposphere. We examine version 1 of the TANSO-FTS TIR CH4 product by comparing co-located CH4 VMR vertical profiles from two other remote-sensing FTS systems: the Canadian Space Agency's Atmospheric Chemistry Experiment FTS (ACEFTS) on SCISAT (version 3.5) and the European Space Agency's Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat (ESA ML2PP version 6 and IMK-IAA reduced-resolution version V5R_CH4_224/225), as well as 16 ground stations with the Network for the Detection of Atmospheric Composition Change (NDACC). This work follows an initial inter-comparison study over the Arctic, which incorporated a ground-based FTS at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Canada, and focuses on tropospheric and lowerstratospheric measurements made at middle and tropical latitudes between 2009 and 2013 (mid-2012 for MIPAS). For comparison, vertical profiles from all instruments are interpolated onto a common pressure grid, and smoothing is applied to ACE-FTS, MIPAS, and NDACC vertical profiles. Smoothing is needed to account for differences between the vertical resolution of each instrument and differences in the dependence on a priori profiles. The smoothing operators use the TANSO-FTS a priori and averaging kernels in all cases. We present zonally averaged mean CH4 differences between each instrument and TANSO-FTS with and without smoothing, and we examine their information content, their sensitive altitude range, their correlation, their a priori dependence, and the variability within each data set. Partial columns are calculated from the VMR vertical profiles, and their correlations are examined. We find that the TANSO-FTS vertical profiles agree with the ACE-FTS and both MIPAS retrievals' vertical profiles within 4% (± ~ 40 ppbv) below 15 km when smoothing is applied to the profiles from instruments with finer vertical resolution but that the relative differences can increase to on the order of 25% when no smoothing is applied. Computed partial columns are tightly correlated for each pair of data sets. We investigate whether the difference between TANSO-FTS and other CH4 VMR data products varies with latitude. Our study reveals a small dependence of around 0.1% per 10 degrees latitude, with smaller differences over the tropics and greater differences towards the poles. [ABSTRACT FROM AUTHOR]

