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In this study, we carried out an independent validation of two methane retrieval algorithms using spectra from the Infrared Atmospheric Sounding Interferometer (IASI) that has been aboard the Meteorological Operational Satellite A (MetOp-A) since 2006. Both algorithms, one developed by the Laboratoire de Météorologie Dynamique (LMD), called the non-linear inference scheme (NLISv8.3), and the other by the Rutherford Appleton Laboratory (RAL), referred to as RALv2.0, provide long-term global CH4 concentrations using distinctively different retrieval approaches (neural network vs. optimal estimation, respectively). They also differ with respect to the vertical range covered, where LMD provides mid-tropospheric dry-air mole fractions (mtCH4), and RAL provides mixing ratio profiles from which we can derive total column-averaged dry-air mole fractions (XCH4) and potentially two partial column layers (qCH4). We compared both CH4 products using the Copernicus Atmospheric Monitoring Service (CAMS) model, in situ profiles (range extended using CAMS model data), and ground-based Fourier transform infrared (FTIR) remote-sensing measurements. The average difference (in mtCH4) with respect to in situ profiles for LMD ranges between −0.3 and 10.9 ppb, while for RAL the XCH4 difference ranges between −4.6 and −1.6 ppb. The standard deviation (SD) of the observed differences between in situ measurements and RAL retrievals is 14.1–21.9 ppb, which is consistently smaller than that between LMD retrievals and in situ measurements (15.2–30.6 ppb). By comparing with ground-based FTIR sites, the mean differences are within ±10 ppb for both RAL and LMD retrievals. However, the SD of the differences at the ground-based FTIR stations shows significantly lower values for RAL (11–15 ppb) than for LMD (about 25 ppb). The long-term trend and seasonal cycles of CH4 derived from the LMD and RAL products are further investigated and discussed. The seasonal variation in XCH4 derived from RAL is consistent with the seasonal variation observed by the ground-based FTIR measurements. However, the overall 2007–2015 XCH4 trend derived from RAL measurements is underestimated, if not adjusted, for an anomaly occurring on 16 May 2013 due to a L1 calibration change. For LMD, we see very good agreement at the (sub)tropics (° N–35° S) but notice deviations in the seasonal cycle (both in the amplitude and phase) and an underestimation of the long-term trend with respect to the RAL and reference data at higher-latitude sites.

Since 2007, the Meteorological Operational satellite (MetOp) series of platforms operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) has provided valuable observations of the Earth's surface and atmosphere for meteorological and climate applications. With 15 years of data already collected, the next generation of MetOp satellites will see this measurement record extend to and beyond 2045. Although a primary role is in operational meteorology, tropospheric temperature and water vapour profiles will be key data products produced using infrared and microwave sounding instruments on board. Considering the MetOp data record that will span 40 years, these profiles will form an essential climate data record (CDR) for studying long-term atmospheric changes. Therefore, the performance of these products must be characterized to support the robustness of any current or future analysis. In this study, we validate 9.5 years of profile data produced using the Infrared and Microwave Sounding (IMS) scheme with the European Space Agency (ESA) Water Vapour Climate Change Initiative (WV_cci) project against radiosondes from two different archives. The Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and Analyzed RadioSoundings Archive (ARSA) data records were chosen for the validation exercise to provide the contrast between global observations (ARSA) with sparser characterized climate measurements (GRUAN). Results from this study show that IMS temperature and water vapour profile biases are within 0.5 K and 10 % of the reference for “global” scales. We further demonstrate the difference between diurnal sampling and cloud amount match-ups on observed biases and discuss the implications that sampling also plays on attributing these effects. Finally, we present the first look at the profile bias stability from the IMS product, where we observe global stabilities ranging from −0.32 ± 0.18 to 0.1 ± 0.27 K per decade and −1.76 ± 0.19 to 0.79 ± 0.83 % ppmv (parts per million by volume) per decade for temperature and water vapour profiles, respectively. We further break down the profile stability into diurnal and latitudinal values and relate all observed results to required climate performance. Overall, we find the results from this study demonstrate the real potential for tropospheric water vapour and temperature profile CDRs from the MetOp series of platforms.