We present vertical soundings (2005-2015) of tropospheric water vapor (H2O) and its D/H isotope ratio (δD) derived from ground-based solar Fourier transform infrared (FTIR) measurements at Zugspitze (47°â€¯N, 11°â€¯E, 2964 m a.s.l.). Beside water vapor profiles with optimized vertical resolution (degrees of freedom for signal, DOFS,  =  2.8), {H2O, δD} pairs with consistent vertical resolution (DOFS  =  1.6 for H2O and δD) applied in this study. The integrated water vapor (IWV) trend of 2.4 [-5.8, 10.6] % decade-1 is statistically insignificant (95 % confidence interval). Under this caveat, the IWV trend estimate is conditionally consistent with the 2005-2015 temperature increase at Zugspitze (1.3 [0.5, 2.1] K decade-1), assuming constant relative humidity. Seasonal variations in free-tropospheric H2O and δD exhibit amplitudes of 140 and 50 % of the respective overall means. The minima (maxima) in January (July) are in agreement with changing sea surface temperature of the Atlantic Ocean. Using extensive backward-trajectory analysis, distinct moisture pathways are identified depending on observed δD levels: low column-based δD values (δDcol < 5th percentile) are associated with air masses originating at higher latitudes (62°â€¯N on average) and altitudes (6.5 km)than high δD values (δDcol > 95th percentile: 46°â€¯N, 4.6 km). Backward-trajectory classification indicates that {H2O, δD} observations are influenced by three long-range-transport patterns towards Zugspitze assessed in previous studies: (i) intercontinental transport from North America (TUS; source region: 25-45°â€¯N, 70-110°â€¯W, 0-2 km altitude), (ii) intercontinental transport from northern Africa (TNA; source region: 15-30°â€¯N, 15°â€¯W-35°â€¯E, 0-2 km altitude), and (iii) stratospheric air intrusions (STIs; source region: > 20°â€¯N, above zonal mean tropopause). The FTIR data exhibit significantly differing signatures in free-tropospheric {H2O, δD} pairs (5 km a.s.l.) - given as the mean with uncertainty of ±2 standard error (SE) - for TUS (VMRH2O  =  2.4 [2.3, 2.6]  ×  103 ppmv, δD  =  -315 [-326, -303] ‰), TNA (2.8 [2.6, 2.9]  ×  103 ppmv, -251 [-257, -246] ‰), and STIs (1.2 [1.1, 1.3]  ×  103 ppmv, -384 [-397, -372] ‰). For TUS events, {H2O, δD} observations depend on surface temperature in the source region and the degree of dehydration having occurred during updraft in warm conveyor belts. During TNA events (dry convection of boundary layer air) relatively moist and weakly HDO-depleted air masses are imported. In contrast, STI events are associated with import of predominantly dry and HDO-depleted air masses. These long-range-transport patterns potentially involve the import of various trace constituents to the central European free troposphere, i.e., import of pollution from North America (e.g., aerosol, ozone, carbon monoxide), Saharan mineral dust, stratospheric ozone, and other airborne species such as pollen. Our results provide evidence that {H2O, δD} observations are a valuable proxy for the transport of such tracers. To validate this finding, we consult a database of transport events (TNA and STI) covering 2013-2015 deduced by data filtering from in situ measurements at Zugspitze and lidar profiles at nearby Garmisch. Indeed, the FTIR data related to these verified TNA events (27 days) exhibit characteristic fingerprints in IWV (5.5 [4.9, 6.1] mm) and δDcol (-266 [-284, -247] ‰), which are significantly distinguishable from the rest of the time series (4.3 [4.1, 4.5] mm, -316 [-324, -308] ‰). This holds true for 136 STI days considering uncertainties of ±1 SE (4.2 [4.0, 4.3] mm, -322 [-327, -316] ‰) with respect to the remainder (4.6 [4.5, 4. 8] mm, -302 [-307, -297] ‰). Furthermore, deep stratospheric intrusions to the Zugspitze summit (in situ humidity and beryllium-7 data filtering) show a significantly lower mean value (-334 [-337, -330] ‰) of lower-tropospheric δD (3-5 km a.s.l.) than the rest of the 2005-2015 time series (-284 [-286, -282] ‰) considering uncertainty of ±2 SE. Our results show that consistent {H2O, δD} observations at Zugspitze can serve as an operational indicator for long-range-transport events potentially affecting regional climate and air quality, as well as human health in central Europe. [ABSTRACT FROM AUTHOR]

NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dryair mole fraction, XCO2 , in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and XCO2 from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 XCO2 retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 XCO2 data quality throughout its mission. [ABSTRACT FROM AUTHOR]

The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument provides the longest continuous dataset of carbon monoxide (CO) from space. We perform the first validation of MOPITT version 6 retrievals using total column CO measurements from groundbased remote-sensing Fourier transform infrared spectrometers (FTSs). Validation uses data recorded at 14 stations, that span a wide range of latitudes (80° N to 78° S), in the Network for the Detection of Atmospheric Composition Change (NDACC). MOPITT measurements are spatially co-located with each station, and different vertical sensitivities between instruments are accounted for by using MOPITT averaging kernels (AKs). All three MOPITT retrieval types are analyzed: thermal infrared (TIR-only), joint thermal and near infrared (TIR-NIR), and near infrared (NIR-only). Generally, MOPITT measurements overestimate CO relative to FTS measurements, but the bias is typically less than 10%. Mean bias is 2.4% for TIR-only, 5.1% for TIR-NIR, and 6.5% for NIR-only. The TIR-NIR and NIR-only products consistently produce a larger bias and lower correlation than the TIR-only. Validation performance of MOPITT for TIR-only and TIR-NIR retrievals over land or water scenes is equivalent. The four MOPITT detector element pixels are validated separately to account for their different uncertainty characteristics. Pixel 1 produces the highest standard deviation and lowest correlation for all three MOPITT products. However, for TIR-only and TIR-NIR, the error-weighted average that includes all four pixels often provides the best correlation, indicating compensating pixel biases and well-captured error characteristics. We find that MOPITT bias does not depend on latitude but rather is influenced by the proximity to rapidly changing atmospheric CO. MOPITT bias drift has been bound geographically to within ±0.5%yr-1 or lower at almost all locations. [ABSTRACT FROM AUTHOR]

This study presents an approach for generating a global land mapping dataset of the satellite measurements of CO2total column (XCO2) using spatio-temporal geostatistics, which makes full use of the joint spatial and temporal dependencies between observations. The mapping approach considers the latitude-zonal seasonal cycles and spatio-temporal correlation structure of XCO2, and obtains global land maps of XCO2, with a spatial grid resolution of 1° latitude by 1° longitude and temporal resolution of 3 days. We evaluate the accuracy and uncertainty of the mapping dataset in the following three ways: (1) in cross-validation, the mapping approach results in a high correlation coefficient of 0.94 between the predictions and observations, (2) in comparison with ground truth provided by the Total Carbon Column Observing Network (TCCON), the predicted XCO2time series and those from TCCON sites are in good agreement, with an overall bias of 0.01 ppm and a standard deviation of the difference of 1.22 ppm and (3) in comparison with model simulations, the spatio-temporal variability of XCO2between the mapping dataset and simulations from the CT2013 and GEOS-Chem are generally consistent. The generated mapping XCO2data in this study provides a new global geospatial dataset in global understanding of greenhouse gases dynamics and global warming. [ABSTRACT FROM PUBLISHER]

We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4 : XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. This work builds on the previously reported theory that takes into account that (1) these ratios are less prone to systematic error than either the full-physics data products or the proxy CH4 data products; and (2) the resulting CH4 and CO2 fluxes are self-consistent. We show that a posteriori fluxes inferred from the GOSAT data generally outperform the fluxes inferred only from in situ data, as expected. GOSAT CH4 and CO2 fluxes are consistent with global growth rates for CO2 and CH4reported by NOAA and have a range of independent data including new profile measurements (0-7 km) over the Amazon Basin that were collected specifically to help validate GOSAT over this geographical region. We find that large-scale multi-year annual a posteriori CO2 fluxes inferred from GOSAT data are similar to those inferred from the in situ surface data but with smaller uncertainties, particularly over the tropics. GOSAT data are consistent with smaller peak-to-peak seasonal amplitudes of CO2 than either the a priori or in situ inversion, particularly over the tropics and the southern extratropics. Over the northern extratropics, GOSAT data show larger uptake than the a priori but less than the in situ inversion, resulting in small net emissions over the year. We also find evidence that the carbon balance of tropical South America was perturbed following the droughts of 2010 and 2012 with net annual fluxes not returning to an approximate annual balance until 2013. In contrast, GOSAT data significantly changed the a priori spatial distribution of CH4 emission with a 40 % increase over tropical South America and tropical Asia and a smaller decrease over Eurasia and temperate South America. We find no evidence from GOSAT that tropical South American CH4 fluxes were dramatically affected by the two large-scale Amazon droughts. However, we find that GOSAT data are consistent with double seasonal peaks in Amazonian fluxes that are reproduced over the 5 years we studied: a small peak from January to April and a larger peak from June to October, which are likely due to superimposed emissions from different geographical regions. [ABSTRACT FROM AUTHOR]