Abstract We document the implementation of the Common Representative Intermediates Mechanism version 2, reduction 5 into the United Kingdom Chemistry and Aerosol model (UKCA) version 10.9. The mechanism is merged with the stratospheric chemistry already used by the StratTrop mechanism, as used in UKCA and the UK Earth System Model, to create a new CRI‐Strat mechanism. CRI‐Strat simulates a more comprehensive treatment of non‐methane volatile organic compounds (NMVOCs) and provides traceability with the Master Chemical Mechanism. In total, CRI‐Strat simulates the chemistry of 233 species competing in 613 reactions (compared to 87 species and 305 reactions in the existing StratTrop mechanism). However, while more than twice as complex than StratTrop, the new mechanism is only 75% more computationally expensive. CRI‐Strat is evaluated against an array of in situ and remote sensing observations and simulations using the StratTrop mechanism in the UKCA model. It is found to increase production of ozone near the surface, leading to higher ozone concentrations compared to surface observations. However, ozone loss is also greater in CRI‐Strat, leading to less ozone away from emission sources and a similar tropospheric ozone burden compared to StratTrop. CRI‐Strat also produces more carbon monoxide than StratTrop, particularly downwind of biogenic VOC emission sources, but has lower burdens of nitrogen oxides as more is converted into reservoir species. The changes to tropospheric ozone and nitrogen budgets are sensitive to the treatment of NMVOC emissions, highlighting the need to reduce uncertainty in these emissions to improve representation of tropospheric chemical composition.

We describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.

Atmospheric ozone plays a key role in air quality and the radiation budget of the Earth, both directly and through its chemical influence on other trace gases. Assessments of the atmospheric ozone distribution and associated climate change therefore demand accurate vertically resolved ozone observations with both stratospheric and tropospheric sensitivity, on both global and regional scales, and both in the long term and at shorter timescales. Such observations have been acquired by two series of European nadir-viewing ozone profilers, namely the scattered-light UV–visible spectrometers of the GOME family, launched regularly since 1995 (GOME, SCIAMACHY, OMI, GOME-2A/B, TROPOMI, and the upcoming Sentinel-5 series), and the thermal infrared emission sounders of the IASI type, launched regularly since 2006 (IASI on Metop platforms and the upcoming IASI-NG on Metop-SG). In particular, several Level-2 retrieved, Level-3 monthly gridded, and Level-4 assimilated nadir ozone profile data products have been improved and harmonized in the context of the ozone project of the European Space Agency's Climate Change Initiative (ESA Ozone_cci). To verify their fitness for purpose, these ozone datasets must undergo a comprehensive quality assessment (QA), including (a) detailed identification of their geographical, vertical, and temporal domains of validity; (b) quantification of their potential bias, noise, and drift and their dependences on major influence quantities; and (c) assessment of the mutual consistency of data from different sounders. For this purpose we have applied to the Ozone_cci Climate Research Data Package (CRDP) released in 2017 the versatile QA and validation system Multi-TASTE, which has been developed in the context of several heritage projects (ESA's Multi-TASTE, EUMETSAT's O3M-SAF, and the European Commission's FP6 GEOmon and FP7 QA4ECV). This work, as the second in a series of four Ozone_cci validation papers, reports for the first time on data content studies, information content studies and ground-based validation for both the GOME- and IASI-type climate data records combined. The ground-based reference measurements have been provided by the Network for the Detection of Atmospheric Composition Change (NDACC), NASA's Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other ozonesonde and lidar stations contributing to the World Meteorological Organisation's Global Atmosphere Watch (WMO GAW). The nadir ozone profile CRDP quality assessment reveals that all nadir ozone profile products under study fulfil the GCOS user requirements in terms of observation frequency and horizontal and vertical resolution. Yet all L2 observations also show sensitivity outliers in the UTLS and are strongly correlated vertically due to substantial averaging kernel fluctuations that extend far beyond the kernel's 15 km FWHM. The CRDP typically does not comply with the GCOS user requirements in terms of total uncertainty and decadal drift, except for the UV–visible L4 dataset. The drift values of the L2 GOME and OMI, the L3 IASI, and the L4 assimilated products are found to be overall insignificant, however, and applying appropriate altitude-dependent bias and drift corrections make the data fit for climate and atmospheric composition monitoring and modelling purposes. Dependence of the Ozone_cci data quality on major influence quantities – resulting in data screening suggestions to users – and perspectives for the Copernicus Sentinel missions are additionally discussed.