The primary instrument on the Greenhouse gases Observing SATellite (GOSAT) is the Thermal And Near infrared Sensor for carbon Observations (TANSO) Fourier Transform Spectrometer (FTS). TANSO-FTS uses three short-wave infrared (SWIR) bands to retrieve total columns of CO2 and CH4 along its optical line-of-sight, and one thermal infrared (TIR) channel to retrieve vertical profiles of CO2 and CH4 volume mixing ratios (VMRs) in the troposphere. We examine version 1 of the TANSO-FTS TIR CH4 product by comparing co-located CH4 VMR vertical profiles from two other remote sensing FTS systems: the Canadian Space Agency's Atmospheric Chemistry Experiment-FTS (ACE-FTS) on SCISAT (version 3.5), and the European Space Agency's Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat (ESA ML2PP version 6 and IMK-IAA reduced-resolution version V5R_CH4_224/225), as well as 16 ground stations with the Network for the Detection of Atmospheric Composition Change (NDACC). This work follows an initial inter-comparison study over the Arctic, which incorporated a ground-based FTS at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Canada, and focuses on tropospheric and lower-stratospheric measurements made at middle and tropical latitudes between 2009 to 2013 (mid 2012 for MIPAS). For comparison, vertical profiles from all instruments are interpolated onto a common pressure grid, and the ACE-FTS, MIPAS, and NDACC vertical profiles are smoothed using the TANSO-FTS averaging kernels. We present zonally-averaged mean CH4 differences between each instrument and TANSO-FTS with and without smoothing, examine their information content, sensitive altitude range, correlation, a priori dependence, and the variability within each data set. Partial columns are calculated from the VMR vertical profiles, and their correlations are examined. We find that the TANSO-FTS vertical profiles agree with the ACE-FTS and both MIPAS retrievals' vertical profiles within 4% below 15km when smoothing is applied to the profiles from instruments with finer vertical resolution, but that the relative differences can increase to on the order of 25% when no smoothing is applied. Computed partial columns are tightly correlated for each pair of data sets. We investigated whether the difference between TANSO-FTS and other CH4 VMR data products varies with latitude. Our study reveals a small dependence of around 0.1% per ten degrees latitude, with smaller differences over the equator, and greater differences towards the poles. [ABSTRACT FROM AUTHOR]

We present vertical soundings (2005-2015) of tropospheric water vapor (H2O) and its D/H isotope ratio (δD) at Mt. Zugspitze (47° N, 11° E, 2964 m a.s.l.) derived from ground-based solar Fourier transform infrared (FTIR) measurements. Beside water vapor profiles with optimized vertical resolution (degrees of freedom for signal DOFS = 2.8), the retrieval provides {H2O, δD} pairs with consistent vertical resolution (DOFS = 1.6 for H2O and δD) applied in this study. The integrated water vapor (IWV) trend of 2.4 [-5.8, 10.6] % per decade (statistically insignificant, 95 % confidence interval) can be reconciled with the 2005-2015 temperature increase at Mt. Zugspitze (1.3 [0.5, 2.1] K per decade) assuming constant relative humidity. Seasonal variations in free-tropospheric H2O and δD exhibit amplitudes of 140 % and 50 % of the respective overall means. The minima (maxima) in January (July) are in agreement with changing sea surface temperature of the Atlantic Ocean. Using extensive backward trajectory analysis, distinct moisture pathways are identified depending on observed δD levels: low column-based δD values (δDcol < 5th percentile) are associated with air masses originating in higher latitudes (62° N on average) and altitudes (6.5 km) compared to high δD values (δDcol > 95th percentile: 46° N, 4.6 km). Backward trajectory classification indicates that {H2O, δD} observations are influenced by three long-range transport patterns towards Mt. Zugspitze assessed in previous studies: (i) intercontinental transport from North America (TUS; source region: 25-45° N, 70-110° W, 0-2 km altitude), (ii) intercontinental transport from Northern Africa (TNA; source region: 15-30° N, 15° W-35° E, 0-2 km altitude), and (iii) stratospheric air intrusions (STI; source region: > 20° N, above zonal mean tropopause). The FTIR data exhibit significantly differing signatures in free-tropospheric {H2O, δD} pairs (given as mean with uncertainty of ±2 standard errors) for TUS (VMRH2O = 2.4 [2.3, 2.6] × 10³ ppmv, δD = -315 [-326, -303] ‰), TNA (2.8 [2.6, 2.9] × 10³ ppmv, -251 [-257, -246] ‰), and STI (1.2 [1.1, 1.3] × 10³ ppmv, -384 [-397, -372] ‰). For TUS events, {H2O, δD} observations depend on surface temperature in the source region and the degree of dehydration having occurred during updraft in warm conveyor belts. During TNA events (dry convection of boundary layer air) relatively moist and weakly HDO-depleted air masses are imported. In contrast, STI events are associated to import of predominantly dry and HDO-depleted air masses. These long-range transport patterns potentially involve the import of various trace constituents to the Central European free troposphere, i.e., import of pollution from North America (e.g., aerosol, ozone, carbon monoxide), Saharan mineral dust, stratospheric ozone and other airborne species such as pollen. Our above results provide evidence that {H2O, δD} observations are a valuable proxy for the potential transport of such tracers. To validate this finding, we consult a data base of transport events (TNA and STI) covering 2013-2015 deduced by data filtering from in situ measurements at Mt. Zugspitze and lidar profiles at near-by Garmisch. Indeed, the FTIR data related to these verified TNA events (27 days) exhibit characteristic fingerprints in IWV (5.5 [4.9, 6.1] mm) and δDcol (-266 [-284, -247] ‰), which are significantly distinguishable from the rest of the time series (4.3 [4.1, 4.5] mm, -316 [-324, -308] ‰). This holds true on 1-σ level for 136 STI days (mean ± 1 standard error: 4.2 [4.0, 4.3] mm, -322 [-327, -316] ‰) with respect to the remainder (4.6 [4.5, 4.8] mm, -302 [-307, -297] ‰). Furthermore, deep stratospheric intrusions to the Zugspitze summit (in situ humidity and beryllium-7 data filtering) show a significantly lower mean value (-334 [-337, -330] ‰) of lower-tropospheric δD (3-5 km a.s.l.) on 2-σ level than the rest of the 2005-2015 time series (-284 [-286, -282] ‰). Our results show that consistent {H2O, δD} observations at Mt. Zugspitze can serve as an operational indicator for long-range transport events potentially affecting regional climate, air quality, as well as human health in Central Europe. [ABSTRACT FROM AUTHOR]

Inverse modeling is a useful tool to retrieve CH4 fluxes; however, evaluation of the applied chemical transport model is an important step before using the inverted emissions. For inversions using column data one concern is how well the model represents stratospheric and tropospheric CH4 respectively when assimilating total column measurements. In this study atmospheric CH4 from three inverse models is compared to FTS (Fourier Transform Spectrometry), satellite and in situ measurements. Using the FTS measurements the model biases are separated into stratospheric and tropospheric contributions. When averaged over all FTS sites the model bias amplitudes (absolute model to FTS differences) are 7.4 ± 5.1 ppb, 6.7 ± 4.8 ppb, and 8.1 ± 5.5 ppb in the troposphere for the models TM3, TM5-4DVAR, LMDz-PYVAR, respectively, and 4.3 ± 9.9 ppb, 4.7 ± 9.9 ppb, and 6.2 ± 11.2 ppb in the stratosphere. The tropospheric model biases show a latitudinal gradient for all models, however there are no clear latitudinal dependencies for stratospheric model biases visible except with the LMDz-PYVAR model. The latitudinal gradient is not present in a comparison with in situ measurements, which is attributed to the different longitudinal coverage of FTS and in situ measurements. Similarly, a latitudinal pattern exists in model biases in vertical CH4 gradients in the troposphere, which indicates vertical transports of tropospheric CH4 is not represented correctly in the models. [ABSTRACT FROM AUTHOR]