This paper describes the global height-resolved methane (CH4) retrieval scheme for the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp, developed at the Rutherford Appleton Laboratory (RAL). The scheme precisely fits measured spectra in the 7.9 micron region to allow information to be retrieved on two independent layers centred in the upper and lower troposphere. It also uses nitrous oxide (N2O) spectral features in the same spectral interval to directly retrieve effective cloud parameters to mitigate errors in retrieved methane due to residual cloud and other geophysical variables. The scheme has been applied to analyse IASI measurements between 2007 and 2015. Results are compared to model fields from the MACC greenhouse gas inversion and independent measurements from satellite (GOSAT), airborne (HIPPO) and ground (TCCON) sensors. The estimated error on methane mixing ratio in the lower- and upper-tropospheric layers ranges from 20 to 100 and from 30 to 40 ppbv, respectively, and error on the derived column-average ranges from 20 to 40 ppbv. Vertical sensitivity extends through the lower troposphere, though it decreases near to the surface. Systematic differences with the other datasets are typically

'The Tropospheric Ozone Assessment Report' (TOAR) is an activity of the International Global Atmospheric Chemistry Project. This paper is a component of the report, focusing on the present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation. Utilizing the TOAR surface ozone database, several figures present the global distribution and trends of daytime average ozone at 2702 non-urban monitoring sites, highlighting the regions and seasons of the world with the greatest ozone levels. Similarly, ozonesonde and commercial aircraft observations reveal ozone’s distribution throughout the depth of the free troposphere. Long-term surface observations are limited in their global spatial coverage, but data from remote locations indicate that ozone in the 21st century is greater than during the 1970s and 1980s. While some remote sites and many sites in the heavily polluted regions of East Asia show ozone increases since 2000, many others show decreases and there is no clear global pattern for surface ozone changes since 2000. Two new satellite products provide detailed views of ozone in the lower troposphere across East Asia and Europe, revealing the full spatial extent of the spring and summer ozone enhancements across eastern China that cannot be assessed from limited surface observations. Sufficient data are now available (ozonesondes, satellite, aircraft) across the tropics from South America eastwards to the western Pacific Ocean, to indicate a likely tropospheric column ozone increase since the 1990s. The 2014–2016 mean tropospheric ozone burden (TOB) between 60°N–60°S from five satellite products is 300 Tg ± 4%. While this agreement is excellent, the products differ in their quantification of TOB trends and further work is required to reconcile the differences. Satellites can now estimate ozone’s global long-wave radiative effect, but evaluation is difficult due to limited in situ observations where the radiative effect is greatest.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) has been operating since March 2002 onboard of the ENVIronmental SATellite of the European Space Agency (ESA). The high resolution (0.035 cm−1 full width half maximum, unapodized) limb-emission measurements acquired by MIPAS in the first two years of operation have very good geographical and temporal coverage and have been re-processed by ESA with the most recent versions (4.61 and 4.62) of the inversion algorithms. The products of this processing chain are pressures at the tangent points and geolocated profiles of temperature and of the volume mixing ratios of six key atmospheric constituents: H2O, O3, HNO3, CH4, N2O and NO2. As for all the measurements made with innovative instruments and techniques, this data set requires a thorough validation. In this paper we present a geophysical validation of the temperature profiles derived from MIPAS measurements by the ESA retrieval algorithm. The validation is carried-out by comparing MIPAS temperature with correlative measurements made by radiosondes, lidars, in-situ and remote sensors operated either from the ground or stratospheric balloons. The results of the intercomparison indicate that the bias of the MIPAS profiles is generally smaller than 1 or 2 K depending on altitude. Furthermore we find that, especially at the edges of the altitude range covered by the MIPAS scan, the random error estimated from the intercomparison is larger (typically by a factor of two to three) than the corresponding estimate derived on the basis of error propagation. In this work we also characterize the discrepancies between MIPAS temperature and the temperature fields resulting from the analyses of the European Centre for Medium-range Weather Forecasts (ECMWF). The bias and the standard deviation of these discrepancies are consistent with those obtained when comparing MIPAS to correlative measurements; however, in this case the detected bias has a peculiar behavior as a function of altitude. This behavior is very similar to that observed in previous studies and is suspected to be due to vertical oscillations in the ECMWF temperature. The current understanding is that, at least in the upper stratosphere (above ≈10 hPa), these oscillations are caused by a discrepancy between model biases and biases of assimilated radiances from primarily nadir sounders.