Quantitative knowledge of water vapor radiative processes in the atmosphere throughout the terrestrial and solar infrared spectrum is still incomplete even though this is crucial input to the radiation codes forming the core of both remote sensing methods and climate simulations. Beside laboratory spectroscopy, ground-based remote sensing field studies in the context of so-called radiative closure experiments are a powerful approach because this is the only way to quantify water absorption under cold atmospheric conditions. For this purpose, we have set up at the Zugspitze (47.42° N, 10.98° E; 2964ma.s.l.) a long-term radiative closure experiment designed to cover the infrared spectrum between 400 and 7800 cm-1 (1.28-25 μm). As a benefit for such experiments, the atmospheric states at the Zugspitze frequently comprise very low integrated water vapor (IWV; minimum=0.1 mm, median=2.3 mm) and very low aerosol optical depth (AOD=0.0024-0.0032 at 7800 cm-1 at air mass 1). All instruments for radiance measurements and atmospheric-state measurements are described along with their measurement uncertainties. Based on all parameter uncertainties and the corresponding radiance Jacobians, a systematic residual radiance uncertainty budget has been set up to characterize the sensitivity of the radiative closure over the whole infrared spectral range. The dominant uncertainty contribution in the spectral windows used for far-infrared (FIR) continuum quantification is from IWV uncertainties, while T profile uncertainties dominate in the mid-infrared (MIR). Uncertainty contributions to near-infrared (NIR) radiance residuals are dominated by water vapor line parameters in the vicinity of the strong water vapor bands. The window regions in between these bands are dominated by solar Fourier transform infrared (FTIR) calibration uncertainties at low NIR wavenumbers, while uncertainties due to AOD become an increasing and dominant contribution towards higher NIR wavenumbers. Exceptions are methane or nitrous oxide bands in the NIR, where the associated line parameter uncertainties dominate the overall uncertainty. As a first demonstration of the Zugspitze closure experiment, a water vapor continuum quantification in the FIR spectral region (400-580 cm-1) has been performed. The resulting FIR foreign-continuum coefficients are consistent with the MT_CKD 2.5.2 continuum model and also agree with the most recent atmospheric closure study carried out in Antarctica. Results from the first determination of the NIR water vapor continuum in a field experiment are detailed in a companion paper (Reichert and Sussmann, 2016) while a novel NIR calibration scheme for the underlying FTIR measurements of incoming solar radiance is presented in another companion paper (Reichert et al., 2016). [ABSTRACT FROM AUTHOR]

We present a first quantification of the nearinfrared (NIR) water vapor continuum absorption from an atmospheric radiative closure experiment carried out at the Zugspitze (47.42° N, 10.98° E; 2964ma.s.l.). Continuum quantification is achieved via radiative closure using radiometrically calibrated solar Fourier transform infrared (FTIR) absorption spectra covering the 2500 to 7800 cm-1 spectral range. The dry atmospheric conditions at the Zugspitze site (IWV 1.4 to 3.3 mm) enable continuum quantification even within water vapor absorption bands, while upper limits for continuum absorption can be provided in the centers of window regions. Throughout 75% of the 2500 to 7800 cm-1 spectral range, the Zugspitze results agree within our estimated uncertainty with the widely used MT_CKD 2.5.2 model (Mlawer et al., 2012). In the wings of water vapor absorption bands, our measurements indicate about 2-5 times stronger continuum absorption than MT_CKD, namely in the 2800 to 3000 cm-1 and 4100 to 4200 cm-1 spectral ranges. The measurements are consistent with the laboratory measurements of Mondelain et al. (2015), which rely on cavity ring-down spectroscopy (CDRS), and the calorimetric- interferometric measurements of Bicknell et al. (2006). Compared to the recent FTIR laboratory studies of Ptashnik et al. (2012, 2013), our measurements are consistent within the estimated errors throughout most of the spectral range. However, in the wings of water vapor absorption bands our measurements indicate typically 2-3 times weaker continuum absorption under atmospheric conditions, namely in the 3200 to 3400, 4050 to 4200, and 6950 to 7050 cm-1 spectral regions. [ABSTRACT FROM AUTHOR]

The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument provides the longest continuous dataset of carbon monoxide (CO) from space. We perform the first validation of MOPITT version 6 retrievals using total column CO measurements from ground-based remote sensing Fourier transform infrared spectrometers (FTSs). Validation uses data recorded at 14 stations, that span a wide range of latitudes (80° N to 78° S), in the Network for the Detection of Atmospheric Composition Change (NDACC). MOPITT measurements are spatially co-located with each station and different vertical sensitivities between instruments are accounted for by using MOPITT averaging kernels. All three MOPITT retrieval types are analyzed: thermal infrared (TIR-only), joint thermal and near infrared (TIR-NIR), and near infrared (NIR-only). Generally, MOPITT measurements overestimate CO relative to FTS measurements, but the bias is typically less than 10 %. Mean bias is 2.8 % for TIR-only, 5.4 % for TIR-NIR and 7.0 % for NIR-only. The TIR-NIR and NIR-only products consistently produce greater bias and lower correlation than the TIR-only. Validation performance of MOPITT for TIR-only and TIR-NIR retrievals over land or water scenes is equivalent. The four MOPITT detector element pixels are validated separately to account for their different uncertainty characteristics. Pixel 1 produces the highest standard deviation and lowest correlation, for all three MOPITT products. However, for TIR only and TIR-NIR, the error-weighted average that includes all four pixels often provides the best correlation, indicating compensating pixel biases and well captured error characteristics. We find that MOPITT bias does not depend on latitude, and rather is influenced by the proximity to rapidly changing atmospheric CO. MOPITT bias drift has been bound geographically to within ±0.5 % yr- or lower at almost all locations. [ABSTRACT FROM AUTHOR]

Quantitative knowledge of water vapor absorption is crucial for accurate climate simulations. An open science question in this context concerns the strength of the water vapor continuum in the near infrared (NIR) at atmospheric temperatures, which is still to be quantified by measurements. This issue can be addressed with radiative closure experiments using solar absorption spectra. However, the spectra used for water vapor continuum quantification have to be radiometrically calibrated. We present for the first time a method that yields sufficient calibration accuracy for NIR water vapor continuum quantification in an atmospheric closure experiment. Our method combines the Langley method with spectral radiance measurements of a hightemperature blackbody calibration source (<2000 K). The calibration scheme is demonstrated in the spectral range 2500 to 7800 cm-1, but minor modifications to the method enable calibration also throughout the remainder of the NIR spectral range. The resulting uncertainty (2σ excluding the contribution due to inaccuracies in the extra-atmospheric solar spectrum (ESS) is below 1% in window regions and up to 1.7% within absorption bands. The overall radiometric accuracy of the calibration depends on the ESS uncertainty, on which at present no firm consensus has been reached in the NIR. However, as is shown in the companion publication Reichert and Sussmann (2016), ESS uncertainty is only of minor importance for the specific aim of this study, i.e., the quantification of the water vapor continuum in a closure experiment. The calibration uncertainty estimate is substantiated by the investigation of calibration self-consistency, which yields compatible results within the estimated errors for 91.1% of the 2500 to 7800 cm-1 range. Additionally, a comparison of a set of calibrated spectra to radiative transfer model calculations yields consistent results within the estimated errors for 97.7% of the spectral range. [ABSTRACT FROM AUTHOR]

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2/ and CH4 (XCH4/ derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT).We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases. [ABSTRACT FROM AUTHOR]

We present a first quantification of the near-infrared (NIR) water vapor continuum absorption from an atmospheric radiative closure experiment carried out at Mt. Zugspitze (47.42° N, 10.98° E, 2964 m a.s.l.). Continuum quantification is achieved via radiative closure using radiometrically calibrated solar FTIR absorption spectra covering the 2500 to 7800 cm−1 spectral range. The dry atmospheric conditions at the Zugspitze site (IWV 1.4 to 3.3 mm) enable continuum quantification even within water vapor absorption bands, while upper limits for continuum absorption can be provided in the centers of window regions. Throughout 75 % of the 2500 to 7800 cm−1 spectral range, the Zugspitze results are agree within our estimated uncertainty with the widely used MT_CKD 2.5.2-model (Mlawer et al., 2012). Notable exceptions are the 2800 to 3000 cm−1 and 4100 to 4200 cm−1 spectral ranges, where our measurements indicate about 5 times stronger continuum absorption than MT_CKD. The measurements are consistent with the laboratory measurements of Mondelain et al. (2015), which rely on cavity ring-down spectroscopy (CDRS), and the calorimetric-interferometric measurements of Bicknell et al. (2006). Compared to the recent FTIR laboratory studies of Ptashnik et al. (2012) and (2013), our measurements indicate 2–5 times weaker continuum absorption under atmospheric conditions in the wings of water vapor absorption bands, namely in the 3200 to 3400 cm−1, 4050 to 4200 cm−1, and 6950 to 7050 cm−1 spectral regions. [ABSTRACT FROM AUTHOR]