Objectives: For attention-deficit hyperactivity disorder (ADHD), treatment seeking is a critical first step in treatment initiation and remains insufficiently understood. The aims of this study were to estimate ADHD treatment-seeking probabilities over the lifetime and to identify predictors of treatment seeking for ADHD separately for males and females., Methods: Data were drawn from 2001 to 2005 as part of the National Epidemiologic Survey on Alcohol and Related Conditions, a two-wave face-to-face survey conducted by the National Institute on Alcohol Abuse and Alcoholism (N=34,653)., Results: The lifetime cumulative probability of ADHD treatment seeking was estimated at 55%. Males identifying as African American, with less than 12 years of education, or paranoid personality disorder or in an older cohort (>30 years old) at the time of interview were more likely to experience delays, whereas males with comorbid alcohol dependence, dysthymic disorder, borderline personality disorder, or histrionic personality disorder were less likely. Among females, older age (>44 years) was the only predictor of a delay to first treatment seeking, whereas bipolar disorder was associated with more rapid treatment seeking. Age of onset had opposite effects on treatment-seeking delays by gender; males but not females with early-onset ADHD were more likely to experience treatment-seeking delays., Conclusions: A large proportion of persons with ADHD do not seek treatment. Furthermore, treatment seeking by males was affected by a greater number of identifiable characteristics, suggesting that males might be more responsive to efforts directed toward expediting treatment entry. Future research should explore how to facilitate early access to treatment for individuals with ADHD.

Background: Despite growing concerns about non-medical prescription drug use and prescription drug use disorders, whether vulnerability for these conditions is drug-specific or occurs through a shared liability and common risk factors is unknown., Methods: Exploratory and confirmatory factor analysis of Wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions were used to examine the latent structure of non-medical prescription drug use and prescription drug use disorders. Multiple Indicators Multiple Causes (MIMIC) analysis was used to examine whether the effect of sociodemographic and psychiatric covariates occurred through the latent factor, directly on each drug class or both., Results: A one-factor model described well the structure of both non-medical prescription drug use and prescription drug use disorders. Younger age, being White, having more intense pain or one of several psychiatric disorders increased the risk of non-medical prescription drug use through the latent factor. The same covariates, except for anxiety disorders also significantly increased the risk of prescription drug use disorders through the latent factor. Older age directly increased the risk of non-medical use of sedatives, and alcohol use disorders decreased the risk of non-medical tranquilizer use. No covariates had direct effects on the risk of any prescription drug use disorders beyond their effect through the latent factor., Conclusion: The risk for non-medical prescription drug use and prescription drug use disorders occurs through a shared liability. Treatment, prevention and policy approaches directed at these drugs as a group maybe more effective than those focused on individual classes of drugs., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

For data analysis of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) atmospheric limb emission spectroscopic experiment on Environmental Satellite microwindows, i.e., small spectral regions for data analysis, have been defined and optimized. A novel optimization scheme has been developed for this purpose that adjusts microwindow boundaries such that the total retrieval error with respect to measurement noise, parameter uncertainties, and systematic errors is minimized. Dedicated databases that contain optimized microwindows for retrieval of vertical profiles of pressure and temperature, H2O, O3, HNO3, CH4, N2O, and NO2 have been generated. Furthermore, a tool for optimal selection of subsets of predefined microwindows for specific retrieval situations has been provided. This tool can be used further for estimating total retrieval errors for a selected microwindow subset. It has been shown by use of this tool that an altitude-dependent definition of microwindows is superior to an altitude-independent definition. For computational efficiency a dedicated microwindow-related list of spectral lines has been defined that contains only those spectral lines that are of relevance for MIPAS limb sounding observations.