Quantitative knowledge of water vapor radiative processes in the atmosphere throughout the terrestrial and solar infrared spectrum is still incomplete even though this is crucial input to the radiation codes forming the core of both remote sensing methods and climate simulations. Beside laboratory spectroscopy, ground-based remote sensing field studies in terms of so-called radiative closure experiments are a powerful approach, because this is the only way to quantify water absorption under cold atmospheric conditions. For this purpose, we have set up at Mt. Zugspitze (47.42° N, 10.98° E, 2964 m a.s.l.) a long-term radiative closure experiment designed to cover the infrared spectrum between 400 to 7800 cm−1 (1.28–25 µm). As a benefit for such experiments, the atmospheric states at Zugspitze frequently comprise very low integrated water vapor (IWV; minimum = 0.1 mm, median = 2.3 mm) and very low aerosol optical depth (AOD = 0.0024–0.0032 at 7800 cm−1 at airmass 1). All instruments for radiance measurements and atmospheric state measurements are described along with their measurement uncertainties. Based on all parameter uncertainties and the corresponding radiance Jacobians, a systematic residual radiance uncertainty budget has been set up to characterize the sensitivity of the radiative closure over the whole infrared spectral range. The dominant uncertainty contribution in the spectral windows used for far-infrared (FIR) continuum quantification is from IWV uncertainties, while T-profile uncertainties dominate in the mid-infrared (MIR). Uncertainty contributions to near-infrared (NIR) radiance residuals are dominated by water vapor line parameters in the vicinity of the strong water vapor bands. The window regions in between these bands are dominated by solar FTIR calibration uncertainties at low NIR wavenumbers, while uncertainties due to AOD become an increasing and dominant contribution towards higher NIR wavenumbers. Exceptions are methane or nitrous oxide bands in the NIR, where the associated line parameter uncertainties dominate the overall uncertainty. As a first demonstration of the Zugspitze closure experiment, a water vapor continuum quantification in the FIR spectral region (400–580 cm−1) has been performed. The resulting FIR foreign continuum coefficients are consistent with the MT_CKD 2.5.2 continuum model and also agree with the most recent atmospheric closure study carried out in Antarctica. Results from the first determination of the NIR water vapor continuum in a field experiment are detailed in a companion paper (Part III) while a novel NIR calibration scheme for the underlying FTIR measurements of incoming solar radiance is presented in another companion paper (Part II). [ABSTRACT FROM AUTHOR]

Satellite measurements of the spatiotemporal distributions of atmospheric CO2 concentrations are a key component for better understanding global carbon cycle characteristics. Currently, several satellite instruments such as the Greenhouse gases Observing SATellite (GOSAT), SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY), and Orbiting Carbon Observatory-2 can be used to measure CO2 column-averaged dry air mole fractions. However, because of cloud effects, a single satellite can only provide limited CO2 data, resulting in significant uncertainty in the characterization of the spatiotemporal distribution of atmospheric CO2 concentrations. In this study, a new physical data fusion technique is proposed to combine the GOSAT and SCIAMACHY measurements. On the basis of the fused dataset, a gap-filling method developed by modeling the spatial correlation structures of CO2 concentrations is presented with the goal of generating global land CO2 distribution maps with high spatiotemporal resolution. The results show that, compared with the single satellite dataset (i.e., GOSAT or SCIAMACHY), the global spatial coverage of the fused dataset is significantly increased (reaching up to approximately 20%), and the temporal resolution is improved by two or three times. The spatial coverage and monthly variations of the generated global CO2 distributions are also investigated. Comparisons with ground-based Total Carbon Column Observing Network (TCCON) measurements reveal that CO2 distributions based on the gap-filling method show good agreement with TCCON records despite some biases. These results demonstrate that the fused dataset as well as the gap-filling method are rather effective to generate global CO2 distribution with high accuracies and high spatiotemporal resolution. [ABSTRACT FROM AUTHOR]